Soil-landscape characterization and mapping to advance the state of spatial soil information on Ethiopian highlands: Implications for site-specific soil management

Soil-landscape characterization and mapping to advance the state of spatial soil information on Ethiopian highlands: Implications for site-specific soil management | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Soil-landscape characterization and mapping to advance the state of spatial soil information on Ethiopian highlands: Implications for site-specific soil management Weldemariam Seifu, Eyasu Elias, Girmay Gebresamuel, Gudina Legesse, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2093235/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Currently, soil characterization and classification are becoming the primary source of information for precision agriculture, land use planning, and management. Thus, this study was focused on perusing the landscape-scale spatial variation of soils in data-scarce areas using toposequence-based ground sampling to characterize and classify the soils. Six typical profiles representing major landforms were opened and studied for their morphological characteristics and physical and chemical properties. Results revealed that the soils were shallow to very deep in depth, moderately acidic to moderately alkaline in soil reaction, non-saline in salinity, and clay to sandy loam in texture. The soils were found to be very low to low in organic carbon, very low to medium in TN, low to medium in av. P, very low in av. S, very low to low in av. B, high to very high in CEC and very low to very high in base saturation. The soils were also found deficient in Zn and sufficient in Fe, Cu, and Mn. Following the field survey and soil analytical results, five main reference soil groups, mollic Leptosols (Eutric), Prothovertio Luvisols (Clayic, Aric, Escalic), Skeletic Fluvisols (Arenic, Densic), Haplic Leptosols (Skeletic), Haplic Vertisols (Endocalcaric, Ochric), and Haplic Cambisols (Arenic, Aric) were identified in the different parts of the topographic positions. Profile − 2, 3, 5, and 6 were classified in I to IV land capability class (LCC) and grouped as arable land with some limitations. They were also in a suitable to a marginally suitable range. The severe constraints to crop cultivation in the area are generally low fertility, erosion hazard, and climate for all soil units. Therefore, continuous manure and compost integration with chemical fertilizer, reducing complete crop residue removal, and soil and water conservation measures are essential to overcome these common and other production limitations. Catena Classification Landscape position soil horizon Toposequence Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 1. Introduction Soils are a non-renewable source and comprise a vital component of the world’s stock of natural capital with a prolonged forming process. Soil takes 100s to 1000s years to form a 1 cm of soil and erode in a relatively short time due to improper use or poor management with little opportunity for regeneration (Jónsson and Davíðsdóttir, 2016 ; Kavitha and Sujatha, 2015 ; Santos-Francés et al., 2022 ). Hence, soil scientists strongly recommend understanding the soil beneath our feet, managing it properly, and avoiding destroying the essential building block of our environment and food security. The soil is perhaps the most difficult, underrated, and little understood matrix (Balestrini et al., 2015 ; Saljnikov et al., 2022 ). There is a saying by the legendary Italian artist Leonardo Da Vinci to explain our nuanced understanding of soil resources, i.e., " we know more about the movement of celestial bodies than about the soil underfoot " (Colby and David, 2019 ). The main ecological functions of soils have grouped into three major categories: (i) regulatory and support functions, (ii) provision functions, and (iii) information, culture, leisure, and religion functions (Devi, 2021; FAO and ITPS, 2015; Nunes et al., 2020 ). Soil is essential for supporting food production (producing about 95% of humanity's food supply) and providing ecosystem services. However, like other habitats and ecosystems, the soil is under increasing pressure due to anthropocentric activities (Jónsson and Davíðsdóttir, 2016 ) to the extent that a new geologic epoch, the Anthropocene, has been proposed (Will et al., 2007 ). Thus, the soil capital is threatened in Ethiopia and elsewhere due to rapid population growth, higher food demand, land use competition, massive vegetation clearing, desertification, overuse, and mismanagement (Bai et al., 2013 ; Elias, 2016 ; IPBES, 2018; Koch et al., 2013 ). These caused it to exceed its capacity to perform, as manifested by land degradation (Chen et al., 2022 ; Saljnikov et al., 2022 ). About 30% of the world's soils are currently degraded (Zurich Megazine, 2021 ). All of the world's topsoil could become unproductive within 60 years if current loss rates continue (Maximillian et al., 2019 ). Therefore, understanding the soil types of a given area is a vital prerequisite to designing optimum management strategies (Sebnie et al., 2021 ). Thus, identifying the spatial distribution of soils and their characteristics is critical because it can enhance natural resources management, predict soil properties in non-sampled locations, and improve sampling designs in agro-ecological and environmental studies. Moreover, given the vital role that soil plays within ecosystems and human life, it is essential to assess soil health, especially on field crop farms that dominate agricultural landscapes like Ethiopia. Therefore, to establish the level baseline of micronutrients, soil analysis is recommended to determine the level of available nutrients (Doula and Sarris, 2016 ). Balancing ecosystem services with agricultural production is essential to meet the needs of a growing global population while minimizing the environmental impacts of agriculture (Udawatta et al., 2017 ). So, analysis and interpretation of spatial variability of soils is a keystone in the site-specific farming system (Iqbal et al., 2005 ) since agricultural soils are in peril (Gebremedhin et al., 2022 ). Various studies on soil properties also confirmed that topographic position largely governs the change in types, characteristics, and distribution of soils (Debele et al., 2018 ; Dessalegn et al., 2014 ; Mulugeta, 2004 ). Above all, information about the distribution of a country's natural resources is vital for many purposes, including local and regional planning, economic forecasting, food security, and environmental protection. Studies also confirmed that the classification of fields into management zones is based on the variability of soil fertility limitations in precision agriculture (Iticha and Takele, 2019 ). Over the last few decades, the need for landscape monitoring and assessment of changes in spatial patterns has grown as knowledge of the types and properties of soils is critical for decision-making regarding crop production and other land-use types (Leenaars et al., 2020 ). Accordingly, soil characterization, classification, and mapping are among the most important stages and building blocks in natural resources assessment tools for understanding the soil-landscape, classifying it, and getting the best understanding of the environment (Ahmed et al., 2013 ; Esu et al., 2008 ). Apart from information about soil forming factors at the site, soil characterization is done through the description of color, texture, structure, consistence, voids, cutans, roots, cementations, nodules/concretions, rock fragments/stones, faunal activity, and horizon boundary of each generic soil horizons (FAO, 2006a ; Saether and De Caritat, 1996 ). The coupling of soil characterization, classification, and mapping provides a powerful resource for humankind's benefit, especially in food security and environmental sustainability (Ahmed et al., 2013 ). However, Ethiopia lags more in defining its spatial soil sources in detail and fine-scale, yet only 1712 soil profiles are detected according to the World Soil Information Service (WoSIS) (Batjes et al., 2020 ). More profile numbers will be studied than the WoSIS reported; however, only a part from there is readily reachable in a consistent format for the use of the international community. Another lag is that no Ethiopian soil classification system was identified, established, and documented with vernacular languages. This, in turn, creates many problems in the soil use system. In much of the country, lack of or fragmented geospatially explicit information on soil-landscape resources is common (Leenaars et al., 2020 ). Thus, providing up-to-date and site-specific soil information to the beneficiaries based on a detailed soil study at the local or watershed level is indispensable for sustainable soil use. Moreover, the United Nations pledged to achieve sustainable development goals (SDGs) by 2030, and regional land use analyses are essential to achieving these goals. Research findings also highlighted that soil resource information is vital for sound soil use planning and sustainable fertility management (Dinssa and Elias, 2021 ; Elias, 2016 ; Fekadu et al., 2018 ; Gebreselassie et al., 2014 ). Previous studies have reported that 19 out of the 28 Major Soil Groups of the FAO-UNSECO Soil Map of the World are found in Ethiopia. Because of this, Ethiopia is called the “ soil museum ” of the world. However, our knowledge of Ethiopia’s soil resources is limited. The soil resources were mapped at 1:2,000,000, which were too coarse and topographically not detailed enough to provide practical information for soil fertility decisions at lower spatial scales (Elias, 2016 ). Past soil survey activities were inadequate in providing basic soil data that can help to manage soils according to the local variability (i.e., watershed or farm scale). Thus, the present study was initiated to characterize and classify the soils of Ayiba catena following the FAO-WRB legends (FAO, 2006a ; IUSS Working Group WRB, 2015 ). This study was, therefore, set out expressly to (i) provide detailed morphological, physical, and chemical properties of the soils in the Ayiba mountainous landscape and (ii) classify the soils according to the FAO-WRB soil classification system and develop a soil map of the watershed to enable soil-specific farm-scale management interventions. 2. Materials And Methods 2.1 Site description: location, climate, soil, land use, and husbandry The research was carried out in the Ayiba watershed (4099.14 ha) of the Emba-Alaje district, southern Tigray, northern Ethiopia. Ayiba watershed is part of the Denakil River basin located between 12°51′18′′–12°54′36′′N and 39°29′24′′–39°35′24′′E (Figure 1). Elevation ranges from 2722 to 3944 meters above sea level (m.a.s.l.) with mountainous landscape and steep terrain at upper and middle slopes. The landform of the study area is dominated by high mountainous relief hills and starkly dissected plateaus with steep slopes (>30% slope gradient) complemented by valley bottoms (Amanuel et al., 2015; Elias, 2016). Regarding the geomorphological setting, an important artefact in the study watershed is different landslides positioned within the toposequence, which occurred due to basaltic parent material deposition down the slope, making them very important for soil distribution (Amanuel et al., 2015; Elias, 2016; Gebresamuel et al., 2022). Regarding soil development, Van de Wauw et al. (2008) described two essential types of mass movements studied in similar geomorphological settings: (a) large-scale landslides which move basaltic parent material downslope; and (b) flows of vertic clays deposited at the foot of the sandstone cliff, or similar secondary flows at the foot of large-scale landslides. The watershed is generally characterized as tepid to cool semi-arid climatic condition with extended 9-10 months of dry periods and 50-60 days of the rainy season and highland agro-ecological zone with a rainfall bi-modally distributed (Amanuel et al., 2015; Elias, 2016; Negash and Israel, 2017). The main rainy season, ‘ Keremti ’ (summer: June to September), is preceded by a short rainy season, ‘ Belgi ’ (spring: February to May), (Table 1), predominantly derived from the Indian Ocean (Elias, 2016; Embaye, 2009; Yemane et al., 2020). Figure 1 . Spatial distribution of the (a) topsoil sampling points and (b) profile sites in the Ayiba watershed in the semi-arid region of Tigray highland, northern Ethiopia. According to the 20 years of weather data obtained from four nearby weather stations (Bora, Maychew, Wedisemero, and Korem), the mean monthly rainfall is 72.88 mm, with total annual precipitation of 853 mm. August is the peak period for main rain season and April is the peak for the slight rain season. The area's mean minimum and maximum monthly temperatures are 7.1 and 25.6 °C, respectively, with a mean temperature of 16.8 °C (Figure 2). The dotted area on the left and right sides designates the dry season. The area's annual potential evapotranspiration (PET) is about 1411 mm (Elias, 2016). Figure 2 . Climatic diagram of Ayiba watershed from 1998- 2018 (NMSA, 2018). Like as noted in previous studies of northern highland Ethiopia (Delelegn et al., 2017; Gelaw et al., 2015; Tekle and Hedlund, 2000; Zeleke and Hurni, 2001), the natural woodland and vegetation of the study watershed had been abandoned in the last more than half century. Only tiny patches of remnant natural forests around churches are presently kept by psychic divining power. There has been religious thinking since antique that "any disturbance to the nature and spirit around the holly church (e.g., cutting a tree, leaving animal for grazing or browsing, etc.) will bring a catastrophic consequence” (personal communication with local elders and priests, 2018). The high rate of deforestation and forest degradation is driven by demand for wood products (for energy and construction purposes) and by pressure from other land uses, agriculture, and cattle ranching to support the alarmingly increasing population growth. Therefore, reducing deforestation and increasing reforestation are expected to make good economic sense in their own right and also support agriculture and rural livelihood. Mixed crop-livestock agricultural systems are the primary means of livelihood in the farming system (Elias, 2016). Cereal and legume crops and some vegetable and fruit crops are grown in the study area (Elias, 2016; Girmay et al., 2014). Wheat ( Triticum aestivum L.), barley ( Hordeum spp.), and Teff ( Eragrostis tef (Zucc.) Trotter) are among the significant cereal crops that supply the bulk of the staples for the population in the study area (Table 1). Legume crops such as fava bean ( Vicia fava L.), field pea ( Pisum sativum L.), Ethiopian pea (Dekeko in Tigrigna) ( Pisum sativum var. basidium ), lentils ( Lens culinaris or Lens esculenta ) are also cultivated for dual purpose, i.e., yield and rotation. Tef-wheat-legumes are the standard crop rotation practice in the area. Besides, some other vegetables and fruits like an onion ( Allium cepa L.), pepper ( Piper nigrum L.), cabbage ( Brassica oleracea L.), and apple ( Malus Domestica L.) are grown by farmers in the watershed (Gebresamuel et al., 2022; Girmay et al., 2014). Chickpea ( Cicer arietinum L.) is sown after harvesting using residual moisture (Table 1). Natural pasture is the primary source of animal feed in areas where farmers practice intensive pasture land grazing with a higher stocking rate, resulting in poor natural pastureland management (Atsbha et al., 2020). Table 1 . Main crops cultivated and the cropping calendar under main rain, short rain, and irrigation scheme in Ayiba area, northern Ethiopia. 2.2 Profile site selection and field description The free-soil survey (traverse survey) method was employed as a survey method along the landscape to detect the variability of soils in the watershed. A transect walk was made to cover the soils at varying physiographic positions and elevations with a team of experts to the Ayiba watershed. Field exploration was conducted to identify the significant soil units and localize profile sampling sites before the actual field survey. In addition, before soil sample collection was done, some basic information about the existing land was gathered from local farmers, elders, and extension experts. A provisional map (1:50,000) was prepared with predefined sampling points distributed throughout the watershed using ArcGIS 10.5 software. Extensive auguring was done to identify mapping units and sites for opening profile pits. The necessary soil survey facilities and formats such as the FAO guidelines for soil profile description (FAO, 2006a), WRB soil classification manual (IUSS Working Group WRB, 2015), Munsell color chart, GPS, soil profile, and auger description sheets were collected and prepared before fieldwork. Slope maps were extracted from a digital elevation model (DEM). The watershed was generally found within a slope range between nearly flat to slopping (1–8%) at the foot slope to steep sloping (>60%) at the upper slopes (Figure 3). Figure 3. Spatial slope map of Ayiba watershed, Northern Ethiopia. A catena was selected from the sloping land escarpment at the north to the valley floor at the south encompassing landform components spinning from crest/summit to foot slope/toe slope (Figure 4a). Accordingly, the selected toposequence was stratified into three landscape positions: upper (Crest + Shoulder), middle (Back slope), and foot (toe slope + depressions) slope positions and two profiles were opened at each place (Figure 4b). From an extensive series of observations along the toposequence, profiles were opened to a depth of 2+ m (unless soil depth is limited or is impracticable due to stoniness) with dimensions of 2 m x1.5 m on a site that was representative of each landscape position. All profiles were geo-referenced, and general site information and soil description were recorded (Table 2). Land use-wise, profiles 1 and 3 were excavated on grassland, while profiles 2, 4, 5, and 6 were excavated on cropland (Table S3). Profiles were described and sampled following the standard procedures to investigate soil morphological, physical, and chemical properties (FAO, 2006a; IUSS Working Group WRB, 2015). Soil morphological descriptions were completed in situ according to FAO guidelines (FAO, 2006a), and soil color notation was described using Munsell Color Company (2009). Figure 4 . (a) Cross profile CD dissected plateau of Ayiba watershed, and (b) conceptual toposequence model showing landscape position and profiles opened at the upper slope, middle slope, and foot slope, respectively. Table 2 . Some site characteristics of the studied profiles along the toposequence of Ayiba watershed, Northern Ethiopia. 2.3 Soil sampling and analysis A systematic stratified sampling procedure was used to distribute sampling throughout the watershed under careful consideration of topography and spatial pattern of land use. A global positioning system (GPS) was used to identify the sites’ longitude, latitude, and elevation. In all soil sampling procedures at each sampling spot, surface litter is scarped, and vegetation cover is removed before collecting samples. Sample spot excluding was also performed if a considerable difference is noted to minimize soil variability among subsamples for composite preparation to minimize outlying results. Soil morphology was described in the field to interpret their characteristics, and disturbed and undisturbed soil samples were collected from each genetic horizon (starting with the lowest horizon and working to the uppermost to avoid contamination) and from each land use type across the topography for laboratory analysis. Soil sampling locations were selected to best represent by considering variation in terrain attributes and drainage facilities. Soil samples were collected using a soil auger. Accordingly, 20 disturbed and undisturbed samples were collected from each generic horizon for soil characterization and classification analysis. The collected soil samples were spread for air-drying (to reduce oxidation of soil carbon), crushed and grounded by pestle and mortar, and sieved with a 2 mm sieve mesh for physical and chemical analysis. Rock fragments and gravels (>mm), visible roots, organic residues, and macro-fauna were removed manually at sampling time before pooling. Finally, the soil samples were taken to the laboratory for analysis. Analysis was done at Tigray soil laboratory center, Mekelle (Ethiopia), and plant nutrition laboratory, College of Environmental Science Resources, Zhejiang University, Hangzhou (China). All the soil samples were analyzed following the standard analytical procedures (Table 3). The interpretation of the measured soil properties was made using Table S1. Table 3 . Soil parameters and methods used to determine in this study. 2.4 Soil classification and mapping of Ayiba watershed Based on the morphological, physical, and chemical properties, the watershed soils were classified into different units (major soils) following the World Reference Base for soil resources (IUSS Working Group WRB, 2015). The presence or absence of specific diagnostic horizons, properties, and materials was used to distinguish soil units and subunits according to the WRB soil classification system. Soils identical in landforms, parent material, relief, topography, and morphology were considered similar and accorded a similar mapping unit. Spatial soil classification was based on the information obtained from field soil profile morphological description and laboratory analysis results following the IUSS Working Group WRB (2015) soil classification legend. 2.5 Soil capability and suitability assessment Soil properties and crop yields are strongly interrelated. Agricultural potential is directly related to Land Capability, as measured on a scale of I to VIII, as presented in Table 4 below; with Classes I to III classified as prime agricultural land that is well suited for annual cultivated crops, whereas Class IV soils may be cultivated under certain circumstances and specific or intensive management practices, and Land Classes V to VIII are not suitable for cultivation (Schoeman et al., 2002). This system is helpful in that it can quickly give one an overview of the agricultural capability and limitations of the soils in question and is helpful for soil capability comparisons. Criticisms of this system, however, include its lack of consideration of the local setting, land use planning, and a lack of financial resources (Nethononda et al., 2014). For this reason, the site's soil capability has also been assessed, taking the local setting into account from field checking. After a qualitative assessment, the soil types were grouped into the soil suitability classes (Table 5) and classified as very suitable, moderately suitable, marginally suitable, and not suitable soils for rainfed cultivation of annual crops (FAO, 1984; Ritung et al., 2007). The suitability of a given piece of land is its natural ability to support specified land use, such as rain-fed agriculture, livestock production, forestry, etc. Table 4. Land Capability Classes, limitations, and land use (Schoeman et al., 2002). Table 5. Definition of the soil suitability classes (FAO, 1984; Ritung et al., 2007). 2.6 Statistical data analysis and software used Soil data obtained from the laboratory work were checked to test the data sets' normality with the Shapiro-Wilk normality test before analysis using R software for Windows. The normality assumption was not violated. Descriptive statistical analyses and variances were then tested following the general linear model (GLM) procedure to obtain the effect of the model: using one-Way ANOA to see the variation among the generic soil horizons. Whenever significant differences among horizon means have been detected, the analysis of variance used Tukey's HSD test at a p <0.05 level of probability to differentiate. Data in the present study were presented as mean±SE. Finally, GIS software (version 10.5) was employed to produce the spatial soil maps of the Ayiba watershed. 3. Result 3.1 Profile site and soil morphological characteristics The site characteristics of the profiles indicated differences in slope, drainage, and extent of water erosion (Table S2). According to FAO (2006a) guideline, the opened profiles were positioned in a slope gradient range of gently sloping to very steep. The upper and middle landscape comprises most of the sloping to very steep slope gradient classes (Figure 3). All profiles were well-drained, but AYB-5 was found poorly drained. All Profile sites showed a range of water erosion processes manifested by sheet, rill, and gully formation (Figure 5). Effects of land use, extensive and intensive farming, and removal of vegetation cover have amplified the erosion process, which was observed at all profiles and their surrounding landscapes. The land use of AYB-1 and 3 are grassland lying on soil developed from basaltic and colluvial parent materials. Whereas that of AYB-2, 4, 5, and 6 represented annual rainfed field cropping with varying land-use histories having soils developed from the outwash of colluvium and alluvium basaltic materials. Rainfed cultivated land, grassland, plantation forest, and barren land were the typical land use type of the upper and middle slopes (eroded sites), while cultivated land and grassland land use dominated the foot slope of the watershed (Seifu et al., 2020). Figure 5. Field photographs of (a) Sheet erosion (upper slope), (b) rill erosion (middle slope), and (c) active gully erosion (foot slope) around the profiles along the soil catena. Most profiles unveiled an A-B-C master horizon sequence. Morphological characteristics of each horizon’s color, texture, structure differentiation, etc., are presented in Table 8. The soil depth varied from 53 cm (shallow) at the upper position to 200+ cm (very deep) at the foot slope position. The thickness of the A-horizon ranged from 0-35 cm along the toposequence. AYB-1 was the shallowest profile indicating little influence of soil-forming processes as rock debris does not accumulate on the spot since they roll down due to gravity. According to IUSS Working Group WRB (2015), the surface horizon of AYB-1 qualifies for mollic epipedons. The diagnostic epipedons of AYB-2 and 3 qualify for argic due to illuvial clay accumulation, high selective clay surface erosion, and the absence of lithic discontinuity. The diagnostic horizons of AYB-4, 5, and 6 were also qualified as paralithic , vertic , and cambic , respectively. Except for AYB-4, which has a weakly developed soil horizon, all the other profiles had well-developed morphological characteristics and deeper rooting depth. AYB-4 is somewhat a strange profile in soil development as it has an A-R-B-R master horizon sequence with a very shallow rooting depth (<35 cm) due to the presence of a lithic contact (R layer) which may probably be developed from the loss process by water erosion. A significant quantity of clay translocation and many distinct clay cutans were observed in the subsoils of AYB-2 and 3 profiles, indicating that eluviation-illuviation processes are active. At the same time, AYB-1 is developed as a result of melanization. AYB-5 and 6 profiles in the foot slope showed a slight clay increase with soil depth but did not qualify for the argic B horizon. In this study, the soils have a color hue of 2.5 – 10YR, a value of 2 - 5, and chroma of 1 - 4 in dry and moist conditions. With this range of color matrix, the soil color of all profiles varied from black to greyish brown (dry) and black to yellowish brown (moist). Boundaries between A- horizon and B- horizon were evident due to the darkening effect of organic matter. The field soil texture by feel method varied in all profiles across toposequence. The surface texture of profiles AYB-1, 2, and 5 were clay dominant, while that of AYB-3, 4, and 6 were sandy loam dominant. The moisture status of surface horizons AYB-1 and 3 were slightly moist. At the same time, AYB-2, 4, 5, and 6 were dry, which might be interconnected to soil organic matter and clay within the horizons. The horizon boundaries, by distinctness-topography, of profiles 1 to 6 had clear-smooth, clear-wavy, clear-smooth, clear-smooth, diffuse-smooth, and diffuse-smooth, respectively. Horizon boundary characteristics also showed slight variations among and within studied profiles along the toposequence (Table 6). Regarding soil structure, all soils were generally friable on the surface but became firm in the subsoil. Explicitly, profiles 1 to 4 had weak to moderate grade surface structure and weak to strong grade subsurface structure in the upper and middle catena. Likewise, in terms of type and size, all profiles were found in massive to crumbly and very fine to medium textured. In AYB-5 the soil structure in the surface horizons is mainly lumpy, mostly created by tillage disturbance, and slightly hard. In the subsurface horizons, soil morphology changes from subangular blocky forms to weakly developed coarse blocky horizons. In AYB-6, soil structure indicated weak to moderate grade, massive to crumbly type, and fine to medium size. In the foot slope, infiltration is slow, and water may stand on the surface in the rainy season for extended periods. All soils exhibited varied consistency in dry, moist, and wet conditions, mostly following friable on the surface and becoming firm in the subsoil (Table 6). Except for AYB-5 at its lower layers showed very slightly effervescent (formed few bubbles), in other profiles, the field CaCO 3 (using 1N HCl solution) was noneffervescent. Table 6. Morphological description of the six profiles studied. 3.2 Soil physical characteristics of the profiles 3.2.1 Soil particle size distribution and clay contrast index The particle size distribution revealed a variation along the toposequence ranging from 18-68%, 14-53%, and 6-68% for sand, silt, and clay parts, respectively. As a result, textural classes of the soils varied from clay to sandy loam texture along with the topography (Table 7). Generally, clay dominates the soil's particle size fraction, followed by sand, then silt. In almost all profiles, percentage sand and clay parts follow decreasing and increasing trends, respectively, with depth in the geomorphic units, except AYB-3 was inconsistence. On the other hand, higher sand content in the surface layer is associated with the selective removal of clay and silt by erosion, as the degree of sand transportability is lower compared to the finer soil fractions. In this study, we have also observed a seasonal water logging at the foot slope, which may probably cause deterioration of structured B-horizon and dispersion of clay particles down with water table front The silt/clay ratio ranged from 0.21 - 4.33 along with the topography, and the ratio ranges from 0.29 – 4.33 in the A-horizons and from 0.21 – 2.94 in the B-horizons and decreases with depth. The highest value of the silt/clay ratio was recorded in the A h -horizon (4.33) of profile 4, followed by the Bw-horizon (2.94) of profile 3, and the lower was recorded at the lower subsoils of AYB-2 (Table 7). The clay contrast index (CCI) ranged from 0.40-0.95, with the highest at AYB-1 and the lowest at AYB-3. Higher CCI indicates lower textural differentiation, while lower CCI indicates higher textural differentiation in the profiles. Accordingly, the clay enrichment of the profiles was found in the following decreasing order: AYB-1 (0.95) < AYB-2 (0.89) < AYB-5 (0.85) < AYB-6 (0.80) < AYB-4 (0.75) < AYB-3 (0.40) (Table 7). AYB-1 to 4 are located on the middle and upper topography, mainly manifested by sloping to a steep slope gradient (Figure 3), intensively cultivated land with free grazing experiences, which all induced erosion on the site and lower clay content by removing the upper horizon. 3.2.2 Bulk densities, total porosity, and water retention capacity The surface bulk densities (BD) of the studied profiles ranged from 1.13 g cm -3 in the A-horizon of profile 1 to 1.46 g cm -3 in the A-horizon of profile 4. In comparison, the subsoil BD ranged from 1.27 g cm -3 in the Bt-horizon of profile 2 to 2.32 g cm -3 in the Bc-horizon of profile 5 (Table 7). The BD along the identified soil horizons was increased with depth. Furthermore, the gravimetric water content of the soils at field capacity (1/3 bar) ranged from 17.9-44.2%, while the amount at the permanent wilting point (15 bar) was between 9.1-32.55%, and the volumetric plant available water content (AWC) of the soils varied from 88-127.8 mm m -1 across soils of the topography (Figure 6). The water retention capacity of AYB-3 was higher, followed by AYB-1 and 2 compared to the other profiles. This may be attributed to relatively higher organic matter and clay values observed in these profiles. Surface soils recorded slightly higher water content at FC and PWP than subhorizon soils. Subhorizon soil water retention at FC of the soils of the study watershed ranged from 24% in Profile 3 to 46% in Profile 2, whereas in the subsurface horizons, it ranged from 12% in Profile 3 to 45% in Profile 2. Available water content (AWC) showed a decreasing pattern but was inconsistent in the lower subsoil of profile 3, which may be due to textural change after the 4 th layer. In surface and subsurface soils, AWC ranged from 10 to 12 and 9 to 15(v %), respectively. Table 7. Soil physical properties were analyzed for the studied profiles along the toposequence. Figure 6. The studied soil profiles average water retention capacity (FC: Field capacity, PWP: permanent wilting point, AWC: Available water content). Error bars indicate the standard error of the mean. 3.3 Chemical characteristics of the studied soils 3.3.1 Soil pH, soil EC, and soil calcium carbonate content The soils are found in the range of neutral to moderately alkaline for pH-H 2 O and the range of moderately acidic to neutral soil reaction for pH-KCl (EthioSIS, 2014) in nature, with pH values varying from 7.14 to 8.31 (pH-H 2 O) and 6.31 to 7.27 (pH-KCl). The pH variation among each generic horizon differed significantly (Table 8). In all soil horizons, pH (H 2 O) was higher than pH (KCl). The delta pH values, the difference between pH (KCl) and pH (H 2 O), indicated that the soils have net negative charges and will hold positively charged ions on the colloidal particles of the exchange site. Regarding the soil electric conductivity (EC), the average values were found in the range of 0.19 (AYB-4) to 0.35 mS cm -1 (AYB-3) with a range between 0.17 to 0.26, 0.15 to 0.32, 0.23 to 0.52, 0.16 to 0.22, 0.09 to 0.38, and 0.22 to 0.49 mS cm -1 in AYB-1 to 6, respectively (Table 8). The EC was generally found very low for all analyzed horizons. Hence, all soils of the profiles were found non-saline, indicating salinity effect on crop growth and yield restriction is below the level it affects or almost negligible (EthioSIS, 2014). The low EC may be due to free drainage conditions, favoring the removal of released bases by percolation and drainage. Table 8. Soil reaction, electrical conductivity, and CaCO3 of soil profiles. Calcium carbonate (CaCO 3 ) content of the surface soils also ranged from 0.35 (AYB-3) to 0.63% (AYB-6), whereas in the subsurface soils, it ranged from 0.62 to 1.14%. Significantly ( p <0.001) higher CaCO 3 content was recorded in the subsoil compared with surface soil (Table 8); which might be due to the parent material or due to the semi-arid climate, which is responsible for the pedogenic processes resulting in the depletion of Ca 2+ ions from the soil solution in the form of calcretes. The CaCO 3 content of the soils ranged from 0.38 to 1.14%, showing an increasing trend with soil depth. The variation with each generic horizon was significant. The field determination of carbonates with 10% HCl also confirmed that there was no audible and/or visible effervescence throughout the soil depth except for a few observed at the subsurface of AYB-5. 3.3.2 The SOC, TN, and C/N ratio analysis Soil organic carbon (SOC) and total nitrogen (TN) were recorded higher in the surface soils and significantly (Table 9) decreased with soil depth with average values ranging between 0.78 and 2.53% and 0.10 and 0.21%, respectively. In comparison, the SOC of subsurface layer soils ranged from 0.62% on the middle slope of degraded grassland (AYB-3) to 1.87% on the upper slope of the exclosure grassland (AYB-1). The TN content of the surface horizons was higher than the subsurface soil horizons, and it followed a similar pattern to that of SOC in all the studied profiles, implying a strong relation between SOC and TN in the soil system. The amount of SOC and TN were relatively high (3.19 and 0.25%, respectively) at the upper slope position of the surface horizons, which might be attributed and correlated to the biomass turnover of the grass. The C/N ratio of the surface soils along the toposequence in the study area ranged from 4.51 to 12.78, while in subsoil horizons, it ranged from 5.44 to 14.04 with an average range of 6.15 to 12.61(Table 9). The variability of the C/N ratio was not significant in each profile, indicating that it was lower than the variability of SOC and TN contents. It may suggest that the C/N ratio is more stable than its elements. Besides, the low variation in the C/N ratio across horizons suggests less variability in the degree of humification of organic matter. On the other hand, in the buried horizons of AYB-5 and 6, the C/N ratio was slightly higher than in the rest of the horizons, which might be probably due to the long-accumulated/sediment undecomposed material rich in carbon in the soil. In almost all profiles, the C/N ration demonstrates a decreasing or increasing systematic variation with depth, suggesting the existence of similar conditions of mineralization in the recognized horizon (Table 9). Table 9. The studied soil profiles are SOC, TN, and C/N ratio, available P, S, and B. 3.3.3 Soil available P, S, B, Exchangeable base, CEC, and base saturation analysis The available phosphorus (av. P) content of the profiles was high in the surface horizons of all profiles, which could be attributed to the relatively higher organic matter contents in the surface layers, application of phosphorus-containing fertilizer on cultivated lands, and presence of free Iron oxide and exchangeable Al 3+ in reduced quantity. Available P content of the soils declined with increasing profile depth in all profiles, but spatially the trend was not consistent - the measured av. P was significantly variable (Table 9) among the different generic horizons except in AYB-4. The highest and lowest av. P was recorded in AYB-5 of Ap and CR horizons. The overall profile means of av. P content was found in 26.52 to 40.09 mg kg −1 soil across the topography (Table 9) and decreased with depth. Regarding Sulphur (S) and Boron (B), the result obtained for both follows the trend of av. P (Table 9). In this study, the average available S content in the studied soil profiles ranged from 0.67 mg kg −1 in profile 2 to 0.80 mg kg −1 in profile 5 (Table 9). The highest and lowest av. S was recorded in AYB-6 of Ap and Bw horizons, respectively. While, av. B was found in the range of 0.19 mg kg −1 soil in the Bw horizon of AYB-1 to 0.77 mg kg −1 soil in the Ap horizon of AYB-6, with an average range of 0.24 to 0.77 mg kg −1 soil across the landscape. In the studied soil profiles, the result revealed that the content of exchangeable Ca 2+ was the dominant exchangeable base, followed by Mg 2+ along the toposequence. Exchangeable basic cations are found in the range 0.07 - 0.49, 0.22 - 2.12, 2.46 - 10.20, and 4.46 - 27.10 across the landscape for Na, K, Mg, and Ca, respectively (Table 10). Generally, the abundance of cations occupying the exchange site followed the order of Ca 2+ > Mg 2+ > K + > Na + throughout the profiles, which was found in how a productive agricultural soil should contain these basic cations. The percent base saturation (PBS) of the soil of the study area varied from 18.7 to 99.4%. Soil horizons in AYB-2 and 6 were recorded as high-value PBS compared to others. Regarding Cation exchange capacity (CEC), the overall CEC of the studied soils ranged from 28.7 to 54.52 cmol (+) kg -1 soil along the toposequence (Table 10). The lowest and highest values were recorded in the topsoil of AYB-2 (cultivated land) and AYB-3 (grassland). Table 10. Exchangeable base (Na, Mg, K, and Ca) and CEC of the studied soil profiles along the toposequence. 3.3.4 Extractable Micronutrients (Fe, Cu, Zn, and Mn) In the studied soil profiles, the mean values of extractable micronutrients (i.e., Fe, Cu, Zn, and Mn) in different soil depths are presented in Table 11. Table 11. Micronutrient availability in the studied soil profiles along the toposequence. The contents of available micronutrients varied with soil depth and showed a decreasing trend with increasing depth. However, their trend with topographic position is inconsistent. The contents of extractable Fe, Cu, Zn, and Mn in the studied profiles ranged from 11.42 to 21.10, 1.15 to 3.79, 0.15 to 1.16, and 3.93 to 12.88 mg kg −1 soil, respectively. The extractable micronutrients followed the order of Fe > Mn > Cu > Zn in their concentration in all profiles across the landscape. The result showed that the surface soil layers had higher contents of available micronutrients than the subsurface soil layers. Mean values of the surface layers' extractable micronutrients were significantly varied compared to the subsurface layers (Table 11). In contrast, the mean difference among profiles along the toposequence was insignificant. 3.4 Soil classification and mapping The soil classification system and maps are the final steps of the soil survey, asserting soils by similar characteristics and/or properties and making the knowledge accessible to policy-makers, farmers, and the scientific community (Bockheim et al., 2014). Soil maps, which can be effectively produced with statistical models in digital soil mapping (DSM), contain vital information on the spatial distribution of soil properties used in fields such as water- and land management and climate studies (van der Westhuizen et al., 2022). Currently, Mendes and Demattê (2022) and Hartemink and Bockheim (2013) explained that soil maps at regional and farm levels are essential for the best management of agricultural practices. Therefore, based on the morphological, physical, and chemical properties, the studied soil profiles were classified according to FAO/WRB legend (IUSS Working Group WRB, 2015). Accordingly, five soil orders were identified: Leptosols, Luvisol, Fluvisol, Cambisol, and Vertisol (Table 12, Figure 7). As reported by Nyssen et al. (2019), Leptosols and bare rock are found on the steepest slopes (>40%), which is concurrent with our result. Table 12. Classification of soils studied at Ayiba watershed according to the FAO-WRB Soil Classification System. Figure 7. Spatial soil map of Ayiba watershed according to WRB system. 3.5 Potential and Limitation of the Studied Soils for Agricultural field crops The soil units represented by AYB-1 and AYB-4 are not suitable for agricultural use (Table 13) due to stoniness, slope steepness, shallow depth, rock outcrops, and highland position with erosion threats and other soil restraining factors which limit the workability of the soil. Hence, agricultural production on these soils will cause a decrease in yield and soil loss due to high erosion hazards, and cultural approaches such as soil cultivation, irrigation, and fertilization are not economically feasible. Thus, it is essential to perform conservative and sustainable agricultural practices in these areas like pasture, perennial fruits, and forests. The lower slope area's soil is very suitable for field crop agricultural use with limited fertility, low erosion, and climate. However, the lower slope soils represented by AYB-5 and AYB-6 are very limited in area coverage to accommodate the population size, which is the main reason for expansion to marginal lands. Besides, during high and prolonged rainfall, the flood flow from all directions is collected to the lower landscape position, damaging farms and grasslands by flood hazards (Seifu et al., 2020). In addition, during the high rainfall season, waterlogging is also common in Vertisol soils and the foot slope soils. However, most agricultural production occurs on the middle topography, which is marginal land, and this unsustainable land use contributes to low and declining crop productivity and further land degradation. The substantial area of marginal lands, many of them in steep areas (<30%) with coarse and degraded soils, could adopt sustainable agricultural technologies like integrated organic and inorganic management practices or growing double legumes to improve the long-term sustainability of the system. Not suitable areas must be excluded from land spreading plans due to the high risk of degradation (environmental, economic, and societal). In contrast, an improvement or remediation plan should be developed and implemented. The soil units in the lower landscape and at a nearly gentle slope of the middle terrain have well-drained, deep soil and are less stony than others. However, erosion, climate, and soil fertility are still significant problems in all topographic positions for agricultural production (Table 13). Table 13. Suitability classification of the different soil units for agricultural field crops. 4. Discussion 4.1. Profile site and soil morphological characteristics The slope, parent materials, and land use types are the major contributing factors to the differences in site characteristics. Effects of land use, extensive and intensive farming, and removal of vegetation cover have amplified the erosion process, which was observed at all profiles and their surrounding landscapes. Debie et al. ( 2019 ) also confirmed that accelerated soil erosion by water is a critical problem in Ethiopia's soil landscape. For instance, Ibrahim et al. ( 2020 ) reported upper topography was well-drained while the middle and valley bottom was poorly drained, and soils in the lower topographic locations were saturated with moisture longer than upper slope soils. Likewise, previous research findings also highlighted that erosion intensity might depend on slope class, topographic position, and land use (Deressa et al., 2018 ; Schaetzl, 2013 ). Schaetzl ( 2013 ) reported that slope controls the movement of matter and energy downslope. It has minimal summit position and an erosional, transportational, and depositional effect on shoulder, middle, and foot slope positions. Soil color may vary with depth in the soil profile and from place to place in a landscape (Phogat et al., 2015 ). Soil color is also used to determine soil classification and its physical, chemical, and biological properties (Baek et al., 2022 ). The variation in soil color matrix noticed within and amongst the profiles might be attributed to the soil's difference in mineralogy and chemical composition, organic matter and clay contents, and drainage condition, which may affect the redoximorphic responses in the soils. Moreover, the yellow and brown color is typically related to the extent of oxidation, hydration, and diffusion of Iron oxides in the soils and mostly due to the presence of goethite and magnetite, respectively (Phogat et al., 2015 ). For instance, the darker color indicates the presence of higher decomposed organic matter ( humus ). As a result, most surface layers have a darker color than subsurface horizons. Others reported similar results in Ethiopia and China (Abate et al., 2014 ; Ali et al., 2010 ; Beyene, 2017 ; Dinssa and Elias, 2021 ; Liu et al., 2016 ). The subsurface horizon (< 80 cm) soil color of the foot slope was dark grey to brown, suggesting that soils comprised fine-textured colluvial and alluvial materials. In harmony with this work, Tunçay and Dengiz ( 2020 ) reported a similar result in Turkey's central Black Sea Region. Soil structure, which refers to how particles of soil are grouped by physical, chemical, and biological processes, is most usefully described in terms of grade (degree of aggregation), class (average size), and type of aggregates (form). The robust structure formed in the subsurface horizons is due to the overlying layers, reduction in organic matter, high clay accumulation, and reduction in plant root abundance, as was also discussed by a previous study (Dinssa and Elias, 2021 ). From A-horizon down to the bedrock R-horizon the structure changes from massive to crumbly structure with depth. All the six profiles showed weak grade granular type soil structure in the A-horizon due to relatively high organic matter content, and the gravel content was observed to be higher in the parent material layer (Boateng et al., 2013 ; Dinssa and Elias, 2021 ; Yitbarek et al., 2016 ). The sticky to very sticky/plastic to very plastic consistency in surface and subsurface horizons indicated low organic matter content and hard to work with these soils. On the other hand, soils with very sticky and very plastic consistency revealed that smectite clays in the soils are high (Ali et al., 2010 ; Kumari and Mohan, 2021 ). Dinssa and Elias ( 2021 ) and Ayalew et al. ( 2015b ) reported a similar result in the soils of Bako Tibe district and Yigossa watershed, Ethiopia. In northern Ethiopia, Nyssen et al. ( 2019 ) also analyzed those mass movements in many landscapes that transported materials from their in situ upland basaltic over the lower-lying sedimentary rocks, raising the chance for clay soil to develop. Available water for plant roots is strongly affected by stoniness (Nyssen et al., 2019 ), and the soil texture becomes fine with an increase in plant root components (Liu et al., 2016 ). 4.2. Soil physical characteristics of the profiles Soil texture is the most stable physical property which influences other soil properties like soil structure, consistency, soil moisture regime and infiltration rate, runoff rate, erodibility, workability, permeability, root penetrability, and fertility of the soil. The soil texture distribution of the fine earth fraction demonstrates an abrupt textural change between surface and subsurface horizons, where an increase in clay is accompanied by a decrease in sand-sized particles across the horizon boundary. The general increase in clay content with depth might be attributed to the vertical translocation of clay through the processes of lessivage and illuviation from surface to subsoil. Likewise, others have reported many findings in different parts of Ethiopia (Fekadu et al., 2018 ; Kebede et al., 2017 ; Yitbarek et al., 2016 ). According to Hazelton and Murphy ( 2016 ) rating the general abundance of the particle distribution was found in low to medium sand, low silt, and very high clay at upper slope profiles; high to very high sand, low to medium silt, and low clay at middle slope profiles; and low to very high sand, low to medium silt, and low to high clay at foot slope profiles. The variation indicates that topography influences the pattern of soil particle distribution over the landscape (Esu et al., 2008 ). The decreasing or increasing pattern in soil fractions with depth indicated the existence of soil water erosion from in situ formation or accumulation and weathering of primary minerals in B-horizons. For instance, the increase in clay content with depth indicates clay migration or probably shows the presence of active eluviation-illuviation pedogenic processes. In contrast, the seasonal water erosion effect and redoximorphic features could explain the decrease at the surface horizon. Clay translocation and enrichment fulfilled requirements for the argic subsurface horizon development (IUSS Working Group WRB, 2015 ; Soil Survey Staff, 2014 ). The variation in soil development may be due to unstable landscape features (rugged and sloppy) where pedogenesis trends are often altered. The water logging at the foot slope, which may probably cause deterioration of structured B-horizon and dispersion of clay particles down with water table front, was similarly reported by Choudhury et al. ( 2016 ). Other authors Li and Lindstrom ( 2001 ) correspondingly explained that water erosion has the potential to modify the spatial patterns of soil properties on hilly landscapes. Our result is also consistent with the justification of Ellerbrock and Gerke ( 2013 ). They revealed that soil particles could be transported along slope gradient during erosion, accumulate in the foot slope position (depressions), and form colluvial soil. Likewise, others also observed a decrease in fine fractions in the steeper slope due to the selective removal of fine particles by water erosion (Ezeabasili et al., 2014 ; Seifu et al., 2020 ; Wubie and Assen, 2020 ). Contrary to our result, Uwitonze et al. ( 2016 ) reported that particle size distribution did not show a clear trend with depth, and Amanual et al. ( 2015 ) described clay content as higher on the top and declining with depth. Bald (2012) reported a similar justification suggesting that clay deposition in the subsurface is episodic, possibly in conjunction with the wet and dry cycle climate experience, regarding the eluviation-illuviation pedogenic processes. According to this idea, fine-grained deposits may be converted into typical loess due to weathering and soil-forming processes. The silt/clay ratio of the subsoil is lower than the surface horizons, and the higher percentage in the surface layers reflects the annual alluvial enrichment of the surface through deposition by annual floods. Such a result suggests the presence of weatherable mineral reserves in the soil (Elias, 2017 ). The result agrees with the report of other findings in Nigeria and Ethiopia (Adegbite et al., 2019 ; Mohammed et al., 2017 ; Sharu et al., 2013 ). According to Asamoa ( 1973 ) and Egbuchua and Ojobor ( 2011 ), the silt/clay ratio below 0.15 indicates that such soils are of old parent material, while those above 0.15 are of young parent materials. Therefore, in our case study, all the profiles along the toposequence recorded far above 0.15, confirming that the soils are young with weatherable reserve materials and have not gone through ferralitic pedogenesis, which was in accord with other findings (Achimota, 2021 ; Adegbite et al., 2019 ; Van Ranst and De Coninck, 2002 ). The variations in degrees of clay enrichment were related to slope positions and land use. The relatively small differences between the highest and lowest amounts of clay contents in the foot slope position are attributed to active pedoturbation through the shrink-swell phenomenon. While the high clay enrichment ratio in the upper position of AYB-1 is probably due to minimum erosion occurrences mainly happened splash and sheet erosion in which its severity is highly correlated to rainfall intensity and longevity. Crusting is more severe in coarse and medium-textured soils than in fine-textured soils, and soils with an organic matter of less than 1% are more prone to crusting (Phogat et al., 2015 ). The relatively lower BD values obtained at the surface soil horizons may be attributed to the structural aggregation of the soils due to relatively high organic matter content and congelifraction. This facilitates the development of porous soil structure with low rooting impedance (Brady and Weil, 2017 ; Washburn, 1979 ), which is common in high latitudes and altitudes (Anonymous, 2008 ). Besides, soil compaction resulting from intensive cultivation and overgrazing might have caused higher bulk density values in the cultivated, and free grazing land uses compared to others. Soil type may be a possible reason for high bulk density and low porosity. Compaction affects nearly all soil properties and functions, affecting roots' growth, distribution, function, and crop productivity. Correspondingly, others reported an increase in soil strength further down the soil profile (Ali et al., 2010 ; Chaudhari et al., 2013 ; Gao et al., 2016 ). The ideal BD for plant growth ranges from < 1.10 g cm − 3 for clay to < 1.6 g cm − 3 for sands (Schoonover and Crim, 2015 ). Thus, following the aforementioned critical values for root penetration, some are expected to be limited and affected, while the rest are in a reasonable range. Per the rating system of the effect of BD on soil condition (Hazelton and Murphy, 2016 ), profiles at upper, middle, and foot slope topography are too compact to very compact, very open to satisfactory, and very available to excessively compact, respectively. The bulk densities in the studied area were moderate in the upper and middle landscape, whereas low to very high in the foot slope landscape. The good record shows that BD is not expected to impede root penetration and water movement restriction in these soils. Nevertheless, the BD values of the studied soils are favorable for crop production since the values are within the range that favors the growth of crops in tropical soils. However, profile 5 (Vertisols) were recorded with relatively high BD ( ≥ 1.6 g cm − 3 ), which might be due to the smectite/montmorillonitic group of clay minerals which show cracks between hard clods when dry and are difficult to till. Such soils need corrective management like manuring, cover crop, and other agronomical recommended field management to Vertisols soil types. Bulk density values exceeding 1.8 g cm − 3 indicated the likely presence of duripans or fragipans (Kefas et al., 2020 ). In addition, the total porosity also almost lay within the usual range of 30–70% (Hazelton and Murphy, 2016 ). Hence, most soils in the Ayiba watershed have an acceptable range of total porosity values for crop production. Water content plays a central role in soil physical dynamic processes, and high water retention capacity enables soils to have more water, which acts as a moisture reserve for plants during water shortage periods (de Lima and da Silva, 2022 ). Soil water holding capacity for use by plants is critically important for all farmers. Soil that stores large amounts of water without waterlogging problems can keep plants alive and well for prolonged periods during droughts. Topography influences soil properties through two main “tools”: The gravity-driven lateral migration and accumulation of water and spatial differentiation of the temperature regime of slopes (Florinsky, 2016 ). According to Hazelton and Murphy ( 2016 ), available soil water holding capacity (%v) for a soil profile is rated as low ( 20). Hence, the AWC at the upper slope was found medium, while low to medium in the mid and foot slopes. Soils that fall below the stated ideal range are probably due to high bulk density caused by intensive cultivation, unrestricted grazing, and low organic matter content due to the complete removal of crop residue. 4.3. Chemical characteristics of the studied soils The lowest pH reading was found in the upper horizon soils at each site, with higher pH values at depth which might be due to the movement of cations from surface soil to subsurface soil. Similar results were also observed and reported by others (Ali et al., 2010 ; Ayalew et al., 2015a ; Sharu et al., 2013 ; Yitbarek et al., 2018 ), who confirmed that an increment in soil pH down horizon might indicate the presence of vertical movements of exchangeable bases, which is caused by decreased in organic matter content with depth. All soil pH records documented at the study site are favorable for most crops per the pH scale stated by EthioSIS (2014) and Hazelton and Murphy ( 2016 ). The low EC may also be due to free drainage conditions, favoring the removal of released bases by percolation and drainage. The variation in soil pH is probably attributed to the nature of the parent material, leaching of basic cations, and presence of CaCO 3 and exchangeable Na as discoursed by Deressa et al. ( 2018 ) and Shalima and Anil ( 2010 ). The higher concentration of CaCO 3 at the subsurface than at the surface horizons might be ascribed to the effect of leaching and parent material which was in accord with the result of others in Ethiopia and else (Ahmed et al., 2018 ; Debele et al., 2018 ; Ozsoy and Aksoy, 2007 ; Sebnie et al., 2021 ). Regarding the rating of CaCO 3, there is no clear and precise rating for the contents of free carbonates, but values of over 40% can be considered highly calcareous (Avery, 1964 ). In addition, FAO ( 2006a ) also stated that soil horizons having a CaCO 3 content of > 15% within 100 cm from the soil surface qualifies for a calcic horizon and such high carbonate contents affect both physical and chemical properties of soils. In the current study, the level of CaCO 3 is recorded far < 15%, which is a very low rate. The results obtained regarding SOC and TN are similar (Akhtaruzzaman et al., 2018 ; Fekadu et al., 2018 ; Ibrahim et al., 2020 ; Ostrowska and Porębska, 2015 ) who quantified SOC and TN that showed significant variation in depth. The values are under the category of low to very low rate for SOC and medium to very low rate for TN according to the rating of EthioSIS (2014), and this coincides with the amounts usually present in arid climates due to the rapid rate of mineralization. The low SOC and TN in most profiles could be ascribed to the removal of vegetation at the expense of cultivation and complete removal of crop residue mainly for livestock feed, limited use of organic fertilizer sources, unrestricted grazing, and rigorous cultivation, which was similar to the result observed in other studies (Ali et al., 2010 ; Elias, 2017 ; Fekadu et al., 2018 ; Sebnie et al., 2021 ). As a result, the low SOC and TN content recorded on most soils cannot sustain crop production for a long time. Thus, the organic matter content has to be substantially enhanced through effective crop residue management and organic fertilizers. The lower the C/N ratio, the faster the decomposition of fresh organic matter. Thus, the C/N ratio influences the decomposition of organic matter, either toward the primary mineralization (low C/N), or towards humification (high C/N) (Yerima and Van Ranst, 2005 ). The C/N ratio mainly controls the decomposition rate and is a source of food and energy for plants in the soil. The higher C/N percentage leads to a slow decomposition rate, nutrient immobilization, and wastage of carbon and energy. In contrast, quite the reverse, in low C/N ratio, but carbon and energy starvation occur and the C/N percentage varies from 10 for leguminous and young plant materials to about > 100 for cereal straws (Thippeshappa and Vadivel, 2011 ). The C/N ratio in plant tissue is variable, depending largely on plant species and age. Still, the end-product of plant tissue decomposition is always humus which has a reasonably constant C/N ratio (Yerima and Van Ranst, 2005 ). The variability of the C/N ratio was not significant in each profile, indicating that it was lower than the variability of SOC and TN contents. It may suggest that the C/N ratio is more stable than its elements. Likewise, in agreement with our finding, Kirkby et al. ( 2011 ) observed insignificant differences between C/N ratios in SOM and the soil. Others like Yitbarek et al. ( 2016 ) in the Abobo area, western Ethiopia, and Yimer ( 2017 ) in the central rift valley area of Ethiopia also reported a similar result. Although the decomposition rate was not measured, a higher C/N ratio signifies moderate stress in the microbial decomposition of organic matter and N-mineralization (Elias, 2017 ). The soil C/N ratio is often considered a soil nitrogen mineralization capacity sign. A C/N ratio of about 10 suggests a relatively better decomposition rate. It indicates better nitrogen availability to plants, and there will be possibilities to incorporate crop residues into the soil without the adverse effect of nitrogen immobilization. According to Gebreselassie ( 2002 ), the optimum range of the C/N ratio is about 10:1 to 12:1, which provides nitrogen over microbial needs. Yerima and Van Ranst ( 2005 ) also classified the C/N ratio as low ( 50). Accordingly, the C/N ratio of the surface soils across the topography may be considered below the optimum range in all soils for microbial needs except at AYB-1 and 6. Sakin et al. ( 2010 ) found the C/N ratio of arable soils much lower than 10, which might indicate N input from external sources, mainly from fertilizers and deposits. On the other hand, prolonged intensive farming also led to a continuous increase in soil nitrogen (Deng et al., 2014 ; Yang et al., 2021 ). The lower P content in the subsurface horizons could be ascribed to the fixation of P by clay minerals and oxides of Iron and Aluminum. The overall profile means av. P content was found in harmony with the result observed in other studies (Bekele et al., 2021 ; Debele et al., 2018 ; Fekadu et al., 2018 ; Raghuvanshi et al., 2020 ; Sebnie et al., 2021 ). Based on the ratings of EthioSIS (2014), the average av. P content was found in the low to medium category. Phosphorus deficiency in Ethiopian soils is well documented as a result of depletion and slow recycling due to a fixation on the inherent low occurrence (Bekele et al., 2021 ; Elias, 2016 ; Fekadu et al., 2018 ; Mesfin et al., 2017 ). Moreover, the low content of av. P could be attributed to fixation by Ca content as Ca-P (Ca bounded) – the significant inorganic P fraction in alkaline soils (Landon, 2014 ). The S and B in agriculture are now gaining importance because their role in increasing crop production is recognized. Available S is the primary source of S taken up by most crops. The source is the SOM via the microbial pool or directly from animal residues, atmospheric inputs, or fertilizers (Zebire et al., 2019 ). Whereas B, usually present in soil solution as a non-ionized molecule (H 3 BO 3 ), is an essential trace element desired for the physiological functioning of higher plants. B deficiency is considered a nutritional disorder that adversely affects the metabolism and growth of plants because B is involved in the multi-structural and functional integrity of the entire plant system. The difference between deficiency and toxicity limits is very narrow; hence, B requires judicious fertility management (Das and Purkait, 2020 ; Shireen et al., 2018 ). Das and Purkait ( 2020 ) also emphasized that site-specific and crop-specific nutrient management should be taken care of while dealing with B soils under divergent geographical and climatic zones. Generally, the av. S and B contents of the studied soil profiles decreased with profile depth and were found in very low and very low to low, respectively (EthioSIS, 2014). Similarly, Dinssa and Elias ( 2021 ) reported very low to low B distribution in the Bako Tribe of western Ethiopia. The pH is retained as the main factor affecting B adsorption in agricultural soils (Santos et al., 2019 ), as well as soil texture, soil moisture, parent material, clay nature and content, Al and Fe (hydr)oxides, clay minerals, calcium carbonate, and organic matter and interrelationship with other elements affect the B concentration in soil (Ahmad et al., 2012 ; Arora and Chahal, 2010 ). For instance, Wójcik ( 2000 ) reported high B deficiency on coarse texture soils and recommended the application of calcium nitrate or ammonium nitrate would be appropriate to keep B more available to plants. Only a small percentage of the available nutrients move freely in the soil solution. Most are loosely bound on mineral and organic surfaces in exchangeable form. This mechanism acts as a storehouse both for nutrient cations and anions. For instance, clay minerals, especially illitic and montmorillonitic types, have large negatively charged surfaces on which cations like Ca 2+ , Mg 2+ , and K + are adsorbed and, therefore, protected against leaching (FAO, 2006b). According to FAO (2006b), a deviation from the order of Ca 2+ > Mg 2+ > K + > Na + can create ion-imbalance problems for plants; thus the result showed appropriate basic cation distribution in the studied soils. The prevalence of Ca 2+ followed by Mg 2+ , K + , and Na + in the exchange site of soils is favorable for plant production (Tizita, 2016 ). The result might be related to the parent material from which the soils developed and their differential attraction to the soil’s exchange complex. The extent of exchangeable base distribution was not consistent along the toposequence. However, soil depth showed an increasing trend for all exchangeable bases. The studied soils were very low to medium in Na, low to very high in K and Ca, and medium to very high in Mg, following the rate suggested for exchangeable bases by EthioSIS (2014). Other previous studies also reported similar findings in Ethiopia's agroecological settings (Abate et al., 2014 ; Abu, 2021 ; Ali et al., 2010 ; Bekele et al., 2021 ). This study observed a trend of PBS with depth, possibly due to the leaching of bases from the overlying layers and subsequent accumulation in the subsurface horizons. The PBS was also recorded very low to very high along the toposequence (EthioSIS, 2014; Hazelton and Murphy, 2016 ). The high base saturation of the soil was consistent with high contents of exchangeable bases (chiefly Ca 2+ and Mg 2+ ), as reported similarly by others (Abu, 2021 ; Elias, 2017 ; Fekadu et al., 2018 ; Sekhar et al., 2014 ). Cation exchange capacity (CEC), the capacity of a soil or any other substance with a negatively charged exchange complex to hold cations in an exchangeable form, mainly depends on the type and proportion of clay minerals and organic matter present in the soil (FAO, 2006b). The result of CEC was found qualified in the range of high to very high rating (EthioSIS, 2014; FAO, 2006b; Hazelton and Murphy, 2016 ), which corresponds to clay content, organic carbon content, and type of clay mineral present. Most studies also showed a direct relationship between organic matter, clay content, and CEC (Fekadu et al., 2018 ; Tizita, 2016 ; Yitbarek et al., 2016 ). The high CEC result revealed that the soils of the studied profiles had good nutrient retention and buffering capacity. Many previous studies confirmed that deforestation, intensive cultivation, land-use change, and the nature of the topographic position led to a decline in CEC (Abate and Kibret, 2016 ; Bore and Bedadi, 2015 ; Sanaullah et al., 2016 ; Yitbarek et al., 2016 ). Micronutrients are essential for good crop performance (Ilori and Shittu, 2015 ). The higher micronutrient soil profile distribution at the surface than in subsurface soils in this study may be attributable to the accumulation of organic matter content on the topsoil or supplementary additions through chemical fertilizers and continuous transport of the micronutrients from root depth (via absorption by plants and subsequent litterfall). A decrease in the extractable micronutrient level of the subsurface horizon also provides evidence that these elements were phytomining and redeposited on the surface with organic matter. The acquisition of biomass in the top layer leads to higher organic matter and increased clay content in the surface soils. Organic matter decreases oxidation and precipitation loss, and the chelating agents present in the organic matter, depending upon their solubility potential, improve micronutrient solubility, thereby increasing their availability. Similar trends have been observed in previous studies (Akhtaruzzaman et al., 2018 ; García-Marco et al., 2014 ; Ivana et al., 2015 ; Jiang et al., 2009 ; Joshi et al., 2020 ; Sarker et al., 2020 ) who reported the highest micronutrient concentrations in topmost of soil, with concentrations decreasing down the profile. These authors also confirmed that available micronutrients are strongly associated with soil organic matter content in surface soil. The results also agree with Yitbarek et al. ( 2016 ), who reported the influence of texture and organic matter content on extractable micronutrients. Moreover, Sharma et al. ( 2004 ) also highlighted that extractable micronutrients increased with increased organic carbon content and CEC and decreased with increasing pH, sand, and calcium carbonate content. Topology, parent materials, irrigation water, land use types, biological cycling, anthropogenic disturbance, leaching, pH, and organic matter contents significantly affected the micronutrient availability to a different extent (Jiang et al., 2009 ; Zhang et al., 2012 ). Others also added (Dibabe et al., 2007 ; Jiang et al., 2009 ) that the high levels of micronutrients are consistent with high organic carbon content and low soil pH. Soil organic matter favors a lower redox potential environment and enhances soil health and the accessibility of micronutrient cations in the soil (Dhaliwal et al., 2019 ). A reduction in the availability of micronutrients with increasing pH can be attributed to the conversion of micronutrients to insoluble forms in soil (Fageria and Baligar, 1997 ). With an increase in pH, the primary soluble form of Mn (Mn 2+ ) oxidizes to form higher oxidation states (Mn 3+ /Mn 4+ ) which are insoluble in soil water and become unavailable to plants. Plants in their divalent state also take up elemental Cu. With an increase in pH, higher oxidation states of Cu predominate, which show more excellent retention by soil colloids (OM, clays, etc.), thus reducing their availability (Ivana et al., 2015 ; Kumar and Babel, 2011 ). According to the critical interpretative values for extractable micronutrients set by EthioSIS (2014), the mean values for extractable Fe, Cu, Zn, and Mn in all profiles were rated as high, medium, low, and high, respectively. Accordingly, none of the soils studied is deficient in Fe, Cu, and Mn; however, Zn deficiency is observed along the toposequence. High calcium carbonate content (> 15%) in neutral to alkaline soils of semi-arid/arid regions, low OM in sandy soils, waterlogging conditions, precipitation or adsorption of zinc with various soil components depending on the soil pH, organic matter, pedogenic oxides, and redox potential are reported to be responsible for low Zn availability (Arunachalam et al., 2013 ; Lal et al., 2022 ). Although the significant contribution of chemical fertilizers (e.g., DAP to supply P) was found effective in nutrient supply for intensive cultivation, the increased use of these fertilizers in an imbalanced manner is also responsible for micronutrient deficiency. The concern regarding the Zn deficiency problem is growing daily as Zn plays numerous roles in the biological functions of plants and humans and is considered an essential micronutrient for their growth and development (Alloway, 2008 ). 4.4. Potential and Limitation of the Studied Soils for Agricultural field crops Soil suitability, the fitness of a given type of soil for a defined use, is a precondition for sustainable land use planning (Doula et al., 2017 ; Sarkar et al., 2014 ) and is necessary for precision as attributes of land can be suitable for specific crops but unsuitable to others. Unsuitable land use has potential limitations or constraints that can severely impair its function or not meet the requirement for a particular service. Pressures on land resources by conversion from their natural state to human use are pushing the productive capacity of land systems to the limit (FAO, 2022 ; Liu et al., 2014 ). Therefore, the erroneous of selecting the correct land for the cultivation of a particular agricultural product is becoming a long-standing and mainly empirical issue. Although many recommended and provided a framework for optimal agricultural land use, it is suspected that much agricultural land use is still below its optimal capability in different parts of the world. The land used for agricultural production must be used according to its potential for optimization and sustainability of soil productivity. This becomes vital to Ethiopia when precision farming is gaining wider acceptance. The relevance is particularly more nowadays in the developing world where the use to which a land functions very often is not related to its capacity. A significant problem of agricultural development in Ethiopia is poor knowledge and appraisal of land suitability for agricultural production. Hence, in this study, the different soil units were classified according to their capability and suitability for agricultural field crops into very suitable soils, moderately suitable soil, marginally suitable soils, and not suitable soils, according to internationally recognized suitability classes outlined by FAO ( 1984 ) and Schoeman et al. ( 2002 ) which can be adapted and applied at both regional and local scale. In harmony with this result, Girmay et al. ( 2018 ) also reported similar problems for Gateno watershed soil suitability analysis. Others also mentioned these problems and signified the importance of soil suitability analysis for particular areas for sustainable land resource use and better production (Alemu et al., 2013 ; Nyssen et al., 2019 ; Yohannes and Soromessa, 2018 ). In addition, Liu et al. ( 2014 ) noted that landscapes are not managed sustainably when marginal lands are cultivated or more fertile. It can lead to soil erosion and degradation, loss of livelihoods, and a decrease in the overall resilience of the social-ecological system. Therefore, employing different soil and water conservation measures and adopting integrated soil fertility management coupled with appropriate agronomic practices and appropriate land-use systems according to their fitness is critically important to reduce the continuing soil degradation and to increase production sustainably. In general, the relationships between features of the landscape, soil characteristics, and soil types will help to advance soil-landscape relations and show a less costly way of acquiring soil foundation since the performance of any crop is mainly dependent on soil properties such as depth, drainage, texture, fertility, etc., as conditioned by climate and topography. 5. Conclusion And Recommendation Low soil fertility and poor management prices constrain crop production in the study area. Hence, detailed information on soil properties by soil characterization and classification is essential to plan operative land use and soil fertility management. With this in mind, detailed soil information is needed to understand the functional variability across landscapes to improve the management and efficiency of agricultural practices and ultimately improve food security in the Ayiba area. Accordingly, this study produced a soil-landscape map of the Ayiba area for more sustainable soil use and production systems. The study involved soil profile description and understanding of soil-landscape relations. Based on the soil morphological, physical, and chemical analysis of the studied soil units: on the plateau and the steepest slope, shallow soils (Leptosols) and bare rock are found on the mountain foot slopes developed, but younger soils occur on the terraced beds (Fluvisol, Luvisol, and Vertisol), and the footslope and valley bottoms developed and deeper soils occur (Vertisol and Cambisol). Some soil physicochemical properties also showed significant variability within each generic horizon along the toposequence. In addition, moving down the slope, soil depth and profile development improved, but soil drainage conditions deteriorated. This study revealed the soils in the study area were found in the range of very low to low in SOC, av.S, and av.B; low to medium in TN and av.P, and high to very high in CEC. Most of the soil attributes measured were better in the lower topographic positions than those in the upper and middle topographic positions. Therefore, the low fertility status of the soils can be brought to better use for agriculture by incrementing soil organic matter level through the incorporation of organic fertilizer sources such as farm yard manure and by reducing the complete removal of crop residues. Moreover, some soil landscapes had a slope position greater than 30% in the study area. Thus, terracing, slope reduction, runoff velocity limitation, and the installation of appropriate drainage should be incorporated into the site management plan to limit soil erosion. These results also suggested that soil management interventions should be based on land use and site-specific information for appropriate resource management, like the application of inorganic fertilizers and rehabilitation of soils over heterogeneous landscapes to improve crop yields in the study area. This study identifies the lower position and some nearly gentle slope gradients of the middle position have suitable land for agricultural purposes. Still, not all these soils can sustain agriculture in the long term. Yet, the high percentage of unsuitable soils for cultivation found in the middle and upper topography clearly shows that the Ayiba watershed certainly has high production potential if correct land management decisions are made, like pasture, forestry, and perennial crop production. Thus, information on soil and related properties obtained from the soil survey and classification can help better delineate soil and land suitability. Declarations Ethics approval and consent to participate Not applicable Consent for publication Not applicable Availability of data and materials Data will be available upon reasonable request from the corresponding author. Competing interests The authors declare no competing interests. Funding Mekelle University CASCAPE project partially funds this research. Authors' contributions - provide individual author contribution WS: Conceptualization, Methodology, Software, Investigation, Resources, Formal analysis, validation, Writing Original Draft, writing review and editing, and Visualization; EE : Methodology, Writing-review and editing, Resources, validation, supervision, and funding acquisition; GG : Methodology, Data curation, writing-review and editing, validation, Visualization, Resources, supervision, and project administration; GL : writing-review and editing, Visualization, and software; and WT : Resources, Data curation, Validation, writing-review and editing, and visualization. Finally, all authors read and approved the final manuscript. Acknowledgments Mekelle University (CASCAPE project) is acknowledged for partial financing and transport service facilitation. We extend our thanks also to Ayiba area farmers for allowing us to open soil profiles and take soil samples from their vicinity. Remarkably, the cooperation of Mr. Haftay Etsay was immense and cherished. Authors and Affiliations Weldemariam Seifu and Wolde Tefera Department of Horticulture and Plant Science, College of Agriculture and Natural Resources, Salale University, Fiche, Oromia, Ethiopia, P.O.Box: 245. Weldemariam Seifu, Eyasu Elias and Gudina Legesse Center for Environmental Science, College of Natural and Computational Sciences, Addis Ababa University, Addis Ababa, Ethiopia, P.O.Box: 1176 Girmay Gebresamuel Land Resources Management and Environmental Protection, Mekelle University, Mekelle, Tigray, Ethiopia, P.O.Box: 231 References Abate N, Kibret K (2016) Effects of Land Use, Soil Depth and Topography on Soil Physicochemical Properties along the Toposequence at the Wadla Delanta Massif, Northcentral Highlands of Ethiopia. Environ Pollution Vol 5. 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Accessed on November 18, 2021 Tables Tables 1-13 are available in the Supplementary Files section. Supplementary Files Tables.docx Suplementaryfile.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-2093235","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":140411883,"identity":"cf0d991e-d215-412d-86a1-c4215f3d0d37","order_by":0,"name":"Weldemariam 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University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Wolde","middleName":"","lastName":"Tefera","suffix":""}],"badges":[],"createdAt":"2022-09-22 14:50:06","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2093235/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2093235/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":27205646,"identity":"b2ba24b8-c870-4361-bd93-c5d01655915a","added_by":"auto","created_at":"2022-09-30 18:34:04","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":202907,"visible":true,"origin":"","legend":"\u003cp\u003eSpatial distribution of the (a) topsoil sampling points and (b) profile sites in Ayiba watershed located in the semi-arid region of Tigray, northern Ethiopia.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-2093235/v1/ae9a1cb7df00518e6deb13ed.png"},{"id":27205745,"identity":"68d190b4-8d88-4ac3-9622-e18d5da2ec04","added_by":"auto","created_at":"2022-09-30 18:34:33","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":49490,"visible":true,"origin":"","legend":"\u003cp\u003eClimatic diagram of Ayiba watershed from 1998- 2018 (NMSA, 2018).\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-2093235/v1/0621ed097a186a1f5a9389e2.png"},{"id":27205772,"identity":"9f129bdc-1fce-454a-af53-3b1710fbce25","added_by":"auto","created_at":"2022-09-30 18:34:36","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":65316,"visible":true,"origin":"","legend":"\u003cp\u003eSpatial slope map of Ayiba watershed, Northern Ethiopia.\u003c/p\u003e","description":"","filename":"Onlinefloatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-2093235/v1/3f0e7fdff6981e851f054106.png"},{"id":27205712,"identity":"4dba9d73-0356-4cba-9ac5-2df707bf5c74","added_by":"auto","created_at":"2022-09-30 18:34:26","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":2226135,"visible":true,"origin":"","legend":"\u003cp\u003e(a) Cross profile CD dissected plateau of Ayiba watershed, and (b) conceptual toposequence model showing landscape position and profiles opened at the upper slope, middle slope, and foot slope, respectively.\u003c/p\u003e","description":"","filename":"Onlinefloatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-2093235/v1/df4f4ff104ab8f1622bdf07d.png"},{"id":27205637,"identity":"18e66243-777c-4808-8ee1-6d6c6ce037bb","added_by":"auto","created_at":"2022-09-30 18:33:58","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":378256,"visible":true,"origin":"","legend":"\u003cp\u003eField photographs of (a) Sheet erosion (upper slope), (b) rill erosion (middle slope), and (c) active gully erosion (foot slope) around the profiles along the soil catena.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-2093235/v1/21d8865a01dea1fcee27f80f.png"},{"id":27205739,"identity":"01ff9cd4-4105-499c-87eb-6077174a55b8","added_by":"auto","created_at":"2022-09-30 18:34:32","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":84755,"visible":true,"origin":"","legend":"\u003cp\u003eThe studied soil profiles average water retention capacity (FC: Field capacity, PWP: permanent wilting point, AWC: Available water content). Error bars indicate the standard error of the mean.\u003c/p\u003e","description":"","filename":"ScreenShot20220930at12.57.20PM.png","url":"https://assets-eu.researchsquare.com/files/rs-2093235/v1/f4a3cdd2ab57b9133926d1e6.png"},{"id":27205709,"identity":"dcfd3e6b-2a28-4308-aca0-d7e63254cb42","added_by":"auto","created_at":"2022-09-30 18:34:26","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":61272,"visible":true,"origin":"","legend":"\u003cp\u003eSpatial soil map of Ayiba watershed according to WRB system.\u003c/p\u003e","description":"","filename":"Onlinefloatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-2093235/v1/ce8a5b6f9ce9593a964cf012.png"},{"id":27206415,"identity":"c1a0cd31-8e3e-4ca0-b64f-aa66407f8c25","added_by":"auto","created_at":"2022-09-30 18:40:13","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4074088,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2093235/v1/8f6cb6dc-b7a0-4d06-a220-71de7d9c277d.pdf"},{"id":27205736,"identity":"b6577732-191b-4763-a03a-a3049e67dba3","added_by":"auto","created_at":"2022-09-30 18:34:32","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":94384,"visible":true,"origin":"","legend":"","description":"","filename":"Tables.docx","url":"https://assets-eu.researchsquare.com/files/rs-2093235/v1/ad24130164feff1bea447f23.docx"},{"id":27205773,"identity":"59699350-d9ac-4bf4-9019-0ba85eba35b3","added_by":"auto","created_at":"2022-09-30 18:34:36","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":25214,"visible":true,"origin":"","legend":"","description":"","filename":"Suplementaryfile.docx","url":"https://assets-eu.researchsquare.com/files/rs-2093235/v1/daccb08c2745e9ca4d049a00.docx"}],"financialInterests":"","formattedTitle":"Soil-landscape characterization and mapping to advance the state of spatial soil information on Ethiopian highlands: Implications for site-specific soil management","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eSoils are a non-renewable source and comprise a vital component of the world\u0026rsquo;s stock of natural capital with a prolonged forming process. Soil takes 100s to 1000s years to form a 1 cm of soil and erode in a relatively short time due to improper use or poor management with little opportunity for regeneration (J\u0026oacute;nsson and Dav\u0026iacute;\u0026eth;sd\u0026oacute;ttir, \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Kavitha and Sujatha, \u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Santos-Franc\u0026eacute;s et al., \u003cspan citationid=\"CR121\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Hence, soil scientists strongly recommend understanding the soil beneath our feet, managing it properly, and avoiding destroying the essential building block of our environment and food security. The soil is perhaps the most difficult, underrated, and little understood matrix (Balestrini et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Saljnikov et al., \u003cspan citationid=\"CR119\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). There is a saying by the legendary Italian artist Leonardo Da Vinci to explain our nuanced understanding of soil resources, i.e., \"\u003cem\u003ewe know more about the movement of celestial bodies than about the soil underfoot\u003c/em\u003e\" (Colby and David, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe main ecological functions of soils have grouped into three major categories: (i) regulatory and support functions, (ii) provision functions, and (iii) information, culture, leisure, and religion functions (Devi, 2021; FAO and ITPS, 2015; Nunes et al., \u003cspan citationid=\"CR110\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Soil is essential for supporting food production (producing about 95% of humanity's food supply) and providing ecosystem services. However, like other habitats and ecosystems, the soil is under increasing pressure due to anthropocentric activities (J\u0026oacute;nsson and Dav\u0026iacute;\u0026eth;sd\u0026oacute;ttir, \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) to the extent that a new geologic epoch, the Anthropocene, has been proposed (Will et al., \u003cspan citationid=\"CR146\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Thus, the soil capital is threatened in Ethiopia and elsewhere due to rapid population growth, higher food demand, land use competition, massive vegetation clearing, desertification, overuse, and mismanagement (Bai et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Elias, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; IPBES, 2018; Koch et al., \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). These caused it to exceed its capacity to perform, as manifested by land degradation (Chen et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Saljnikov et al., \u003cspan citationid=\"CR119\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). About 30% of the world's soils are currently degraded (Zurich Megazine, \u003cspan citationid=\"CR159\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). All of the world's topsoil could become unproductive within 60 years if current loss rates continue (Maximillian et al., \u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTherefore, understanding the soil types of a given area is a vital prerequisite to designing optimum management strategies (Sebnie et al., \u003cspan citationid=\"CR128\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Thus, identifying the spatial distribution of soils and their characteristics is critical because it can enhance natural resources management, predict soil properties in non-sampled locations, and improve sampling designs in agro-ecological and environmental studies. Moreover, given the vital role that soil plays within ecosystems and human life, it is essential to assess soil health, especially on field crop farms that dominate agricultural landscapes like Ethiopia. Therefore, to establish the level baseline of micronutrients, soil analysis is recommended to determine the level of available nutrients (Doula and Sarris, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Balancing ecosystem services with agricultural production is essential to meet the needs of a growing global population while minimizing the environmental impacts of agriculture (Udawatta et al., \u003cspan citationid=\"CR140\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). So, analysis and interpretation of spatial variability of soils is a keystone in the site-specific farming system (Iqbal et al., \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2005\u003c/span\u003e) since agricultural soils are in peril (Gebremedhin et al., \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Various studies on soil properties also confirmed that topographic position largely governs the change in types, characteristics, and distribution of soils (Debele et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Dessalegn et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Mulugeta, \u003cspan citationid=\"CR105\" class=\"CitationRef\"\u003e2004\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAbove all, information about the distribution of a country's natural resources is vital for many purposes, including local and regional planning, economic forecasting, food security, and environmental protection. Studies also confirmed that the classification of fields into management zones is based on the variability of soil fertility limitations in precision agriculture (Iticha and Takele, \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Over the last few decades, the need for landscape monitoring and assessment of changes in spatial patterns has grown as knowledge of the types and properties of soils is critical for decision-making regarding crop production and other land-use types (Leenaars et al., \u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Accordingly, soil characterization, classification, and mapping are among the most important stages and building blocks in natural resources assessment tools for understanding the soil-landscape, classifying it, and getting the best understanding of the environment (Ahmed et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Esu et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Apart from information about soil forming factors at the site, soil characterization is done through the description of color, texture, structure, consistence, voids, cutans, roots, cementations, nodules/concretions, rock fragments/stones, faunal activity, and horizon boundary of each generic soil horizons (FAO, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2006a\u003c/span\u003e; Saether and De Caritat, \u003cspan citationid=\"CR117\" class=\"CitationRef\"\u003e1996\u003c/span\u003e). The coupling of soil characterization, classification, and mapping provides a powerful resource for humankind's benefit, especially in food security and environmental sustainability (Ahmed et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHowever, Ethiopia lags more in defining its spatial soil sources in detail and fine-scale, yet only 1712 soil profiles are detected according to the World Soil Information Service (WoSIS) (Batjes et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). More profile numbers will be studied than the WoSIS reported; however, only a part from there is readily reachable in a consistent format for the use of the international community. Another lag is that no Ethiopian soil classification system was identified, established, and documented with vernacular languages. This, in turn, creates many problems in the soil use system. In much of the country, lack of or fragmented geospatially explicit information on soil-landscape resources is common (Leenaars et al., \u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Thus, providing up-to-date and site-specific soil information to the beneficiaries based on a detailed soil study at the local or watershed level is indispensable for sustainable soil use. Moreover, the United Nations pledged to achieve sustainable development goals (SDGs) by 2030, and regional land use analyses are essential to achieving these goals. Research findings also highlighted that soil resource information is vital for sound soil use planning and sustainable fertility management (Dinssa and Elias, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Elias, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Fekadu et al., \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Gebreselassie et al., \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePrevious studies have reported that 19 out of the 28 Major Soil Groups of the FAO-UNSECO Soil Map of the World are found in Ethiopia. Because of this, Ethiopia is called the \u0026ldquo;\u003cem\u003esoil museum\u003c/em\u003e\u0026rdquo; of the world. However, our knowledge of Ethiopia\u0026rsquo;s soil resources is limited. The soil resources were mapped at 1:2,000,000, which were too coarse and topographically not detailed enough to provide practical information for soil fertility decisions at lower spatial scales (Elias, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Past soil survey activities were inadequate in providing basic soil data that can help to manage soils according to the local variability (i.e., watershed or farm scale). Thus, the present study was initiated to characterize and classify the soils of Ayiba catena following the FAO-WRB legends (FAO, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2006a\u003c/span\u003e; IUSS Working Group WRB, \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). This study was, therefore, set out expressly to (i) provide detailed morphological, physical, and chemical properties of the soils in the Ayiba mountainous landscape and (ii) classify the soils according to the FAO-WRB soil classification system and develop a soil map of the watershed to enable soil-specific farm-scale management interventions.\u003c/p\u003e"},{"header":"2. Materials And Methods","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003e2.1\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003eSite description: location, climate, soil, land use, and husbandry\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe research was carried out in the Ayiba watershed (4099.14 ha) of the Emba-Alaje district, southern Tigray, northern Ethiopia. Ayiba watershed is part of the Denakil River basin located between 12\u0026deg;51\u0026prime;18\u0026prime;\u0026prime;\u0026ndash;12\u0026deg;54\u0026prime;36\u0026prime;\u0026prime;N and 39\u0026deg;29\u0026prime;24\u0026prime;\u0026prime;\u0026ndash;39\u0026deg;35\u0026prime;24\u0026prime;\u0026prime;E (Figure 1). Elevation ranges from 2722 to 3944 meters above sea level (m.a.s.l.) with mountainous landscape and steep terrain at upper and middle slopes. The landform of the study area is dominated by high mountainous relief hills and starkly dissected plateaus with steep slopes (\u0026gt;30% slope gradient) complemented by valley bottoms (Amanuel et al., 2015; Elias, 2016). \u0026nbsp;Regarding the geomorphological setting, an important artefact in the study watershed is different landslides positioned within the toposequence, which occurred due to basaltic parent material deposition down the slope, making them very important for soil distribution (Amanuel et al., 2015; Elias, 2016; Gebresamuel et al., 2022). Regarding soil development, Van de Wauw et al. (2008) described two essential types of mass movements studied in similar geomorphological settings: (a) large-scale landslides which move basaltic parent material downslope; and (b) flows of vertic clays deposited at the foot of the sandstone cliff, or similar secondary flows at the foot of large-scale landslides.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe watershed is generally characterized as tepid to cool semi-arid climatic condition with extended 9-10 months of dry periods and 50-60 days of the rainy season and highland agro-ecological zone with a rainfall bi-modally distributed\u0026nbsp;(Amanuel et al., 2015; Elias, 2016; Negash and Israel, 2017).\u0026nbsp;The main rainy season, \u0026lsquo;\u003cem\u003eKeremti\u003c/em\u003e\u0026rsquo; (summer: June to September), is preceded by a short rainy season, \u0026lsquo;\u003cem\u003eBelgi\u003c/em\u003e\u0026rsquo; (spring: February to May), (Table 1), predominantly derived from the Indian Ocean\u0026nbsp;(Elias, 2016; Embaye, 2009; Yemane et al., 2020).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e1\u003c/strong\u003e. Spatial distribution of the (a) topsoil sampling points and (b) profile sites in the Ayiba watershed in the semi-arid region of Tigray highland, northern Ethiopia.\u003c/p\u003e\n\u003cp\u003eAccording to the 20 years of weather data obtained from four nearby weather stations (Bora, Maychew, Wedisemero, and Korem), the mean monthly rainfall is 72.88 mm, with total annual precipitation of 853 mm. August is the peak period for main rain season and April is the peak for the slight rain season. The area\u0026apos;s mean minimum and maximum monthly temperatures are 7.1 and 25.6 \u0026deg;C, respectively, with a mean temperature of 16.8 \u0026deg;C (Figure 2). The dotted area on the left and right sides designates the dry season.\u0026nbsp;The area\u0026apos;s annual potential evapotranspiration (PET) is about 1411 mm\u0026nbsp;(Elias, 2016).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e2\u003c/strong\u003e. Climatic diagram of Ayiba watershed from 1998- 2018\u0026nbsp;(NMSA, 2018).\u003c/p\u003e\n\u003cp\u003eLike as noted in previous studies of northern highland Ethiopia\u0026nbsp;(Delelegn et al., 2017; Gelaw et al., 2015; Tekle and Hedlund, 2000; Zeleke and Hurni, 2001), the natural woodland and vegetation of the study watershed had been abandoned in the last more than half century. Only tiny patches of remnant natural forests around churches are presently kept by psychic divining power. There has been religious thinking since antique that \u0026quot;any disturbance to the nature and spirit around the holly church (e.g., cutting a tree, leaving animal for grazing or browsing, etc.) will bring a catastrophic consequence\u0026rdquo; (personal communication with local elders and priests, 2018). The high rate of deforestation and forest degradation is driven by demand for wood products (for energy and construction purposes) and by pressure from other land uses, agriculture, and cattle ranching to support the alarmingly increasing population growth. Therefore, reducing deforestation and increasing reforestation are expected to make good economic sense in their own right and also support agriculture and rural livelihood.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMixed crop-livestock agricultural systems are the primary means of livelihood\u0026nbsp;in the\u0026nbsp;farming system\u0026nbsp;(Elias, 2016). Cereal and legume crops and some vegetable and fruit crops are grown in the study area\u0026nbsp;(Elias, 2016; Girmay et al., 2014). Wheat (\u003cem\u003eTriticum aestivum\u0026nbsp;\u003c/em\u003eL.), barley (\u003cem\u003eHordeum\u0026nbsp;\u003c/em\u003espp.), and Teff (\u003cem\u003eEragrostis\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003cem\u003etef\u003c/em\u003e (Zucc.) Trotter) are among the significant cereal crops\u0026nbsp;that supply the bulk of the staples for the population in the study area\u0026nbsp;(Table 1). Legume crops such as fava bean (\u003cem\u003eVicia fava\u0026nbsp;\u003c/em\u003eL.), field pea (\u003cem\u003ePisum sativum\u0026nbsp;\u003c/em\u003eL.), Ethiopian pea (Dekeko in Tigrigna) (\u003cem\u003ePisum sativum\u003c/em\u003e var. \u003cem\u003ebasidium\u003c/em\u003e), lentils (\u003cem\u003eLens culinaris\u003c/em\u003e or \u003cem\u003eLens esculenta\u003c/em\u003e) are also cultivated for dual purpose, i.e., yield and rotation.\u0026nbsp;Tef-wheat-legumes are the standard crop rotation practice in the area. Besides,\u0026nbsp;some other vegetables and fruits like an onion (\u003cem\u003eAllium cepa\u0026nbsp;\u003c/em\u003eL.), pepper (\u003cem\u003ePiper nigrum\u0026nbsp;\u003c/em\u003eL.), cabbage (\u003cem\u003eBrassica oleracea\u0026nbsp;\u003c/em\u003eL.), and apple (\u003cem\u003eMalus Domestica\u0026nbsp;\u003c/em\u003eL.) are grown by farmers in the watershed\u0026nbsp;(Gebresamuel et al., 2022; Girmay et al., 2014). Chickpea (\u003cem\u003eCicer arietinum\u003c/em\u003e L.) is sown\u0026nbsp;after harvesting using residual moisture (Table 1).\u0026nbsp;Natural pasture is the primary source of animal feed in areas where farmers practice intensive pasture land grazing with a higher stocking rate, resulting in poor natural pastureland management\u0026nbsp;(Atsbha et al., 2020).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e1\u003c/strong\u003e. Main crops cultivated and the cropping calendar under main rain, short rain, and irrigation scheme in Ayiba area, northern Ethiopia.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2 Profile\u003c/strong\u003e \u003cstrong\u003esite selection and field description\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe free-soil survey (traverse survey) method was employed as a survey method along the landscape to detect the variability of soils in the watershed. A transect walk was made to cover the soils at varying physiographic positions and elevations with a team of experts to the Ayiba watershed. Field exploration was conducted to identify the significant soil units and localize profile sampling sites before the actual field survey. In addition, before soil sample collection was done, some basic information about the existing land was gathered from local farmers, elders, and extension experts. A provisional map (1:50,000) was prepared with predefined sampling points distributed throughout the watershed using ArcGIS 10.5 software. Extensive auguring was done to identify mapping units and sites for opening profile pits. The necessary soil survey facilities and formats such as the FAO guidelines for soil profile description (FAO, 2006a), WRB soil classification manual (IUSS Working Group WRB, 2015), Munsell color chart, GPS, soil profile, and auger description sheets were collected and prepared before fieldwork. Slope maps were extracted from a digital elevation model (DEM). The watershed was generally found within a slope range between nearly flat to slopping (1\u0026ndash;8%) at the foot slope to steep sloping (\u0026gt;60%) at the upper slopes (Figure 3).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFigure 3.\u0026nbsp;Spatial slope map of Ayiba watershed, Northern Ethiopia.\u003c/p\u003e\n\u003cp\u003eA catena was selected from the\u0026nbsp;sloping land\u0026nbsp;escarpment at the north to the valley floor at the south encompassing landform components spinning from crest/summit to foot slope/toe slope (Figure 4a). Accordingly, the selected toposequence was stratified into three landscape positions:\u0026nbsp;upper (Crest + Shoulder), middle (Back slope), and foot (toe slope + depressions) slope positions and two profiles were opened at each place (Figure 4b).\u0026nbsp;From an extensive series of observations along the toposequence, profiles were opened to a depth of 2+ m (unless soil depth is limited or is impracticable due to stoniness) with dimensions of 2 m x1.5 m on a site that was representative of each landscape position. All profiles were geo-referenced, and general site information and soil description were recorded (Table 2). Land use-wise, profiles 1 and 3 were excavated on grassland, while profiles 2, 4, 5, and 6 were excavated on cropland (Table S3). Profiles were described and sampled following the standard procedures to investigate soil morphological, physical, and chemical properties\u0026nbsp;(FAO, 2006a; IUSS Working Group WRB, 2015). Soil morphological descriptions were completed \u003cem\u003ein situ\u003c/em\u003e according to FAO guidelines\u0026nbsp;(FAO, 2006a), and soil color notation was described using\u0026nbsp;Munsell Color Company (2009).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure 4\u003c/strong\u003e. (a) Cross profile CD dissected plateau of Ayiba watershed, and (b) conceptual toposequence model showing landscape position and profiles opened at the upper slope, middle slope, and foot slope, respectively.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2\u003c/strong\u003e. Some site characteristics of the studied profiles along the toposequence of Ayiba watershed, Northern Ethiopia.\u003c/p\u003e\n\u003cp\u003e2.3\u0026nbsp;\u003cstrong\u003eSoil sampling and analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA systematic stratified sampling procedure was used to distribute sampling throughout the watershed under careful consideration of topography and spatial pattern of land use. A global positioning system (GPS) was used to identify the sites\u0026rsquo; longitude, latitude, and elevation. In all soil sampling procedures at each sampling spot, surface litter is scarped, and vegetation cover is removed before collecting samples. Sample spot excluding was also performed if a considerable difference is noted to minimize soil variability among subsamples for composite preparation to minimize outlying results. Soil morphology was described in the field to interpret their characteristics, and disturbed and undisturbed soil samples were collected from each genetic horizon (starting with the lowest horizon and working to the uppermost to avoid contamination) and from each land use type across the topography for laboratory analysis. Soil sampling locations were selected to best represent by considering variation in terrain attributes and drainage facilities. Soil samples were collected using a soil auger. Accordingly, 20 disturbed and undisturbed samples were collected from each generic horizon for soil characterization and classification analysis.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe collected soil samples were spread for air-drying (to reduce oxidation of soil carbon), crushed and grounded by\u0026nbsp;pestle and mortar, and sieved with a 2 mm sieve mesh for physical and chemical analysis. Rock fragments and gravels (\u0026gt;mm), visible roots, organic residues, and\u0026nbsp;macro-fauna were removed manually at sampling time before pooling. Finally,\u0026nbsp;the soil samples were taken to the laboratory for analysis. Analysis was done at Tigray soil laboratory center, Mekelle (Ethiopia), and plant nutrition laboratory, College of Environmental Science Resources, Zhejiang University, Hangzhou (China).\u0026nbsp;All the soil samples were analyzed following the standard analytical procedures (Table 3).\u0026nbsp;The interpretation of the measured soil properties was made using Table S1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3\u003c/strong\u003e. Soil parameters and methods used to determine in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.4 Soil classification and mapping of Ayiba watershed\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBased on the morphological, physical, and chemical properties, the watershed soils were classified into different units (major soils) following the World Reference Base for soil resources (IUSS Working Group WRB, 2015). The presence or absence of specific diagnostic horizons, properties, and materials was used to distinguish soil units and subunits according to the WRB soil classification system. Soils identical in landforms, parent material, relief, topography, and morphology were considered similar and accorded a similar mapping unit. Spatial soil classification was based on the information obtained from field soil profile morphological description and laboratory analysis results following the IUSS Working Group WRB (2015) soil classification legend.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.5 Soil\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ecapability and suitability assessment\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSoil properties and crop yields are strongly interrelated. Agricultural potential is directly related to Land Capability, as measured on a scale of I to VIII,\u0026nbsp;as presented in Table 4\u0026nbsp;below; with Classes I to III classified as prime agricultural land that is\u0026nbsp;well suited for annual cultivated crops, whereas Class IV soils may be cultivated under certain\u0026nbsp;circumstances and specific or intensive management practices, and Land Classes V to VIII are\u0026nbsp;not suitable for cultivation\u0026nbsp;(Schoeman et al., 2002).\u0026nbsp;This system is helpful in that it can quickly give one an overview of the agricultural capability and limitations of the soils in question and is helpful for soil capability comparisons. Criticisms of this system, however, include its lack of consideration of the local setting, land use planning, and a lack of financial resources\u0026nbsp;(Nethononda et al., 2014). For this reason, the site\u0026apos;s soil capability has also been assessed, taking the local setting into account from field checking.\u0026nbsp;After a qualitative assessment, the soil types were grouped into the soil suitability classes (Table 5) and classified as very suitable, moderately suitable, marginally suitable, and not suitable soils for rainfed cultivation of annual crops\u0026nbsp;(FAO, 1984; Ritung et al., 2007).\u0026nbsp;The suitability of a given piece of land is its natural ability to support specified land use,\u0026nbsp;such as rain-fed agriculture, livestock production, forestry, etc.\u003c/p\u003e\n\u003cp\u003eTable\u0026nbsp;4.\u0026nbsp;Land Capability Classes, limitations, and land use\u0026nbsp;(Schoeman et al., 2002).\u003c/p\u003e\n\u003cp\u003eTable 5. Definition of the soil suitability classes (FAO, 1984; Ritung et al., 2007).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003c/strong\u003e\u003cstrong\u003e2.6 Statistical data analysis\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;and software used\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSoil data obtained from the laboratory work were\u0026nbsp;checked to test the data sets\u0026apos; normality with the Shapiro-Wilk normality test\u0026nbsp;before analysis using R software for Windows. The\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003enormality assumption was not violated. Descriptive statistical analyses and variances were then tested following the general linear model (GLM) procedure to obtain the effect of the model: using one-Way ANOA to see the variation among the generic soil horizons. Whenever significant differences among horizon means have been detected, the analysis of variance used Tukey\u0026apos;s HSD test at a \u003cem\u003ep\u003c/em\u003e\u0026lt;0.05 level of probability to differentiate. Data in the present study were presented as mean\u0026plusmn;SE. Finally, GIS software (version 10.5) was employed to produce the spatial soil maps of the Ayiba watershed.\u0026nbsp;\u003c/p\u003e"},{"header":"3. Result","content":"\u003ch2\u003e3.1 Profile site and soil morphological characteristics\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eThe site characteristics of the profiles indicated differences in slope, drainage, and extent of water erosion (Table S2). According to FAO (2006a) guideline, the opened profiles were positioned in a slope gradient range of gently sloping to very steep. The upper and middle landscape comprises most of the sloping to very steep slope gradient classes (Figure 3). All profiles were well-drained, but AYB-5 was found poorly drained. All Profile sites showed a range of water erosion processes manifested by sheet, rill, and gully formation (Figure 5). Effects of land use, extensive and intensive farming, and removal of vegetation cover have amplified the erosion process, which was observed at all profiles and their surrounding landscapes. The land use of AYB-1 and 3 are grassland lying on soil developed from basaltic and colluvial parent materials. Whereas that of AYB-2, 4, 5, and 6 represented annual rainfed field cropping with varying land-use histories having soils developed from the outwash of colluvium and alluvium basaltic materials. Rainfed cultivated land, grassland, plantation forest, and barren land were the typical land use type of the upper and middle slopes (eroded sites), while cultivated land and grassland land use dominated the foot slope of the watershed (Seifu et al., 2020).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFigure 5. Field photographs of (a) Sheet erosion (upper slope), (b) rill erosion (middle slope), and (c) active gully erosion (foot slope) around the profiles along the soil catena.\u003c/p\u003e\n\u003cp\u003eMost profiles unveiled an A-B-C master horizon sequence. Morphological characteristics of each horizon\u0026rsquo;s color, texture, structure differentiation, etc., are presented in\u0026nbsp;Table 8. The soil depth varied from 53 cm (shallow) at the upper position to 200+ cm (very deep) at the foot slope position. The thickness of the A-horizon ranged from 0-35 cm along the toposequence. AYB-1 was the shallowest profile indicating little influence of soil-forming processes as rock debris does not accumulate on the spot since they roll down due to gravity. According to\u0026nbsp;IUSS Working Group WRB (2015),\u0026nbsp;the surface horizon of AYB-1 qualifies for \u003cem\u003emollic\u003c/em\u003e epipedons. The diagnostic epipedons of AYB-2 and 3 qualify for \u003cem\u003eargic\u003c/em\u003e due to illuvial clay accumulation, high selective clay surface erosion, and the absence of \u003cem\u003elithic\u003c/em\u003e discontinuity. The diagnostic horizons of AYB-4, 5, and 6 were also qualified as\u0026nbsp;\u003cem\u003eparalithic\u003c/em\u003e,\u0026nbsp;\u003cem\u003evertic\u003c/em\u003e, and \u003cem\u003ecambic\u003c/em\u003e, respectively. Except for AYB-4, which has a weakly developed soil horizon, all the other profiles had well-developed morphological characteristics and deeper rooting depth. AYB-4 is somewhat a strange profile in soil development as it has an A-R-B-R master horizon sequence with a very shallow rooting depth (\u0026lt;35 cm) due to the presence of a lithic contact (R layer) which may probably be developed from the loss process by water erosion. A significant quantity of clay translocation and many distinct clay cutans were observed in the subsoils of AYB-2 and 3 profiles, indicating that eluviation-illuviation processes are active. At the same time, AYB-1 is developed as a result of\u0026nbsp;melanization. AYB-5 and 6 profiles in the foot slope showed a slight clay increase with soil depth but did not qualify for the \u003cem\u003eargic\u003c/em\u003e B horizon.\u003c/p\u003e\n\u003cp\u003eIn this study, the soils have a color hue of 2.5 \u0026ndash; 10YR, a value of 2 - 5, and chroma of 1 - 4 in dry and moist conditions. With this range of color matrix, the soil color of all profiles varied from black to greyish brown (dry) and black to yellowish brown (moist). Boundaries between A- horizon and B- horizon were evident due to the darkening effect of organic matter. The field soil texture by feel method varied in all profiles across toposequence. The surface texture of profiles AYB-1, 2, and 5 were clay dominant, while that of AYB-3, 4, and 6 were sandy loam dominant. The moisture status of surface horizons AYB-1 and 3 were slightly moist. At the same time, AYB-2, 4, 5, and 6 were dry, which might be interconnected to soil organic matter and clay within the horizons. The horizon boundaries, by distinctness-topography, of profiles 1 to 6 had clear-smooth, clear-wavy, clear-smooth, clear-smooth, diffuse-smooth, and diffuse-smooth, respectively.\u0026nbsp;Horizon boundary characteristics also showed slight variations among and within studied profiles along the toposequence (Table 6).\u003c/p\u003e\n\u003cp\u003eRegarding soil structure, all soils were generally friable on the surface but became firm in the subsoil. Explicitly, profiles 1 to 4 had weak to moderate grade surface structure and weak to strong grade subsurface structure in the upper and middle catena. Likewise, in terms of type and size, all profiles were found in massive to crumbly and very fine to medium textured. In AYB-5 the soil structure in the surface horizons is mainly lumpy, mostly created by tillage disturbance, and slightly hard. In the subsurface horizons, soil morphology changes from subangular blocky forms to weakly developed coarse blocky horizons. In AYB-6, soil structure indicated weak to moderate grade, massive to crumbly type, and fine to medium size. In the foot slope, infiltration is slow, and water may stand on the\u0026nbsp;surface in the rainy season for extended periods.\u0026nbsp;All soils exhibited varied consistency in dry, moist, and wet conditions, mostly following friable on the surface and becoming firm in the subsoil (Table 6).\u0026nbsp;Except for AYB-5 at its lower layers showed very slightly effervescent (formed few bubbles), in other profiles, the field CaCO\u003csub\u003e3\u003c/sub\u003e (using 1N HCl solution) was noneffervescent.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 6. Morphological description of the six profiles studied.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e3.2 Soil physical characteristics of the profiles\u003c/h2\u003e\n\u003ch3\u003e3.2.1 Soil particle size distribution and clay contrast index\u0026nbsp;\u003c/h3\u003e\n\u003cp\u003eThe\u0026nbsp;particle size distribution revealed a variation along the toposequence ranging from 18-68%, 14-53%, and 6-68% for sand, silt, and clay parts, respectively. As a result, textural classes of the soils varied from clay to sandy loam texture along with the topography (Table 7). Generally, clay dominates the soil\u0026apos;s particle size fraction, followed by sand, then silt. In almost all profiles, percentage sand and clay parts follow decreasing and increasing trends, respectively, with depth in the geomorphic units, except AYB-3 was inconsistence.\u0026nbsp;On the other hand, higher sand content in the surface layer is associated with the selective removal of clay and silt by erosion, as the degree of sand transportability is lower compared to the finer soil fractions.\u0026nbsp;In this study, we have also observed a seasonal water logging at the foot slope, which may probably cause deterioration of structured B-horizon and dispersion of clay particles down with water table front\u003c/p\u003e\n\u003cp\u003eThe silt/clay ratio ranged from 0.21 - 4.33 along with the topography, and the ratio ranges from 0.29 \u0026ndash; 4.33 in the A-horizons and from 0.21 \u0026ndash; 2.94 in the B-horizons and decreases with depth. The highest value of the silt/clay ratio was recorded in the A\u003csub\u003eh\u003c/sub\u003e-horizon (4.33) of profile 4, followed by the Bw-horizon (2.94) of profile 3, and the lower was recorded at the lower subsoils of AYB-2 (Table 7). The clay contrast index (CCI) ranged from 0.40-0.95, with the highest at AYB-1 and the lowest at AYB-3. Higher CCI indicates lower textural differentiation, while lower CCI indicates higher textural differentiation in the profiles. Accordingly, the clay enrichment of the profiles was found in the following decreasing order: AYB-1 (0.95) \u0026lt; AYB-2 (0.89) \u0026lt; AYB-5 (0.85) \u0026lt; AYB-6 (0.80) \u0026lt; AYB-4 (0.75) \u0026lt; AYB-3 (0.40) (Table 7). AYB-1 to 4 are located on the middle and upper topography, mainly manifested by sloping to a steep slope gradient (Figure 3), intensively cultivated land with free grazing experiences, which all induced erosion on the site and lower clay content by removing the upper horizon.\u003c/p\u003e\n\u003ch3\u003e3.2.2 Bulk densities, total porosity, and water retention capacity\u003c/h3\u003e\n\u003cp\u003eThe surface bulk densities (BD) of the studied profiles ranged from 1.13 g cm\u003csup\u003e-3\u003c/sup\u003e in the A-horizon of profile 1 to 1.46 g cm\u003csup\u003e-3\u003c/sup\u003e in the A-horizon of profile 4. In comparison, the subsoil BD ranged from 1.27 g cm\u003csup\u003e-3\u003c/sup\u003e in the Bt-horizon of profile 2 to 2.32 g cm\u003csup\u003e-3\u003c/sup\u003e in the Bc-horizon of profile 5 (Table 7). The BD along the identified soil horizons was increased with depth. Furthermore, the gravimetric water content of the soils at field capacity (1/3 bar) ranged from 17.9-44.2%, while the amount at the permanent wilting point (15 bar) was between 9.1-32.55%, and the volumetric plant available water content (AWC) of the soils varied from 88-127.8 mm m\u003csup\u003e-1\u003c/sup\u003e across soils of the topography (Figure 6). The water retention capacity of AYB-3 was higher, followed by AYB-1 and 2 compared to the other profiles. This may be attributed to relatively higher organic matter and clay values observed in these profiles. Surface soils recorded slightly higher water content at FC and PWP than subhorizon soils. Subhorizon soil water retention at FC of the soils of the study watershed ranged from 24% in Profile 3 to 46% in Profile 2, whereas in the subsurface horizons, it ranged from 12% in Profile 3 to 45% in Profile 2. Available water content (AWC) showed a decreasing pattern but was inconsistent in the lower subsoil of profile 3, which may be due to textural change after the 4\u003csup\u003eth\u003c/sup\u003e layer. In surface and subsurface soils, AWC ranged from 10 to 12 and 9 to 15(v %), respectively.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 7. Soil physical properties were analyzed for the studied profiles along the toposequence.\u003c/p\u003e\n\u003cp\u003eFigure 6. The studied soil profiles average water retention capacity (FC: Field capacity, PWP: permanent wilting point, AWC: Available water content). Error bars indicate the standard error of the mean.\u003c/p\u003e\n\u003ch2\u003e3.3 Chemical characteristics of the studied soils\u003c/h2\u003e\n\u003ch3\u003e3.3.1 Soil pH, soil EC, and soil calcium carbonate content\u0026nbsp;\u003c/h3\u003e\n\u003cp\u003eThe soils are found in the range of neutral to moderately alkaline for pH-H\u003csub\u003e2\u003c/sub\u003eO and the range of moderately acidic to neutral soil reaction for pH-KCl (EthioSIS, 2014) in nature, with pH values varying from 7.14 \u0026nbsp;to 8.31 (pH-H\u003csub\u003e2\u003c/sub\u003eO) and 6.31 to 7.27 (pH-KCl). The pH variation among each generic horizon differed significantly (Table 8). In all soil horizons, pH (H\u003csub\u003e2\u003c/sub\u003eO) was higher than pH (KCl). The delta pH values, the difference between pH (KCl) and pH (H\u003csub\u003e2\u003c/sub\u003eO), indicated that the soils have net negative charges and will hold positively charged ions on the colloidal particles of the exchange site.\u0026nbsp;Regarding the soil electric conductivity (EC), the average values were found in the range of 0.19 (AYB-4) to 0.35\u0026nbsp;mS cm\u003csup\u003e-1\u003c/sup\u003e (AYB-3) with a range between 0.17 to 0.26, 0.15 to 0.32, 0.23 to 0.52, 0.16 to 0.22, 0.09 to 0.38, and 0.22 to 0.49 mS cm\u003csup\u003e-1\u003c/sup\u003e in AYB-1 to 6, respectively (Table 8). The EC was generally found very low for all analyzed horizons. Hence, all soils of the profiles were found non-saline, indicating salinity effect on crop growth and yield restriction is below the level it affects or almost negligible (EthioSIS, 2014). The low EC may be due to free drainage conditions, favoring the removal of released bases by percolation and drainage.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 8. Soil reaction, electrical conductivity, and CaCO3 of soil profiles.\u003c/p\u003e\n\u003cp\u003eCalcium carbonate (CaCO\u003csub\u003e3\u003c/sub\u003e) content of the surface soils also ranged from 0.35 (AYB-3) to 0.63% (AYB-6), whereas in the subsurface soils, it ranged from 0.62 to 1.14%. Significantly (\u003cem\u003ep\u003c/em\u003e\u0026lt;0.001) higher CaCO\u003csub\u003e3\u003c/sub\u003e content was recorded in the subsoil compared with surface soil (Table 8); which might be due to the parent material or due to the semi-arid climate, which is responsible for the pedogenic processes resulting in the depletion of Ca\u003csup\u003e2+\u003c/sup\u003e ions from the soil solution in the form of calcretes. The CaCO\u003csub\u003e3\u003c/sub\u003e content of the soils ranged from 0.38 to 1.14%, showing an increasing trend with soil depth. The variation with each generic horizon was significant. The field determination of carbonates with 10% HCl also confirmed that there was no audible and/or visible effervescence throughout the soil depth except for a few observed at the subsurface of AYB-5.\u003c/p\u003e\n\u003ch3\u003e3.3.2 The SOC, TN, and C/N ratio analysis\u0026nbsp;\u003c/h3\u003e\n\u003cp\u003eSoil organic carbon (SOC) and total nitrogen (TN) were recorded higher in the surface soils and significantly (Table 9) decreased with soil depth with average values ranging between 0.78 and 2.53% and 0.10 and 0.21%, respectively. In comparison, the SOC of subsurface layer soils ranged from 0.62% on the middle slope of degraded grassland (AYB-3) to 1.87% on the upper slope of the exclosure grassland (AYB-1). The TN content of the surface horizons was higher than the subsurface soil horizons, and it followed a similar pattern to that of SOC in all the studied profiles, implying a strong relation between SOC and TN in the soil system. The amount of SOC and TN were relatively high (3.19 and 0.25%, respectively) at the upper slope position of the surface horizons, which might be attributed and correlated to the biomass turnover of the grass.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe C/N ratio of the surface soils along the toposequence in the study area ranged from 4.51 to 12.78, while in subsoil horizons, it ranged from 5.44 to 14.04\u0026nbsp;with an average range of 6.15 to 12.61(Table 9).\u0026nbsp;The variability of the C/N ratio was not significant in each profile, indicating that it was lower than the variability of SOC and TN contents. It may suggest that the C/N ratio is more stable than its elements. Besides, the low variation in the C/N ratio across horizons suggests less variability in the degree of humification of organic matter. On the other hand, in the buried horizons of AYB-5 and 6, the C/N ratio was slightly higher than in the rest of the horizons, which might be probably due to the long-accumulated/sediment undecomposed material rich in carbon in the soil. In almost all profiles, the C/N ration demonstrates a decreasing or increasing systematic variation with depth, suggesting the existence of similar conditions of mineralization in the recognized horizon (Table 9).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 9. The studied soil profiles are SOC, TN, and C/N ratio, available P, S, and B.\u003c/p\u003e\n\u003ch3\u003e3.3.3 Soil available P, S, B, Exchangeable base, CEC, and base saturation analysis\u0026nbsp;\u003c/h3\u003e\n\u003cp\u003eThe available phosphorus (av. P) content of the profiles was high in the surface horizons of all profiles,\u0026nbsp;which could be attributed to the relatively higher organic matter contents in the surface layers, application of phosphorus-containing fertilizer on cultivated lands, and presence of free Iron oxide and exchangeable Al\u003csup\u003e3+\u0026nbsp;\u003c/sup\u003ein reduced quantity.\u0026nbsp;Available P content of the soils declined with increasing profile depth in all profiles, but spatially the trend was not consistent\u0026nbsp;- the measured av. P was significantly variable (Table 9) among the different generic horizons except in AYB-4.\u0026nbsp;The highest and lowest av. P was recorded in AYB-5 of Ap and CR horizons.\u0026nbsp;The overall profile means of av. P content was found in 26.52 to 40.09\u0026nbsp;mg\u0026nbsp;kg\u003csup\u003e\u0026minus;1\u003c/sup\u003e soil across the topography (Table 9) and decreased with depth.\u003c/p\u003e\n\u003cp\u003eRegarding Sulphur (S) and Boron (B), the result obtained for both follows the trend of av. P (Table 9). In this study, the average available S content in the studied soil profiles ranged from 0.67 mg\u0026nbsp;kg\u003csup\u003e\u0026minus;1\u003c/sup\u003e in profile 2 to 0.80 mg kg\u003csup\u003e\u0026minus;1\u003c/sup\u003e in profile 5 (Table 9). The highest and lowest av. S was recorded in AYB-6 of Ap and Bw horizons, respectively. While, av. B was found in the range of 0.19 mg\u0026nbsp;kg\u003csup\u003e\u0026minus;1\u003c/sup\u003e soil in the Bw horizon of AYB-1 to 0.77 mg kg\u003csup\u003e\u0026minus;1\u003c/sup\u003e soil in the Ap horizon of AYB-6, with an average range of 0.24 to 0.77 mg kg\u003csup\u003e\u0026minus;1\u003c/sup\u003e soil across the landscape.\u003c/p\u003e\n\u003cp\u003eIn the studied soil profiles, the result revealed that the content of exchangeable Ca\u003csup\u003e2+\u003c/sup\u003e was the dominant exchangeable base, followed by Mg\u003csup\u003e2+\u003c/sup\u003e along the toposequence. Exchangeable basic cations are found in the range 0.07 - 0.49, 0.22 - 2.12, 2.46 - 10.20, and 4.46 - 27.10 across the landscape for Na, K, Mg, and Ca, respectively (Table 10). Generally, the abundance of cations occupying the exchange site followed the order of Ca\u003csup\u003e2+\u0026nbsp;\u003c/sup\u003e\u0026gt; Mg\u003csup\u003e2+\u0026nbsp;\u003c/sup\u003e\u0026gt; K\u003csup\u003e+\u0026nbsp;\u003c/sup\u003e\u0026gt; Na\u003csup\u003e+\u003c/sup\u003e throughout the profiles, which was found in how a productive agricultural soil should contain these basic cations. The percent base saturation (PBS) of the soil of the study area varied from 18.7 to 99.4%. Soil horizons in AYB-2 and 6 were recorded as high-value PBS compared to others. Regarding Cation exchange capacity (CEC),\u0026nbsp;the overall CEC of the studied soils ranged from 28.7 to 54.52 cmol\u003csub\u003e\u0026nbsp;(+)\u003c/sub\u003e kg\u003csup\u003e-1\u003c/sup\u003e soil along the toposequence (Table 10). The lowest and highest values were recorded in the topsoil of AYB-2 (cultivated land) and AYB-3 (grassland).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 10. Exchangeable base (Na, Mg, K, and Ca) and CEC of the studied soil profiles along the toposequence.\u003c/p\u003e\n\u003ch3\u003e3.3.4 Extractable Micronutrients (Fe, Cu, Zn, and Mn)\u003c/h3\u003e\n\u003cp\u003eIn the studied soil profiles, the mean values of extractable micronutrients (i.e., Fe, Cu, Zn, and Mn) in different soil depths are presented in Table 11.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 11. Micronutrient availability in the studied soil profiles along the toposequence.\u003c/p\u003e\n\u003cp\u003eThe contents of available micronutrients varied with soil depth and showed a decreasing trend with increasing depth. However, their trend with topographic position is inconsistent.\u0026nbsp;The contents of extractable Fe, Cu, Zn, and Mn in the studied profiles ranged from 11.42 to 21.10, 1.15 to 3.79, 0.15 to 1.16, and 3.93 to 12.88 mg kg\u003csup\u003e\u0026minus;1\u003c/sup\u003e soil, respectively. The extractable micronutrients followed the order of Fe \u0026gt; Mn \u0026gt; Cu \u0026gt; Zn in their concentration in all profiles across the landscape. The result showed that the surface soil layers had higher contents of available micronutrients than the subsurface soil layers. Mean values of the surface layers\u0026apos; extractable micronutrients were significantly varied compared to the subsurface layers (Table 11). In contrast, the mean difference among profiles along the toposequence was insignificant.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e3.4 Soil classification and mapping\u003c/h2\u003e\n\u003cp\u003eThe soil classification system and maps are the final steps of the soil survey, asserting soils by similar characteristics and/or properties and making the knowledge accessible to policy-makers, farmers, and the scientific community (Bockheim et al., 2014). Soil maps, which can be effectively produced with statistical models in digital soil mapping (DSM), contain vital information on the spatial distribution of soil properties used in fields such as water- and land management and climate studies (van der Westhuizen et al., 2022). Currently, Mendes and Dematt\u0026ecirc; (2022) and \u0026nbsp;Hartemink and Bockheim (2013) explained that soil maps at regional and farm levels are essential for the best management of agricultural practices. Therefore, based on the morphological, physical, and chemical properties, the studied soil profiles were classified according to FAO/WRB legend (IUSS Working Group WRB, 2015). Accordingly, five soil orders were identified: Leptosols, Luvisol, Fluvisol, Cambisol, and Vertisol (Table 12, Figure 7). As reported by Nyssen et al. (2019), Leptosols and bare rock are found on the steepest slopes (\u0026gt;40%), which is concurrent with our result.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 12. Classification of soils studied at Ayiba watershed according to the FAO-WRB Soil Classification System.\u003c/p\u003e\n\u003cp\u003eFigure 7. Spatial soil map of Ayiba watershed according to WRB system.\u003c/p\u003e\n\u003ch2\u003e3.5 Potential and Limitation of the Studied Soils for Agricultural field crops\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eThe soil units represented by AYB-1 and AYB-4 are not suitable for agricultural use (Table 13) due to stoniness, slope steepness, shallow depth, rock outcrops, and highland position with erosion threats and other soil restraining factors which limit the workability of the soil. Hence, agricultural production on these soils will cause a decrease in yield and soil loss due to high erosion hazards, and cultural approaches such as soil cultivation, irrigation, and fertilization are not economically feasible. Thus, it is essential to perform conservative and sustainable agricultural practices in these areas like pasture, perennial fruits, and forests. The lower slope area\u0026apos;s soil is very suitable for field crop agricultural use with limited fertility, low erosion, and climate. However, the lower slope soils represented by AYB-5 and AYB-6 are very limited in area coverage to accommodate the population size, which is the main reason for expansion to marginal lands.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBesides, during high and prolonged rainfall, the flood flow from all directions is collected to the lower landscape position, damaging farms and grasslands by flood hazards\u0026nbsp;(Seifu et al., 2020). In addition, during the high rainfall season, waterlogging is also common in Vertisol soils and the foot slope soils. However, most agricultural production occurs on the middle topography, which is marginal land, and this unsustainable land use contributes to low and declining crop productivity and further land degradation. The substantial area of marginal lands, many of them in steep areas (\u0026lt;30%) with coarse and degraded soils, could adopt sustainable agricultural technologies like integrated organic and inorganic management practices or growing double legumes to improve the long-term sustainability of the system.\u0026nbsp;Not suitable areas must be excluded from land spreading plans due to the high risk of degradation (environmental, economic, and societal).\u003c/p\u003e\n\u003cp\u003eIn contrast, an improvement or remediation plan should be developed and implemented.\u0026nbsp;The soil units in the lower landscape and at a nearly gentle slope of the middle terrain have well-drained, deep soil and are less stony than others. However, erosion, climate, and soil fertility are still significant problems in all topographic positions for agricultural production (Table 13).\u003c/p\u003e\n\u003cp\u003eTable 13. Suitability classification of the different soil units for agricultural field crops.\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003e4.1. Profile site and soil morphological characteristics\u003c/h2\u003e \u003cp\u003eThe slope, parent materials, and land use types are the major contributing factors to the differences in site characteristics. Effects of land use, extensive and intensive farming, and removal of vegetation cover have amplified the erosion process, which was observed at all profiles and their surrounding landscapes. Debie et al. (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) also confirmed that accelerated soil erosion by water is a critical problem in Ethiopia's soil landscape. For instance, Ibrahim et al. (\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) reported upper topography was well-drained while the middle and valley bottom was poorly drained, and soils in the lower topographic locations were saturated with moisture longer than upper slope soils. Likewise, previous research findings also highlighted that erosion intensity might depend on slope class, topographic position, and land use (Deressa et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Schaetzl, \u003cspan citationid=\"CR125\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Schaetzl (\u003cspan citationid=\"CR125\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) reported that slope controls the movement of matter and energy downslope. It has minimal summit position and an erosional, transportational, and depositional effect on shoulder, middle, and foot slope positions.\u003c/p\u003e \u003cp\u003eSoil color may vary with depth in the soil profile and from place to place in a landscape (Phogat et al., \u003cspan citationid=\"CR114\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Soil color is also used to determine soil classification and its physical, chemical, and biological properties (Baek et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The variation in soil color matrix noticed within and amongst the profiles might be attributed to the soil's difference in mineralogy and chemical composition, organic matter and clay contents, and drainage condition, which may affect the redoximorphic responses in the soils. Moreover, the yellow and brown color is typically related to the extent of oxidation, hydration, and diffusion of Iron oxides in the soils and mostly due to the presence of goethite and magnetite, respectively (Phogat et al., \u003cspan citationid=\"CR114\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). For instance, the darker color indicates the presence of higher decomposed organic matter (\u003cem\u003ehumus\u003c/em\u003e). As a result, most surface layers have a darker color than subsurface horizons. Others reported similar results in Ethiopia and China (Abate et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Ali et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Beyene, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Dinssa and Elias, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Liu et al., \u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The subsurface horizon (\u0026lt;\u0026thinsp;80 cm) soil color of the foot slope was dark grey to brown, suggesting that soils comprised fine-textured colluvial and alluvial materials. In harmony with this work, Tun\u0026ccedil;ay and Dengiz (\u003cspan citationid=\"CR139\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) reported a similar result in Turkey's central Black Sea Region.\u003c/p\u003e \u003cp\u003eSoil structure, which refers to how particles of soil are grouped by physical, chemical, and biological processes, is most usefully described in terms of grade (degree of aggregation), class (average size), and type of aggregates (form). The robust structure formed in the subsurface horizons is due to the overlying layers, reduction in organic matter, high clay accumulation, and reduction in plant root abundance, as was also discussed by a previous study (Dinssa and Elias, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). From A-horizon down to the bedrock R-horizon the structure changes from massive to crumbly structure with depth. All the six profiles showed weak grade granular type soil structure in the A-horizon due to relatively high organic matter content, and the gravel content was observed to be higher in the parent material layer (Boateng et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Dinssa and Elias, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Yitbarek et al., \u003cspan citationid=\"CR153\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe sticky to very sticky/plastic to very plastic consistency in surface and subsurface horizons indicated low organic matter content and hard to work with these soils. On the other hand, soils with very sticky and very plastic consistency revealed that smectite clays in the soils are high (Ali et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Kumari and Mohan, \u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Dinssa and Elias (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and Ayalew et al. (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2015b\u003c/span\u003e) reported a similar result in the soils of Bako Tibe district and Yigossa watershed, Ethiopia. In northern Ethiopia, Nyssen et al. (\u003cspan citationid=\"CR111\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) also analyzed those mass movements in many landscapes that transported materials from their \u003cem\u003ein situ\u003c/em\u003e upland basaltic over the lower-lying sedimentary rocks, raising the chance for clay soil to develop. Available water for plant roots is strongly affected by stoniness (Nyssen et al., \u003cspan citationid=\"CR111\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), and the soil texture becomes fine with an increase in plant root components (Liu et al., \u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec23\" class=\"Section2\"\u003e \u003ch2\u003e4.2. Soil physical characteristics of the profiles\u003c/h2\u003e \u003cp\u003eSoil texture is the most stable physical property which influences other soil properties like soil structure, consistency, soil moisture regime and infiltration rate, runoff rate, erodibility, workability, permeability, root penetrability, and fertility of the soil. The soil texture distribution of the fine earth fraction demonstrates an abrupt textural change between surface and subsurface horizons, where an increase in clay is accompanied by a decrease in sand-sized particles across the horizon boundary. The general increase in clay content with depth might be attributed to the vertical translocation of clay through the processes of lessivage and illuviation from surface to subsoil. Likewise, others have reported many findings in different parts of Ethiopia (Fekadu et al., \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Kebede et al., \u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Yitbarek et al., \u003cspan citationid=\"CR153\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). According to Hazelton and Murphy (\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) rating the general abundance of the particle distribution was found in low to medium sand, low silt, and very high clay at upper slope profiles; high to very high sand, low to medium silt, and low clay at middle slope profiles; and low to very high sand, low to medium silt, and low to high clay at foot slope profiles. The variation indicates that topography influences the pattern of soil particle distribution over the landscape (Esu et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2008\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe decreasing or increasing pattern in soil fractions with depth indicated the existence of soil water erosion from \u003cem\u003ein situ\u003c/em\u003e formation or accumulation and weathering of primary minerals in B-horizons. For instance, the increase in clay content with depth indicates clay migration or probably shows the presence of active eluviation-illuviation pedogenic processes. In contrast, the seasonal water erosion effect and redoximorphic features could explain the decrease at the surface horizon. Clay translocation and enrichment fulfilled requirements for the argic subsurface horizon development (IUSS Working Group WRB, \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Soil Survey Staff, \u003cspan citationid=\"CR135\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). The variation in soil development may be due to unstable landscape features (rugged and sloppy) where pedogenesis trends are often altered.\u003c/p\u003e \u003cp\u003eThe water logging at the foot slope, which may probably cause deterioration of structured B-horizon and dispersion of clay particles down with water table front, was similarly reported by Choudhury et al. (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Other authors Li and Lindstrom (\u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e2001\u003c/span\u003e) correspondingly explained that water erosion has the potential to modify the spatial patterns of soil properties on hilly landscapes. Our result is also consistent with the justification of Ellerbrock and Gerke (\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). They revealed that soil particles could be transported along slope gradient during erosion, accumulate in the foot slope position (depressions), and form colluvial soil. Likewise, others also observed a decrease in fine fractions in the steeper slope due to the selective removal of fine particles by water erosion (Ezeabasili et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Seifu et al., \u003cspan citationid=\"CR129\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Wubie and Assen, \u003cspan citationid=\"CR148\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eContrary to our result, Uwitonze et al. (\u003cspan citationid=\"CR141\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) reported that particle size distribution did not show a clear trend with depth, and Amanual et al. (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) described clay content as higher on the top and declining with depth. Bald (2012) reported a similar justification suggesting that clay deposition in the subsurface is episodic, possibly in conjunction with the wet and dry cycle climate experience, regarding the eluviation-illuviation pedogenic processes. According to this idea, fine-grained deposits may be converted into typical loess due to weathering and soil-forming processes.\u003c/p\u003e \u003cp\u003eThe silt/clay ratio of the subsoil is lower than the surface horizons, and the higher percentage in the surface layers reflects the annual alluvial enrichment of the surface through deposition by annual floods. Such a result suggests the presence of weatherable mineral reserves in the soil (Elias, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The result agrees with the report of other findings in Nigeria and Ethiopia (Adegbite et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Mohammed et al., \u003cspan citationid=\"CR104\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Sharu et al., \u003cspan citationid=\"CR133\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). According to Asamoa (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e1973\u003c/span\u003e) and Egbuchua and Ojobor (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), the silt/clay ratio below 0.15 indicates that such soils are of old parent material, while those above 0.15 are of young parent materials. Therefore, in our case study, all the profiles along the toposequence recorded far above 0.15, confirming that the soils are young with weatherable reserve materials and have not gone through ferralitic pedogenesis, which was in accord with other findings (Achimota, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Adegbite et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Van Ranst and De Coninck, \u003cspan citationid=\"CR144\" class=\"CitationRef\"\u003e2002\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe variations in degrees of clay enrichment were related to slope positions and land use. The relatively small differences between the highest and lowest amounts of clay contents in the foot slope position are attributed to active pedoturbation through the shrink-swell phenomenon. While the high clay enrichment ratio in the upper position of AYB-1 is probably due to minimum erosion occurrences mainly happened splash and sheet erosion in which its severity is highly correlated to rainfall intensity and longevity. Crusting is more severe in coarse and medium-textured soils than in fine-textured soils, and soils with an organic matter of less than 1% are more prone to crusting (Phogat et al., \u003cspan citationid=\"CR114\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe relatively lower BD values obtained at the surface soil horizons may be attributed to the structural aggregation of the soils due to relatively high organic matter content and congelifraction. This facilitates the development of porous soil structure with low rooting impedance (Brady and Weil, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Washburn, \u003cspan citationid=\"CR145\" class=\"CitationRef\"\u003e1979\u003c/span\u003e), which is common in high latitudes and altitudes (Anonymous, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Besides, soil compaction resulting from intensive cultivation and overgrazing might have caused higher bulk density values in the cultivated, and free grazing land uses compared to others. Soil type may be a possible reason for high bulk density and low porosity. Compaction affects nearly all soil properties and functions, affecting roots' growth, distribution, function, and crop productivity. Correspondingly, others reported an increase in soil strength further down the soil profile (Ali et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Chaudhari et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Gao et al., \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe ideal BD for plant growth ranges from \u0026lt;\u0026thinsp;1.10 g cm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e for clay to \u0026lt;\u0026thinsp;1.6 g cm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e for sands (Schoonover and Crim, \u003cspan citationid=\"CR127\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Thus, following the aforementioned critical values for root penetration, some are expected to be limited and affected, while the rest are in a reasonable range. Per the rating system of the effect of BD on soil condition (Hazelton and Murphy, \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), profiles at upper, middle, and foot slope topography are too compact to very compact, very open to satisfactory, and very available to excessively compact, respectively. The bulk densities in the studied area were moderate in the upper and middle landscape, whereas low to very high in the foot slope landscape. The good record shows that BD is not expected to impede root penetration and water movement restriction in these soils.\u003c/p\u003e \u003cp\u003eNevertheless, the BD values of the studied soils are favorable for crop production since the values are within the range that favors the growth of crops in tropical soils. However, profile 5 (Vertisols) were recorded with relatively high BD (\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026ge;\u003c/span\u003e\u0026thinsp;1.6 g cm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e), which might be due to the smectite/montmorillonitic group of clay minerals which show cracks between hard clods when dry and are difficult to till. Such soils need corrective management like manuring, cover crop, and other agronomical recommended field management to Vertisols soil types. Bulk density values exceeding 1.8 g cm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e indicated the likely presence of duripans or fragipans (Kefas et al., \u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In addition, the total porosity also almost lay within the usual range of 30\u0026ndash;70% (Hazelton and Murphy, \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Hence, most soils in the Ayiba watershed have an acceptable range of total porosity values for crop production.\u003c/p\u003e \u003cp\u003eWater content plays a central role in soil physical dynamic processes, and high water retention capacity enables soils to have more water, which acts as a moisture reserve for plants during water shortage periods (de Lima and da Silva, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Soil water holding capacity for use by plants is critically important for all farmers. Soil that stores large amounts of water without waterlogging problems can keep plants alive and well for prolonged periods during droughts. Topography influences soil properties through two main \u0026ldquo;tools\u0026rdquo;: The gravity-driven lateral migration and accumulation of water and spatial differentiation of the temperature regime of slopes (Florinsky, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). According to Hazelton and Murphy (\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), available soil water holding capacity (%v) for a soil profile is rated as low (\u0026lt;\u0026thinsp;10), medium (10\u0026ndash;20), and high (\u0026gt;\u0026thinsp;20). Hence, the AWC at the upper slope was found medium, while low to medium in the mid and foot slopes. Soils that fall below the stated ideal range are probably due to high bulk density caused by intensive cultivation, unrestricted grazing, and low organic matter content due to the complete removal of crop residue.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003e4.3. Chemical characteristics of the studied soils\u003c/h2\u003e \u003cp\u003eThe lowest pH reading was found in the upper horizon soils at each site, with higher pH values at depth which might be due to the movement of cations from surface soil to subsurface soil. Similar results were also observed and reported by others (Ali et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Ayalew et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2015a\u003c/span\u003e; Sharu et al., \u003cspan citationid=\"CR133\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Yitbarek et al., \u003cspan citationid=\"CR154\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), who confirmed that an increment in soil pH down horizon might indicate the presence of vertical movements of exchangeable bases, which is caused by decreased in organic matter content with depth. All soil pH records documented at the study site are favorable for most crops per the pH scale stated by EthioSIS (2014) and Hazelton and Murphy (\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The low EC may also be due to free drainage conditions, favoring the removal of released bases by percolation and drainage. The variation in soil pH is probably attributed to the nature of the parent material, leaching of basic cations, and presence of CaCO\u003csub\u003e3\u003c/sub\u003e and exchangeable Na as discoursed by Deressa et al. (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) and Shalima and Anil (\u003cspan citationid=\"CR131\" class=\"CitationRef\"\u003e2010\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe higher concentration of CaCO\u003csub\u003e3\u003c/sub\u003e at the subsurface than at the surface horizons might be ascribed to the effect of leaching and parent material which was in accord with the result of others in Ethiopia and else (Ahmed et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Debele et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Ozsoy and Aksoy, \u003cspan citationid=\"CR113\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Sebnie et al., \u003cspan citationid=\"CR128\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Regarding the rating of CaCO\u003csub\u003e3,\u003c/sub\u003e there is no clear and precise rating for the contents of free carbonates, but values of over 40% can be considered highly calcareous (Avery, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e1964\u003c/span\u003e). In addition, FAO (\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2006a\u003c/span\u003e) also stated that soil horizons having a CaCO\u003csub\u003e3\u003c/sub\u003e content of \u0026gt;\u0026thinsp;15% within 100 cm from the soil surface qualifies for a calcic horizon and such high carbonate contents affect both physical and chemical properties of soils. In the current study, the level of CaCO\u003csub\u003e3\u003c/sub\u003e is recorded far\u0026thinsp;\u0026lt;\u0026thinsp;15%, which is a very low rate.\u003c/p\u003e \u003cp\u003eThe results obtained regarding SOC and TN are similar (Akhtaruzzaman et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Fekadu et al., \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Ibrahim et al., \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Ostrowska and Porębska, \u003cspan citationid=\"CR112\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) who quantified SOC and TN that showed significant variation in depth. The values are under the category of low to very low rate for SOC and medium to very low rate for TN according to the rating of EthioSIS (2014), and this coincides with the amounts usually present in arid climates due to the rapid rate of mineralization. The low SOC and TN in most profiles could be ascribed to the removal of vegetation at the expense of cultivation and complete removal of crop residue mainly for livestock feed, limited use of organic fertilizer sources, unrestricted grazing, and rigorous cultivation, which was similar to the result observed in other studies (Ali et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Elias, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Fekadu et al., \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Sebnie et al., \u003cspan citationid=\"CR128\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). As a result, the low SOC and TN content recorded on most soils cannot sustain crop production for a long time. Thus, the organic matter content has to be substantially enhanced through effective crop residue management and organic fertilizers.\u003c/p\u003e \u003cp\u003eThe lower the C/N ratio, the faster the decomposition of fresh organic matter. Thus, the C/N ratio influences the decomposition of organic matter, either toward the primary mineralization (low C/N), or towards humification (high C/N) (Yerima and Van Ranst, \u003cspan citationid=\"CR151\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). The C/N ratio mainly controls the decomposition rate and is a source of food and energy for plants in the soil. The higher C/N percentage leads to a slow decomposition rate, nutrient immobilization, and wastage of carbon and energy. In contrast, quite the reverse, in low C/N ratio, but carbon and energy starvation occur and the C/N percentage varies from 10 for leguminous and young plant materials to about\u0026thinsp;\u0026gt;\u0026thinsp;100 for cereal straws (Thippeshappa and Vadivel, \u003cspan citationid=\"CR137\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). The C/N ratio in plant tissue is variable, depending largely on plant species and age. Still, the end-product of plant tissue decomposition is always humus which has a reasonably constant C/N ratio (Yerima and Van Ranst, \u003cspan citationid=\"CR151\" class=\"CitationRef\"\u003e2005\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe variability of the C/N ratio was not significant in each profile, indicating that it was lower than the variability of SOC and TN contents. It may suggest that the C/N ratio is more stable than its elements. Likewise, in agreement with our finding, Kirkby et al. (\u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) observed insignificant differences between C/N ratios in SOM and the soil. Others like Yitbarek et al. (\u003cspan citationid=\"CR153\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) in the Abobo area, western Ethiopia, and Yimer (\u003cspan citationid=\"CR152\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) in the central rift valley area of Ethiopia also reported a similar result. Although the decomposition rate was not measured, a higher C/N ratio signifies moderate stress in the microbial decomposition of organic matter and N-mineralization (Elias, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe soil C/N ratio is often considered a soil nitrogen mineralization capacity sign. A C/N ratio of about 10 suggests a relatively better decomposition rate. It indicates better nitrogen availability to plants, and there will be possibilities to incorporate crop residues into the soil without the adverse effect of nitrogen immobilization. According to Gebreselassie (\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2002\u003c/span\u003e), the optimum range of the C/N ratio is about 10:1 to 12:1, which provides nitrogen over microbial needs. Yerima and Van Ranst (\u003cspan citationid=\"CR151\" class=\"CitationRef\"\u003e2005\u003c/span\u003e) also classified the C/N ratio as low (\u0026lt;\u0026thinsp;10), medium (around 20), and high (\u0026gt;\u0026thinsp;50). Accordingly, the C/N ratio of the surface soils across the topography may be considered below the optimum range in all soils for microbial needs except at AYB-1 and 6. Sakin et al. (\u003cspan citationid=\"CR118\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) found the C/N ratio of arable soils much lower than 10, which might indicate N input from external sources, mainly from fertilizers and deposits. On the other hand, prolonged intensive farming also led to a continuous increase in soil nitrogen (Deng et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Yang et al., \u003cspan citationid=\"CR149\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe lower P content in the subsurface horizons could be ascribed to the fixation of P by clay minerals and oxides of Iron and Aluminum. The overall profile means av. P content was found in harmony with the result observed in other studies (Bekele et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Debele et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Fekadu et al., \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Raghuvanshi et al., \u003cspan citationid=\"CR115\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Sebnie et al., \u003cspan citationid=\"CR128\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Based on the ratings of EthioSIS (2014), the average av. P content was found in the low to medium category. Phosphorus deficiency in Ethiopian soils is well documented as a result of depletion and slow recycling due to a fixation on the inherent low occurrence (Bekele et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Elias, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Fekadu et al., \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Mesfin et al., \u003cspan citationid=\"CR103\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Moreover, the low content of av. P could be attributed to fixation by Ca content as Ca-P (Ca bounded) \u0026ndash; the significant inorganic P fraction in alkaline soils (Landon, \u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe S and B in agriculture are now gaining importance because their role in increasing crop production is recognized. Available S is the primary source of S taken up by most crops. The source is the SOM via the microbial pool or directly from animal residues, atmospheric inputs, or fertilizers (Zebire et al., \u003cspan citationid=\"CR156\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Whereas B, usually present in soil solution as a non-ionized molecule (H\u003csub\u003e3\u003c/sub\u003eBO\u003csub\u003e3\u003c/sub\u003e), is an essential trace element desired for the physiological functioning of higher plants. B deficiency is considered a nutritional disorder that adversely affects the metabolism and growth of plants because B is involved in the multi-structural and functional integrity of the entire plant system. The difference between deficiency and toxicity limits is very narrow; hence, B requires judicious fertility management (Das and Purkait, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Shireen et al., \u003cspan citationid=\"CR134\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Das and Purkait (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) also emphasized that site-specific and crop-specific nutrient management should be taken care of while dealing with B soils under divergent geographical and climatic zones.\u003c/p\u003e \u003cp\u003eGenerally, the av. S and B contents of the studied soil profiles decreased with profile depth and were found in very low and very low to low, respectively (EthioSIS, 2014). Similarly, Dinssa and Elias (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) reported very low to low B distribution in the Bako Tribe of western Ethiopia. The pH is retained as the main factor affecting B adsorption in agricultural soils (Santos et al., \u003cspan citationid=\"CR122\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), as well as soil texture, soil moisture, parent material, clay nature and content, Al and Fe (hydr)oxides, clay minerals, calcium carbonate, and organic matter and interrelationship with other elements affect the B concentration in soil (Ahmad et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Arora and Chahal, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). For instance, W\u0026oacute;jcik (\u003cspan citationid=\"CR147\" class=\"CitationRef\"\u003e2000\u003c/span\u003e) reported high B deficiency on coarse texture soils and recommended the application of calcium nitrate or ammonium nitrate would be appropriate to keep B more available to plants.\u003c/p\u003e \u003cp\u003eOnly a small percentage of the available nutrients move freely in the soil solution. Most are loosely bound on mineral and organic surfaces in exchangeable form. This mechanism acts as a storehouse both for nutrient cations and anions. For instance, clay minerals, especially illitic and montmorillonitic types, have large negatively charged surfaces on which cations like Ca\u003csup\u003e2+\u003c/sup\u003e, Mg \u003csup\u003e2+\u003c/sup\u003e, and K\u003csup\u003e+\u003c/sup\u003e are adsorbed and, therefore, protected against leaching (FAO, 2006b). According to FAO (2006b), a deviation from the order of Ca\u003csup\u003e2+\u003c/sup\u003e \u0026gt; Mg\u003csup\u003e2+\u003c/sup\u003e \u0026gt; K\u003csup\u003e+\u003c/sup\u003e \u0026gt; Na\u003csup\u003e+\u003c/sup\u003e can create ion-imbalance problems for plants; thus the result showed appropriate basic cation distribution in the studied soils. The prevalence of Ca\u003csup\u003e2+\u003c/sup\u003e followed by Mg\u003csup\u003e2+\u003c/sup\u003e, K\u003csup\u003e+\u003c/sup\u003e, and Na\u003csup\u003e+\u003c/sup\u003e in the exchange site of soils is favorable for plant production (Tizita, \u003cspan citationid=\"CR138\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The result might be related to the parent material from which the soils developed and their differential attraction to the soil\u0026rsquo;s exchange complex. The extent of exchangeable base distribution was not consistent along the toposequence. However, soil depth showed an increasing trend for all exchangeable bases. The studied soils were very low to medium in Na, low to very high in K and Ca, and medium to very high in Mg, following the rate suggested for exchangeable bases by EthioSIS (2014). Other previous studies also reported similar findings in Ethiopia's agroecological settings (Abate et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Abu, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Ali et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Bekele et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This study observed a trend of PBS with depth, possibly due to the leaching of bases from the overlying layers and subsequent accumulation in the subsurface horizons. The PBS was also recorded very low to very high along the toposequence (EthioSIS, 2014; Hazelton and Murphy, \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The high base saturation of the soil was consistent with high contents of exchangeable bases (chiefly Ca\u003csup\u003e2+\u003c/sup\u003e and Mg\u003csup\u003e2+\u003c/sup\u003e), as reported similarly by others (Abu, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Elias, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Fekadu et al., \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Sekhar et al., \u003cspan citationid=\"CR130\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eCation exchange capacity (CEC), the capacity of a soil or any other substance with a negatively charged exchange complex to hold cations in an exchangeable form, mainly depends on the type and proportion of clay minerals and organic matter present in the soil (FAO, 2006b). The result of CEC was found qualified in the range of high to very high rating (EthioSIS, 2014; FAO, 2006b; Hazelton and Murphy, \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), which corresponds to clay content, organic carbon content, and type of clay mineral present. Most studies also showed a direct relationship between organic matter, clay content, and CEC (Fekadu et al., \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Tizita, \u003cspan citationid=\"CR138\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Yitbarek et al., \u003cspan citationid=\"CR153\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The high CEC result revealed that the soils of the studied profiles had good nutrient retention and buffering capacity. Many previous studies confirmed that deforestation, intensive cultivation, land-use change, and the nature of the topographic position led to a decline in CEC (Abate and Kibret, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Bore and Bedadi, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Sanaullah et al., \u003cspan citationid=\"CR120\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Yitbarek et al., \u003cspan citationid=\"CR153\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMicronutrients are essential for good crop performance (Ilori and Shittu, \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). The higher micronutrient soil profile distribution at the surface than in subsurface soils in this study may be attributable to the accumulation of organic matter content on the topsoil or supplementary additions through chemical fertilizers and continuous transport of the micronutrients from root depth (via absorption by plants and subsequent litterfall). A decrease in the extractable micronutrient level of the subsurface horizon also provides evidence that these elements were phytomining and redeposited on the surface with organic matter. The acquisition of biomass in the top layer leads to higher organic matter and increased clay content in the surface soils. Organic matter decreases oxidation and precipitation loss, and the chelating agents present in the organic matter, depending upon their solubility potential, improve micronutrient solubility, thereby increasing their availability. Similar trends have been observed in previous studies (Akhtaruzzaman et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Garc\u0026iacute;a-Marco et al., \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Ivana et al., \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Jiang et al., \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Joshi et al., \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Sarker et al., \u003cspan citationid=\"CR124\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) who reported the highest micronutrient concentrations in topmost of soil, with concentrations decreasing down the profile. These authors also confirmed that available micronutrients are strongly associated with soil organic matter content in surface soil. The results also agree with Yitbarek et al. (\u003cspan citationid=\"CR153\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), who reported the influence of texture and organic matter content on extractable micronutrients. Moreover, Sharma et al. (\u003cspan citationid=\"CR132\" class=\"CitationRef\"\u003e2004\u003c/span\u003e) also highlighted that extractable micronutrients increased with increased organic carbon content and CEC and decreased with increasing pH, sand, and calcium carbonate content.\u003c/p\u003e \u003cp\u003eTopology, parent materials, irrigation water, land use types, biological cycling, anthropogenic disturbance, leaching, pH, and organic matter contents significantly affected the micronutrient availability to a different extent (Jiang et al., \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Zhang et al., \u003cspan citationid=\"CR158\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Others also added (Dibabe et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Jiang et al., \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) that the high levels of micronutrients are consistent with high organic carbon content and low soil pH. Soil organic matter favors a lower redox potential environment and enhances soil health and the accessibility of micronutrient cations in the soil (Dhaliwal et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). A reduction in the availability of micronutrients with increasing pH can be attributed to the conversion of micronutrients to insoluble forms in soil (Fageria and Baligar, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e1997\u003c/span\u003e). With an increase in pH, the primary soluble form of Mn (Mn\u003csup\u003e2+\u003c/sup\u003e) oxidizes to form higher oxidation states (Mn\u003csup\u003e3+\u003c/sup\u003e/Mn\u003csup\u003e4+\u003c/sup\u003e) which are insoluble in soil water and become unavailable to plants. Plants in their divalent state also take up elemental Cu. With an increase in pH, higher oxidation states of Cu predominate, which show more excellent retention by soil colloids (OM, clays, etc.), thus reducing their availability (Ivana et al., \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Kumar and Babel, \u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAccording to the critical interpretative values for extractable micronutrients set by EthioSIS (2014), the mean values for extractable Fe, Cu, Zn, and Mn in all profiles were rated as high, medium, low, and high, respectively. Accordingly, none of the soils studied is deficient in Fe, Cu, and Mn; however, Zn deficiency is observed along the toposequence. High calcium carbonate content (\u0026gt;\u0026thinsp;15%) in neutral to alkaline soils of semi-arid/arid regions, low OM in sandy soils, waterlogging conditions, precipitation or adsorption of zinc with various soil components depending on the soil pH, organic matter, pedogenic oxides, and redox potential are reported to be responsible for low Zn availability (Arunachalam et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Lal et al., \u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Although the significant contribution of chemical fertilizers (e.g., DAP to supply P) was found effective in nutrient supply for intensive cultivation, the increased use of these fertilizers in an imbalanced manner is also responsible for micronutrient deficiency. The concern regarding the Zn deficiency problem is growing daily as Zn plays numerous roles in the biological functions of plants and humans and is considered an essential micronutrient for their growth and development (Alloway, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2008\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec25\" class=\"Section2\"\u003e \u003ch2\u003e4.4. Potential and Limitation of the Studied Soils for Agricultural field crops\u003c/h2\u003e \u003cp\u003eSoil suitability, the fitness of a given type of soil for a defined use, is a precondition for sustainable land use planning (Doula et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Sarkar et al., \u003cspan citationid=\"CR123\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) and is necessary for precision as attributes of land can be suitable for specific crops but unsuitable to others. Unsuitable land use has potential limitations or constraints that can severely impair its function or not meet the requirement for a particular service. Pressures on land resources by conversion from their natural state to human use are pushing the productive capacity of land systems to the limit (FAO, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Liu et al., \u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Therefore, the erroneous of selecting the correct land for the cultivation of a particular agricultural product is becoming a long-standing and mainly empirical issue. Although many recommended and provided a framework for optimal agricultural land use, it is suspected that much agricultural land use is still below its optimal capability in different parts of the world.\u003c/p\u003e \u003cp\u003eThe land used for agricultural production must be used according to its potential for optimization and sustainability of soil productivity. This becomes vital to Ethiopia when precision farming is gaining wider acceptance. The relevance is particularly more nowadays in the developing world where the use to which a land functions very often is not related to its capacity. A significant problem of agricultural development in Ethiopia is poor knowledge and appraisal of land suitability for agricultural production. Hence, in this study, the different soil units were classified according to their capability and suitability for agricultural field crops into very suitable soils, moderately suitable soil, marginally suitable soils, and not suitable soils, according to internationally recognized suitability classes outlined by FAO (\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e1984\u003c/span\u003e) and Schoeman et al. (\u003cspan citationid=\"CR126\" class=\"CitationRef\"\u003e2002\u003c/span\u003e) which can be adapted and applied at both regional and local scale.\u003c/p\u003e \u003cp\u003eIn harmony with this result, Girmay et al. (\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) also reported similar problems for Gateno watershed soil suitability analysis. Others also mentioned these problems and signified the importance of soil suitability analysis for particular areas for sustainable land resource use and better production (Alemu et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Nyssen et al., \u003cspan citationid=\"CR111\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Yohannes and Soromessa, \u003cspan citationid=\"CR155\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). In addition, Liu et al. (\u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) noted that landscapes are not managed sustainably when marginal lands are cultivated or more fertile. It can lead to soil erosion and degradation, loss of livelihoods, and a decrease in the overall resilience of the social-ecological system.\u003c/p\u003e \u003cp\u003eTherefore, employing different soil and water conservation measures and adopting integrated soil fertility management coupled with appropriate agronomic practices and appropriate land-use systems according to their fitness is critically important to reduce the continuing soil degradation and to increase production sustainably. In general, the relationships between features of the landscape, soil characteristics, and soil types will help to advance soil-landscape relations and show a less costly way of acquiring soil foundation since the performance of any crop is mainly dependent on soil properties such as depth, drainage, texture, fertility, etc., as conditioned by climate and topography.\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Conclusion And Recommendation","content":"\u003cp\u003eLow soil fertility and poor management prices constrain crop production in the study area. Hence, detailed information on soil properties by soil characterization and classification is essential to plan operative land use and soil fertility management. With this in mind, detailed soil information is needed to understand the functional variability across landscapes to improve the management and efficiency of agricultural practices and ultimately improve food security in the Ayiba area. Accordingly, this study produced a soil-landscape map of the Ayiba area for more sustainable soil use and production systems. The study involved soil profile description and understanding of soil-landscape relations. Based on the soil morphological, physical, and chemical analysis of the studied soil units: on the plateau and the steepest slope, shallow soils (Leptosols) and bare rock are found on the mountain foot slopes developed, but younger soils occur on the terraced beds (Fluvisol, Luvisol, and Vertisol), and the footslope and valley bottoms developed and deeper soils occur (Vertisol and Cambisol). Some soil physicochemical properties also showed significant variability within each generic horizon along the toposequence. In addition, moving down the slope, soil depth and profile development improved, but soil drainage conditions deteriorated.\u003c/p\u003e \u003cp\u003eThis study revealed the soils in the study area were found in the range of very low to low in SOC, av.S, and av.B; low to medium in TN and av.P, and high to very high in CEC. Most of the soil attributes measured were better in the lower topographic positions than those in the upper and middle topographic positions. Therefore, the low fertility status of the soils can be brought to better use for agriculture by incrementing soil organic matter level through the incorporation of organic fertilizer sources such as farm yard manure and by reducing the complete removal of crop residues. Moreover, some soil landscapes had a slope position greater than 30% in the study area. Thus, terracing, slope reduction, runoff velocity limitation, and the installation of appropriate drainage should be incorporated into the site management plan to limit soil erosion. These results also suggested that soil management interventions should be based on land use and site-specific information for appropriate resource management, like the application of inorganic fertilizers and rehabilitation of soils over heterogeneous landscapes to improve crop yields in the study area. This study identifies the lower position and some nearly gentle slope gradients of the middle position have suitable land for agricultural purposes. Still, not all these soils can sustain agriculture in the long term. Yet, the high percentage of unsuitable soils for cultivation found in the middle and upper topography clearly shows that the Ayiba watershed certainly has high production potential if correct land management decisions are made, like pasture, forestry, and perennial crop production. Thus, information on soil and related properties obtained from the soil survey and classification can help better delineate soil and land suitability.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData will be available upon reasonable request from the corresponding author.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMekelle University CASCAPE project partially funds this research. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions - provide individual author contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWS:\u003c/strong\u003e Conceptualization, Methodology, Software, Investigation, Resources, Formal analysis, validation, Writing Original Draft, writing review and editing, and Visualization; \u003cstrong\u003eEE\u003c/strong\u003e: Methodology, Writing-review and editing, Resources, validation, supervision, and funding acquisition; \u003cstrong\u003eGG\u003c/strong\u003e: Methodology, Data curation, writing-review and editing, validation, Visualization, Resources, supervision, and project administration; \u003cem\u003e\u003cstrong\u003eGL\u003c/strong\u003e:\u003c/em\u003e writing-review and editing, Visualization, and software; \u003cstrong\u003e\u0026nbsp;and WT\u003c/strong\u003e: Resources, Data curation, Validation, writing-review and editing, and visualization. Finally, all authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMekelle University (CASCAPE project) is acknowledged for partial financing and transport service facilitation. \u0026nbsp; We extend our thanks also to Ayiba area farmers for allowing us to open soil profiles and take soil samples from their vicinity. Remarkably, the cooperation of Mr. Haftay Etsay was immense and cherished.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors and Affiliations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eWeldemariam Seifu and Wolde Tefera\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDepartment of Horticulture and Plant Science, College of Agriculture and Natural Resources, Salale University, Fiche, Oromia, Ethiopia, P.O.Box: 245.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eWeldemariam Seifu, Eyasu Elias\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/em\u003e\u003c/strong\u003e\u003cem\u003eand \u003cstrong\u003eGudina Legesse\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eCenter for Environmental Science, College of Natural and Computational Sciences, Addis Ababa University, Addis Ababa, Ethiopia, P.O.Box: 1176\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eGirmay Gebresamuel\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLand Resources Management and Environmental Protection, Mekelle University, Mekelle, Tigray, Ethiopia, P.O.Box: 231\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAbate N, Kibret K (2016) Effects of Land Use, Soil Depth and Topography on Soil Physicochemical Properties along the Toposequence at the Wadla Delanta Massif, Northcentral Highlands of Ethiopia. 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Accessed on November 18, 2021\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1-13 are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Catena, Classification, Landscape position, soil horizon, Toposequence","lastPublishedDoi":"10.21203/rs.3.rs-2093235/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2093235/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eCurrently, soil characterization and classification are becoming the primary source of information for precision agriculture, land use planning, and management. Thus, this study was focused on perusing the landscape-scale spatial variation of soils in data-scarce areas using toposequence-based ground sampling to characterize and classify the soils. Six typical profiles representing major landforms were opened and studied for their morphological characteristics and physical and chemical properties. Results revealed that the soils were shallow to very deep in depth, moderately acidic to moderately alkaline in soil reaction, non-saline in salinity, and clay to sandy loam in texture. The soils were found to be very low to low in organic carbon, very low to medium in TN, low to medium in av. P, very low in av. S, very low to low in av. B, high to very high in CEC and very low to very high in base saturation. The soils were also found deficient in Zn and sufficient in Fe, Cu, and Mn. Following the field survey and soil analytical results, five main reference soil groups, mollic Leptosols (Eutric), Prothovertio Luvisols (Clayic, Aric, Escalic), Skeletic Fluvisols (Arenic, Densic), Haplic Leptosols (Skeletic), Haplic Vertisols (Endocalcaric, Ochric), and Haplic Cambisols (Arenic, Aric) were identified in the different parts of the topographic positions. Profile − 2, 3, 5, and 6 were classified in I to IV land capability class (LCC) and grouped as arable land with some limitations. They were also in a suitable to a marginally suitable range. The severe constraints to crop cultivation in the area are generally low fertility, erosion hazard, and climate for all soil units. Therefore, continuous manure and compost integration with chemical fertilizer, reducing complete crop residue removal, and soil and water conservation measures are essential to overcome these common and other production limitations.\u003c/p\u003e","manuscriptTitle":"Soil-landscape characterization and mapping to advance the state of spatial soil information on Ethiopian highlands: Implications for site-specific soil management","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-09-30 18:11:58","doi":"10.21203/rs.3.rs-2093235/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2ae87491-7506-4ca0-a739-2d431a537447","owner":[],"postedDate":"September 30th, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2022-09-30T18:11:59+00:00","versionOfRecord":[],"versionCreatedAt":"2022-09-30 18:11:58","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-2093235","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2093235","identity":"rs-2093235","version":["v1"]},"buildId":"omnImTCwR2MFx8CMYfrG7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}