Soil salinity sodicity and irrigation water quality in the Ethiopian Main Rift Valley and implications for sustainable management

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Increasing salt accumulation in soils and irrigation water threatens crop water productivity, soil health, and the long-term sustainability of irrigated systems. This study assessed soil salinity and sodicity, evaluated irrigation water quality, and identified management strategies for salt-affected agroecosystems. Field investigations were conducted in Kewet and Efratana Gidim districts, where 30 soil and six irrigation water samples were collected from representative landforms, including alluvial plains, river terraces, and micro-depressions influenced by hot springs. Soil properties, electrical conductivity (ECe), sodium adsorption ratio (SAR), and residual sodium carbonate (RSC) were analyzed. Results showed that a substantial proportion of sampled soils exhibited moderate to high salinity and sodicity levels, indicating significant degradation risks under current irrigation practices. Clay-rich Vertisols and Fluvisols dominated the area, with high cation exchange capacity, shrink–swell behavior, and slickensides that enhance salt retention and restrict infiltration. Salt concentrations increased with depth, with sodium and sulfate predominating, suggesting vertical redistribution under irrigation and episodic flooding. Irrigation water, particularly from Kora Spring, showed elevated SAR and RSC, increasing sodicity risks and reducing root-zone water availability. Integrated management strategies, including optimized irrigation scheduling, periodic leaching, improved drainage, soil amendments, and salt-tolerant crops, are essential to sustain productivity. These findings provide practical guidance for salinity management and contribute to understanding soil–water–climate interactions in salt-affected agroecosystems. Soil salinity Sodicity Irrigation water quality Sodium adsorption ratio (SAR) Ethiopian Rift Valley Sustainable land management Salt-affected soils Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1. Introduction Ensuring sustainable agricultural production in the twenty-first century remains a critical global challenge, particularly as the world population is projected to approach 10 billion by 2050, with the majority of growth occurring in developing regions such as sub-Saharan Africa (United Nations, 2019 ). In these regions, agricultural systems are heavily dependent on finite soil and water resources, which are increasingly vulnerable to degradation. Ethiopia exemplifies this challenge, where rapid population growth and rising food demand coincide with shrinking per capita arable land, declining soil fertility, and intensified pressure on land and water resources(FAO, 2021 ). Among the various forms of land degradation, soil salinity and sodicity are recognized as major constraints to sustainable agriculture, particularly in arid and semi-arid regions where evapotranspiration frequently exceeds precipitation (Gupta & Abrol, 1990 ; Szabolcs, 1974 ). Globally, more than one-third of irrigated lands in dry regions are affected by salinity, leading to substantial yield losses and reduced water productivity (Qadir et al., 2014 ; Rengasamy, 2006 ). Salinity-induced degradation directly impairs farm-level water management, disrupts crop water relations, and lowers irrigation water-use efficiency, thereby threatening food security and rural livelihoods. Historical evidence from major irrigated river basins, including the Indus, Tigris–Euphrates, and Nile, illustrates that inadequate irrigation and drainage management can trigger widespread soil salinization with long-term socio-economic consequences (FAO, 2011 ; Tanji & Wallender, 2012 ). Ethiopia harbors approximately 11 million hectares of salt-affected soils—the largest extent in Africa with the Ethiopian Main Rift Valley system and the Awash Basin being among the most severely impacted regions (Abegaz et al., 2022 ; Szabolcs, 1977 ). The Ethiopian Rift Valley is a tectonically active, internally drained system characterized by low relief plains, alkaline parent materials, shallow groundwater tables, and high evaporative demand, all of which favor the accumulation of soluble salts in irrigated landscapes (Ayenew et al., 2020 ; Chernet et al., 2021 ). Within this broader system, the Upper Awash Valley represents a critical upstream agricultural zone where irrigation development is expanding rapidly. At both farm and regional scales within the Ethiopian Rift Valley system, irrigation expansion without coordinated water allocation, drainage infrastructure, and water quality monitoring has intensified secondary salinization and sodication (Taddese & Bekele, 1996 ; Tsige et al., 2000 ). Recent studies emphasize that salinity problems in the Rift Valley are increasingly linked to declining water quality, groundwater upwelling, and reuse of marginal and saline water sources, especially under climate-induced water scarcity (Ayenew et al., 2020 ; Qadir et al., 2021 ). Despite these trends, significant knowledge gaps persist regarding the spatial distribution, severity, and controlling mechanisms of salinity in the Upper Awash Basin within the wider Ethiopian Rift Valley context, particularly in Kewet and Efratana Gidim districts(Ashenafi & Qureshi, 2021 ; Jiru et al., 2025 ). The physical and chemical properties of soils, which determine water flow and salinity patterns, are largely shaped by factors such as parent material, topography, climate, and vegetation (Gupta & Abrol, 1990 ; Szabolcs, 1974 ). In the Ethiopian Rift Valley, Vertisols and clay-rich Fluvisols dominate irrigated lowlands, exhibiting high clay content, shrink–swell behavior, and elevated cation exchange capacities, which enhance sodium retention and restrict leaching under inadequate drainage(Abegaz et al., 2022 ). Soil salinity is further aggravated by human practices such as intensive irrigation, land clearing, fertilizer use, and modification of natural drainage systems, particularly under high evapotranspiration and variable rainfall conditions (Ayers & Westcot, 1985 ; FAO, 1992 ). These interactions reduce infiltration, impair root-zone water availability, and ultimately decrease crop water productivity, especially in smallholder irrigation schemes. In the Upper Awash Valley, irrigation water quality plays a decisive role in shaping salinity and sodicity dynamics. Water sources within the Ethiopian Rift Valley commonly exhibit elevated electrical conductivity (EC), sodium adsorption ratio (SAR), and residual sodium carbonate (RSC), reflecting prolonged water–rock interaction and geothermal influence (Ayenew et al., 2020 ; Singh et al., 1992 ). When such waters are applied to clay-rich soils, they accelerate soil structural degradation, surface crusting, and reduced hydraulic conductivity. Seasonal climatic variability further intensifies these processes, with peak soil salinity commonly occurring during dry periods when evapotranspiration exceeds leaching potential (FAO, 1992 ; Maas, 1990 ). These conditions directly constrain crop growth, reduce yields, and lower irrigation water-use efficiency across Rift Valley irrigation systems. This study adopts a diagnostic approach to evaluate soil salinity and irrigation water quality as key constraints to efficient agricultural water management in irrigated systems, rather than quantifying crop yields or productivity. Effective salinity management in the Ethiopian Rift Valley therefore requires integrated approaches that combine improved irrigation scheduling, adequate drainage, periodic leaching, soil amendments, and the strategic use of salt-tolerant crops (Ayers & Westcot, 1985 ; Qadir et al., 2014 ; Qadir et al., 2008 ). Given increasing water scarcity, the controlled and informed use of saline and marginal-quality water is becoming unavoidable, making site-specific soil–water assessments essential for sustaining agricultural production(Pereira et al., 2009 ; Qadir et al., 2021 ). The significance of this study lies in its integrated soil–water management perspective applied within the Ethiopian Main Rift Valley system, combining physicochemical soil characterization, salinity and sodicity assessment, and irrigation water quality evaluation to elucidate degradation processes in the Upper Awash Basin. By explicitly linking soil properties, irrigation practices, water quality, and crop water relations, this research advances understanding beyond conventional assessments that treat soil or water constraints in isolation (Ashenafi & Qureshi, 2021 ; Jiru et al., 2025 ). Focusing on Kewet and Efratana Gidim districts understudied yet agriculturally important areas—this study extends salinity research to upstream Rift Valley irrigation systems. This research aims to provide a comprehensive assessment of soil properties, salinity and sodicity status, and irrigation water quality in Kewet and Efratana Gidim districts. The study seeks to clarify how interactions among soil characteristics, irrigation water quality, and management practices within the Ethiopian Rift Valley system influence crop water relations, crop productivity, and irrigation water-use efficiency under saline conditions. The findings are intended to support farm-level decision-making, guide regional irrigation and drainage planning, and inform sustainable salinity management strategies, including improved use of saline water in agriculture, thereby enhancing long-term agricultural resilience in Ethiopia’s Main Rift Valley. 2. Materials and Methods 2.1. Study Area Description and Sampling Sites The study was conducted in the Awash River Basin, situated on the eastern plateau of the East African Rift Valley in central Ethiopia (Fig. 1 ). The study area is located at approximately 10°53′02″ N latitude and 39°54′51″ E longitude, with a mean elevation of about 1,197 m above sea level. The basin is characterized by heterogeneous topography, comprising low-lying valley bottoms, gently undulating plateaus, and dissected hills, which collectively influence drainage patterns, soil development, and land use. Hydrologically, the area is dominated by the Awash River and its tributary network, which serve as the principal sources of surface water for irrigation and contribute to the recharge of shallow groundwater systems. These water resources support extensive irrigated agriculture, particularly along river valleys and alluvial plains, where irrigation has intensified over recent decades. Land use in the study area is diverse and includes irrigated and rainfed croplands, communal grazing areas, rural settlements, and remnants of natural vegetation. Sampling sites were purposively selected to represent the spatial variability of the study area, with particular emphasis on differences in Reference Soil Group, irrigation water sources, management practices, and observed salinity and sodicity conditions. This sampling design enabled assessment of soil–water interactions across contrasting landscape positions and irrigation environments within the basin. 2.2. Climate of the Study Area The climate of the Kewet and Efratana Gidim districts in the Awash River Basin is characterized by pronounced seasonal variability in both temperature and rainfall (Fig. 2 ). The area experiences a unimodal rainfall regime, with the majority of annual precipitation occurring during the main rainy season (June–September), while the period from October to May is predominantly dry. Monthly rainfall peaks in July and August, whereas negligible precipitation is recorded during the dry months, particularly from November to February. Air temperature exhibits relatively moderate seasonal fluctuations compared with rainfall. Monthly maximum temperatures generally range from approximately 25 to 30°C, with the highest values observed during the late dry and early rainy seasons (April–June). Minimum temperatures vary between about 10 and 17°C, resulting in mean monthly temperatures of roughly 18–24°C throughout the year. This combination of high temperatures and limited rainfall during the prolonged dry season leads to atmospheric water demand that exceeds precipitation. The strong seasonality of rainfall and temperature has important implications for irrigation water management and soil processes in the study area. During the dry season, high evaporative demand and limited rainfall favor soil moisture depletion and salt accumulation in the root zone, whereas the rainy season promotes partial leaching of accumulated salts and temporary improvement of soil moisture conditions. Consequently, the observed climatic regime plays a critical role in controlling water availability, irrigation requirements, and soil–water interactions under irrigated agriculture. 2.3. Geology, Geomorphology, and Soil Formation Kewet and Efratana Gidim districts are located within the Upper Awash Basin, forming part of the western margin of the Main Ethiopian Rift (MER ) , a tectonically active segment of the East African Rift System. The area is underlain predominantly by Miocene–Pliocene volcanic sequences, including extensive basaltic lava flows and ignimbrites, with localized rhyolitic and felsic volcanic deposits. These volcanic rocks serve as mineral-rich parent material, influencing soil physicochemical properties such as clay content, cation exchange capacity (CEC), and base saturation. They also regulate groundwater flow and storage, creating conditions conducive to both irrigation and salinity development. Overlying the volcanic basement, Quaternary alluvial, fluvial, and lacustrine sediments occupy the rift lowlands, forming broad valley floors and floodplains. These unconsolidated deposits, derived from erosion of adjacent highlands and escarpments, provide fertile surfaces for agriculture but are highly susceptible to salt accumulation, particularly under intensive irrigation and in areas influenced by numerous saline hot springs. The geomorphology of the districts reflects the active tectonics of the MER. The lowland rift floor consists of extensive alluvial plains, river terraces, and depositional fans, which facilitate irrigated agriculture but also concentrate salts due to shallow water tables and high evapotranspiration. Steep rift shoulders and escarpments expose volcanic bedrock and control sediment supply, drainage patterns, and localized microclimates. The thermal and saline springs, frequently aligned along fault zones, contribute substantial dissolved salts to both surface and groundwater, enhancing the risk of soil salinization and sodicity in adjacent croplands. Soil formation in the study area is controlled by the interaction of parent material, sediment deposition, topography, climate, and hydrology. The weathering of basaltic and ignimbrite units produces clay-rich Vertisols and Fluvisols, characterized by high CEC, shrink-swell behavior, and vertic features such as slickensides and cracks. These properties support nutrient retention and water storage but exacerbate susceptibility to sodicity when irrigated with sodium-rich water. Alluvial deposition and surface runoff further influence the spatial distribution of salts, while human interventions—irrigation management, fertilizer application, and land use change—interact with these natural processes, accelerating salinity development. The cumulative effects of soil texture, hydrology, geomorphology, and irrigation water quality, including inputs from hot springs, determine the spatial patterns of salinization and strongly influence the sustainability of agricultural production in the Upper Awash Basin. 2.4. Land Use and Land Cover Assessment Understanding the spatial distribution of land use and land cover (LULC) is essential for evaluating soil properties, irrigation practices, and salinity dynamics in Kewet and Efratana Gidim districts. LULC patterns influence the availability and movement of water, sediment, and soluble salts, and thus play a key role in shaping soil formation processes and salinization risk. In this study, LULC was assessed using a combination of remote sensing data, satellite imagery, and field verification, with particular attention to the distribution of irrigated and rainfed agricultural lands, natural vegetation, and water bodies. The study area is predominantly characterized by agricultural land, reflecting both irrigated and rainfed cultivation on alluvial lowlands and river terraces. These agricultural fields are interspersed with shrublands, grasslands, and limited forest patches, which have undergone significant reduction in extent due to land clearing and agricultural expansion. Barren lands and built-up areas are also present, generally concentrated near settlements and along transportation corridors, while rivers, irrigation canals, and natural water bodies, including the Awash River, constitute minor but critical features influencing local hydrology and soil salinity patterns. Field observations and GPS-based ground truthing were conducted to verify the accuracy of remote sensing interpretations and to identify areas influenced by saline hot springs, which contribute dissolved salts to surface and groundwater. This approach allowed for a detailed characterization of LULC classes and their spatial arrangement, providing a robust framework for linking land use patterns with soil properties and water quality degradation in the Upper Awash Basin. The resulting LULC dataset serves as a key input for analyzing the interactions between human interventions, irrigation practices, and natural geomorphic processes that drive salinity and sodicity dynamics in the study area. 2.5. Field Soil and Water Sample Collection To characterize the soil physicochemical properties and evaluate the influence of irrigation water on salinity dynamics, systematic soil and water sampling was conducted across representative sites in Kewet and Efratana Gidim districts. Sampling locations were selected based on land use, topography, proximity to irrigation infrastructure, and the presence of hot springs, which are known to contribute elevated salt loads to both soils and water resources. All necessary field permissions were obtained from the relevant local administrative authorities at kebele, woreda, and zonal levels prior to the commencement of the study. Local land users and community representatives were also informed about the study objectives, and their consent was obtained before any field activities were conducted. This study did not involve formal human participants. Informal discussions with local farmers and agricultural experts were conducted solely for general contextual understanding and did not constitute structured data collection requiring informed consent. Soil samples were collected from each genetic horizon of the profiles. Detailed field observations were recorded for each profile, including soil color, texture, structure, presence of vertic features, and visible salt crusts. Samples were air-dried, passed through a 2 mm sieve, and stored for laboratory analyses. Laboratory measurements included pH, electrical conductivity (ECe), exchangeable cations, sodium adsorption ratio (SAR), residual sodium carbonate (RSC), and other key chemical properties. Water samples were collected from irrigation canals, rivers, and hot springs using pre-cleaned polyethylene bottles, following standard protocols to prevent contamination. Sampling sites included major irrigation intakes, distribution channels, and natural water bodies used by local farmers. Parameters such as pH, electrical conductivity (ECw), major cations (Na⁺, Ca²⁺, Mg²⁺, K⁺), and anions (HCO₃⁻, CO₃²⁻, SO₄²⁻, Cl⁻) were determined in the laboratory. Special attention was given to hot springs, which are characterized by elevated concentrations of dissolved salts, to evaluate their contribution to soil salinization in adjacent agricultural fields. The combined soil and water sampling strategy enabled a comprehensive assessment of the interactions between irrigation practices, hot spring inflows, and soil properties, providing critical insights into the mechanisms driving salinity and sodicity in the study area. This integrated approach supports the evaluation of sustainable land and water management practices in Kewet and Efratana Gidim districts. 2.6. Laboratory Analysis of Soil and Water Samples All collected soil and water samples were analyzed in the laboratory to determine physicochemical properties and salinity-related parameters following standard procedures. Soil samples were first air-dried, ground, and sieved through a 2 mm mesh to remove coarse fragments. The analyses included soil texture using the hydrometer method, soil pH and electrical conductivity (ECe) in a 1:2.5 soil-to-water suspension, cation exchange capacity (CEC) by ammonium acetate extraction, and exchangeable cations (Ca²⁺, Mg²⁺, K⁺, Na⁺) quantified using atomic absorption spectrophotometry. The sodium adsorption ratio (SAR) and residual sodium carbonate (RSC) were calculated to assess the potential sodicity hazard. Organic carbon content was determined by the Walkley-Black method, while total nitrogen was measured using the Kjeldahl digestion technique. Water samples were analyzed for pH, electrical conductivity (ECw), major cations, and anions following procedures outlined by the FAO. (1992) and Ayers and Westcot ( 1985 ). Cations (Na⁺, K⁺, Ca²⁺, Mg²⁺) were measured using flame photometry and atomic absorption spectrophotometry, whereas anions (HCO₃⁻, CO₃²⁻, SO₄²⁻, Cl⁻) were quantified using titrimetric and spectrophotometric method s . The sodium hazard classification, SAR, and RSC were derived from these data to evaluate the suitability of irrigation water, with particular emphasis on waters influenced by hot springs, which exhibited elevated salt concentrations. Quality control measures, including the use of replicate samples, blanks, and standard solutions, were employed throughout the analyses to ensure reliability and accuracy. The resulting dataset provided a comprehensive basis for assessing soil salinity, sodicity, and water quality degradation, enabling the study to elucidate the interactions between irrigation practices, natural hydrogeochemical inputs, and soil formation processes in Kewet and Efratana Gidim districts. 2.7. Irrigation Water Quality Assessment and Calculation of Sodicity Indices Irrigation water quality was evaluated using standard chemical indices relevant to salinity and sodicity hazards in irrigated agriculture. Water samples were analyzed for major soluble cations (Na⁺, Ca²⁺, Mg²⁺, and K⁺) and anions (HCO₃⁻, CO₃²⁻, Cl⁻, and SO₄²⁻) following standard analytical procedures (APHA, 2017 ). Electrical conductivity of irrigation water (ECw) was measured at 25°C using a conductivity meter. All ionic concentrations were converted and expressed in milliequivalents per liter (me L⁻¹) prior to further analysis. The sodium adsorption ratio (SAR), an indicator of the sodicity hazard of irrigation water, was calculated according to the U.S. Salinity Laboratory method (Richards, 1954 ): SAR = Na⁺ / √[(Ca²⁺ + Mg²⁺) / 2]-----------------------------------------------------Eq. 1. Where Na⁺, Ca²⁺, and Mg²⁺ represent the concentrations of sodium, calcium, and magnesium in me L⁻¹. SAR was used to assess the potential of irrigation water to promote sodium accumulation on soil exchange sites, which can lead to clay dispersion, surface sealing, and reduced soil infiltration (Ayers & Westcot, 1985 ; Rengasamy, 2006 ). The residual sodium carbonate (RSC) was calculated to evaluate the tendency of carbonate and bicarbonate ions to precipitate calcium and magnesium, thereby increasing sodium dominance in the soil solution (Gupta & Abrol, 1990 ; Richards, 1954 ): RSC = (HCO₃⁻ + CO₃²⁻) − (Ca²⁺ + Mg²⁺) -----------------------------------------------------Eq. 2 where all ions are expressed in me L⁻¹. Positive RSC values indicate a greater risk of sodicity development due to the removal of Ca²⁺ and Mg²⁺ from solution. Irrigation water was classified for salinity (C1–C4) and sodicity hazards based on ECw and SAR thresholds following FAO guidelines (Ayers & Westcot, 1985 ). These indices were applied diagnostically to identify constraints on soil structure, infiltration, and root-zone water availability rather than to directly quantify crop yield or water productivity. 2.8. Data Analysis and Interpretation Descriptive statistics, including mean, standard deviation, and range, were computed for all soil and water parameters to summarize spatial variability. Graphical representations, such as depth profile plots, boxplots were used to illustrate trends in salinity, sodicity, and other key variables. Where applicable, comparisons with historical datasets and regional studies were made to contextualize findings within the broader Upper Awash Basin. This integrated analytical approach allowed for a comprehensive assessment of the interactions between soil properties, water quality, geomorphology, and human interventions, thereby providing a solid foundation for formulating evidence-based recommendations for sustainable land and water management in the study area. 2.9. Statement of Human and Animal Rights This study did not involve humans or animals. All procedures performed were limited to soil and water sampling in accordance with institutional guidelines. 3. Results 3.1. Soil Physical Properties Relevant to Water Movement Soils across Sewir, Basha, and Jewuha districts are dominated by Vertisols and Fluvisols occurring primarily on valley bottoms, river terraces, and irrigated plains. These soils are clay-rich, with surface horizons containing > 30% clay and subsoils often exceeding 50%, contributing to high water-holding capacity but reduced permeability. Pronounced shrink–swell behavior, along with the presence of slickensides and cracks, strongly influences water infiltration, storage, and root penetration, particularly in subsoil horizons. Soil pH ranged from neutral to moderately alkaline (7.2–8.4) and generally increased with depth, indicating accumulation of basic cations in lower horizons. Organic carbon content was low to moderate, consistent with intensive cultivation and limited organic residue inputs, affecting soil structure and nutrient cycling. Exchangeable cations followed the order Ca²⁺ > Mg²⁺ > K⁺ > Na ⁺ , and high clay content resulted in elevated cation exchange capacity (CEC). While high CEC enhances nutrient retention, it also increases susceptibility to clay dispersion and infiltration limitations under high exchangeable sodium, potentially affecting root-zone water availability (Fig. 1 a, b). Table.1 Depth-wise physicochemical characteristics of soils under irrigated and adjacent land units Depth S Si C H 2 O KCl ECe ESP Ca Mg K Na CEC BS Ca:Mg OC cm % pH 1:2.5 (dS/m) Exchangeable cations, cmolc kg- 1 % % 0–30 12.2 20.8 67 7.2 6.8 0.13 0.66 34 4 1.79 0.3 44 91 9 2.13 30–50 10.5 20.1 69.4 7.8 7.2 0.13 0.62 35 8.8 0.54 0.3 54.8 81.5 4 1.19 50–85 9.7 19.8 70.5 7.6 8.2 0.18 0.73 43 14 0.47 0.4 55.6 100 3 1.19 85–120 18.8 19.1 62.1 7.6 7.4 0.19 0.79 43 11 0.38 0.4 55.4 99 4 0.86 0–30 4.7 22.7 72.6 7.4 7.2 2.86 27.6 53 16.8 1.3 17.6 64 100 3 2.56 30–60 5.9 18 76.1 8 7.8 2.96 35.2 54.9 13.6 0.6 24.8 65 100 4 2.07 60–83 5.3 19.8 74.9 8.2 7.8 5.18 44.6 50 7.2 0.5 25.7 67 100 7 1.16 83–115 3.4 26.4 70.2 8.4 8 4.32 50.8 40.5 13 0.5 32.5 64 100 3 0.63 115–150 4.9 31.7 63.4 8.4 8.2 4.29 57.4 38 1.08 0.51 36.3 63 100 35 0.21 0–30 7.8 25.4 66.8 7.4 7.2 0.09 0.01 45 10 1.9 0.3 50 100 4.5 1.92 30–65 8.5 17.9 73.6 7.6 7.4 0.08 0.01 50 18 0.5 0.8 54 100 2.8 1.19 65–110 9.5 16.3 74.2 8.4 8.2 0.19 0.01 47 17 0.5 0.3 59 100 2.8 0.75 110–150 24.7 25.1 50.2 7.6 7.4 0.39 0.01 50 8 0.6 0.3 51 100 6.3 0.59 0–30 12 45.1 42.3 7.8 7.2 0.18 0.01 45 4.6 0.6 0.5 47.4 100 10 0.73 30–63 17.9 33.8 48 7.6 7.3 1.13 0.01 39 6 0.6 0.6 45.2 100 7 0.72 63–90 15.6 40.9 43.5 7.8 7.3 0.16 0.01 40.5 4.6 0.5 0.5 47.6 100 9 0.78 90–126 43.8 29.4 26.8 7.8 7.3 0.17 0.01 48.8 7.2 0.4 0.4 46 100 7 0.41 126–150 81.9 4.5 13.6 8 7.4 0.12 0.01 28 8.4 0.5 0.5 37.8 100 3 0.24 0–30 9 15 75.6 8.4 7.8 0.25 0.01 38 8 2.1 0.6 48.8 100 5 1.9 30–85 28 31 41.7 8.4 8 6.43 29.3 41 22 2.7 20 67 100 2 1.27 85–150 34 27 69.3 8.4 8.2 5.06 40.5 34.5 29.4 3.2 26 64 100 1 0.72 0–30 27.5 40.2 32.2 7.6 7.4 1.6 0.03 35 11 0.4 1.5 49 98 3 1.92 30–45 24 39.5 36.5 7.8 7.6 0.36 0.03 29.6 9.4 0.2 1.6 47.8 84 3 1.32 45–65 48.5 20.2 30.7 7.6 7.4 0.37 0.09 31 15 0.1 3.9 41.6 100 2 0.63 65–95 26 32.5 41.5 7.4 7.2 0.39 0.06 40.6 6.4 0.5 2.9 45.4 100 6 0.92 Table 1 presents the vertical distribution of soil texture, pH, salinity (ECe), sodicity (ESP), exchangeable cations, base saturation (BS), and organic carbon (OC) across representative profiles. Surface horizons generally exhibit low ECe and ESP, whereas subsoil layers show progressively higher exchangeable Na and ESP, indicating depth-dependent salt and sodium accumulation. These patterns correspond to restrict leaching and limited internal drainage, corroborating the observed salinity trends described in Section 3.2. Overall, the structural and textural properties of these soils provide a mechanistic framework for understanding water movement, root-zone limitations, and salinity accumulation under irrigated conditions, forming the basis for subsequent analysis of irrigation water quality and soil–water interactions. 3.2. Depth-Dependent Variations in Soil Salinity and Sodicity under Irrigation Soil salinity and sodicity exhibited clear and consistent depth-dependent patterns across the study sites, reflecting the combined effects of soil development and irrigation practices. Electrical conductivity of the saturated paste extract (ECe) increased systematically with depth, with subsoil horizons frequently exceeding the critical salinity threshold of 4 dS m⁻¹. This trend was most pronounced in uncultivated profiles at Sewir and Basha, where ECe increased from 7.51 dS m⁻¹ in the surface layer (0–15 cm) to 9.15 dS m⁻¹ at 105–150 cm. In contrast, cultivated soils generally showed lower ECe values throughout the profile, indicating reduced salt accumulation under regular irrigation and soil management. Exchangeable sodium percentage (ESP) followed a similar vertical trend. Surface layers (0–30 cm) generally remained below the sodicity threshold, whereas subsoil horizons (> 30 cm) exhibited substantially higher and more variable ESP values, with several profiles exceeding 15%. Depth-aggregated results confirmed a marked increase in both ECe and ESP with depth, identifying salinity and sodicity as predominantly subsurface constraints in the irrigated soils. Table . -2 Soluble chemical composition of uncultivated soils near the Sewir River Depth(cm) PH(1:2.5 soil water) Ece (mmhos/cm) at 250c soluble cations(cmol(+)/kg soluble anions(cmol(+)/kg Ca 2+ Mg 2+ K + Na + CO 3 2− HCO 3 − SO4 2 − Cl − 0–15 8.40 7.51 2.00 1.32 1.41 5.77 0.20 1.28 2.75 2.80 15–45 8.48 8.30 2.15 0.66 1.15 8.65 0.20 1.29 3.50 2.81 45–80 8.43 8.54 1.75 0.16 1.03 8.76 2.20 1.36 3.80 1.74 80–105 8.5 9.10 1.95 0.08 0.64 8.9 2.40 1.38 3.60 2.01 105–150 8.55 9.15 1.60 0.16 1.03 9.44 2.20 1.48 3.80 2.21 150–195 8.40 9.11 1.55 0.16 1.22 9.66 2.40 1.45 3.60 1.99 Table 2 presents the baseline soluble cation and anion concentrations in uncultivated soils adjacent to the river, illustrating that Na⁺, SO₄²⁻, and Cl⁻ dominate the soluble fraction. ECe increases slightly with depth, indicating that natural salinity and sodicity are significant even without irrigation. This supports the interpretation that observed salinity trends in irrigated fields are influenced by both irrigation practices and inherent soil–water dynamics. Field observations corroborated the analytical results. Surface horizons commonly showed white salt crusts associated with evaporative concentration, while deeper horizons were darker, compact, and dense, reflecting subsurface salt accumulation under irrigation. Median values further illustrate this vertical contrast: topsoil ECe and ESP were approximately 0.8 dS m⁻¹ and 3.5%, respectively, whereas subsoil medians reached about 8 dS m⁻¹ and 15%, with considerable variability among profiles. Overall, the pronounced vertical differentiation of salinity and sodicity highlights the importance of depth-specific assessment in irrigated systems. Integration of profile data, baseline soluble ions, and depth-aggregated analysis provides a robust basis for identifying subsurface salinity and sodicity risks that are not evident from surface measurements alone, forming a critical reference for irrigation management and soil amendment strategies. 3.3. Irrigation Water Quality and Soil–Water Interactions Irrigation water quality across the study area posed moderate to high salinity and sodicity risks, with direct implications for soil chemical conditions and crop productivity. Electrical conductivity of irrigation water (ECw) ranged from 0.22 to 1.06 dS m⁻¹, with the highest values recorded at Kora Spring, reflecting potential for greater salt loading under continuous irrigation. Sodium was the dominant cation (0.84–6.78 me L⁻¹), while bicarbonate was the dominant anion (1.55–5.79 me L⁻¹), indicating that these waters are prone to sodium enrichment in the soil profile. Sodium adsorption ratio (SAR) values ranged from 1.0 to 5.5, indicating moderate sodicity hazard, whereas residual sodium carbonate (RSC) varied from − 0.66 to 4.0 me L⁻¹, with some sources exceeding recommended thresholds. These chemical characteristics suggest that prolonged use of certain water sources could result in soil structural degradation and reduced infiltration, particularly in clay-rich Vertisols. Based on standard classification schemes, most irrigation sources fall under high salinity hazard (C3) , while sodicity risk varies from low to medium, highlighting significant spatial variability among sources. Table.- Error! Use the Home tab to apply 0 to the text that you want to appear here. -3 Chemical properties of irrigation water from different sources in the study area Site Location PH(1:2.5 soil water) ECw (dS/m) at 25 0 c soluble cations(cmol(+)/kg SAR soluble anions(cmol(+)/kg RSC Ca 2+ Mg 2+ K + Na + CO3 2− HCO 3− SO4 2− Cl − (me/l) Sewir River up 8.5 0.22 0.87 0.45 0.1 0.84 1 0.5 1.55 0.11 0.27 0.73 kora spring (Local name) 8.8 1.06 1.17 1.83 0.15 6.78 5.5 1.5 5.5 2 1.34 4.0 Se+Kora 8.6 0.9 1.23 3.51 0.18 5.52 3.6 1.4 5.79 1.54 1.3 2.45 Tikure div 8.5 0.9 2.73 1.43 0.17 4.71 3.3 0.4 3.1 3.37 1.6 -0.66 Se.R down 8.6 0.97 1.99 1.1 0.16 6.2 5 0.33 3.45 2.45 1.45 0.69 Eddo Chekecheq 8.8 0.95 0.97 0.75 0.12 1.54 1.7 0.43 2.75 0.33 0.39 1.46 Depth-wise soil profile data further confirmed that fields irrigated with higher-SAR and higher-RSC waters consistently exhibited elevated ECe and ESP in subsoil layers, demonstrating that the impact of irrigation water quality is most pronounced below the plough layer. This indicates preferential accumulation of salts and sodium in horizons with restricted permeability and limited natural leaching, increasing the risk of subsurface salinity and sodicity over time. Field observations supported these findings. Surface horizons frequently exhibited white salt crusts, while deeper layers were darker, compact, and enriched in soluble salts. Shrinkage cracks, typical of clay-rich Vertisols, were commonly observed, further highlighting the role of shrink–swell dynamics in the heterogeneous distribution of salts within the profile. Table.-4 Salinity and sodicity hazard classification of irrigation water sources Site Location SAR RSC Salinity class Sodicity class RSC class Sewir River up 5.00 0.69 High(C3) low kora spring 5.5 4 High(C3) high Se+Kora 3.6 2.45 High(C3 ) medium Tikure div 3.3 -0.66 High(C3) none Se.R down 1.00 0.73 Medium(C2) low Eddo Chekecheq 1.7 1.46 High(C3) medium Table 4 classifies irrigation water sources according to standard salinity (C1–C4), sodicity, and RSC hazard indices. Most sources fall in the high salinity (C3) class, with sodicity and RSC risks ranging from low to high. This highlights that without adequate leaching, drainage, and amendments, prolonged irrigation could exacerbate subsoil salinity, reduce infiltration, and negatively affect crop growth. Overall, the results indicate that irrigation water quality is a primary determinant of depth-dependent soil salinity and sodicity in the Upper Awash Valley. Subsoil accumulation of salts and exchangeable sodium represents a significant constraint to root-zone water availability, soil structure, and irrigation efficiency. These findings emphasize the importance of integrating irrigation water quality assessment with detailed soil profile analysis for effective water and soil management, including targeted leaching, drainage improvement, and crop selection for salinity tolerance. 3.4. Relationships among Soil and Water Quality Indicators Pearson correlation analysis revealed strong and consistent relationships among key soil chemical and physical indicators (Fig. 5 ). Electrical conductivity of the saturated paste extract (ECe) showed a very strong positive correlation with exchangeable sodium percentage (ESP) ( r = 0.90), indicating that increases in soil salinity were closely associated with rising sodicity. Similarly, ESP was strongly correlated with exchangeable Na ⁺ (r = 0.91), confirming that sodium accumulation dominated salinity sodicity interactions across the studied soil profiles. Cation exchange capacity (CEC) exhibited strong positive correlations with Ca²⁺ and Mg²⁺ (r ≈ 0.78–0.80), reflecting the influence of clay-rich mineralogy on base cation retention. These relationships were consistent across surface and subsoil layers, indicating stable exchange complexes in fine-textured soils. Moderate positive correlations were observed between soil water content and clay fraction (r = 0.60), demonstrating greater moisture retention in finer-textured soils. In contrast, sand content was weakly and negatively correlated with soil water content (r = − 0.19), reflecting reduced water-holding capacity in coarser soil fractions. Overall, the correlation structure highlights the close coupling between soil texture, cation exchange properties, and salinity sodicity indicators, emphasizing that sodium-driven chemical degradation is most pronounced in clay-dominated soils under irrigation. 4. Discussion 4.1. Soil Properties, Vertic Features, and Depth-Wise Salinity Patterns The soils of Kewet and Efratana Gidim districts are strongly influenced by inherent soil properties, geomorphic position, and long-term irrigation under semi-arid conditions. Vertisols and clay-rich Fluvisols dominate the lowland plains, valley bottoms, and river terraces, exhibiting surface clay contents above 30% and subsoil layers often exceeding 50% (Abrol, 1988 ). These soils exhibit characteristic vertic properties such as slickensides, shrink–swell dynamics, and recurrent surface cracking, which strongly influence water holding capacity, infiltration rates, root growth, and nutrient accessibility (Weil & Brady, 2017 ). High cation exchange capacity (CEC), primarily due to montmorillonitic clays, promotes retention of divalent cations (Ca²⁺, Mg²⁺) and partially mitigates the adverse effects of sodium on soil structure. However, these high-activity clays can also lead to vertical salt accumulation where leaching is insufficient(Qadir & Schubert, 2002 ; Rengasamy, 2010 ). Field observations revealed prominent salt crusts on the soil surface and compacted, saline subsoil layers (Fig. 4 a, b), consistent with measured ECe and ESP values (Tables 2 , 5, 7). Soil pH generally ranged from neutral to moderately alkaline (7.2–8.4), increasing with depth due to accumulation of exchangeable Ca²⁺ and Mg²⁺, which can promote clay dispersion and reduce infiltration(Qadir et al., 2007 ; Rengasamy, 2006 ). Maximum topsoil salinity occurred between March and May, coinciding with high evapotranspiration and low rainfall, highlighting the role of climate in salt redistribution (FAO., 1992; Maas, 2000a ). 4.2. 4.2. Irrigation Water Quality and Salinity Hazards Irrigation water quality emerged as a critical driver of soil salinization and sodicity. Electrical conductivity (ECw) ranged from 0.22 to 1.06 dS m⁻¹, with Kora Spring exceeding permissible limits (Ayers & Westcot, 1985 ). High bicarbonate concentrations induced precipitation of Ca²⁺ and Mg²⁺, increasing the relative prevalence of Na⁺ in the soil solution and promoting sodicity hazards (Singh et al., 1992 ). SAR values ranged from 1.0 to 5.5, and RSC ranged from − 0.66 to 4.0 me L⁻¹, with Kora Spring exceeding the critical threshold of 2.5 me L⁻¹ (Ayers & Westcot, 1985 ; Qadir et al., 2007 ). High SAR and RSC water are widely reported to reduce soil permeability, induce surface crusting, and limit root water uptake, even in soils with high CEC(Rengasamy, 2006 ). Although crop productivity was not measured, these diagnostic indicators suggest potential reductions in water availability to crops and inferred limitations on yield. When combined with clay-rich Vertisols and Fluvisols, the use of marginal-quality irrigation water accelerates sodium accumulation in subsoil layers, reinforcing depth-wise increases in ESP and structural degradation. Similar observations have been reported in irrigated drylands worldwide, such as the Indus Basin, Pakistan, and the Murray–Darling Basin, Australia, where prolonged use of marginal-quality water reduced infiltration and increased soil structural degradation (Qadir et al., 2007 ; Rengasamy, 2006 ). Integrating these insights with local soil data underscores the diagnostic utility of combining soil and water quality information to identify constraints on agricultural water use. 4.3. Soil–Water Interactions and Salt Accumulation Mechanisms The distribution and severity of salinity in Kewet and Efratana Gidim districts are strongly influenced by the interactions between soil properties, irrigation practices, and water availability. Fine-textured Vertisols and Fluvisols exhibit high water retention and limited drainage, promoting salt accumulation when irrigation water and shallow saline groundwater interact under high evaporative demand. Depth-aggregated analysis revealed that salinity and sodicity hazards are predominantly concentrated below the plough layer, highlighting subsurface constraints often overlooked in surface-focused assessments (Abrol, 1988 ; Qadir et al., 2014 ; Rengasamy, 2006 ). Salt accumulation is primarily driven by capillary rise, groundwater chemistry, evapotranspiration, and irrigation management. In areas with shallow water tables, saline groundwater is drawn into the root zone, where evaporation concentrates salts near the surface, forming conspicuous white crusts while compacting subsoil layers(Hillel, 2000 ; Shamseldin et al., 2018 ). Fine-textured soils with high capillarity amplify upward salt flux, allowing salinization to occur even under moderate irrigation if drainage is inadequate and groundwater remains near the surface. These processes explain the heterogeneous vertical and spatial distributions of electrical conductivity (ECe) and exchangeable sodium percentage (ESP) observed across the study area (FAO., 2017; Qadir et al., 2014 ). Figure 6 illustrates these processes. Surface salts develop at saline discharge areas due to evaporation, while subsurface salts accumulate via capillary rise and lateral groundwater flow. Fine-textured soils intensify upward salt transport, creating vertical gradients in ECe and ESP. The water table acts as a continuous source of salts, linking soil texture, hydrology, and irrigation dynamics to the observed salinity patterns in Kewet and Efratana Gidim districts, Ethiopia (ENSVY & GFC., 2015; Hillel, 2000 ; Rengasamy, 2006 ). 4.4. Land Use, Management, and Salinity Patterns Land-use intensity strongly influenced salinity distribution. The irrigated alluvial plains and terraces showed the highest ECe and ESP values, indicating the combined effects of clay-rich Vertisols, frequent irrigation, and nearby saline springs (Ashenafi & Qureshi, 2021 ; FAO, 1992 ). Rainfed croplands, shrublands, and natural grasslands showed lower salinity, illustrating the mitigating effect of reduced anthropogenic disturbance and vegetation cover. Conversely, rainfed and less-disturbed land-use systems exhibited lower salinity, underscoring the protective role of reduced irrigation pressure and vegetative cover. Correlation analyses revealed strong positive relationships between irrigation intensity and ECe (r = 0.72) and between SAR and ESP (r = 0.81), confirming the critical role of water quality in maintaining soil structure (Corwin & Lesch, 2005 ; Oster & Jayawardane, 1998 ). In some coarse-textured depressions, unexpectedly high salt accumulation occurred due to capillary rise, intermittent flooding, and preferential flow, highlighting how topography and hydrology can supersede conventional texture-based predictions (Corwin & Scudiero, 2019 ; Scanlon et al., 2007 ). Integrated management strategies including optimized irrigation scheduling, periodic leaching, improved drainage, and adoption of salt-tolerant crops are essential. Soil amendments such as gypsum or organic matter enhance aggregate stability, while participatory farmer engagement and policy support facilitate long-term adoption. 4.5. Unexpected Findings and Conceptual Insights Field observations revealed localized salt accumulation in profiles where irrigation was moderate and soil texture relatively uniform outcomes that initially appeared inconsistent with conventional salinity models focused on high irrigation volumes alone. The conceptual model (Fig. 6 ) reconciles these observations by highlighting the pivotal role of shallow groundwater and capillary rise as drivers of root-zone salinization, independent of irrigation intensity. In fine-textured Vertisols, limited vertical percolation amplifies upward salt transport from saline groundwater, causing stratification of ECe and ESP even with moderate irrigation application. Traditional assessments based primarily on irrigation volume or soil texture may therefore underestimate salinity risk when groundwater–soil water interactions and evaporative fluxes are not accounted for (FAO, 2017 ; Shamseldin et al., 2018 ). Integrating groundwater depth, capillary flux, and evaporative demand into predictive frameworks yields stronger alignment between theoretical mechanisms and field data. Such a mechanistic understanding explains observed surface crusts, subsurface compaction, and vertical salinity gradients, and provides a robust basis for designing adaptive irrigation scheduling, leaching, and drainage enhancements to mitigate salinity impacts (Qadir et al., 2014 ; Rengasamy, 2006 ). 4.6. Implications for Agricultural Water Management The pronounced depth-wise accumulation of salinity and sodicity in clay-rich, Vertic soils has important implications for agricultural water management in irrigated systems. Irrigation using moderately saline water, together with low leaching fractions and restricted internal drainage, favors salt accumulation in subsoil horizons, thereby limiting effective root-zone depth, reducing crop water uptake, and increasing osmotic stress on plants (Ayers & Westcot, 1985 ; Rengasamy, 2010 ). These conditions necessitate integrated irrigation and drainage management, including the application of controlled leaching fractions and the installation or maintenance of surface and subsurface drainage to prevent progressive salt build-up (Corwin et al., 2007 ). Furthermore, irrigation scheduling that accounts for soil hydraulic behavior and cracking dynamics of Vertisols is critical to improve water-use efficiency while minimizing salt concentration during drying cycles (Qadir et al., 2007 ). The incorporation of chemical amendments such as gypsum can alleviate sodicity effects by improving soil structure and permeability, thereby enhancing leaching efficiency (FAO., 2017). In parallel, the adoption of salt-tolerant crop varieties and appropriate cropping systems provides a practical adaptation strategy where water quality constraints cannot be easily overcome. Overall, these findings underscore that sustainable agricultural water management requires linking irrigation water quality monitoring with soil-specific management interventions to maintain long-term soil productivity and irrigation performance. 4.7. Study Limitations Crop productivity and water-use efficiency were not directly measured; all yield and water limitations are inferred from soil and water diagnostics (Maas, 2000b ; Qadir et al., 2006 ). The sampling density (30 soil and 6 water samples) may not fully capture spatial variability, and seasonal dynamics were partially monitored. Groundwater chemistry was not explicitly incorporated. Despite these constraints, the study provides a robust diagnostic basis for identifying constraints on crop water use and soil management in salt-affected semi-arid irrigation systems. Future work should integrate groundwater chemistry, seasonal monitoring, and remote sensing to improve prediction of salinity risk and guide adaptive irrigation management. 4.8. Future Directions and Research Implications Long-term, multi-season monitoring of soil salinity and sodicity is essential to capture temporal variability driven by climate, irrigation scheduling, and groundwater fluctuations (Pereira et al., 2020 ; Qadir et al., 2021 ). Repeated measurements across wet and dry seasons will allow quantification of seasonal salt redistribution between topsoil and subsoil layers, improving understanding of dynamic salinity processes under changing climatic conditions. Integration of groundwater depth and chemistry data is critical for refining salinity risk assessments in irrigated Vertisols. Coupling soil profile measurements with groundwater monitoring wells enables quantification of capillary flux and its contribution to root-zone salinization, strengthening mechanistic links between observed field salinity patterns and hydrological processes. Advances in geospatial tools provide opportunities to scale plot-level findings to landscape assessments. Remote sensing indices, digital soil mapping, and hydrological modeling can identify salinity-prone zones and guide targeted management interventions, which is particularly valuable in data-scarce semi-arid regions. From a management perspective, further research should evaluate adaptive strategies under local conditions, including field-based trials on salt-tolerant crop varieties, optimized irrigation scheduling, and the application of gypsum or organic amendments to improve soil structure and reduce sodium hazards. Linking biophysical outcomes with farmer decision-making will enhance practical relevance and adoption. Finally, socio-economic dimensions deserve greater attention. Future research should assess farmer knowledge, irrigation practices, and adoption barriers to salinity mitigation technologies, enabling the design of climate-informed and socially acceptable management policies. A holistic framework integrating soil science, hydrology, agronomy, and socio-economics is essential for sustaining agricultural productivity in Ethiopia’s Main Rift Valley. 5. Conclusion This study demonstrates that soil salinity and sodicity in Kewet and Efratana Gidim Districts, part of the Ethiopian Main Rift Valley, are governed by the interplay of soil properties, irrigation water quality, and land-use practices. Clay-rich Vertisols and Fluvisols, with high cation exchange capacity and shrink–swell behavior, promote salt retention and vertical redistribution under irrigated conditions. Laboratory analyses identified sodium as the dominant cation, with sulfate and bicarbonate as major anions, confirming the spatially and temporally heterogeneous nature of salinity and sodicity in the region. Irrigation water, particularly from sources with elevated SAR and RSC, exacerbates sodicity risks, reducing soil structural stability and root-zone water availability. Seasonal peaks in salinity highlight the compounded effects of semi-arid climate, high evapotranspiration, and irrigation practices on soil hydraulic function and potential crop water uptake. Sustainable management of salt-affected systems requires integrated strategies, including optimized irrigation scheduling, periodic leaching, improved drainage, and the adoption of salt-tolerant crops. Soil amendments and organic matter incorporation can enhance soil structure, reduce sodicity, and improve resilience. Farmer training, extension support, and policy measures are essential to ensure the uptake of adaptive, climate-resilient practices. Regionally and across the Ethiopian Main Rift Valley, the findings provide a diagnostic framework for improving irrigation efficiency and sustaining productivity. Globally, they reinforce that salinity and sodicity are critical constraints in irrigated drylands, necessitating climate-informed soil and water management. Overall, this study establishes a scientific basis for targeted interventions to maintain agricultural productivity and safeguard soil health in salt-prone irrigation systems. Declarations Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Field Permission Local land users and community representatives were also informed about the study objectives, and their consent was obtained before any field activities were conducted. Consent to Participate Informal discussions with local farmers and agricultural experts were conducted solely for general contextual understanding and did not constitute structured data collection requiring informed consent. Author Contribution Mekonnen Getahun Sisay (corresponding author): Conceptualization, study design, field investigation, data collection, laboratory analysis, data interpretation, writing—original draft preparation, and manuscript revision. The author confirms sole responsibility for overall research coordination and approves the final version of the manuscript for submission.Other co-authors: Provided substantial contributions to study conceptualization, field and laboratory support, data interpretation, and critical review of the manuscript. All authors have read and approved the final version of the manuscript and agree to be accountable for all aspects of the work. Acknowledgement The authors would like to acknowledge the support provided by Bahir Dar University, particularly the College of Agriculture and Environmental Sciences, Bahir Dar University, for facilitating the research and providing institutional and technical support. The authors also extend their sincere appreciation to the staff and technicians who assisted with field sampling and laboratory analyses. Special thanks are given to local farmers and land managers for their cooperation and access to the study sites during data collection Data Availability The datasets generated and analyzed during this study, including soil properties, water quality parameters, and irrigation data, are available from the corresponding author upon reasonable request. Access may be subject to confidentiality agreements with the participating farmers and supporting institutions. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board 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-9156925","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":624482830,"identity":"83ad0339-8552-4da3-8f16-022913487c9f","order_by":0,"name":"Mekonnen Getahun","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABLElEQVRIiWNgGAWjYFACNgSTGYjl2JgZGx8AGTx8hLUwg7UY87M3NxuAtLARqyVxZs/xNgk061GAbntb4uPCHTZ58u79Bz8Xtt1h3HAjsa3ya46dDBsD88NHNzC1mJ05dth45pm0YsMzh5mlZ7Y9YzYAarktuy0Z6DA2Y+McLFpupLdJ87YdTtw4I5kBxGADa5HcxgzUwsMmjU3L/ecgLf8TN85/zPwbqIUHpKVYcls9bi032I4BtRxInC/BzAayRUKy52Ab48dth3FrOZOWbMzblpy4gSfZzJrn3GEDfvbGZmnGbcd52Jhx+OX4McPHvG12ifPbDz6+zVN2uL6Nmf3hx5/bqu2BEfTwMRYtcGBwAInDzAMm8SgHAfkGJA7jDwKqR8EoGAWjYEQBAF2VZcMD+on3AAAAAElFTkSuQmCC","orcid":"","institution":"Bahir univrsity, College of Agriculture and Environmental Science","correspondingAuthor":true,"prefix":"","firstName":"Mekonnen","middleName":"","lastName":"Getahun","suffix":""},{"id":624482831,"identity":"1056ea95-bbd2-48b4-a96d-58092fdf17b1","order_by":1,"name":"Enyew Adgo","email":"","orcid":"","institution":"Bahir univrsity, College of Agriculture and Environmental Science","correspondingAuthor":false,"prefix":"","firstName":"Enyew","middleName":"","lastName":"Adgo","suffix":""},{"id":624482834,"identity":"cb46f822-044d-47fb-b048-7f429c5d18a4","order_by":2,"name":"Alemayehu Regassa Tolossa","email":"","orcid":"","institution":"Jimma University","correspondingAuthor":false,"prefix":"","firstName":"Alemayehu","middleName":"Regassa","lastName":"Tolossa","suffix":""},{"id":624482836,"identity":"859d62b7-fee5-414d-a12e-5da8391a739d","order_by":3,"name":"Zenabu Getahun","email":"","orcid":"","institution":"Department of Land Administration and Surveying, Bahir Dar University","correspondingAuthor":false,"prefix":"","firstName":"Zenabu","middleName":"","lastName":"Getahun","suffix":""}],"badges":[],"createdAt":"2026-03-18 08:54:00","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9156925/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9156925/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107174681,"identity":"fcae372f-c125-49e4-9c32-6ad5fabb1fe8","added_by":"auto","created_at":"2026-04-17 15:27:11","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1084620,"visible":true,"origin":"","legend":"\u003cp\u003eLocation map of the study areas within the Awash River Basin, Amhara Region, Ethiopia.\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-9156925/v1/30153b94151f44907aca770b.png"},{"id":107174672,"identity":"413af6a4-3be5-4cbf-9377-bc158d978226","added_by":"auto","created_at":"2026-04-17 15:27:09","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":18756,"visible":true,"origin":"","legend":"\u003cp\u003eMonthly climograph showing maximum (Tmax), minimum (Tmin), and mean (Tavg) air temperatures and total monthly precipitation for Kewet and Efratana Gidim, Amhara Region, Ethiopia. Climate data represent long-term regional monthly averages and illustrate the strong seasonality of rainfall and temperature relevant to irrigation water management.\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-9156925/v1/2cae7d973534097f43eca9f3.png"},{"id":107481529,"identity":"3616d286-bf14-4e78-a017-9f99b2f490a7","added_by":"auto","created_at":"2026-04-22 02:18:46","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":427520,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDepth-wise variation of ECe and ESP across representative soil profiles under irrigated and uncultivated conditions\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-9156925/v1/75a9165f59d66da6018637fa.png"},{"id":107174678,"identity":"670481a7-a125-4b93-9c33-ec827aeed862","added_by":"auto","created_at":"2026-04-17 15:27:11","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":961141,"visible":true,"origin":"","legend":"\u003cp\u003eField observation of salt-affected soils showing visible white salt crusts along the soil profile, indicating substantial accumulation of soluble salts—mainly sodium and sulfate ions. Surface layers exhibit salt deposition driven by intense evaporation, whereas subsurface horizons reflect downward leaching and redistribution of salts under irrigation. The presence of shrinkage cracks in the clay-rich matrix (typical of Vertisols) further demonstrates shrink–swell dynamics that influence the heterogeneous distribution of salts within the profile. \u003cstrong\u003eNote:\u003c/strong\u003e Visual diagnosis of salt-affected soils can be made through field indicators: completely white surfaces denote saline soils, grey-colored surfaces indicate saline–sodic soils, and brownish-black crusts are characteristic of sodic soi\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-9156925/v1/1b1f4932edcbbe5cea546427.png"},{"id":107174674,"identity":"8d632398-7754-483b-89f6-4a4031997593","added_by":"auto","created_at":"2026-04-17 15:27:09","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":173048,"visible":true,"origin":"","legend":"\u003cp\u003ePearson correlation matrix illustrating relationships among soil physical and chemical properties in irrigated soils of the Kewet and Efratana Gidim districts, Ethiopia. Strong positive correlations among ECe, ESP, and exchangeable Na⁺ indicate the coupled development of salinity and sodicity under irrigation. Clay content shows positive associations with CEC and divalent cations, reflecting texture-controlled nutrient retention. Color intensity represents the strength and direction of correlations (blue = negative, red = positive).\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-9156925/v1/da4168c495dfc352b2afd410.png"},{"id":107482931,"identity":"c20b23d8-d9b9-4520-8e55-26e5e16ef27b","added_by":"auto","created_at":"2026-04-22 02:25:38","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":406236,"visible":true,"origin":"","legend":"\u003cp\u003eConceptual diagram of soil salinity processes showing surface salt accumulation, subsurface salt, capillary rise, and water table interactions adapted from (ENSVY \u0026amp; GFC., 2015)\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-9156925/v1/70cb54b1ba5f42a429a4b9fd.png"},{"id":107485474,"identity":"72210fd4-8b1e-4e28-b496-9f87a882c6c3","added_by":"auto","created_at":"2026-04-22 02:35:02","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3841986,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9156925/v1/92472c49-f1b6-402f-8b72-539892610fec.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Soil salinity sodicity and irrigation water quality in the Ethiopian Main Rift Valley and implications for sustainable management","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eEnsuring sustainable agricultural production in the twenty-first century remains a critical global challenge, particularly as the world population is projected to approach 10\u0026nbsp;billion by 2050, with the majority of growth occurring in developing regions such as sub-Saharan Africa (United Nations, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). In these regions, agricultural systems are heavily dependent on finite soil and water resources, which are increasingly vulnerable to degradation. Ethiopia exemplifies this challenge, where rapid population growth and rising food demand coincide with shrinking per capita arable land, declining soil fertility, and intensified pressure on land and water resources(FAO, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAmong the various forms of land degradation, soil salinity and sodicity are recognized as major constraints to sustainable agriculture, particularly in arid and semi-arid regions where evapotranspiration frequently exceeds precipitation (Gupta \u0026amp; Abrol, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e1990\u003c/span\u003e; Szabolcs, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e1974\u003c/span\u003e). Globally, more than one-third of irrigated lands in dry regions are affected by salinity, leading to substantial yield losses and reduced water productivity (Qadir et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Rengasamy, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Salinity-induced degradation directly impairs farm-level water management, disrupts crop water relations, and lowers irrigation water-use efficiency, thereby threatening food security and rural livelihoods. Historical evidence from major irrigated river basins, including the Indus, Tigris\u0026ndash;Euphrates, and Nile, illustrates that inadequate irrigation and drainage management can trigger widespread soil salinization with long-term socio-economic consequences (FAO, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Tanji \u0026amp; Wallender, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eEthiopia harbors approximately 11\u0026nbsp;million hectares of salt-affected soils\u0026mdash;the largest extent in Africa with the Ethiopian Main Rift Valley system and the Awash Basin being among the most severely impacted regions (Abegaz et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Szabolcs, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e1977\u003c/span\u003e). The Ethiopian Rift Valley is a tectonically active, internally drained system characterized by low relief plains, alkaline parent materials, shallow groundwater tables, and high evaporative demand, all of which favor the accumulation of soluble salts in irrigated landscapes (Ayenew et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Chernet et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Within this broader system, the Upper Awash Valley represents a critical upstream agricultural zone where irrigation development is expanding rapidly.\u003c/p\u003e \u003cp\u003eAt both farm and regional scales within the Ethiopian Rift Valley system, irrigation expansion without coordinated water allocation, drainage infrastructure, and water quality monitoring has intensified secondary salinization and sodication (Taddese \u0026amp; Bekele, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e1996\u003c/span\u003e; Tsige et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). Recent studies emphasize that salinity problems in the Rift Valley are increasingly linked to declining water quality, groundwater upwelling, and reuse of marginal and saline water sources, especially under climate-induced water scarcity (Ayenew et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Qadir et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Despite these trends, significant knowledge gaps persist regarding the spatial distribution, severity, and controlling mechanisms of salinity in the Upper Awash Basin within the wider Ethiopian Rift Valley context, particularly in Kewet and Efratana Gidim districts(Ashenafi \u0026amp; Qureshi, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Jiru et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe physical and chemical properties of soils, which determine water flow and salinity patterns, are largely shaped by factors such as parent material, topography, climate, and vegetation (Gupta \u0026amp; Abrol, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e1990\u003c/span\u003e; Szabolcs, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e1974\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the Ethiopian Rift Valley, Vertisols and clay-rich Fluvisols dominate irrigated lowlands, exhibiting high clay content, shrink\u0026ndash;swell behavior, and elevated cation exchange capacities, which enhance sodium retention and restrict leaching under inadequate drainage(Abegaz et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Soil salinity is further aggravated by human practices such as intensive irrigation, land clearing, fertilizer use, and modification of natural drainage systems, particularly under high evapotranspiration and variable rainfall conditions (Ayers \u0026amp; Westcot, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1985\u003c/span\u003e; FAO, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1992\u003c/span\u003e). These interactions reduce infiltration, impair root-zone water availability, and ultimately decrease crop water productivity, especially in smallholder irrigation schemes.\u003c/p\u003e \u003cp\u003eIn the Upper Awash Valley, irrigation water quality plays a decisive role in shaping salinity and sodicity dynamics. Water sources within the Ethiopian Rift Valley commonly exhibit elevated electrical conductivity (EC), sodium adsorption ratio (SAR), and residual sodium carbonate (RSC), reflecting prolonged water\u0026ndash;rock interaction and geothermal influence (Ayenew et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Singh et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e1992\u003c/span\u003e). When such waters are applied to clay-rich soils, they accelerate soil structural degradation, surface crusting, and reduced hydraulic conductivity. Seasonal climatic variability further intensifies these processes, with peak soil salinity commonly occurring during dry periods when evapotranspiration exceeds leaching potential (FAO, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1992\u003c/span\u003e; Maas, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e1990\u003c/span\u003e). These conditions directly constrain crop growth, reduce yields, and lower irrigation water-use efficiency across Rift Valley irrigation systems.\u003c/p\u003e \u003cp\u003eThis study adopts a diagnostic approach to evaluate soil salinity and irrigation water quality as key constraints to efficient agricultural water management in irrigated systems, rather than quantifying crop yields or productivity.\u003c/p\u003e \u003cp\u003eEffective salinity management in the Ethiopian Rift Valley therefore requires integrated approaches that combine improved irrigation scheduling, adequate drainage, periodic leaching, soil amendments, and the strategic use of salt-tolerant crops (Ayers \u0026amp; Westcot, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1985\u003c/span\u003e; Qadir et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Qadir et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Given increasing water scarcity, the controlled and informed use of saline and marginal-quality water is becoming unavoidable, making site-specific soil\u0026ndash;water assessments essential for sustaining agricultural production(Pereira et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Qadir et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe significance of this study lies in its integrated soil\u0026ndash;water management perspective applied within the Ethiopian Main Rift Valley system, combining physicochemical soil characterization, salinity and sodicity assessment, and irrigation water quality evaluation to elucidate degradation processes in the Upper Awash Basin. By explicitly linking soil properties, irrigation practices, water quality, and crop water relations, this research advances understanding beyond conventional assessments that treat soil or water constraints in isolation (Ashenafi \u0026amp; Qureshi, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Jiru et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Focusing on Kewet and Efratana Gidim districts understudied yet agriculturally important areas\u0026mdash;this study extends salinity research to upstream Rift Valley irrigation systems.\u003c/p\u003e \u003cp\u003eThis research aims to provide a comprehensive assessment of soil properties, salinity and sodicity status, and irrigation water quality in Kewet and Efratana Gidim districts. The study seeks to clarify how interactions among soil characteristics, irrigation water quality, and management practices within the Ethiopian Rift Valley system influence crop water relations, crop productivity, and irrigation water-use efficiency under saline conditions. The findings are intended to support farm-level decision-making, guide regional irrigation and drainage planning, and inform sustainable salinity management strategies, including improved use of saline water in agriculture, thereby enhancing long-term agricultural resilience in Ethiopia\u0026rsquo;s Main Rift Valley.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Study Area Description and Sampling Sites\u003c/h2\u003e \u003cp\u003eThe study was conducted in the Awash River Basin, situated on the eastern plateau of the East African Rift Valley in central Ethiopia (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The study area is located at approximately 10\u0026deg;53\u0026prime;02\u0026Prime; N latitude and 39\u0026deg;54\u0026prime;51\u0026Prime; E longitude, with a mean elevation of about 1,197 m above sea level. The basin is characterized by heterogeneous topography, comprising low-lying valley bottoms, gently undulating plateaus, and dissected hills, which collectively influence drainage patterns, soil development, and land use.\u003c/p\u003e \u003cp\u003eHydrologically, the area is dominated by the Awash River and its tributary network, which serve as the principal sources of surface water for irrigation and contribute to the recharge of shallow groundwater systems. These water resources support extensive irrigated agriculture, particularly along river valleys and alluvial plains, where irrigation has intensified over recent decades. Land use in the study area is diverse and includes irrigated and rainfed croplands, communal grazing areas, rural settlements, and remnants of natural vegetation.\u003c/p\u003e \u003cp\u003eSampling sites were purposively selected to represent the spatial variability of the study area, with particular emphasis on differences in Reference Soil Group, irrigation water sources, management practices, and observed salinity and sodicity conditions. This sampling design enabled assessment of soil\u0026ndash;water interactions across contrasting landscape positions and irrigation environments within the basin.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Climate of the Study Area\u003c/h2\u003e \u003cp\u003eThe climate of the Kewet and Efratana Gidim districts in the Awash River Basin is characterized by pronounced seasonal variability in both temperature and rainfall (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The area experiences a unimodal rainfall regime, with the majority of annual precipitation occurring during the main rainy season (June\u0026ndash;September), while the period from October to May is predominantly dry. Monthly rainfall peaks in July and August, whereas negligible precipitation is recorded during the dry months, particularly from November to February.\u003c/p\u003e \u003cp\u003eAir temperature exhibits relatively moderate seasonal fluctuations compared with rainfall. Monthly maximum temperatures generally range from approximately 25 to 30\u0026deg;C, with the highest values observed during the late dry and early rainy seasons (April\u0026ndash;June). Minimum temperatures vary between about 10 and 17\u0026deg;C, resulting in mean monthly temperatures of roughly 18\u0026ndash;24\u0026deg;C throughout the year. This combination of high temperatures and limited rainfall during the prolonged dry season leads to atmospheric water demand that exceeds precipitation.\u003c/p\u003e \u003cp\u003eThe strong seasonality of rainfall and temperature has important implications for irrigation water management and soil processes in the study area. During the dry season, high evaporative demand and limited rainfall favor soil moisture depletion and salt accumulation in the root zone, whereas the rainy season promotes partial leaching of accumulated salts and temporary improvement of soil moisture conditions. Consequently, the observed climatic regime plays a critical role in controlling water availability, irrigation requirements, and soil\u0026ndash;water interactions under irrigated agriculture.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Geology, Geomorphology, and Soil Formation\u003c/h2\u003e \u003cp\u003eKewet and Efratana Gidim districts are located within the Upper Awash Basin, forming part of the western margin of the Main Ethiopian Rift (MER\u003cb\u003e)\u003c/b\u003e, a tectonically active segment of the East African Rift System. The area is underlain predominantly by Miocene\u0026ndash;Pliocene volcanic sequences, including extensive basaltic lava flows and ignimbrites, with localized rhyolitic and felsic volcanic deposits. These volcanic rocks serve as mineral-rich parent material, influencing soil physicochemical properties such as clay content, cation exchange capacity (CEC), and base saturation. They also regulate groundwater flow and storage, creating conditions conducive to both irrigation and salinity development. Overlying the volcanic basement, Quaternary alluvial, fluvial, and lacustrine sediments occupy the rift lowlands, forming broad valley floors and floodplains. These unconsolidated deposits, derived from erosion of adjacent highlands and escarpments, provide fertile surfaces for agriculture but are highly susceptible to salt accumulation, particularly under intensive irrigation and in areas influenced by numerous saline hot springs.\u003c/p\u003e \u003cp\u003eThe geomorphology of the districts reflects the active tectonics of the MER. The lowland rift floor consists of extensive alluvial plains, river terraces, and depositional fans, which facilitate irrigated agriculture but also concentrate salts due to shallow water tables and high evapotranspiration. Steep rift shoulders and escarpments expose volcanic bedrock and control sediment supply, drainage patterns, and localized microclimates. The thermal and saline springs, frequently aligned along fault zones, contribute substantial dissolved salts to both surface and groundwater, enhancing the risk of soil salinization and sodicity in adjacent croplands.\u003c/p\u003e \u003cp\u003eSoil formation in the study area is controlled by the interaction of parent material, sediment deposition, topography, climate, and hydrology. The weathering of basaltic and ignimbrite units produces clay-rich Vertisols and Fluvisols, characterized by high CEC, shrink-swell behavior, and vertic features such as slickensides and cracks. These properties support nutrient retention and water storage but exacerbate susceptibility to sodicity when irrigated with sodium-rich water. Alluvial deposition and surface runoff further influence the spatial distribution of salts, while human interventions\u0026mdash;irrigation management, fertilizer application, and land use change\u0026mdash;interact with these natural processes, accelerating salinity development. The cumulative effects of \u003cb\u003esoil\u003c/b\u003e texture, hydrology, geomorphology, and irrigation water quality, including inputs from hot springs, determine the spatial patterns of salinization and strongly influence the sustainability of agricultural production in the Upper Awash Basin.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Land Use and Land Cover Assessment\u003c/h2\u003e \u003cp\u003eUnderstanding the spatial distribution of land use and land cover (LULC) is essential for evaluating soil properties, irrigation practices, and salinity dynamics in Kewet and Efratana Gidim districts. LULC patterns influence the availability and movement of water, sediment, and soluble salts, and thus play a key role in shaping soil formation processes and salinization risk. In this study, LULC was assessed using a combination of remote sensing data, satellite imagery, and field verification, with particular attention to the distribution of irrigated and rainfed agricultural lands, natural vegetation, and water bodies.\u003c/p\u003e \u003cp\u003eThe study area is predominantly characterized by agricultural land, reflecting both irrigated and rainfed cultivation on alluvial lowlands and river terraces. These agricultural fields are interspersed with shrublands, grasslands, and limited forest patches, which have undergone significant reduction in extent due to land clearing and agricultural expansion. Barren lands and built-up areas are also present, generally concentrated near settlements and along transportation corridors, while rivers, irrigation canals, and natural water bodies, including the Awash River, constitute minor but critical features influencing local hydrology and soil salinity patterns.\u003c/p\u003e \u003cp\u003eField observations and GPS-based ground truthing were conducted to verify the accuracy of remote sensing interpretations and to identify areas influenced by saline hot springs, which contribute dissolved salts to surface and groundwater. This approach allowed for a detailed characterization of LULC classes and their spatial arrangement, providing a robust framework for linking land use patterns with soil properties and water quality degradation in the Upper Awash Basin. The resulting LULC dataset serves as a key input for analyzing the interactions between human interventions, irrigation practices, and natural geomorphic processes that drive salinity and sodicity dynamics in the study area.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Field Soil and Water Sample Collection\u003c/h2\u003e \u003cp\u003eTo characterize the soil physicochemical properties and evaluate the influence of irrigation water on salinity dynamics, systematic soil and water sampling was conducted across representative sites in Kewet and Efratana Gidim districts. Sampling locations were selected based on land use, topography, proximity to irrigation infrastructure, and the presence of hot springs, which are known to contribute elevated salt loads to both soils and water resources.\u003c/p\u003e \u003cp\u003e All necessary field permissions were obtained from the relevant local administrative authorities at kebele, woreda, and zonal levels prior to the commencement of the study. Local land users and community representatives were also informed about the study objectives, and their consent was obtained before any field activities were conducted. This study did not involve formal human participants. Informal discussions with local farmers and agricultural experts were conducted solely for general contextual understanding and did not constitute structured data collection requiring informed consent.\u003c/p\u003e \u003cp\u003eSoil samples were collected from each genetic horizon of the profiles. Detailed field observations were recorded for each profile, including soil color, texture, structure, presence of vertic features, and visible salt crusts. Samples were air-dried, passed through a 2 mm sieve, and stored for laboratory analyses. Laboratory measurements included pH, electrical conductivity (ECe), exchangeable cations, sodium adsorption ratio (SAR), residual sodium carbonate (RSC), and other key chemical properties.\u003c/p\u003e \u003cp\u003eWater samples were collected from irrigation canals, rivers, and hot springs using pre-cleaned polyethylene bottles, following standard protocols to prevent contamination. Sampling sites included major irrigation intakes, distribution channels, and natural water bodies used by local farmers. Parameters such as pH, electrical conductivity (ECw), major cations (Na⁺, Ca\u0026sup2;⁺, Mg\u0026sup2;⁺, K⁺), and anions (HCO₃⁻, CO₃\u0026sup2;⁻, SO₄\u0026sup2;⁻, Cl⁻) were determined in the laboratory. Special attention was given to hot springs, which are characterized by elevated concentrations of dissolved salts, to evaluate their contribution to soil salinization in adjacent agricultural fields.\u003c/p\u003e \u003cp\u003eThe combined soil and water sampling strategy enabled a comprehensive assessment of the interactions between irrigation practices, hot spring inflows, and soil properties, providing critical insights into the mechanisms driving salinity and sodicity in the study area. This integrated approach supports the evaluation of sustainable land and water management practices in Kewet and Efratana Gidim districts.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6. Laboratory Analysis of Soil and Water Samples\u003c/h2\u003e \u003cp\u003eAll collected soil and water samples were analyzed in the laboratory to determine physicochemical properties and salinity-related parameters following standard procedures. Soil samples were first air-dried, ground, and sieved through a 2 mm mesh to remove coarse fragments. The analyses included soil texture using the hydrometer method, soil pH and electrical conductivity (ECe) in a 1:2.5 soil-to-water suspension, cation exchange capacity \u003cb\u003e(CEC)\u003c/b\u003e by ammonium acetate extraction, and exchangeable cations (Ca\u0026sup2;⁺, Mg\u0026sup2;⁺, K⁺, Na⁺) quantified using atomic absorption spectrophotometry. The sodium adsorption ratio \u003cb\u003e(SAR)\u003c/b\u003e and residual sodium carbonate \u003cb\u003e(RSC)\u003c/b\u003e were calculated to assess the potential sodicity hazard. Organic carbon content was determined by the Walkley-Black method, while total nitrogen was measured using the Kjeldahl digestion technique.\u003c/p\u003e \u003cp\u003eWater samples were analyzed for pH, electrical conductivity (ECw), major cations, and anions following procedures outlined by the FAO. (1992) and Ayers and Westcot (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1985\u003c/span\u003e). Cations (Na⁺, K⁺, Ca\u0026sup2;⁺, Mg\u0026sup2;⁺) were measured using flame photometry and atomic absorption spectrophotometry, whereas anions (HCO₃⁻, CO₃\u0026sup2;⁻, SO₄\u0026sup2;⁻, Cl⁻) were quantified using titrimetric and spectrophotometric method\u003cb\u003es\u003c/b\u003e. The sodium hazard classification, SAR, and RSC were derived from these data to evaluate the suitability of irrigation water, with particular emphasis on waters influenced by hot springs, which exhibited elevated salt concentrations.\u003c/p\u003e \u003cp\u003eQuality control measures, including the use of replicate samples, blanks, and standard solutions, were employed throughout the analyses to ensure reliability and accuracy. The resulting dataset provided a comprehensive basis for assessing soil salinity, sodicity, and water quality degradation, enabling the study to elucidate the interactions between irrigation practices, natural hydrogeochemical inputs, and soil formation processes in Kewet and Efratana Gidim districts.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.7. Irrigation Water Quality Assessment and Calculation of Sodicity Indices\u003c/h2\u003e \u003cp\u003eIrrigation water quality was evaluated using standard chemical indices relevant to salinity and sodicity hazards in irrigated agriculture. Water samples were analyzed for major soluble cations (Na⁺, Ca\u0026sup2;⁺, Mg\u0026sup2;⁺, and K⁺) and anions (HCO₃⁻, CO₃\u0026sup2;⁻, Cl⁻, and SO₄\u0026sup2;⁻) following standard analytical procedures (APHA, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Electrical conductivity of irrigation water (ECw) was measured at 25\u0026deg;C using a conductivity meter. All ionic concentrations were converted and expressed in milliequivalents per liter (me L⁻\u0026sup1;) prior to further analysis.\u003c/p\u003e \u003cp\u003eThe sodium adsorption ratio (SAR), an indicator of the sodicity hazard of irrigation water, was calculated according to the U.S. Salinity Laboratory method (Richards, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e1954\u003c/span\u003e):\u003c/p\u003e \u003cp\u003eSAR\u0026thinsp;=\u0026thinsp;Na⁺ / \u0026radic;[(Ca\u0026sup2;⁺ + Mg\u0026sup2;⁺) / 2]-----------------------------------------------------Eq.\u0026nbsp;1.\u003c/p\u003e \u003cp\u003eWhere Na⁺, Ca\u0026sup2;⁺, and Mg\u0026sup2;⁺ represent the concentrations of sodium, calcium, and magnesium in me L⁻\u0026sup1;. SAR was used to assess the potential of irrigation water to promote sodium accumulation on soil exchange sites, which can lead to clay dispersion, surface sealing, and reduced soil infiltration (Ayers \u0026amp; Westcot, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1985\u003c/span\u003e; Rengasamy, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2006\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe residual sodium carbonate (RSC) was calculated to evaluate the tendency of carbonate and bicarbonate ions to precipitate calcium and magnesium, thereby increasing sodium dominance in the soil solution (Gupta \u0026amp; Abrol, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e1990\u003c/span\u003e; Richards, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e1954\u003c/span\u003e):\u003c/p\u003e \u003cp\u003eRSC = (HCO₃⁻ + CO₃\u0026sup2;⁻) \u0026minus; (Ca\u0026sup2;⁺ + Mg\u0026sup2;⁺) -----------------------------------------------------Eq.\u0026nbsp;2\u003c/p\u003e \u003cp\u003ewhere all ions are expressed in me L⁻\u0026sup1;. Positive RSC values indicate a greater risk of sodicity development due to the removal of Ca\u0026sup2;⁺ and Mg\u0026sup2;⁺ from solution.\u003c/p\u003e \u003cp\u003eIrrigation water was classified for salinity (C1\u0026ndash;C4) and sodicity hazards based on ECw and SAR thresholds following FAO guidelines (Ayers \u0026amp; Westcot, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1985\u003c/span\u003e). These indices were applied diagnostically to identify constraints on soil structure, infiltration, and root-zone water availability rather than to directly quantify crop yield or water productivity.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.8. Data Analysis and Interpretation\u003c/h2\u003e \u003cp\u003eDescriptive statistics, including mean, standard deviation, and range, were computed for all soil and water parameters to summarize spatial variability. Graphical representations, such as depth profile plots, boxplots were used to illustrate trends in salinity, sodicity, and other key variables. Where applicable, comparisons with historical datasets and regional studies were made to contextualize findings within the broader Upper Awash Basin.\u003c/p\u003e \u003cp\u003eThis integrated analytical approach allowed for a comprehensive assessment of the interactions between soil properties, water quality, geomorphology, and human interventions, thereby providing a solid foundation for formulating evidence-based recommendations for sustainable land and water management in the study area.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e2.9. Statement of Human and Animal Rights\u003c/h2\u003e \u003cp\u003eThis study did not involve humans or animals. All procedures performed were limited to soil and water sampling in accordance with institutional guidelines.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n \u003ch2\u003e3.1. Soil Physical Properties Relevant to Water Movement\u003c/h2\u003e\n \u003cp\u003eSoils across Sewir, Basha, and Jewuha districts are dominated by Vertisols and Fluvisols occurring primarily on valley bottoms, river terraces, and irrigated plains. These soils are clay-rich, with surface horizons containing\u0026thinsp;\u0026gt;\u0026thinsp;30% clay and subsoils often exceeding 50%, contributing to high water-holding capacity but reduced permeability. Pronounced shrink\u0026ndash;swell behavior, along with the presence of slickensides and cracks, strongly influences water infiltration, storage, and root penetration, particularly in subsoil horizons.\u003c/p\u003e\n \u003cp\u003eSoil pH ranged from neutral to moderately alkaline (7.2\u0026ndash;8.4) and generally increased with depth, indicating accumulation of basic cations in lower horizons. Organic carbon content was low to moderate, consistent with intensive cultivation and limited organic residue inputs, affecting soil structure and nutrient cycling. Exchangeable cations followed the order Ca\u0026sup2;⁺ \u0026gt; Mg\u0026sup2;⁺ \u0026gt; K⁺ \u0026gt; Na\u003cstrong\u003e⁺\u003c/strong\u003e, and high clay content resulted in elevated cation exchange capacity (CEC). While high CEC enhances nutrient retention, it also increases susceptibility to clay dispersion and infiltration limitations under high exchangeable sodium, potentially affecting root-zone water availability (Fig. \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea, b).\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eTable.1\u003c/strong\u003e Depth-wise physicochemical characteristics of soils under irrigated and adjacent land units\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eDepth\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eSi\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003eH\u003csub\u003e2\u003c/sub\u003eO\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003eKCl\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003eECe\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003eESP\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003eCa\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003eMg\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003eK\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003eNa\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003eCEC\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c14\"\u003e\n \u003cp\u003eBS\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c15\"\u003e\n \u003cp\u003eCa:Mg\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c16\"\u003e\n \u003cp\u003eOC\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003ecm\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\n \u003cp\u003epH 1:2.5\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e(dS/m)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"5\" nameend=\"c13\" namest=\"c9\"\u003e\n \u003cp\u003eExchangeable cations, cmolc kg-\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c14\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colname=\"c16\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e0\u0026ndash;30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e12.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e20.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e7.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e6.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\n \u003cp\u003e0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\n \u003cp\u003e1.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\n \u003cp\u003e91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c15\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e\n \u003cp\u003e2.13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e30\u0026ndash;50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e10.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e20.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e69.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e7.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e7.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\n \u003cp\u003e0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e8.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\n \u003cp\u003e0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003e54.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\n \u003cp\u003e81.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c15\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e\n \u003cp\u003e1.19\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e50\u0026ndash;85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e9.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e19.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e70.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e7.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e8.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\n \u003cp\u003e0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\n \u003cp\u003e0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003e55.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c15\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e\n \u003cp\u003e1.19\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e85\u0026ndash;120\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e18.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e19.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e62.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e7.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e7.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\n \u003cp\u003e0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\n \u003cp\u003e0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003e55.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\n \u003cp\u003e99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c15\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e\n \u003cp\u003e0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e0\u0026ndash;30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e4.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e22.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e72.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e7.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e7.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\n \u003cp\u003e2.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\n \u003cp\u003e27.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e16.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\n \u003cp\u003e1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e17.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003e64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c15\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e\n \u003cp\u003e2.56\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e30\u0026ndash;60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e5.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e76.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e7.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\n \u003cp\u003e2.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\n \u003cp\u003e35.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e54.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e13.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e24.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003e65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c15\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e\n \u003cp\u003e2.07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e60\u0026ndash;83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e5.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e19.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e74.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e8.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e7.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\n \u003cp\u003e5.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\n \u003cp\u003e44.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e7.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e25.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003e67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c15\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e\n \u003cp\u003e1.16\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e83\u0026ndash;115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e3.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e26.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e70.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e8.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\n \u003cp\u003e4.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\n \u003cp\u003e50.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e40.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e32.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003e64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c15\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e115\u0026ndash;150\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e4.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e31.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e63.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e8.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e8.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\n \u003cp\u003e4.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\n \u003cp\u003e57.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e1.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\n \u003cp\u003e0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e36.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003e63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c15\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e0\u0026ndash;30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e7.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e25.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e66.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e7.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e7.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\n \u003cp\u003e1.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c15\"\u003e\n \u003cp\u003e4.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e\n \u003cp\u003e1.92\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e30\u0026ndash;65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e8.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e17.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e73.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e7.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e7.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c15\"\u003e\n \u003cp\u003e2.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e\n \u003cp\u003e1.19\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e65\u0026ndash;110\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e9.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e16.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e74.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e8.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e8.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c15\"\u003e\n \u003cp\u003e2.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e110\u0026ndash;150\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e24.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e25.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e50.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e7.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e7.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\n \u003cp\u003e0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c15\"\u003e\n \u003cp\u003e6.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e0\u0026ndash;30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e45.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e42.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e7.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e7.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e4.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003e47.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c15\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e\n \u003cp\u003e0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e30\u0026ndash;63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e17.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e33.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e7.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e7.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\n \u003cp\u003e1.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003e45.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c15\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e63\u0026ndash;90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e15.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e40.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e43.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e7.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e7.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e40.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e4.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003e47.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c15\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e\n \u003cp\u003e0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e90\u0026ndash;126\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e43.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e29.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e26.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e7.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e7.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\n \u003cp\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e48.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e7.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c15\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e\n \u003cp\u003e0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e126\u0026ndash;150\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e81.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e4.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e13.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e7.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e8.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003e37.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c15\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e\n \u003cp\u003e0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e0\u0026ndash;30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e75.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e8.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e7.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\n \u003cp\u003e2.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003e48.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c15\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e\n \u003cp\u003e1.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e30\u0026ndash;85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e41.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e8.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\n \u003cp\u003e6.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\n \u003cp\u003e29.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\n \u003cp\u003e2.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003e67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c15\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e\n \u003cp\u003e1.27\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e85\u0026ndash;150\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e69.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e8.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e8.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\n \u003cp\u003e5.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\n \u003cp\u003e40.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e34.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e29.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\n \u003cp\u003e3.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003e64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c15\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e0\u0026ndash;30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e27.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e40.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e32.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e7.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e7.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\n \u003cp\u003e1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\n \u003cp\u003e98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c15\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e\n \u003cp\u003e1.92\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e30\u0026ndash;45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e39.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e36.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e7.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e7.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\n \u003cp\u003e0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e29.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e9.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003e47.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\n \u003cp\u003e84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c15\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e\n \u003cp\u003e1.32\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e45\u0026ndash;65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e48.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e20.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e30.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e7.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e7.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\n \u003cp\u003e0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e3.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003e41.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c15\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e65\u0026ndash;95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e32.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e41.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e7.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e7.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\n \u003cp\u003e0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e40.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e6.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e2.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003e45.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c15\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c16\"\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eTable 1 presents the vertical distribution of soil texture, pH, salinity (ECe), sodicity (ESP), exchangeable cations, base saturation (BS), and organic carbon (OC) across representative profiles.\u003c/p\u003e\n \u003cp\u003eSurface horizons generally exhibit low ECe and ESP, whereas subsoil layers show progressively higher exchangeable Na and ESP, indicating depth-dependent salt and sodium accumulation. These patterns correspond to restrict leaching and limited internal drainage, corroborating the observed salinity trends described in Section 3.2. Overall, the structural and textural properties of these soils provide a mechanistic framework for understanding water movement, root-zone limitations, and salinity accumulation under irrigated conditions, forming the basis for subsequent analysis of irrigation water quality and soil\u0026ndash;water interactions.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n \u003ch2\u003e3.2. Depth-Dependent Variations in Soil Salinity and Sodicity under Irrigation\u003c/h2\u003e\n \u003cp\u003eSoil salinity and sodicity exhibited clear and consistent depth-dependent patterns across the study sites, reflecting the combined effects of soil development and irrigation practices. Electrical conductivity of the saturated paste extract (ECe) increased systematically with depth, with subsoil horizons frequently exceeding the critical salinity threshold of 4 dS m⁻\u0026sup1;. This trend was most pronounced in uncultivated profiles at Sewir and Basha, where ECe increased from 7.51 dS m⁻\u0026sup1; in the surface layer (0\u0026ndash;15 cm) to 9.15 dS m⁻\u0026sup1; at 105\u0026ndash;150 cm. In contrast, cultivated soils generally showed lower ECe values throughout the profile, indicating reduced salt accumulation under regular irrigation and soil management.\u003c/p\u003e\n \u003cp\u003eExchangeable sodium percentage (ESP) followed a similar vertical trend. Surface layers (0\u0026ndash;30 cm) generally remained below the sodicity threshold, whereas subsoil horizons (\u0026gt;\u0026thinsp;30 cm) exhibited substantially higher and more variable ESP values, with several profiles exceeding 15%. Depth-aggregated results confirmed a marked increase in both ECe and ESP with depth, identifying salinity and sodicity as predominantly subsurface constraints in the irrigated soils.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eTable\u003c/strong\u003e.\u003cstrong\u003e-2\u003c/strong\u003e Soluble chemical composition of uncultivated soils near the Sewir River\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003eDepth(cm)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003ePH(1:2.5 soil water)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003eEce (mmhos/cm) at 250c\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"4\" nameend=\"c7\" namest=\"c4\"\u003e\n \u003cp\u003esoluble cations(cmol(+)/kg\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"4\" nameend=\"c11\" namest=\"c8\"\u003e\n \u003cp\u003esoluble anions(cmol(+)/kg\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eCa\u003csup\u003e2+\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003eMg\u003csup\u003e2+\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003eK\u003csup\u003e+\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003eNa\u003csup\u003e+\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003eCO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003eHCO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003eSO4\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003eCl\u003csup\u003e\u0026minus;\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e0\u0026ndash;15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e8.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e7.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e2.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e1.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e1.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\n \u003cp\u003e5.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\n \u003cp\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\n \u003cp\u003e1.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\n \u003cp\u003e2.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\n \u003cp\u003e2.80\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e15\u0026ndash;45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e8.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e8.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e2.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e1.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\n \u003cp\u003e8.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\n \u003cp\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\n \u003cp\u003e1.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\n \u003cp\u003e3.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\n \u003cp\u003e2.81\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e45\u0026ndash;80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e8.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e8.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e1.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\n \u003cp\u003e8.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\n \u003cp\u003e2.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\n \u003cp\u003e1.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\n \u003cp\u003e3.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\n \u003cp\u003e1.74\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e80\u0026ndash;105\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e8.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e9.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e1.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e0.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\n \u003cp\u003e8.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\n \u003cp\u003e2.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\n \u003cp\u003e1.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\n \u003cp\u003e3.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\n \u003cp\u003e2.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e105\u0026ndash;150\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e8.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e9.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e1.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\n \u003cp\u003e9.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\n \u003cp\u003e2.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\n \u003cp\u003e1.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\n \u003cp\u003e3.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\n \u003cp\u003e2.21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e150\u0026ndash;195\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e8.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e9.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e1.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e1.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\n \u003cp\u003e9.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\n \u003cp\u003e2.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\n \u003cp\u003e1.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\n \u003cp\u003e3.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\n \u003cp\u003e1.99\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eTable 2 presents the baseline soluble cation and anion concentrations in uncultivated soils adjacent to the river, illustrating that Na⁺, SO₄\u0026sup2;⁻, and Cl⁻ dominate the soluble fraction. ECe increases slightly with depth, indicating that natural salinity and sodicity are significant even without irrigation. This supports the interpretation that observed salinity trends in irrigated fields are influenced by both irrigation practices and inherent soil\u0026ndash;water dynamics.\u003c/p\u003e\n \u003cp\u003eField observations corroborated the analytical results. Surface horizons commonly showed white salt crusts associated with evaporative concentration, while deeper horizons were darker, compact, and dense, reflecting subsurface salt accumulation under irrigation. Median values further illustrate this vertical contrast: topsoil ECe and ESP were approximately 0.8 dS m⁻\u0026sup1; and 3.5%, respectively, whereas subsoil medians reached about 8 dS m⁻\u0026sup1; and 15%, with considerable variability among profiles.\u003c/p\u003e\n \u003cp\u003eOverall, the pronounced vertical differentiation of salinity and sodicity highlights the importance of depth-specific assessment in irrigated systems. Integration of profile data, baseline soluble ions, and depth-aggregated analysis provides a robust basis for identifying subsurface salinity and sodicity risks that are not evident from surface measurements alone, forming a critical reference for irrigation management and soil amendment strategies.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\n \u003ch2\u003e3.3. Irrigation Water Quality and Soil\u0026ndash;Water Interactions\u003c/h2\u003e\n \u003cp\u003eIrrigation water quality across the study area posed moderate to high salinity and sodicity risks, with direct implications for soil chemical conditions and crop productivity. Electrical conductivity of irrigation water (ECw) ranged from 0.22 to 1.06 dS m⁻\u0026sup1;, with the highest values recorded at Kora Spring, reflecting potential for greater salt loading under continuous irrigation. Sodium was the dominant cation (0.84\u0026ndash;6.78 me L⁻\u0026sup1;), while bicarbonate was the dominant anion (1.55\u0026ndash;5.79 me L⁻\u0026sup1;), indicating that these waters are prone to sodium enrichment in the soil profile.\u003c/p\u003e\n \u003cp\u003eSodium adsorption ratio (SAR) values ranged from 1.0 to 5.5, indicating moderate sodicity hazard, whereas residual sodium carbonate (RSC) varied from \u0026minus;\u0026thinsp;0.66 to 4.0 me L⁻\u0026sup1;, with some sources exceeding recommended thresholds. These chemical characteristics suggest that prolonged use of certain water sources could result in soil structural degradation and reduced infiltration, particularly in clay-rich Vertisols. Based on standard classification schemes, most irrigation sources fall under high salinity hazard \u003cstrong\u003e(C3)\u003c/strong\u003e, while sodicity risk varies from low to medium, highlighting significant spatial variability among sources.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eTable.-\u003c/strong\u003eError! Use the Home tab to apply 0 to the text that you want to appear here.\u003cstrong\u003e-3 Chemical properties of irrigation water from different sources in the study area\u003c/strong\u003e\u003c/p\u003e\n \u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003eSite Location\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003ePH(1:2.5 soil water)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003eECw (dS/m) at 25\u003csup\u003e0\u003c/sup\u003ec\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"5\" nameend=\"c8\" namest=\"c4\"\u003e\n \u003cp\u003esoluble cations(cmol(+)/kg\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003eSAR\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"4\" nameend=\"c13\" namest=\"c10\"\u003e\n \u003cp\u003esoluble anions(cmol(+)/kg\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c14\"\u003e\n \u003cp\u003eRSC\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eCa\u003csup\u003e2+\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\n \u003cp\u003eMg\u003csup\u003e2+\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003eK\u003csup\u003e+\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003eNa\u003csup\u003e+\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003eCO3\u003csup\u003e2\u0026minus;\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003eHCO\u003csup\u003e3\u0026minus;\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003eSO4\u003csup\u003e2\u0026minus;\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003eCl\u003csup\u003e\u0026minus;\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c14\"\u003e\n \u003cp\u003e(me/l)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eSewir River up\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e8.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003e1.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003e0.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\n \u003cp\u003e0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003ekora spring (Local name)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e8.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e1.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e1.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e6.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e5.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003e5.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003e1.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\n \u003cp\u003e4.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eSe+Kora\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e8.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e1.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e3.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e5.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e3.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003e5.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e1.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003e1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\n \u003cp\u003e2.45\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eTikure div\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e8.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e2.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e1.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\n \u003cp\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e4.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e3.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003e3.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e3.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003e1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\n \u003cp\u003e-0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eSe.R down\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e8.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e1.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e6.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003e3.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e2.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003e1.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\n \u003cp\u003e0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eEddo Chekecheq\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e8.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e1.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003e2.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003e0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\n \u003cp\u003e1.46\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003eDepth-wise soil profile data further confirmed that fields irrigated with higher-SAR and higher-RSC waters consistently exhibited elevated ECe and ESP in subsoil layers, demonstrating that the impact of irrigation water quality is most pronounced below the plough layer. This indicates preferential accumulation of salts and sodium in horizons with restricted permeability and limited natural leaching, increasing the risk of subsurface salinity and sodicity over time.\u003c/p\u003e\n \u003cp\u003eField observations supported these findings. Surface horizons frequently exhibited white salt crusts, while deeper layers were darker, compact, and enriched in soluble salts. Shrinkage cracks, typical of clay-rich Vertisols, were commonly observed, further highlighting the role of shrink\u0026ndash;swell dynamics in the heterogeneous distribution of salts within the profile.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eTable.-4\u003c/strong\u003e Salinity and sodicity hazard classification of irrigation water sources\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\" class=\"fr-table-selection-hover\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eSite Location\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eSAR\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eRSC\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eSalinity class\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003eSodicity class\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003eRSC class\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eSewir River up\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e5.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eHigh(C3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003elow\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003ekora spring\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e5.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eHigh(C3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003ehigh\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eSe+Kora\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e3.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e2.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eHigh(C3\u0026nbsp;)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003emedium\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eTikure div\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e3.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e-0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eHigh(C3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003enone\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eSe.R down\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eMedium(C2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003elow\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eEddo Chekecheq\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e1.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eHigh(C3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003emedium\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eTable 4 classifies irrigation water sources according to standard salinity (C1\u0026ndash;C4), sodicity, and RSC hazard indices. Most sources fall in the high salinity (C3) class, with sodicity and RSC risks ranging from low to high. This highlights that without adequate leaching, drainage, and amendments, prolonged irrigation could exacerbate subsoil salinity, reduce infiltration, and negatively affect crop growth.\u003c/p\u003e\n \u003cp\u003eOverall, the results indicate that irrigation water quality is a primary determinant of depth-dependent soil salinity and sodicity in the Upper Awash Valley. Subsoil accumulation of salts and exchangeable sodium represents a significant constraint to root-zone water availability, soil structure, and irrigation efficiency. These findings emphasize the importance of integrating irrigation water quality assessment with detailed soil profile analysis for effective water and soil management, including targeted leaching, drainage improvement, and crop selection for salinity tolerance.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\n \u003ch2\u003e3.4. Relationships among Soil and Water Quality Indicators\u003c/h2\u003e\n \u003cp\u003ePearson correlation analysis revealed strong and consistent relationships among key soil chemical and physical indicators (Fig. \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Electrical conductivity of the saturated paste extract (ECe) showed a very strong positive correlation with exchangeable sodium percentage (ESP) \u003cstrong\u003e(\u003c/strong\u003er\u0026thinsp;=\u0026thinsp;0.90), indicating that increases in soil salinity were closely associated with rising sodicity. Similarly, ESP was strongly correlated with exchangeable Na\u003cstrong\u003e⁺\u003c/strong\u003e (r\u0026thinsp;=\u0026thinsp;0.91), confirming that sodium accumulation dominated salinity sodicity interactions across the studied soil profiles.\u003c/p\u003e\n \u003cp\u003eCation exchange capacity (CEC) exhibited strong positive correlations with Ca\u0026sup2;⁺ and Mg\u0026sup2;⁺ (r\u0026thinsp;\u0026asymp;\u0026thinsp;0.78\u0026ndash;0.80), reflecting the influence of clay-rich mineralogy on base cation retention. These relationships were consistent across surface and subsoil layers, indicating stable exchange complexes in fine-textured soils.\u003c/p\u003e\n \u003cp\u003eModerate positive correlations were observed between soil water content and clay fraction (r\u0026thinsp;=\u0026thinsp;0.60), demonstrating greater moisture retention in finer-textured soils. In contrast, sand content was weakly and negatively correlated with soil water content (r\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;0.19), reflecting reduced water-holding capacity in coarser soil fractions.\u003c/p\u003e\n \u003cp\u003eOverall, the correlation structure highlights the close coupling between soil texture, cation exchange properties, and salinity sodicity indicators, emphasizing that sodium-driven chemical degradation is most pronounced in clay-dominated soils under irrigation.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e4.1. Soil Properties, Vertic Features, and Depth-Wise Salinity Patterns\u003c/h2\u003e \u003cp\u003eThe soils of Kewet and Efratana Gidim districts are strongly influenced by inherent soil properties, geomorphic position, and long-term irrigation under semi-arid conditions. Vertisols and clay-rich Fluvisols dominate the lowland plains, valley bottoms, and river terraces, exhibiting surface clay contents above 30% and subsoil layers often exceeding 50% (Abrol, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e1988\u003c/span\u003e). These soils exhibit characteristic vertic properties such as slickensides, shrink\u0026ndash;swell dynamics, and recurrent surface cracking, which strongly influence water holding capacity, infiltration rates, root growth, and nutrient accessibility (Weil \u0026amp; Brady, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). High cation exchange capacity (CEC), primarily due to montmorillonitic clays, promotes retention of divalent cations (Ca\u0026sup2;⁺, Mg\u0026sup2;⁺) and partially mitigates the adverse effects of sodium on soil structure. However, these high-activity clays can also lead to vertical salt accumulation where leaching is insufficient(Qadir \u0026amp; Schubert, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Rengasamy, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Field observations revealed prominent salt crusts on the soil surface and compacted, saline subsoil layers (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea, b), consistent with measured ECe and ESP values (Tables\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, 5, 7). Soil pH generally ranged from neutral to moderately alkaline (7.2\u0026ndash;8.4), increasing with depth due to accumulation of exchangeable Ca\u0026sup2;⁺ and Mg\u0026sup2;⁺, which can promote clay dispersion and reduce infiltration(Qadir et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Rengasamy, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Maximum topsoil salinity occurred between March and May, coinciding with high evapotranspiration and low rainfall, highlighting the role of climate in salt redistribution (FAO., 1992; Maas, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2000a\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e4.2. 4.2. Irrigation Water Quality and Salinity Hazards\u003c/h2\u003e \u003cp\u003eIrrigation water quality emerged as a critical driver of soil salinization and sodicity. Electrical conductivity (ECw) ranged from 0.22 to 1.06 dS m⁻\u0026sup1;, with Kora Spring exceeding permissible limits (Ayers \u0026amp; Westcot, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1985\u003c/span\u003e). High bicarbonate concentrations induced precipitation of Ca\u0026sup2;⁺ and Mg\u0026sup2;⁺, increasing the relative prevalence of Na⁺ in the soil solution and promoting sodicity hazards (Singh et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e1992\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSAR values ranged from 1.0 to 5.5, and RSC ranged from \u0026minus;\u0026thinsp;0.66 to 4.0 me L⁻\u0026sup1;, with Kora Spring exceeding the critical threshold of 2.5 me L⁻\u0026sup1; (Ayers \u0026amp; Westcot, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1985\u003c/span\u003e; Qadir et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). High SAR and RSC water are widely reported to reduce soil permeability, induce surface crusting, and limit root water uptake, even in soils with high CEC(Rengasamy, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Although crop productivity was not measured, these diagnostic indicators suggest potential reductions in water availability to crops and inferred limitations on yield. When combined with clay-rich Vertisols and Fluvisols, the use of marginal-quality irrigation water accelerates sodium accumulation in subsoil layers, reinforcing depth-wise increases in ESP and structural degradation.\u003c/p\u003e \u003cp\u003eSimilar observations have been reported in irrigated drylands worldwide, such as the Indus Basin, Pakistan, and the Murray\u0026ndash;Darling Basin, Australia, where prolonged use of marginal-quality water reduced infiltration and increased soil structural degradation (Qadir et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Rengasamy, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Integrating these insights with local soil data underscores the diagnostic utility of combining soil and water quality information to identify constraints on agricultural water use.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e4.3. Soil\u0026ndash;Water Interactions and Salt Accumulation Mechanisms\u003c/h2\u003e \u003cp\u003eThe distribution and severity of salinity in Kewet and Efratana Gidim districts are strongly influenced by the interactions between soil properties, irrigation practices, and water availability. Fine-textured Vertisols and Fluvisols exhibit high water retention and limited drainage, promoting salt accumulation when irrigation water and shallow saline groundwater interact under high evaporative demand. Depth-aggregated analysis revealed that salinity and sodicity hazards are predominantly concentrated below the plough layer, highlighting subsurface constraints often overlooked in surface-focused assessments (Abrol, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e1988\u003c/span\u003e; Qadir et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Rengasamy, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2006\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSalt accumulation is primarily driven by capillary rise, groundwater chemistry, evapotranspiration, and irrigation management. In areas with shallow water tables, saline groundwater is drawn into the root zone, where evaporation concentrates salts near the surface, forming conspicuous white crusts while compacting subsoil layers(Hillel, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Shamseldin et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Fine-textured soils with high capillarity amplify upward salt flux, allowing salinization to occur even under moderate irrigation if drainage is inadequate and groundwater remains near the surface. These processes explain the heterogeneous vertical and spatial distributions of electrical conductivity (ECe) and exchangeable sodium percentage (ESP) observed across the study area (FAO., 2017; Qadir et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e illustrates these processes. Surface salts develop at saline discharge areas due to evaporation, while subsurface salts accumulate via capillary rise and lateral groundwater flow. Fine-textured soils intensify upward salt transport, creating vertical gradients in ECe and ESP. The water table acts as a continuous source of salts, linking soil texture, hydrology, and irrigation dynamics to the observed salinity patterns in Kewet and Efratana Gidim districts, Ethiopia (ENSVY \u0026amp; GFC., 2015; Hillel, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Rengasamy, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2006\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e4.4. Land Use, Management, and Salinity Patterns\u003c/h2\u003e \u003cp\u003eLand-use intensity strongly influenced salinity distribution. The irrigated alluvial plains and terraces showed the highest ECe and ESP values, indicating the combined effects of clay-rich Vertisols, frequent irrigation, and nearby saline springs (Ashenafi \u0026amp; Qureshi, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; FAO, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1992\u003c/span\u003e). Rainfed croplands, shrublands, and natural grasslands showed lower salinity, illustrating the mitigating effect of reduced anthropogenic disturbance and vegetation cover. Conversely, rainfed and less-disturbed land-use systems exhibited lower salinity, underscoring the protective role of reduced irrigation pressure and vegetative cover.\u003c/p\u003e \u003cp\u003eCorrelation analyses revealed strong positive relationships between irrigation intensity and ECe (r\u0026thinsp;=\u0026thinsp;0.72) and between SAR and ESP (r\u0026thinsp;=\u0026thinsp;0.81), confirming the critical role of water quality in maintaining soil structure (Corwin \u0026amp; Lesch, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Oster \u0026amp; Jayawardane, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). In some coarse-textured depressions, unexpectedly high salt accumulation occurred due to capillary rise, intermittent flooding, and preferential flow, highlighting how topography and hydrology can supersede conventional texture-based predictions (Corwin \u0026amp; Scudiero, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Scanlon et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2007\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIntegrated management strategies including optimized irrigation scheduling, periodic leaching, improved drainage, and adoption of salt-tolerant crops are essential. Soil amendments such as gypsum or organic matter enhance aggregate stability, while participatory farmer engagement and policy support facilitate long-term adoption.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003e4.5. Unexpected Findings and Conceptual Insights\u003c/h2\u003e \u003cp\u003eField observations revealed localized salt accumulation in profiles where irrigation was moderate and soil texture relatively uniform outcomes that initially appeared inconsistent with conventional salinity models focused on high irrigation volumes alone. The conceptual model (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e) reconciles these observations by highlighting the pivotal role of shallow groundwater and capillary rise as drivers of root-zone salinization, independent of irrigation intensity. In fine-textured Vertisols, limited vertical percolation amplifies upward salt transport from saline groundwater, causing stratification of ECe and ESP even with moderate irrigation application. Traditional assessments based primarily on irrigation volume or soil texture may therefore underestimate salinity risk when groundwater\u0026ndash;soil water interactions and evaporative fluxes are not accounted for (FAO, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Shamseldin et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Integrating groundwater depth, capillary flux, and evaporative demand into predictive frameworks yields stronger alignment between theoretical mechanisms and field data. Such a mechanistic understanding explains observed surface crusts, subsurface compaction, and vertical salinity gradients, and provides a robust basis for designing adaptive irrigation scheduling, leaching, and drainage enhancements to mitigate salinity impacts (Qadir et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Rengasamy, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2006\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec23\" class=\"Section2\"\u003e \u003ch2\u003e4.6. Implications for Agricultural Water Management\u003c/h2\u003e \u003cp\u003eThe pronounced depth-wise accumulation of salinity and sodicity in clay-rich, Vertic soils has important implications for agricultural water management in irrigated systems. Irrigation using moderately saline water, together with low leaching fractions and restricted internal drainage, favors salt accumulation in subsoil horizons, thereby limiting effective root-zone depth, reducing crop water uptake, and increasing osmotic stress on plants (Ayers \u0026amp; Westcot, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1985\u003c/span\u003e; Rengasamy, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). These conditions necessitate integrated irrigation and drainage management, including the application of controlled leaching fractions and the installation or maintenance of surface and subsurface drainage to prevent progressive salt build-up (Corwin et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2007\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFurthermore, irrigation scheduling that accounts for soil hydraulic behavior and cracking dynamics of Vertisols is critical to improve water-use efficiency while minimizing salt concentration during drying cycles (Qadir et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). The incorporation of chemical amendments such as gypsum can alleviate sodicity effects by improving soil structure and permeability, thereby enhancing leaching efficiency (FAO., 2017). In parallel, the adoption of salt-tolerant crop varieties and appropriate cropping systems provides a practical adaptation strategy where water quality constraints cannot be easily overcome. Overall, these findings underscore that sustainable agricultural water management requires linking irrigation water quality monitoring with soil-specific management interventions to maintain long-term soil productivity and irrigation performance.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003e4.7. Study Limitations\u003c/h2\u003e \u003cp\u003eCrop productivity and water-use efficiency were not directly measured; all yield and water limitations are inferred from soil and water diagnostics (Maas, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2000b\u003c/span\u003e; Qadir et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). The sampling density (30 soil and 6 water samples) may not fully capture spatial variability, and seasonal dynamics were partially monitored. Groundwater chemistry was not explicitly incorporated. Despite these constraints, the study provides a robust diagnostic basis for identifying constraints on crop water use and soil management in salt-affected semi-arid irrigation systems. Future work should integrate groundwater chemistry, seasonal monitoring, and remote sensing to improve prediction of salinity risk and guide adaptive irrigation management.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec25\" class=\"Section2\"\u003e \u003ch2\u003e4.8. Future Directions and Research Implications\u003c/h2\u003e \u003cp\u003eLong-term, multi-season monitoring of soil salinity and sodicity is essential to capture temporal variability driven by climate, irrigation scheduling, and groundwater fluctuations (Pereira et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Qadir et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Repeated measurements across wet and dry seasons will allow quantification of seasonal salt redistribution between topsoil and subsoil layers, improving understanding of dynamic salinity processes under changing climatic conditions.\u003c/p\u003e \u003cp\u003eIntegration of groundwater depth and chemistry data is critical for refining salinity risk assessments in irrigated Vertisols. Coupling soil profile measurements with groundwater monitoring wells enables quantification of capillary flux and its contribution to root-zone salinization, strengthening mechanistic links between observed field salinity patterns and hydrological processes.\u003c/p\u003e \u003cp\u003eAdvances in geospatial tools provide opportunities to scale plot-level findings to landscape assessments. Remote sensing indices, digital soil mapping, and hydrological modeling can identify salinity-prone zones and guide targeted management interventions, which is particularly valuable in data-scarce semi-arid regions.\u003c/p\u003e \u003cp\u003eFrom a management perspective, further research should evaluate adaptive strategies under local conditions, including field-based trials on salt-tolerant crop varieties, optimized irrigation scheduling, and the application of gypsum or organic amendments to improve soil structure and reduce sodium hazards. Linking biophysical outcomes with farmer decision-making will enhance practical relevance and adoption.\u003c/p\u003e \u003cp\u003eFinally, socio-economic dimensions deserve greater attention. Future research should assess farmer knowledge, irrigation practices, and adoption barriers to salinity mitigation technologies, enabling the design of climate-informed and socially acceptable management policies. A holistic framework integrating soil science, hydrology, agronomy, and socio-economics is essential for sustaining agricultural productivity in Ethiopia\u0026rsquo;s Main Rift Valley.\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThis study demonstrates that soil salinity and sodicity in Kewet and Efratana Gidim Districts, part of the Ethiopian Main Rift Valley, are governed by the interplay of soil properties, irrigation water quality, and land-use practices. Clay-rich Vertisols and Fluvisols, with high cation exchange capacity and shrink\u0026ndash;swell behavior, promote salt retention and vertical redistribution under irrigated conditions. Laboratory analyses identified sodium as the dominant cation, with sulfate and bicarbonate as major anions, confirming the spatially and temporally heterogeneous nature of salinity and sodicity in the region.\u003c/p\u003e \u003cp\u003eIrrigation water, particularly from sources with elevated SAR and RSC, exacerbates sodicity risks, reducing soil structural stability and root-zone water availability. Seasonal peaks in salinity highlight the compounded effects of semi-arid climate, high evapotranspiration, and irrigation practices on soil hydraulic function and potential crop water uptake.\u003c/p\u003e \u003cp\u003eSustainable management of salt-affected systems requires integrated strategies, including optimized irrigation scheduling, periodic leaching, improved drainage, and the adoption of salt-tolerant crops. Soil amendments and organic matter incorporation can enhance soil structure, reduce sodicity, and improve resilience. Farmer training, extension support, and policy measures are essential to ensure the uptake of adaptive, climate-resilient practices.\u003c/p\u003e \u003cp\u003eRegionally and across the Ethiopian Main Rift Valley, the findings provide a diagnostic framework for improving irrigation efficiency and sustaining productivity. Globally, they reinforce that salinity and sodicity are critical constraints in irrigated drylands, necessitating climate-informed soil and water management. Overall, this study establishes a scientific basis for targeted interventions to maintain agricultural productivity and safeguard soil health in salt-prone irrigation systems.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eDeclaration of Competing Interest\u003c/h2\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\n\u003ch2\u003eField Permission\u003c/h2\u003e\n\u003cp\u003eLocal land users and community representatives were also informed about the study objectives, and their consent was obtained before any field activities were conducted.\u003c/p\u003e\n\u003ch2\u003eConsent to Participate\u003c/h2\u003e\n\u003cp\u003eInformal discussions with local farmers and agricultural experts were conducted solely for general contextual understanding and did not constitute structured data collection requiring informed consent.\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eMekonnen Getahun Sisay (corresponding author): Conceptualization, study design, field investigation, data collection, laboratory analysis, data interpretation, writing\u0026mdash;original draft preparation, and manuscript revision. The author confirms sole responsibility for overall research coordination and approves the final version of the manuscript for submission.Other co-authors: Provided substantial contributions to study conceptualization, field and laboratory support, data interpretation, and critical review of the manuscript. All authors have read and approved the final version of the manuscript and agree to be accountable for all aspects of the work.\u003c/p\u003e\n\u003ch2\u003eAcknowledgement\u003c/h2\u003e\n\u003cp\u003eThe authors would like to acknowledge the support provided by Bahir Dar University, particularly the College of Agriculture and Environmental Sciences, Bahir Dar University, for facilitating the research and providing institutional and technical support. The authors also extend their sincere appreciation to the staff and technicians who assisted with field sampling and laboratory analyses. Special thanks are given to local farmers and land managers for their cooperation and access to the study sites during data collection\u003c/p\u003e\n\u003ch2\u003eData Availability\u003c/h2\u003e\n\u003cp\u003eThe datasets generated and analyzed during this study, including soil properties, water quality parameters, and irrigation data, are available from the corresponding author upon reasonable request. Access may be subject to confidentiality agreements with the participating farmers and supporting institutions.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAbegaz A, van Keulen H, Oosterveer P. Soil degradation and management challenges in Ethiopia\u0026rsquo;s Rift Valley. Land Degrad Dev. 2022;33:1\u0026ndash;15.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAbrol I. Salt-affected soils and their management. Soil Bull. 1988;39:99\u0026ndash;110.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAPHA. 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Ethiop J Nat Resour. 2000;2(1):63\u0026ndash;78.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUnited Nations. World Population Prospects. United Nations Department of Economic and Social Affairs; 2019.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWeil RR, Brady NC. The Nature and Properties of Soils. 15th ed. New Jersey: Prentice Hall Inc.; 2017.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"discover-sustainability","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"disu","sideBox":"Learn more about [Discover Sustainability](https://www.springer.com/43621)","snPcode":"","submissionUrl":"","title":"Discover Sustainability","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Soil salinity, Sodicity, Irrigation water quality, Sodium adsorption ratio (SAR), Ethiopian Rift Valley, Sustainable land management, Salt-affected soils","lastPublishedDoi":"10.21203/rs.3.rs-9156925/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9156925/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSoil salinity and sodicity are major constraints to sustainable agriculture in semi-arid regions, particularly in Ethiopia\u0026rsquo;s Main Rift Valley. Increasing salt accumulation in soils and irrigation water threatens crop water productivity, soil health, and the long-term sustainability of irrigated systems. This study assessed soil salinity and sodicity, evaluated irrigation water quality, and identified management strategies for salt-affected agroecosystems. Field investigations were conducted in Kewet and Efratana Gidim districts, where 30 soil and six irrigation water samples were collected from representative landforms, including alluvial plains, river terraces, and micro-depressions influenced by hot springs. Soil properties, electrical conductivity (ECe), sodium adsorption ratio (SAR), and residual sodium carbonate (RSC) were analyzed. Results showed that a substantial proportion of sampled soils exhibited moderate to high salinity and sodicity levels, indicating significant degradation risks under current irrigation practices. Clay-rich Vertisols and Fluvisols dominated the area, with high cation exchange capacity, shrink\u0026ndash;swell behavior, and slickensides that enhance salt retention and restrict infiltration. Salt concentrations increased with depth, with sodium and sulfate predominating, suggesting vertical redistribution under irrigation and episodic flooding. Irrigation water, particularly from Kora Spring, showed elevated SAR and RSC, increasing sodicity risks and reducing root-zone water availability. Integrated management strategies, including optimized irrigation scheduling, periodic leaching, improved drainage, soil amendments, and salt-tolerant crops, are essential to sustain productivity. These findings provide practical guidance for salinity management and contribute to understanding soil\u0026ndash;water\u0026ndash;climate interactions in salt-affected agroecosystems.\u003c/p\u003e","manuscriptTitle":"Soil salinity sodicity and irrigation water quality in the Ethiopian Main Rift Valley and implications for sustainable management","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-17 15:26:58","doi":"10.21203/rs.3.rs-9156925/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-05-18T09:10:58+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-14T19:02:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"81111182898948990963622540081647726955","date":"2026-04-16T17:19:13+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-16T07:44:19+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-16T07:06:11+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"280179439215179117762812586252537517732","date":"2026-04-16T06:41:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"105857989167970252837568022526755150730","date":"2026-04-11T06:44:27+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-10T03:55:02+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-10T03:53:36+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-04-09T10:02:35+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-08T12:22:32+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Sustainability","date":"2026-04-08T12:07:15+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-sustainability","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"disu","sideBox":"Learn more about [Discover Sustainability](https://www.springer.com/43621)","snPcode":"","submissionUrl":"","title":"Discover Sustainability","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"555d55f1-9261-4452-82a3-4fef36454856","owner":[],"postedDate":"April 17th, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Revision requested","date":"2026-05-18T09:10:58+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-14T19:02:53+00:00","index":51,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[],"tags":[],"updatedAt":"2026-05-18T09:25:41+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-17 15:26:58","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9156925","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9156925","identity":"rs-9156925","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}