An Investigation on the Geologic, climatic, and anthropogenic controls on the morphology of the Progo River, Indonesia

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Faustino-Eslava, Noelynna T. Ramos, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7415481/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This study investigates the geologic, climatic, and anthropogenic factors controlling morphological changes along the Progo River in Daerah Istimewa Yogyakarta (DIY), Indonesia. The CAESAR-Lisflood model was applied to assess the relative effects of climate and geology on watershed morphology and sediment discharge, with validation using Google Earth Engine (GEE). Datasets including GEE imagery, a geological map, Shuttle Radar Topography Mission Digital Elevation Model (SRTM DEM), field observations, and petrographic analysis were integrated to identify morphologic changes related to geological conditions. Comparison of GEE images from 2002 and 2022 produced a morphology change map that highlighted erosion and accretion zones over two decades. Normalized Difference Vegetation Index (NDVI) analysis, combined with rainfall data, was used to evaluate climatic impacts, while fieldwork and community interviews provided insights into human influences. Results indicate that lithology, geological structure, slope, and grain size strongly influence river morphology. Larger boulders and resistant bedrock limit erosion, whereas fine-grained and weakly consolidated sediments in lower reaches erode rapidly, especially under heavy rainfall. Limestone exhibits lower resistance to erosion than volcanic breccia. Annual precipitation data show no significant long-term trend, and seasonal variability could not be assessed, suggesting only a limited climatic role. Anthropogenic factors—including dam construction, quarrying, and land use changes—emerge as the most significant drivers of morphological change. Additionally, the 2010 eruption of Mount Merapi contributed large volumes of loose material, temporarily enhancing sediment transport. These findings underscore the combined but unequal influence of natural and human factors on river system dynamics. river morphology river dynamics human-river interaction river characterization and monitoring Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 Figure 13 Figure 14 Figure 15 Introduction The genesis and development of drainage systems are strongly influenced by underlying geology and the interaction of endogenetic and exogenetic processes (Mahala, 2019). Bedrock properties, tectonic deformation, and structural features determine river evolution, while geology interacts with climate to shape topography, drainage patterns, relief, and sediment transport. Rock characteristics such as mineral composition, hardness, and degree of weathering influence sediment availability and grain size, which in turn control the rate and pathways of sediment delivery. Channels, valley floors, and hillslopes all reflect this geologic–climatic interplay. Processes such as landslides and debris flows can rapidly deliver coarse material into rivers, forming constrictions or natural dams, while earth flows may displace large volumes into channels. These processes create a hierarchy of landforms that regulate sediment transport and hydrologic behavior (Grant et al. 2003 ). Both natural and human drivers contribute to river morphology. Natural processes—bank erosion, bed scouring, and sandbar accretion—alter channel geometry, while anthropogenic activities such as bank revetment, quarrying, and irrigation infrastructure accelerate change. High sediment supply with low discharge promotes silt deposition and rapid sandbar formation (Chaiwongsaen and Choowong, 2019 ). Continuous feedback between flow dynamics and channel form results in evolving morphology, which may cause severe bank failures, posing risks to agriculture, navigation, and infrastructure. These dynamics complicate identification of causative mechanisms, particularly in localized scour events (Nguyen et al. 2022 ). The Progo River in Central Java and Daerah Istimewa Yogyakarta (DIY), Indonesia, illustrates these interactions. This meandering river drains ~ 17,432 km² and receives sediment from volcanic and non-volcanic terrains (Ikhsan et al. 2019 ). The 2010 eruption of Mount Merapi introduced large volumes of loose material, altering sediment loads and accelerating morphological change. Shifts in channel form affect erosion and sedimentation patterns, influencing hydraulic stability and the safety of structures along the river corridor (Harsanto, 2015 ; Fitriadin et al. 2017 ). Human activities further intensify morphological dynamics. Zamroni et al. ( 2020 ) examined a 2.24 km middle–lower reach and highlighted the impacts of agricultural expansion, industrial growth, settlement development, quarrying, dam construction, and unmanaged waste disposal. These factors exacerbate erosion–accretion processes. Given rivers’ dynamic nature, continuous monitoring is essential to guide sustainable management (Manjusree et al. 2013 ). Although many studies investigate river morphology, they often emphasize a single driver—geology (rock strength, tectonics, slope), climate (rainfall variability, discharge), or human activities (land use, infrastructure) (Alam and Islam 2017 ; Shrestha et al. 2020; Wang et al. 2020; Kayitesi et al. 2022 ). Few, however, integrate all three. This study addresses that gap by analyzing the combined effects of geologic, climatic, and anthropogenic factors on morphological changes in the Progo River, DIY Province. Through modeling, remote sensing, fieldwork, and petrographic analysis, the research examines how lithology, structure, slope, and sediment characteristics interact with rainfall variability and human activities to shape channel evolution. The findings provide a more holistic understanding of the processes driving morphological change and support evidence-based management strategies for regulating land use, quarrying, and infrastructure development in the Progo River system. Study area and geological characteristics The Progo River is located in the Daerah Istimewa Yogyakarta (DIY) Province, Indonesia (Fig. 1 a), and drains an area of approximately 17,432 km². The province contains diverse landscapes, ranging from coastal plains to the peak of Mount Merapi (2,930 masl). Hilly areas dominate the region, including the Sewu Mountains (52%; 150–700 masl), Menoreh Mountains (22%; 0–572 masl), and Mount Merapi (18%; 80–2,911 masl), while lowlands between these ranges account for 8% (0–80 masl). Most of DIY Province (65.65%) lies between 100 and 500 masl, with smaller proportions below 100 m (28.84%), between 500 and 1,000 m (5.04%), and above 1,000 m (0.47%). The climate is humid tropical, with a mean annual rainfall of 2,070 mm over 99 rainy days, an average temperature of 26.7°C, and an average humidity of 83.4%. Soils include lithosol, latosol, alluvial, regosol, grumusol, Mediterranean, and rendzina types (Setyawan et al. 2015 ). Mount Merapi dominates the northern region of DIY and connects to the southern coast through the Code River, a tributary that bisects Yogyakarta City. The Merapi plain, bordering the Winongo and Code Rivers downstream of the Opak River, has abundant groundwater and surface water. The Code River also functions as a lava channel during eruptions while supporting cultural, religious, and ecotourism activities (Seftyono, 2010 ; Trisnaning et al. 2022 ). DIY Province occupies a valley bordered by the Southern Mountains to the east and the Kulonprogo Mountains to the west (Pramumijoyo, 2009 ). The study area, located within Kulonprogo and Bantul Regencies, is influenced by the regional tectonic framework of the active-margin system. Subduction of the Indian Oceanic Plate beneath the Eurasian Continental Plate has generated the accretionary zone south of Java, associated volcanism, and the development of Java’s magmatic arc. This system also produced fore-arc basins to the south and back-arc basins in northern Java and the Java Sea. The Kulonprogo region is thus considered part of the magmatic arc (Widagdo et al. 2016 ). The geology around the Progo River comprises seven formations, from oldest to youngest: Diorite, Nanggulan Formation, Kebobutak Formation, Sentolo Formation, Young Volcanic Deposits of Merapi Volcano, Colluvium, and Alluvium. Diorite occurs as hornblende diorite intrusions formed during Oligocene–Miocene magmatism. The Nanggulan Formation, of Eocene to early Oligocene age, contains sandstone, lignite, limestone, claystone, and tuff rich in mollusk and foraminifera fossils. The Kebobutak Formation (Late Oligocene–Early Miocene) consists of andesite breccia, tuff, lapilli tuff, agglomerate, and volcanic rocks. The Sentolo Formation comprises limestone and sandstone, underlain by carbonate tuff (Pranata and Gilidian, 2017 ; Zamroni et al. 2021 ). The Young Volcanic Deposits of Merapi include undifferentiated tuff, breccia, ash, agglomerate, and lava. Colluvium consists of unsorted debris derived from the Kebobutak Formation, while Alluvium comprises clay, silt, sand, and gravel along streams and coastal plains (Rahardjo et al. 1995). Methods The methodological approach of this study was divided into two primary stages: (1) river modeling analysis and (2) assessment of geologic, climatic, and anthropogenic impacts on river morphological change. A schematic overview of the research design is presented in Fig. 2 . Analysis of the river modelling The first stage of this study simulated the hydromorphological dynamics of the Progo River using the CAESAR-Lisflood landscape evolution model. River modeling provides a quantitative framework to examine how sediment supply, grain-size distribution, and precipitation influence channel morphology. A key challenge lies in selecting empirical closure relations for sediment transport, which strongly affect model performance. CAESAR-Lisflood integrates hydrological and hydraulic components with multi-class sediment transport algorithms, enabling simulation of erosion, deposition, and slope processes such as soil creep and landslides. The model has been widely applied worldwide to reproduce both long-term landform changes and short-term geomorphic events (Pasculli and Audisio 2015 ; Thapa et al. 2024 ). It balances computational efficiency with accuracy at spatial and temporal scales relevant to river reach studies. The model distributes water flow across a grid of uniform cells, adjusting elevation values at each time step to simulate erosion and deposition. Landscape evolution emerges from iterative updates of fluvial and hillslope processes. Four primary modules define CAESAR-Lisflood (Liu and Coulthard 2017 ): hydrology, fluvial erosion and deposition, surface flow, and slope processes. For the Progo River application, model initialization required (a) digital elevation models (SRTM and DEMNAS), (b) sediment grain-size distribution, (c) slope gradients, and (d) daily rainfall data (1992–2022, NASA POWER). The model grid was set to 50 m × 50 m pixels (2,500 m² each). Erosion and deposition volumes were calculated per pixel, allowing detection of localized morphological adjustments. At each time step, erosion or deposition was determined by flow hydraulics and slope-driven mass wasting, with updated topography feeding subsequent iterations across the 30-year simulation period. CAESAR-Lisflood was chosen because the Progo River is strongly shaped by human activity, land-use change, and sediment regulation. Despite this complexity, the model effectively captured the roles of rainfall, sediment supply, and grain-size dynamics in channel evolution, providing erosion and deposition patterns for further evaluation against geologic, climatic, and anthropogenic drivers. Analysis of the impacts of geologic on the river morphological changes Geological controls shape river morphology primarily through grain size, slope, geological structures, and lithology (Grant et al. 2003 ; Aswathy et al. 2008 ). Each of these elements influences erosion, accretion, channel stability, and long-term geomorphic evolution. Grain size analysis Sediment grain size is a fundamental determinant of erosion resistance. Fine-grained sediments such as clay and silt are more prone to entrainment, whereas coarser gravels and cobbles stabilize banks and bars. Grain sizes were classified using the Wentworth ( 1922 ) scale (Table 1 ). Table 1 Wentworth ( 1922 ) grain sizes classification Millimeters (mm) Wentworth size class > 256 Boulder 64–256 Cobble 4–64 Pebble 2–4 Granule 1–2 Very coarse sand 1/2–1 Coarse sand 1/4–1/2 Medium sand 1/8–1/4 Fine sand 1/16–1/8 Very fine sand 1/32–1/16 Coarse silt 1/64–1/32 Medium silt 1/128–1/64 Fine silt 1/256–1/128 Very fine silt < 1/256 Clay Field sampling was conducted along middle-reach sections of the Progo River where both erosion-prone and erosion-resistant banks were present. At each site, 100 clasts were measured using the Wolman pebble count method (Wolman, 1954 ) at 1 m intervals. Samples were grouped according to Wentworth classes, and results were mapped to create a grain size distribution map. By overlaying the grain-size distribution map with the morphology change maps (2002 vs. 2022, derived from Google Earth Engine imagery), the relationship between grain size and bank stability was evaluated. Finer-grained areas were hypothesized to exhibit greater erosion and lateral channel migration. Slope analysis Slope exerts a strong control on river energy and morphology. Two categories were assessed: riverbank slope and channel slope. Riverbank slope determines susceptibility to undercutting and mass failure. Slope categories were defined as very gentle (0–8°), gentle (8–15°), moderate (15–25°), steep (25–45°), and very steep (> 45°). Channel slope reflects the longitudinal gradient of the riverbed and was derived from SRTM DEM (30 m resolution) and DEMNAS. Longitudinal profiles were generated at 25 m contour intervals, allowing analysis of slope breaks and knickpoints (Ghosh, 2023 ). Overlaying slope distribution maps with morphology change maps revealed that gentler slopes (8–15°) corresponded with greater sinuosity and lateral migration, whereas steeper slopes produced straighter, higher-velocity channels. Geological structure analysis Structural geology strongly influences river alignment, incision, and valley morphology. DEM data were analyzed to identify lineaments—linear or curvilinear features indicative of faults, fractures, and tectonic structures. Lineament orientation and frequency were plotted as rose diagrams using RockWorks software (Chenrai, 2012 ). Field surveys validated DEM-derived lineaments, focusing on joints, scarps, faults, and folds. Structural controls were further assessed using longitudinal river profiles, which act as proxies for uplift and deformation (Siddiqui, 2017 ). Convexities and rapids within the profile were interpreted as evidence of tectonic activity, coarse debris influx, or resistant lithologies. By comparing lineament trends with river orientation and morphology changes, the structural influence on channel evolution was clarified. Lithology analysis Lithology governs resistance to erosion and sediment supply. A lithological distribution map was compiled from regional geological maps and refined through field mapping. Outcrops were examined for weathering degree following Regmi et al. ( 2013 ), classifying rocks as fresh, slightly, moderately, severely, or completely weathered. Petrographic thin sections were prepared to determine mineral composition, texture, and fabric (Ngapna et al. 2018 ). These data were related to erosion resistance, with weaker lithologies (e.g., volcanic tuffs, unconsolidated alluvium) expected to exhibit higher erosion rates compared to resistant limestones. Lithology maps were then overlaid with the morphology change map to identify correlations between bedrock type and erosion/accretion zones. Analysis of the impacts of climatic on the river morphological changes Climatic variability, particularly rainfall, strongly influences hydrological regimes and riverbank stability. Monthly rainfall data (2002–2022) were obtained from the NASA POWER database (Stackhouse 2010 ) and analyzed for interannual variability and long-term trends. Rainfall anomalies were compared with GEE-derived morphology maps to assess whether wetter years enhanced erosion or drier years promoted accretion. Riverbank erosion rates were quantified from annual river area differences using Landsat imagery (2002–2022); negative values indicated accretion, while positive values reflected erosion. Correlation analyses between rainfall and erosion/accretion rates were performed in SPSS and Excel. Vegetation cover, measured through NDVI values extracted from GEE (Nones and Guerrero 2019 ), was evaluated at upper, middle, and lower reaches to assess its role in moderating climatic effects on channel stability. Analysis of the impacts of anthropogenic on the river morphological changes Human activities have become major drivers of river morphology in the Progo Basin. Land use change was assessed using Landsat time-series imagery (2002–2022) processed in Google Earth Engine (GEE). A supervised classification approach, with training datasets from high-resolution aerial photography (Zurqani et al. 2018 ), categorized land cover into agriculture, forest, built-up areas, and bare soil. By comparing classified maps across years, zones of LULC transformation were identified and overlaid with morphological change maps to evaluate spatial correspondence with channel evolution. To refine the analysis, NDVI thresholds detected vegetation loss in riparian corridors (50–100 m buffers). Vegetation pixel values ranged from 0.312 to 1, while soil ranged from 0.0938 to 0.364. Year-to-year vegetation reduction was interpreted as anthropogenic disturbance linked to agriculture, quarrying, or urbanization. Field observations documented quarrying, sand mining, and construction, while semi-structured interviews provided insights on dam construction, irrigation, and cultural uses of the river. Literature sources triangulated these findings. To quantify anthropogenic impacts, linear regression models in SPSS and Excel linked NDVI-based vegetation loss with erosion/accretion rates. This analysis tested the hypothesis that reduced vegetation cover accelerates soil erosion and channel instability (Kayitesi et al. 2022 ). Results and Discussion The river modeling The CAESAR-Lisflood model of the Progo River is shown in Fig. 3 . The model indicates almost no erosion in the upper reach (east), while erosion dominated the west side (yellow). After the confluence of two branches in the upper reach, deposition became dominant (green). This deposition likely came from sediment eroded from steeply sloped riverbanks, where deposition exceeded erosion. In the middle reach, erosion dominated, with deposition barely visible. The greater depth of the middle reach likely caused sediments to settle in deeper zones, remaining unseen at the surface. The lower reach experienced stronger erosion than the upper and middle reaches due to faster currents that eroded riverbanks, even though slopes were gentler. River meandering also intensified erosion in this section, while its depth limited deposition. However, the model used only rainfall data and limited geological inputs (slopes and grain size), omitting lithology, geological structure, and anthropogenic activities. Human activities significantly affect river morphology, yet they are not represented. Therefore, the next step is to confirm the influence of geologic, climatic, and anthropogenic factors. GEE imagery can track yearly changes, while fieldwork helps validate the roles of lithology, structure, and human impacts on river morphology. The impacts of geologic on the river morphological changes A survey of the Progo River’s morphology identified four key geological factors influencing changes: grain size, slope, geological structure, and lithology. A morphology change map (Fig. 4 ) from GEE images comparing 2002 and 2022 was created to analyze these impacts. Over twenty years, erosion and accretion occurred across the upper, middle, and lower reaches. In the upper reach (Fig. 5 a), some sections on the west side were unclear in GEE images, making detection difficult. Overall, erosion and accretion were minor in the upper and parts of the middle reach (Fig. 5 a–b) because the river shows little meander change. In contrast, the middle reach (Fig. 5 c) displayed significant erosion and accretion, leading to meander shifts. The lower reach (Fig. 5 d) experienced the greatest erosion, altering meander direction due to higher flow velocity. Variations in river stability across reaches are closely linked to geological factors, discussed below. Grain size impacts Grain size strongly influences river morphology along the Progo River. A grain-size distribution map with pie diagrams (Fig. 5 ) shows clear downstream fining: the upper reach is dominated by boulders and cobbles, the middle reach by pebbles and granules, and the lower reach by fine sediments from sand to clay. In the upper reach, andesitic boulders to pebbles are frequently deposited as mid-channel and point bars, largely sourced from volcanic eruptions. These coarse materials are transported downstream but accumulate before reaching the lower river. In the middle reach, smaller grains such as pebbles and granules dominate, carried farther by moderate currents. The lower reach contains predominantly fine sediments—sand, silt, and clay—easily eroded and redistributed by river flows. Here, deposition rarely forms stable bars, as fine sediments are continuously reworked. The dam in the middle reaches further limits the downstream movement of coarse material, while marine input adds complexity to sediment supply in the estuary. When compared with morphological change maps, grain size distribution reveals a strong relationship with channel dynamics. In the upper reach, resistant bedrock combined with boulder- and cobble-sized sediments restricts change, as currents cannot easily mobilize such large particles, limiting erosion. The middle reach shows greater adjustments, with erosion of cut banks and transport of pebble-to-granule material visible in GEE imagery from the past two decades. These sediments are readily mobilized and deposited downstream. The lower reach exhibits the most dynamic changes, where frequent high flows erode and redeposit fine sediments, forming and removing mid-channel bars. This reflects both upstream sediment supply and downstream marine influences. Overall, the Progo River follows the principle of downstream fining—coarse sediments upstream and finer sediments downstream—though transitions are often abrupt, such as from medium gravel to medium sand. This reflects selective transport, abrasion, and sorting, with collisions increasing roundness and reducing particle size. Slope processes and tectonic activity also contribute to sediment refinement. Coarser particles stabilize channels, while finer sediments drive frequent morphological adjustments. Grain-size data were quantified using Wolman pebble counts at two representative sites. Pie diagrams shows, at location b, in the upper reach, coarse particles dominated: >128 mm was 19%, 90–128 mm was 29%, 64–90 mm was 35%, 45–64 mm was 17%, and < 45 mm was 0%, while the total grain size at location c: 64 mm was 0%. This difference clearly illustrates the downstream fining trend. Larger particles at location b stabilize channels, limiting erosion (1.68 ha), while finer sediments at location c are easily mobilized, producing greater morphological change (2.85 ha). Thus, grain size is a key control on Progo River morphology: coarse sediments enhance channel stability upstream, while finer sediments downstream promote dynamic erosion and deposition. Slope impacts SRTM DEM analysis and fieldwork revealed that the study area is dominated by very gentle (0–8°) to gentle (8–15°) slopes. Riverbanks in the upper and middle reaches (locations a–d) mostly exhibit moderate (15–25°) to high (25–45°) slopes, while the lower reach (location e) is dominated by gentle slopes (8–15°). When slope distribution (Fig. 6 ) was overlaid with the morphology change map, erosion was evident in both gentle and steep riverbanks, suggesting that slope alone cannot fully explain morphological change. In the upper and middle reaches, high slopes coincide with resistant lithology. Bedrock-dominated banks restrict erosion, yet loose materials such as boulders and gravel from surface weathering and rockfall are common in catchments. These materials are delivered to the channel, supplying sediment that contributes to downstream accretion. In the lower reach, although slopes are gentler, sedimentary materials are less consolidated and highly erodible, especially during extreme rainfall. Such events may trigger large-scale erosional processes, producing significant sediment loads that shape downstream morphology (Ghimire 2020 ). The longitudinal profile of the Progo River further clarifies slope-morphology interactions. Elevation decreases sharply in the upper reach, dropping 37 m in the first 5 km (7.4 m per 1 km). Between 5 and 40 km, the decrease slows to 25 m per 10 km (2.5 m per 1 km). These steep upstream slopes promote erosion and material loss, but resistant bedrock reduces visible riverbank retreat. Instead, loose weathered material tends to accumulate in channels, partially stabilizing banks. Downstream, gentler slopes coincide with finer-grained lithology and broader drainage areas, conditions more favorable to sediment deposition. The relationship between channel slope, lithology, and drainage area aligns with the graded stream concept. Steeper slopes dominate near narrow headwater catchments where coarse lithologies prevail, while broader drainage areas downstream reduce channel slope and erosive potential (Baumann et al. 2018 ; Negi et al. 2023 ). Overall, slope strongly influences sediment supply: steep, resistant upstream banks provide coarse material through rockfall and weathering, whereas gentler, weaker downstream slopes contribute fine sediments through erosion. Together, these processes drive the continuous morphological adjustment of the Progo River. Geological structure impacts A lineament map of the Progo River was created using DEM data (Fig. 7 ). Geological structures were identified as linear and curved features, most of which occur in the upper reach, with fewer in the middle reach. A rose diagram indicated dominant NW–SE and secondary N–S orientations. These lineaments may correspond to major geological structures, escarpments, and topographic highs or lows (Chaabouni et al. 2012 ). Field verification revealed a reverse fault at location a and zones of bedrock destruction at location b, both interpreted as traces of the Progo Fault in the western part of the river (Saputra et al. 2021 ). These structures originated from the Java tectonic trend that controlled the development of Kulon Progo Mountain (Syafri et al. 2013 ). The lineament map was compared with morphology change data to evaluate structural control on the Progo River. In the upper reach, geological structures cut through bedrock, triggering rockfall and localized bank erosion. While GEE imagery confirms erosion, the resulting material also contributed to downstream sediment discharge and accretion. Although less extensive than in the lower reach, tectonic structures clearly shaped erosion and sedimentation patterns. Active tectonics deform the valley gradient, altering slope, meandering, and bedload transport to maintain equilibrium (Dar et al. 2019 ). The longitudinal profile highlights deformation in the upper reach, where elevation dropped 37 m within the first 5 km (7.4 m/km), compared to the basin-wide average of 2.5 m/km. Such steepening suggests tectonic subsidence and uplift. Longitudinal profiles are reliable indicators of neotectonic deformation in earthquake-prone regions (Siddiqui 2017 ). Increased gradients enhance stream energy and bank erosion (Qureshi and Khan 2020 ). Although resistant lithology may limit surface erosion, tectonic subsidence promotes significant bank collapse, with loosened material infilling the channel. Knickpoints in the profile, often in volcanic breccias, further indicate structural control. Their occurrence without lithological contrasts supports tectonic influence rather than material resistance (Blanc et al. 2020 ). Lithology impacts Six locations in the study area were explored to identify the lithological characteristics of the outcrops at each site. Table 2 presents the lithological outcrop identifications in the study area. Table 2 The lithological outcrop identification in the study area Location Lithological outcrop characteristics a Volcanic breccia, basalt fragments with a boulder size, tuff matrices, slightly weathered, a thickness of 0.5 m b Volcanic breccia, basalt fragments with a pebble size, tuff matrices, fresh, a thickness of 2 m c Intercalated weathering-resistant volcanic breccia and tuff. Volcanic breccia in the upper part consists of basalt fragments with a pebble size, tuff matrices, slightly weathered, and a thickness of 0.5 m. The tuff in the center is slightly weathered and has a thickness of 0.3 m. Volcanic breccia at the bottom consists of basalt fragments with a granule size, tuff matrices, fresh, and a thickness of 0.8 m. d Volcanic breccia, basalt fragments with a pebble size, tuff matrices, slightly weathered, a thickness of 1 m e Limestone, fresh, clastic, a thickness of 3 m, f Limestone, slightly weathered, clastic, a thickness of 2 m g Loose sedimentary materials with sand, silt, and clay materials, a thickness of 2 m h Loose sedimentary materials with sand, silt, and clay materials, a thickness of 1 m The geological map with lithological distribution (Fig. 8 ) was overlaid with morphology change data to evaluate lithology’s role in controlling river morphology, particularly the resistance of riverbank materials to erosion. Lithological observations and petrographic analyses identified the main rock types. In the upper reach, erosion rates are low because volcanic breccia is highly resistant to weathering. At locations a and d, weathered breccia produces loose fragments from granules to boulders that are difficult to transport, resulting in relatively stable areas in GEE imagery. Resistant breccia also occurs at location b, while intercalated breccia and tuff appear at location c. These deposits, part of the Young Volcanic Deposits of Merapi Volcano, show limited erosion. In the middle reach, limestone of the Sentolo Formation is exposed (locations e and f), while the lower reach is dominated by loose sedimentary materials. Clastic limestone is more erodible than volcanic breccia. Limestone grains (1/16–2 mm) are finer than breccia fragments (4–>256 mm), which are harder for currents to mobilize. In addition, limestone dissolves readily in water, enhancing riverbank erosion (Chaigne et al. 2023 ). Weakly compacted sediments in the lower reach are also highly erodible. For petrographic analysis (Fig. 9 ), nine hand specimens were collected from six locations (a–f) and classified following Schmid ( 1981 ), Streckeisen ( 1976 ), and Dunham and Ham ( 1962 ). Results show that volcanic breccias of the Merapi deposits stabilize the Progo Riverbed. While lithological contrasts influence morphology (Blanc et al. 2020 ), structural controls may better explain observed variations. Petrographic observations revealed tuffs at locations a, b, c, and d, occurring as volcanic breccia matrices and single lithology. Schmidt (1981) classified these tuffs into three categories: crystal tuff at locations a and c (middle), vitric tuff at locations b and d, and lithic tuff at location c (top). Petrographic analysis shows that the crystal tuff at location a (Fig. 9 a) contains 2% quartz, 3% clinopyroxene, 50% feldspar, 40% volcanic glass, and 5% opaque minerals. The vitric tuff at location b (Fig. 9 b) contains 2% quartz, 2% orthopyroxene, 7% feldspar, 60% volcanic glass, 28% lithic fragments, and 1% opaque minerals. The lithic tuff at location c (top) (Fig. 9 c) contains 1% quartz, 2% orthopyroxene, 50% lithic fragments, 12% feldspar, 34% volcanic glass, and 1% opaque minerals. Meanwhile, the crystal tuff at location c (middle) (Fig. 9 d) contains 4% quartz, 4% clinopyroxene, 1% hornblende, 45% feldspar, 42% volcanic glass, and 4% opaque minerals. Unlike most rocks, volcanic rocks form rapidly. Two main stages occur: the ejection of fragments during eruptions (tuffs) and the cooling or sedimentation of volcanic ash. Pyroclastic material, from fine sand to clay-sized ash and pumice, forms the tuff matrix. Rapid cooling results in incomplete crystallization, leaving sharp, angular fragments in a poorly consolidated matrix. This creates complex pore networks with distinct macro- and microporosities that strongly influence weathering (Wedekind et al. 2013 ). High volcanic glass content further promotes alteration to zeolites and clays. Vitric tuffs typically show high porosity, large pores, and water absorption of 15–31 wt%, whereas crystal tuffs have lower porosity, smaller pores, and absorption of 6–16 wt%. Crystal tuffs also contain swelling clays and zeolites, reducing vapor permeability but increasing expansion. In the study area, volcanic breccia matrices show weathering, loosening fragments that accumulate in channels. Plutonic rocks at locations b and c (bottom), occurring as volcanic breccia fragments, were classified as basalts following Streckeisen ( 1976 ). At location b (Fig. 9 e), basalt consists of quartz, 5% orthopyroxene, 3% opaque minerals, 45% plagioclase, 4% clinopyroxene, 23% groundmass, and 20% vesicles. At location c (Fig. 9 f), it contains 2% quartz, 55% plagioclase, 5% clinopyroxene, 2% orthopyroxene, 2% opaque minerals, and 34% groundmass. Compared with the matrix, volcanic breccia fragments are more resistant to erosion. When the matrix weathers, basalt clasts remain and accumulate in channels. These coarse, erosion-resistant fragments are difficult to transport, explaining the relative stability of channel and point bars in the upper reach as shown in GEE imagery. Erosion here is therefore limited mainly to weathering of the breccia matrix, while basalt persists in the channels. Limestone at locations e and f was petrographically classified, following Dunham and Ham ( 1962 ), as wackestone. At location e (Fig. 9 g), wackestone contains 2% quartz, 3% opaque minerals, 35% fossils, 1% glauconite, and 59% clay carbonate. At location f (Fig. 9 h), it consists of 2% quartz, 1% opaque minerals, 50% fossils, 4% glauconite, and 43% clay carbonate. Wackestone is mud-supported with > 10% bioclasts, fully cemented by lime mud, which prevents reservoir space development (Qi et al. 2021 ). Carbonate grains float in lime mud, typically > 20 microns in size (Smith 2013 ). Due to clay content, pressure-solution seams often form (Zepu et al. 2017 ). Clay carbonate minerals, acting as cement, occur abundantly in both samples, with authigenic minerals precipitating in pores and around grains during diagenesis. Detrital quartz and feldspar are commonly replaced by carbonate cement. Glauconite precipitates along grain surfaces or fractures and may fully replace feldspar, muscovite, or clays (Baiyegunhi et al. 2021 ). These limestones represent altered lithologies with significant mineral replacement. Evidence of advanced alteration at location f corresponds with greater weathering and erosion observed in the middle reach in GEE imagery. The impacts of climatic on the river morphological changes Three representative points of the study area were selected to analyze the impact of climate on river morphological changes (Fig. 10 a). Annual precipitation (2002–2022) and riverbank erosion at each point were examined (Fig. 10 b). Regression analysis between annual precipitation and erosion produced p-values of 0.724 (upper reach), 0.704 (middle reach), and 0.983 (lower reach), with R² values of 0.0067, 0.0078, and 0.00002, respectively. These results indicate a weak negative correlation between precipitation and riverbank erosion. High erosion events often occurred during years of low rainfall (e.g., 2011 in the upper reach, 2015 in the middle and lower reaches), while low erosion or net accretion coincided with higher rainfall (e.g., 2014 at all points). Overall, annual rainfall remained relatively stable, and its influence on erosion was not significant. The study area lacks extreme weather events such as typhoons, making rainfall variability a limited driver of morphological change. Several factors explain the weak correlation:(1) Annual precipitation does not always correspond to runoff or infiltration in the Progo River, as runoff characteristics determine erosion more than rainfall itself (Martínez-Murillo et al. 2013 ); (2) heavy rainfall may weaken bank material, but erosion may only occur later when thresholds are exceeded, as in 2019 when erosion doubled despite reduced rainfall compared to 2018; (3) LULC strongly influences runoff, with forested areas contributing less sediment than bare land or settlements; and (4) rainfall partly influences erosion, but anthropogenic factors, such as quarrying and dam construction, play a larger role (Ferrier et al. 2013 ; Prasetya et al. 2021 ). In conclusion, climatic factors affect river morphology, but the Progo River shows limited direct response to precipitation, as anthropogenic and geological controls are more dominant. The impacts of anthropogenic activities on the river morphological changes An anthropogenic map (Fig. 11 ) illustrates human activities influencing Progo River morphology. Quarrying, dam construction, and LULC changes increase sediment supply to the channel, enhancing river accretion and altering morphological dynamics. Impacts of quarrying activities There is no definitive record of when quarrying began on the Progo River, though interviews with miners suggest activity since 1978. Current practices include large-scale extraction of boulders, gravel, and sand using heavy equipment, alongside small-scale community quarrying with simple tools, both legal and illegal. Interviews were conducted at two sites: location b represents small-scale quarrying, where workers extract gravel and sand manually, producing about 3 m³ per day (two trucks, 1.5 m³ each). Location c represents mechanized quarrying, with heavy equipment extracting up to 120 m³ daily (15 trucks, 8 m³ each). Morphological analysis (2018–2022, Fig. 12 ) shows erosion at location b reached 0.18 ha, compared to 1.96 ha at location c, confirming that high extraction volumes cause greater riverbank erosion. Quarrying alters river morphology in three main ways: (1) reducing sediment load, which lowers bed levels and disrupts transport; (2) altering grain-size distribution, as selective extraction of medium-to-coarse sand accelerates bed coarsening and erosion; and (3) steepening bed slopes, as quarry pits deepen channels, increasing velocity and localized erosion (Bhattacharya and Das Chatterjee 2021 ). Abandoned pits along riverbanks further contribute to long-term geomorphic instability. Impacts of dam construction Constructed between 2016 and 2018, Kamijoro Dam (Fig. 11 e) is located in the middle reach of the Progo River, providing irrigation for 2,370 ha and serving as a public space for recreation and sports (Kementerian PUPR 2021 ). GEE images were used to analyze downstream morphology before, during, and after dam construction (Fig. 13 ). In 2016, no construction was visible, serving as a baseline. By 2017, during the initial stage, accretion of 9.39 ha appeared downstream of the construction site. In 2018, at the final stage, accretion reached 8.02 ha. These changes were likely caused by sediment from land clearing, channel widening, and dredging activities. In 2019, after completion, no new accretion was observed; instead, erosion occurred at several points. Dams can trap large volumes of sediment, altering natural sediment transport and causing “hungry water” conditions downstream, which erode riverbeds and banks. Additionally, dams reduce flood peaks and modify flow characteristics, leading to significant morphological adjustments in downstream reaches of rivers (Vu et al. 2024 ). Impacts of land use and land cover change The NDVI of the Progo River was analyzed to assess the impacts of land use and land cover (LULC) on river morphology from 2002 to 2022. Figure 14 a–c shows NDVI maps for 2002 and 2022, vegetation–erosion–accretion trends, and regression results. Soil and vegetation pixel ranges were 0.0938–0.364 and 0.312–1, respectively. In 2002, bare and wet land dominated riverbanks, but by 2022 forests had become the main cover. Vegetation decline occurred in several years (2005, 2006, 2009, 2011, 2012, 2016, 2018, and 2019), influencing erosion and accretion (Fig. 14 b). Regression analysis indicated a strong positive correlation (R² = 0.91, p < 0.0001) between vegetation cover, soil erosion, and river accretion (Fig. 14 c). Increased vegetation reduced erosion and sediment discharge, while vegetation loss intensified channel erosion and deposition. Forests affect hydrology through evapotranspiration, infiltration, and root stabilization. Although afforestation may increase evapotranspiration and lower streamflow, forests generally enhance infiltration, recharge groundwater, stabilize banks, and reduce sediment loads. Streams in forested areas typically show greater stability, with broader, more stable channels, lower discharge, slower velocities, and reduced sediment input. Conversely, vegetation loss decreases infiltration, increases runoff, reduces baseflow, and accelerates peak flows, leading to higher flood volumes, sediment transport, and erosion risks. Forest root systems are essential for binding soil, reducing water deficits, and preventing small landslides, underscoring the critical role of vegetation in maintaining river stability (Kayitesi et al. 2022 ). A special event (the impacts of the Merapi Volcano eruption) Volcanic events during and after eruptions significantly impact nearby river systems. These impacts include high volcaniclastic sediment inflow, formation and collapse of natural dams, drainage disruptions, changes in slope gradients, lava dome collapse, surface roughness, mass wasting, alterations in channel geometry, and interruptions in river flow. The duration of fluvial system recovery or transition depends on the severity of these disruptions (O’Shea 2009; Dipayana et al. 2013 ). Merapi Volcano, located upstream of the Progo River (Fig. 15 a), erupted explosively in October 2010, the largest in over a century. Unlike the typical dome collapses that produce “Merapi-type” pyroclastic density currents, this eruption generated multiple explosions, ash columns rising to 17 km, and pyroclastic density currents reaching 16 km from the summit. Lava domes extruded at exceptionally high rates, up to 35 m³ s⁻¹ (Jousset and Pallister 2013 ). Approximately 150 million m³ of volcanic material entered rivers draining the volcano, including the Progo River. This material triggered debris flows that caused major morphological changes, particularly in the middle and downstream reaches (Fitriadin et al. 2017 ). Following the eruption, the Progo River experienced both bed degradation and aggradation. Bed degradation was the main factor driving riverbank erosion (Harsanto 2015 ). From April to July 2010, before the eruption, erosion and accretion measured 9.72 ha and 14.22 ha, respectively. From July 2010 to March 2011, erosion rose dramatically to 186.23 ha, while accretion decreased to 3.69 ha (Fig. 15 b). Post-eruption, high discharges carrying debris flows eroded banks significantly, while much of the volcanic material was deposited in channels, filling degraded beds. Debris flows in the central slope altered hydraulic conditions, leading to localized degradation and aggradation. Downstream, sedimentation caused watergate clogging, while simulations suggest that continued sediment supply may reduce further bed degradation (Fitriadin et al. 2017 ). The timeline of the Progo River Geological factors influenced Progo River morphology over long timescales, while climatic factors were not the main drivers of change. In contrast, anthropogenic activities caused significant structural changes within short periods. The timeline (2002–2022) highlights how each controlling factor shaped river morphology, as summarized in Table 3 . Table 3 The detailed timeline experienced by the Progo River from 2002 to 2022 Year Controlling factors Progo River’s conditions 2002 Anthropogenic activity Quarrying activities started in 1978 and continue to this day. 2005 Anthropogenic activity Loss of vegetation has increased soil erosion and increased river accretion in the Progo River. 2010 Merapi Volcano activity The eruption of Merapi Volcano caused significant riverbank erosion in the Progo River. 2012 Anthropogenic activity Loss of vegetation has increased soil erosion and increased river accretion in the Progo River. 2017 Anthropogenic activity During the initial stage of dam construction in the middle reach area of the Progo River, a significant amount of accretion occurred downstream of the area after the dam construction site due to sedimentary materials from land clearing 2018 Anthropogenic activity In the final stage of dam construction, significant accretion occurred due to sedimentary materials from land clearing during dam construction. 2019 Anthropogenic activity The period after the dam construction was completed did not show any new accretion from the previous year; instead, erosion occurred at several points downstream after the dam construction. 2022 Anthropogenic activity Quarrying activities from previous years resulted in erosion in several locations in the Progo River, both in the upper, middle, and lower reach areas. Conclusion GEE images validated several results from river modeling, highlighting the role of geology in shaping morphology. Grain size and lithology explained the patterns: the upper reach showed minimal erosion due to coarse grains, resistant lithology, and bedrock, while pebble and granule deposits formed cut banks in the middle reach. In contrast, the lower reach, composed of loose sand to clay, was the most eroded section. Accretion was most evident after the confluence of two tributaries in the upper reach, where sediment input and transport increased. However, coarse grains were less mobile, causing localized deposition. Moderate to steep riverbank slopes further influenced erosion–accretion dynamics. Annual erosion rates from GEE confirmed the dominance of low erosion (yellow), aligning with the model. Stable rainfall, without extreme events, also limited climatic drivers of erosion. Yet, unlike the model, GEE and fieldwork revealed significant accretion in the lower reach. This discrepancy stems from the model’s exclusion of lithology, human activities, and marine sediment input. Anthropogenic activities significantly alter the Progo River morphology through quarrying, dam construction, and land use/land cover (LULC) changes. Quarrying, both small- and large-scale, accelerates riverbank erosion, alters sediment load and grain size, and creates unstable pits. The Kamijoro Dam (2016–2018) modified downstream morphology by trapping sediment, reducing flood peaks, and causing erosion from “hungry water” conditions. LULC analysis (2002–2022) revealed strong correlations between vegetation cover, erosion, and accretion, with forested areas stabilizing banks and reducing sediment loads, while vegetation loss increased erosion and flood risk. Collectively, these activities drive long-term geomorphic instability. Overall, geology governs long-term processes, while anthropogenic activities accelerate rapid morphological changes in the Progo River. Declarations Conflict of interest The authors declare no competing interests. Author Contribution All authors contributed to the idea and design of the study. A.Z. wrote the first draft of the manuscript, F.I.G. created the CAESAR-Lisflood model of the Progo River, and the other authors provided feedback on it. All authors have read and approved the final manuscript. Acknowledgement The Southeast Asian Regional Center for Graduate Study and Research in Agriculture (SEARCA) and the Deutscher Akademischer Austauschdienst (DAAD) funded our research. We thank Muhammad Ginong Pratidhina, Dadi Fathoni Wibowo, Haris Nur Eka Prasetya, Ayu Atikha Reinaty, and Alan Prahutama for their technical assistance with this research. We also thank Dr. Jillian Aira Ratio for assessing the material before submission. References Alam AK, Islam MB (2017) Recent changes in Jadukata fan (Bangladesh) in response to Holocene tectonics. 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2","display":"","copyAsset":false,"role":"figure","size":99139,"visible":true,"origin":"","legend":"\u003cp\u003eThe flowchart of the methodology\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-7415481/v1/1f22231007e5c1d2efa43106.png"},{"id":92584040,"identity":"1c2645a2-09e1-4232-8fa4-1ce6daffbe33","added_by":"auto","created_at":"2025-10-01 10:08:49","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":218448,"visible":true,"origin":"","legend":"\u003cp\u003eThe CAESAR-Lisflood model of the Progo River\u003c/p\u003e","description":"","filename":"image3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7415481/v1/6ce8a0348f1a91d4caab8a17.jpeg"},{"id":92584034,"identity":"a60035cf-85ef-4f81-82a3-2018a4631cd3","added_by":"auto","created_at":"2025-10-01 10:08:49","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":271320,"visible":true,"origin":"","legend":"\u003cp\u003eA morphology change map from GEE images compares the Progo River in 2002 and 2022, (a) erosion and accretion in the upper reach area, (b) erosion and accretion in the middle reach area, (c) changes in river meanders in the middle reach area, and (d) changes in river meanders in the lower reach area\u003c/p\u003e","description":"","filename":"image4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7415481/v1/3b6f546de5a52e0651324010.jpeg"},{"id":92584072,"identity":"be0affad-501b-4144-9167-7938f94f0900","added_by":"auto","created_at":"2025-10-01 10:08:52","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":198330,"visible":true,"origin":"","legend":"\u003cp\u003eA grain size distribution map and the percentage of grain size on the pie diagram at location b and c of the study area; (a) (b) the upper reach area is dominated by boulders to cobble, (c) (d) the middle reach area is dominated by pebbles to granules, and (e) (f) (g) the lower reach area is dominated by sand to clay-sized sediment grains\u003c/p\u003e","description":"","filename":"image5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7415481/v1/a5bf2c06ddfa56e9008d1a33.jpg"},{"id":92584041,"identity":"b5c56e7c-05ff-4834-a4a3-72bd517b1c24","added_by":"auto","created_at":"2025-10-01 10:08:49","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":171374,"visible":true,"origin":"","legend":"\u003cp\u003eSlope spatial distribution map and longitudinal river profile of the Progo River; (a) a moderate slope, (b) a high slope, (c) a gentle slope on the left and a moderate slope on the right, (d) a gentle slope on the left and a moderate slope on the right, and (e) a moderate slope on the left and a gentle slope on the right\u003c/p\u003e","description":"","filename":"image6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7415481/v1/d861c20f17a0684631f8617c.jpg"},{"id":92584056,"identity":"3c063eed-4bf8-4840-9015-88912fab9ff7","added_by":"auto","created_at":"2025-10-01 10:08:50","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":168516,"visible":true,"origin":"","legend":"\u003cp\u003eLineament map of the Progo River with (a) reverse fault, (b) bedrock destruction, (c) rose diagram, and (d) longitudinal river profile\u003c/p\u003e","description":"","filename":"image7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7415481/v1/b6af76e81e0869f333abaf2f.jpg"},{"id":92584025,"identity":"4735e14f-7d2d-42c9-a4b9-219a0eb81992","added_by":"auto","created_at":"2025-10-01 10:08:47","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":234320,"visible":true,"origin":"","legend":"\u003cp\u003eGeological map and the formation cross-section (redrawn after Rahardjo et al. 1995), with lithological distribution, (a) weathered volcanic breccia, (b) resistant volcanic breccia, (c) intercalated weathering-resistant volcanic breccia and tuff, (d) weathered volcanic breccia, (e) resistant limestone, (f) weathered limestone, (g) loose sedimentary materials, and (h) loose sedimentary materials\u003c/p\u003e","description":"","filename":"image8.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7415481/v1/69135e289b4aa18090747f94.jpg"},{"id":92584833,"identity":"e2a7ba8d-d619-4940-85e5-47282eadaed5","added_by":"auto","created_at":"2025-10-01 10:16:50","extension":"jpg","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":293364,"visible":true,"origin":"","legend":"\u003cp\u003ePhotomicrographs of volcanic breccia matrices (locations a–d), volcanic breccia fragments (locations b and c), and limestones (locations e and f) under cross- and plane-polarized light, showing the mineral assemblages of quartz (Qtz), feldspar (Fs/Plg), clinopyroxene (Cpx), orthopyroxene (Opx), hornblende (Hbl), volcanic glass (Gv), lithic fragments (Lf), groundmass (Gm), vesicles (Vs), fossils (Fsl), glauconite (Glt), clay carbonate (Ccb), and opaque minerals (Opq)\u003c/p\u003e","description":"","filename":"image9.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7415481/v1/74fc59467d80ac1c4f588d46.jpg"},{"id":92584027,"identity":"6d99a79e-03a6-4df4-85d6-8d9d72e44161","added_by":"auto","created_at":"2025-10-01 10:08:47","extension":"jpg","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":190386,"visible":true,"origin":"","legend":"\u003cp\u003e(a) Three representative points of the study area, (b) Annual precipitation (2002–2022), and (c) riverbank erosion at each point.\u003c/p\u003e","description":"","filename":"image10.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7415481/v1/8ef50ce001527f170f3f5385.jpg"},{"id":92584026,"identity":"762c310c-2675-4ad6-97cc-55fdfaa3d81c","added_by":"auto","created_at":"2025-10-01 10:08:47","extension":"jpeg","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":256337,"visible":true,"origin":"","legend":"\u003cp\u003eAnthropogenic map of the study area, (a) Boulders quarrying, (b) Gravel quarrying, (c) (d) Sand quarrying, (e) Dam construction, and (e) (f) Post-quarrying activity holes.\u003c/p\u003e","description":"","filename":"image11.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7415481/v1/b6e262ea3dc228a2d615346f.jpeg"},{"id":92584070,"identity":"5d438181-eee5-4eb7-bd99-e3e409b12b43","added_by":"auto","created_at":"2025-10-01 10:08:51","extension":"jpeg","order_by":12,"title":"Figure 12","display":"","copyAsset":false,"role":"figure","size":179893,"visible":true,"origin":"","legend":"\u003cp\u003eMorphological changes at quarrying locations b and c (2018–2022)\u003c/p\u003e","description":"","filename":"image12.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7415481/v1/7ee48e5cff68ce627b77ac4c.jpeg"},{"id":92584062,"identity":"e23dd2a7-e735-4f6a-914c-640fb0c8b570","added_by":"auto","created_at":"2025-10-01 10:08:50","extension":"jpeg","order_by":13,"title":"Figure 13","display":"","copyAsset":false,"role":"figure","size":154813,"visible":true,"origin":"","legend":"\u003cp\u003eGEE images in the period before (2016), beginning (2017), end (2018), and after (2019) the Kamijoro Dam construction\u003c/p\u003e","description":"","filename":"image13.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7415481/v1/bea2030dc347d22547060062.jpeg"},{"id":92584018,"identity":"62db18c3-4495-4229-a769-dbe14c6c2c66","added_by":"auto","created_at":"2025-10-01 10:08:46","extension":"jpg","order_by":14,"title":"Figure 14","display":"","copyAsset":false,"role":"figure","size":137125,"visible":true,"origin":"","legend":"\u003cp\u003e(a) NDVI of the Progo River in 2002 and 2022; (b) Vegetation area, soil erosion, and river accretion (2002–2022); (c) Regression analysis between vegetation area, and soil erosion and river accretion.\u003c/p\u003e","description":"","filename":"image14.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7415481/v1/b5d5d76b4ff8a4d81f242137.jpg"},{"id":92584054,"identity":"c6dc1454-720d-4241-b5a9-bfeae8ca36bc","added_by":"auto","created_at":"2025-10-01 10:08:50","extension":"jpg","order_by":15,"title":"Figure 15","display":"","copyAsset":false,"role":"figure","size":131554,"visible":true,"origin":"","legend":"\u003cp\u003e(a) The location of the Merapi Volcano, and (b) Progo River morphological changes before the Merapi Volcano eruption (April and July 2010) and after the Merapi Volcano eruption (March 2011)\u003c/p\u003e","description":"","filename":"image15.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7415481/v1/d29e9a90040d6e2ccee708ad.jpg"},{"id":94987102,"identity":"99273786-7b66-4fce-9641-4661d36eb440","added_by":"auto","created_at":"2025-11-03 07:01:15","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3890501,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7415481/v1/b9e2daf3-de49-40a1-ab54-bcd979e9edad.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"An Investigation on the Geologic, climatic, and anthropogenic controls on the morphology of the Progo River, Indonesia","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe genesis and development of drainage systems are strongly influenced by underlying geology and the interaction of endogenetic and exogenetic processes (Mahala, 2019). Bedrock properties, tectonic deformation, and structural features determine river evolution, while geology interacts with climate to shape topography, drainage patterns, relief, and sediment transport. Rock characteristics such as mineral composition, hardness, and degree of weathering influence sediment availability and grain size, which in turn control the rate and pathways of sediment delivery. Channels, valley floors, and hillslopes all reflect this geologic\u0026ndash;climatic interplay. Processes such as landslides and debris flows can rapidly deliver coarse material into rivers, forming constrictions or natural dams, while earth flows may displace large volumes into channels. These processes create a hierarchy of landforms that regulate sediment transport and hydrologic behavior (Grant et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2003\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eBoth natural and human drivers contribute to river morphology. Natural processes\u0026mdash;bank erosion, bed scouring, and sandbar accretion\u0026mdash;alter channel geometry, while anthropogenic activities such as bank revetment, quarrying, and irrigation infrastructure accelerate change. High sediment supply with low discharge promotes silt deposition and rapid sandbar formation (Chaiwongsaen and Choowong, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Continuous feedback between flow dynamics and channel form results in evolving morphology, which may cause severe bank failures, posing risks to agriculture, navigation, and infrastructure. These dynamics complicate identification of causative mechanisms, particularly in localized scour events (Nguyen et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe Progo River in Central Java and Daerah Istimewa Yogyakarta (DIY), Indonesia, illustrates these interactions. This meandering river drains\u0026thinsp;~\u0026thinsp;17,432 km\u0026sup2; and receives sediment from volcanic and non-volcanic terrains (Ikhsan et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The 2010 eruption of Mount Merapi introduced large volumes of loose material, altering sediment loads and accelerating morphological change. Shifts in channel form affect erosion and sedimentation patterns, influencing hydraulic stability and the safety of structures along the river corridor (Harsanto, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Fitriadin et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Human activities further intensify morphological dynamics. Zamroni et al. (\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) examined a 2.24 km middle\u0026ndash;lower reach and highlighted the impacts of agricultural expansion, industrial growth, settlement development, quarrying, dam construction, and unmanaged waste disposal. These factors exacerbate erosion\u0026ndash;accretion processes. Given rivers\u0026rsquo; dynamic nature, continuous monitoring is essential to guide sustainable management (Manjusree et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAlthough many studies investigate river morphology, they often emphasize a single driver\u0026mdash;geology (rock strength, tectonics, slope), climate (rainfall variability, discharge), or human activities (land use, infrastructure) (Alam and Islam \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Shrestha et al. 2020; Wang et al. 2020; Kayitesi et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Few, however, integrate all three. This study addresses that gap by analyzing the combined effects of geologic, climatic, and anthropogenic factors on morphological changes in the Progo River, DIY Province. Through modeling, remote sensing, fieldwork, and petrographic analysis, the research examines how lithology, structure, slope, and sediment characteristics interact with rainfall variability and human activities to shape channel evolution. The findings provide a more holistic understanding of the processes driving morphological change and support evidence-based management strategies for regulating land use, quarrying, and infrastructure development in the Progo River system.\u003c/p\u003e\n\u003ch3\u003eStudy area and geological characteristics\u003c/h3\u003e\n\u003cp\u003eThe Progo River is located in the Daerah Istimewa Yogyakarta (DIY) Province, Indonesia (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea), and drains an area of approximately 17,432 km². The province contains diverse landscapes, ranging from coastal plains to the peak of Mount Merapi (2,930 masl). Hilly areas dominate the region, including the Sewu Mountains (52%; 150–700 masl), Menoreh Mountains (22%; 0–572 masl), and Mount Merapi (18%; 80–2,911 masl), while lowlands between these ranges account for 8% (0–80 masl). Most of DIY Province (65.65%) lies between 100 and 500 masl, with smaller proportions below 100 m (28.84%), between 500 and 1,000 m (5.04%), and above 1,000 m (0.47%). The climate is humid tropical, with a mean annual rainfall of 2,070 mm over 99 rainy days, an average temperature of 26.7°C, and an average humidity of 83.4%. Soils include lithosol, latosol, alluvial, regosol, grumusol, Mediterranean, and rendzina types (Setyawan et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Mount Merapi dominates the northern region of DIY and connects to the southern coast through the Code River, a tributary that bisects Yogyakarta City. The Merapi plain, bordering the Winongo and Code Rivers downstream of the Opak River, has abundant groundwater and surface water. The Code River also functions as a lava channel during eruptions while supporting cultural, religious, and ecotourism activities (Seftyono, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Trisnaning et al. \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eDIY Province occupies a valley bordered by the Southern Mountains to the east and the Kulonprogo Mountains to the west (Pramumijoyo, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). The study area, located within Kulonprogo and Bantul Regencies, is influenced by the regional tectonic framework of the active-margin system. Subduction of the Indian Oceanic Plate beneath the Eurasian Continental Plate has generated the accretionary zone south of Java, associated volcanism, and the development of Java’s magmatic arc. This system also produced fore-arc basins to the south and back-arc basins in northern Java and the Java Sea. The Kulonprogo region is thus considered part of the magmatic arc (Widagdo et al. \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The geology around the Progo River comprises seven formations, from oldest to youngest: Diorite, Nanggulan Formation, Kebobutak Formation, Sentolo Formation, Young Volcanic Deposits of Merapi Volcano, Colluvium, and Alluvium. Diorite occurs as hornblende diorite intrusions formed during Oligocene–Miocene magmatism. The Nanggulan Formation, of Eocene to early Oligocene age, contains sandstone, lignite, limestone, claystone, and tuff rich in mollusk and foraminifera fossils. The Kebobutak Formation (Late Oligocene–Early Miocene) consists of andesite breccia, tuff, lapilli tuff, agglomerate, and volcanic rocks. The Sentolo Formation comprises limestone and sandstone, underlain by carbonate tuff (Pranata and Gilidian, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Zamroni et al. \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The Young Volcanic Deposits of Merapi include undifferentiated tuff, breccia, ash, agglomerate, and lava. Colluvium consists of unsorted debris derived from the Kebobutak Formation, while Alluvium comprises clay, silt, sand, and gravel along streams and coastal plains (Rahardjo et al. 1995).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Methods","content":"\u003cp\u003eThe methodological approach of this study was divided into two primary stages: (1) river modeling analysis and (2) assessment of geologic, climatic, and anthropogenic impacts on river morphological change. A schematic overview of the research design is presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\n\u003ch3\u003eAnalysis of the river modelling\u003c/h3\u003e\n\u003cp\u003eThe first stage of this study simulated the hydromorphological dynamics of the Progo River using the CAESAR-Lisflood landscape evolution model. River modeling provides a quantitative framework to examine how sediment supply, grain-size distribution, and precipitation influence channel morphology. A key challenge lies in selecting empirical closure relations for sediment transport, which strongly affect model performance. CAESAR-Lisflood integrates hydrological and hydraulic components with multi-class sediment transport algorithms, enabling simulation of erosion, deposition, and slope processes such as soil creep and landslides. The model has been widely applied worldwide to reproduce both long-term landform changes and short-term geomorphic events (Pasculli and Audisio \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Thapa et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). It balances computational efficiency with accuracy at spatial and temporal scales relevant to river reach studies. The model distributes water flow across a grid of uniform cells, adjusting elevation values at each time step to simulate erosion and deposition. Landscape evolution emerges from iterative updates of fluvial and hillslope processes. Four primary modules define CAESAR-Lisflood (Liu and Coulthard \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2017\u003c/span\u003e): hydrology, fluvial erosion and deposition, surface flow, and slope processes.\u003c/p\u003e\u003cp\u003eFor the Progo River application, model initialization required (a) digital elevation models (SRTM and DEMNAS), (b) sediment grain-size distribution, (c) slope gradients, and (d) daily rainfall data (1992\u0026ndash;2022, NASA POWER). The model grid was set to 50 m \u0026times; 50 m pixels (2,500 m\u0026sup2; each). Erosion and deposition volumes were calculated per pixel, allowing detection of localized morphological adjustments. At each time step, erosion or deposition was determined by flow hydraulics and slope-driven mass wasting, with updated topography feeding subsequent iterations across the 30-year simulation period. CAESAR-Lisflood was chosen because the Progo River is strongly shaped by human activity, land-use change, and sediment regulation. Despite this complexity, the model effectively captured the roles of rainfall, sediment supply, and grain-size dynamics in channel evolution, providing erosion and deposition patterns for further evaluation against geologic, climatic, and anthropogenic drivers.\u003c/p\u003e\n\u003ch3\u003eAnalysis of the impacts of geologic on the river morphological changes\u003c/h3\u003e\n\u003cp\u003eGeological controls shape river morphology primarily through grain size, slope, geological structures, and lithology (Grant et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Aswathy et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Each of these elements influences erosion, accretion, channel stability, and long-term geomorphic evolution.\u003c/p\u003e\n\u003ch3\u003eGrain size analysis\u003c/h3\u003e\n\u003cp\u003eSediment grain size is a fundamental determinant of erosion resistance. Fine-grained sediments such as clay and silt are more prone to entrainment, whereas coarser gravels and cobbles stabilize banks and bars. Grain sizes were classified using the Wentworth (\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e1922\u003c/span\u003e) scale (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eWentworth (\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e1922\u003c/span\u003e) grain sizes classification\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMillimeters (mm)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWentworth size class\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;256\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBoulder\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e64\u0026ndash;256\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCobble\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4\u0026ndash;64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePebble\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u0026ndash;4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGranule\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u0026ndash;2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVery coarse sand\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1/2\u0026ndash;1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCoarse sand\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1/4\u0026ndash;1/2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMedium sand\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1/8\u0026ndash;1/4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFine sand\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1/16\u0026ndash;1/8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVery fine sand\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1/32\u0026ndash;1/16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCoarse silt\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1/64\u0026ndash;1/32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMedium silt\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1/128\u0026ndash;1/64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFine silt\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1/256\u0026ndash;1/128\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVery fine silt\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;1/256\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eClay\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eField sampling was conducted along middle-reach sections of the Progo River where both erosion-prone and erosion-resistant banks were present. At each site, 100 clasts were measured using the Wolman pebble count method (Wolman, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e1954\u003c/span\u003e) at 1 m intervals. Samples were grouped according to Wentworth classes, and results were mapped to create a grain size distribution map. By overlaying the grain-size distribution map with the morphology change maps (2002 vs. 2022, derived from Google Earth Engine imagery), the relationship between grain size and bank stability was evaluated. Finer-grained areas were hypothesized to exhibit greater erosion and lateral channel migration.\u003c/p\u003e\n\u003ch3\u003eSlope analysis\u003c/h3\u003e\n\u003cp\u003eSlope exerts a strong control on river energy and morphology. Two categories were assessed: riverbank slope and channel slope. Riverbank slope determines susceptibility to undercutting and mass failure. Slope categories were defined as very gentle (0\u0026ndash;8\u0026deg;), gentle (8\u0026ndash;15\u0026deg;), moderate (15\u0026ndash;25\u0026deg;), steep (25\u0026ndash;45\u0026deg;), and very steep (\u0026gt;\u0026thinsp;45\u0026deg;). Channel slope reflects the longitudinal gradient of the riverbed and was derived from SRTM DEM (30 m resolution) and DEMNAS. Longitudinal profiles were generated at 25 m contour intervals, allowing analysis of slope breaks and knickpoints (Ghosh, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Overlaying slope distribution maps with morphology change maps revealed that gentler slopes (8\u0026ndash;15\u0026deg;) corresponded with greater sinuosity and lateral migration, whereas steeper slopes produced straighter, higher-velocity channels.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eGeological structure analysis\u003c/h2\u003e\u003cp\u003eStructural geology strongly influences river alignment, incision, and valley morphology. DEM data were analyzed to identify lineaments\u0026mdash;linear or curvilinear features indicative of faults, fractures, and tectonic structures. Lineament orientation and frequency were plotted as rose diagrams using RockWorks software (Chenrai, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eField surveys validated DEM-derived lineaments, focusing on joints, scarps, faults, and folds. Structural controls were further assessed using longitudinal river profiles, which act as proxies for uplift and deformation (Siddiqui, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Convexities and rapids within the profile were interpreted as evidence of tectonic activity, coarse debris influx, or resistant lithologies. By comparing lineament trends with river orientation and morphology changes, the structural influence on channel evolution was clarified.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eLithology analysis\u003c/h3\u003e\n\u003cp\u003eLithology governs resistance to erosion and sediment supply. A lithological distribution map was compiled from regional geological maps and refined through field mapping. Outcrops were examined for weathering degree following Regmi et al. (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), classifying rocks as fresh, slightly, moderately, severely, or completely weathered. Petrographic thin sections were prepared to determine mineral composition, texture, and fabric (Ngapna et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). These data were related to erosion resistance, with weaker lithologies (e.g., volcanic tuffs, unconsolidated alluvium) expected to exhibit higher erosion rates compared to resistant limestones.\u003c/p\u003e\u003cp\u003eLithology maps were then overlaid with the morphology change map to identify correlations between bedrock type and erosion/accretion zones.\u003c/p\u003e\n\u003ch3\u003eAnalysis of the impacts of climatic on the river morphological changes\u003c/h3\u003e\n\u003cp\u003eClimatic variability, particularly rainfall, strongly influences hydrological regimes and riverbank stability. Monthly rainfall data (2002\u0026ndash;2022) were obtained from the NASA POWER database (Stackhouse \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) and analyzed for interannual variability and long-term trends. Rainfall anomalies were compared with GEE-derived morphology maps to assess whether wetter years enhanced erosion or drier years promoted accretion.\u003c/p\u003e\u003cp\u003eRiverbank erosion rates were quantified from annual river area differences using Landsat imagery (2002\u0026ndash;2022); negative values indicated accretion, while positive values reflected erosion. Correlation analyses between rainfall and erosion/accretion rates were performed in SPSS and Excel. Vegetation cover, measured through NDVI values extracted from GEE (Nones and Guerrero \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), was evaluated at upper, middle, and lower reaches to assess its role in moderating climatic effects on channel stability.\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eAnalysis of the impacts of anthropogenic on the river morphological changes\u003c/h2\u003e\u003cp\u003eHuman activities have become major drivers of river morphology in the Progo Basin. Land use change was assessed using Landsat time-series imagery (2002\u0026ndash;2022) processed in Google Earth Engine (GEE). A supervised classification approach, with training datasets from high-resolution aerial photography (Zurqani et al. \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), categorized land cover into agriculture, forest, built-up areas, and bare soil. By comparing classified maps across years, zones of LULC transformation were identified and overlaid with morphological change maps to evaluate spatial correspondence with channel evolution.\u003c/p\u003e\u003cp\u003eTo refine the analysis, NDVI thresholds detected vegetation loss in riparian corridors (50\u0026ndash;100 m buffers). Vegetation pixel values ranged from 0.312 to 1, while soil ranged from 0.0938 to 0.364. Year-to-year vegetation reduction was interpreted as anthropogenic disturbance linked to agriculture, quarrying, or urbanization. Field observations documented quarrying, sand mining, and construction, while semi-structured interviews provided insights on dam construction, irrigation, and cultural uses of the river. Literature sources triangulated these findings. To quantify anthropogenic impacts, linear regression models in SPSS and Excel linked NDVI-based vegetation loss with erosion/accretion rates. This analysis tested the hypothesis that reduced vegetation cover accelerates soil erosion and channel instability (Kayitesi et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e"},{"header":"Results and Discussion","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eThe river modeling\u003c/h2\u003e\u003cp\u003eThe CAESAR-Lisflood model of the Progo River is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. The model indicates almost no erosion in the upper reach (east), while erosion dominated the west side (yellow). After the confluence of two branches in the upper reach, deposition became dominant (green). This deposition likely came from sediment eroded from steeply sloped riverbanks, where deposition exceeded erosion. In the middle reach, erosion dominated, with deposition barely visible. The greater depth of the middle reach likely caused sediments to settle in deeper zones, remaining unseen at the surface. The lower reach experienced stronger erosion than the upper and middle reaches due to faster currents that eroded riverbanks, even though slopes were gentler. River meandering also intensified erosion in this section, while its depth limited deposition.\u003c/p\u003e\u003cp\u003eHowever, the model used only rainfall data and limited geological inputs (slopes and grain size), omitting lithology, geological structure, and anthropogenic activities. Human activities significantly affect river morphology, yet they are not represented. Therefore, the next step is to confirm the influence of geologic, climatic, and anthropogenic factors. GEE imagery can track yearly changes, while fieldwork helps validate the roles of lithology, structure, and human impacts on river morphology.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eThe impacts of geologic on the river morphological changes\u003c/h2\u003e\u003cp\u003eA survey of the Progo River\u0026rsquo;s morphology identified four key geological factors influencing changes: grain size, slope, geological structure, and lithology. A morphology change map (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) from GEE images comparing 2002 and 2022 was created to analyze these impacts. Over twenty years, erosion and accretion occurred across the upper, middle, and lower reaches. In the upper reach (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea), some sections on the west side were unclear in GEE images, making detection difficult. Overall, erosion and accretion were minor in the upper and parts of the middle reach (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea\u0026ndash;b) because the river shows little meander change. In contrast, the middle reach (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ec) displayed significant erosion and accretion, leading to meander shifts. The lower reach (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ed) experienced the greatest erosion, altering meander direction due to higher flow velocity. Variations in river stability across reaches are closely linked to geological factors, discussed below.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eGrain size impacts\u003c/h2\u003e\u003cp\u003eGrain size strongly influences river morphology along the Progo River. A grain-size distribution map with pie diagrams (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e) shows clear downstream fining: the upper reach is dominated by boulders and cobbles, the middle reach by pebbles and granules, and the lower reach by fine sediments from sand to clay. In the upper reach, andesitic boulders to pebbles are frequently deposited as mid-channel and point bars, largely sourced from volcanic eruptions. These coarse materials are transported downstream but accumulate before reaching the lower river. In the middle reach, smaller grains such as pebbles and granules dominate, carried farther by moderate currents. The lower reach contains predominantly fine sediments\u0026mdash;sand, silt, and clay\u0026mdash;easily eroded and redistributed by river flows. Here, deposition rarely forms stable bars, as fine sediments are continuously reworked. The dam in the middle reaches further limits the downstream movement of coarse material, while marine input adds complexity to sediment supply in the estuary.\u003c/p\u003e\u003cp\u003eWhen compared with morphological change maps, grain size distribution reveals a strong relationship with channel dynamics. In the upper reach, resistant bedrock combined with boulder- and cobble-sized sediments restricts change, as currents cannot easily mobilize such large particles, limiting erosion. The middle reach shows greater adjustments, with erosion of cut banks and transport of pebble-to-granule material visible in GEE imagery from the past two decades. These sediments are readily mobilized and deposited downstream. The lower reach exhibits the most dynamic changes, where frequent high flows erode and redeposit fine sediments, forming and removing mid-channel bars. This reflects both upstream sediment supply and downstream marine influences. Overall, the Progo River follows the principle of downstream fining\u0026mdash;coarse sediments upstream and finer sediments downstream\u0026mdash;though transitions are often abrupt, such as from medium gravel to medium sand. This reflects selective transport, abrasion, and sorting, with collisions increasing roundness and reducing particle size. Slope processes and tectonic activity also contribute to sediment refinement. Coarser particles stabilize channels, while finer sediments drive frequent morphological adjustments.\u003c/p\u003e\u003cp\u003eGrain-size data were quantified using Wolman pebble counts at two representative sites. Pie diagrams shows, at location b, in the upper reach, coarse particles dominated: \u0026gt;128 mm was 19%, 90\u0026ndash;128 mm was 29%, 64\u0026ndash;90 mm was 35%, 45\u0026ndash;64 mm was 17%, and \u0026lt;\u0026thinsp;45 mm was 0%, while the total grain size at location c: \u0026lt;11 mm was 71%, 11\u0026ndash;16 mm was 1%, 16\u0026ndash;22 mm was 7%, 22\u0026ndash;32 mm was 15%, 32\u0026ndash;45 mm was 5%, 45\u0026ndash;64 was 1%, and \u0026gt;\u0026thinsp;64 mm was 0%. This difference clearly illustrates the downstream fining trend. Larger particles at location b stabilize channels, limiting erosion (1.68 ha), while finer sediments at location c are easily mobilized, producing greater morphological change (2.85 ha). Thus, grain size is a key control on Progo River morphology: coarse sediments enhance channel stability upstream, while finer sediments downstream promote dynamic erosion and deposition.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003eSlope impacts\u003c/h2\u003e\u003cp\u003eSRTM DEM analysis and fieldwork revealed that the study area is dominated by very gentle (0\u0026ndash;8\u0026deg;) to gentle (8\u0026ndash;15\u0026deg;) slopes. Riverbanks in the upper and middle reaches (locations a\u0026ndash;d) mostly exhibit moderate (15\u0026ndash;25\u0026deg;) to high (25\u0026ndash;45\u0026deg;) slopes, while the lower reach (location e) is dominated by gentle slopes (8\u0026ndash;15\u0026deg;). When slope distribution (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e) was overlaid with the morphology change map, erosion was evident in both gentle and steep riverbanks, suggesting that slope alone cannot fully explain morphological change.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eIn the upper and middle reaches, high slopes coincide with resistant lithology. Bedrock-dominated banks restrict erosion, yet loose materials such as boulders and gravel from surface weathering and rockfall are common in catchments. These materials are delivered to the channel, supplying sediment that contributes to downstream accretion. In the lower reach, although slopes are gentler, sedimentary materials are less consolidated and highly erodible, especially during extreme rainfall. Such events may trigger large-scale erosional processes, producing significant sediment loads that shape downstream morphology (Ghimire \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The longitudinal profile of the Progo River further clarifies slope-morphology interactions. Elevation decreases sharply in the upper reach, dropping 37 m in the first 5 km (7.4 m per 1 km). Between 5 and 40 km, the decrease slows to 25 m per 10 km (2.5 m per 1 km). These steep upstream slopes promote erosion and material loss, but resistant bedrock reduces visible riverbank retreat. Instead, loose weathered material tends to accumulate in channels, partially stabilizing banks. Downstream, gentler slopes coincide with finer-grained lithology and broader drainage areas, conditions more favorable to sediment deposition.\u003c/p\u003e\u003cp\u003eThe relationship between channel slope, lithology, and drainage area aligns with the graded stream concept. Steeper slopes dominate near narrow headwater catchments where coarse lithologies prevail, while broader drainage areas downstream reduce channel slope and erosive potential (Baumann et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Negi et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Overall, slope strongly influences sediment supply: steep, resistant upstream banks provide coarse material through rockfall and weathering, whereas gentler, weaker downstream slopes contribute fine sediments through erosion. Together, these processes drive the continuous morphological adjustment of the Progo River.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003eGeological structure impacts\u003c/h2\u003e\u003cp\u003eA lineament map of the Progo River was created using DEM data (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). Geological structures were identified as linear and curved features, most of which occur in the upper reach, with fewer in the middle reach. A rose diagram indicated dominant NW\u0026ndash;SE and secondary N\u0026ndash;S orientations. These lineaments may correspond to major geological structures, escarpments, and topographic highs or lows (Chaabouni et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Field verification revealed a reverse fault at location a and zones of bedrock destruction at location b, both interpreted as traces of the Progo Fault in the western part of the river (Saputra et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). These structures originated from the Java tectonic trend that controlled the development of Kulon Progo Mountain (Syafri et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe lineament map was compared with morphology change data to evaluate structural control on the Progo River. In the upper reach, geological structures cut through bedrock, triggering rockfall and localized bank erosion. While GEE imagery confirms erosion, the resulting material also contributed to downstream sediment discharge and accretion. Although less extensive than in the lower reach, tectonic structures clearly shaped erosion and sedimentation patterns. Active tectonics deform the valley gradient, altering slope, meandering, and bedload transport to maintain equilibrium (Dar et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe longitudinal profile highlights deformation in the upper reach, where elevation dropped 37 m within the first 5 km (7.4 m/km), compared to the basin-wide average of 2.5 m/km. Such steepening suggests tectonic subsidence and uplift. Longitudinal profiles are reliable indicators of neotectonic deformation in earthquake-prone regions (Siddiqui \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Increased gradients enhance stream energy and bank erosion (Qureshi and Khan \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Although resistant lithology may limit surface erosion, tectonic subsidence promotes significant bank collapse, with loosened material infilling the channel. Knickpoints in the profile, often in volcanic breccias, further indicate structural control. Their occurrence without lithological contrasts supports tectonic influence rather than material resistance (Blanc et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003eLithology impacts\u003c/h2\u003e\u003cp\u003eSix locations in the study area were explored to identify the lithological characteristics of the outcrops at each site. Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents the lithological outcrop identifications in the study area.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eThe lithological outcrop identification in the study area\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLocation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLithological outcrop characteristics\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ea\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVolcanic breccia, basalt fragments with a boulder size, tuff matrices, slightly weathered, a thickness of 0.5 m\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eb\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVolcanic breccia, basalt fragments with a pebble size, tuff matrices, fresh, a thickness of 2 m\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ec\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIntercalated weathering-resistant volcanic breccia and tuff. Volcanic breccia in the upper part consists of basalt fragments with a pebble size, tuff matrices, slightly weathered, and a thickness of 0.5 m. The tuff in the center is slightly weathered and has a thickness of 0.3 m. Volcanic breccia at the bottom consists of basalt fragments with a granule size, tuff matrices, fresh, and a thickness of 0.8 m.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVolcanic breccia, basalt fragments with a pebble size, tuff matrices, slightly weathered, a thickness of 1 m\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ee\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLimestone, fresh, clastic, a thickness of 3 m,\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLimestone, slightly weathered, clastic, a thickness of 2 m\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLoose sedimentary materials with sand, silt, and clay materials, a thickness of 2 m\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eh\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLoose sedimentary materials with sand, silt, and clay materials, a thickness of 1 m\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe geological map with lithological distribution (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e) was overlaid with morphology change data to evaluate lithology\u0026rsquo;s role in controlling river morphology, particularly the resistance of riverbank materials to erosion. Lithological observations and petrographic analyses identified the main rock types. In the upper reach, erosion rates are low because volcanic breccia is highly resistant to weathering. At locations a and d, weathered breccia produces loose fragments from granules to boulders that are difficult to transport, resulting in relatively stable areas in GEE imagery. Resistant breccia also occurs at location b, while intercalated breccia and tuff appear at location c. These deposits, part of the Young Volcanic Deposits of Merapi Volcano, show limited erosion. In the middle reach, limestone of the Sentolo Formation is exposed (locations e and f), while the lower reach is dominated by loose sedimentary materials. Clastic limestone is more erodible than volcanic breccia. Limestone grains (1/16\u0026ndash;2 mm) are finer than breccia fragments (4\u0026ndash;\u0026gt;256 mm), which are harder for currents to mobilize. In addition, limestone dissolves readily in water, enhancing riverbank erosion (Chaigne et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Weakly compacted sediments in the lower reach are also highly erodible.\u003c/p\u003e\u003cp\u003eFor petrographic analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e), nine hand specimens were collected from six locations (a\u0026ndash;f) and classified following Schmid (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e1981\u003c/span\u003e), Streckeisen (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e1976\u003c/span\u003e), and Dunham and Ham (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e1962\u003c/span\u003e). Results show that volcanic breccias of the Merapi deposits stabilize the Progo Riverbed. While lithological contrasts influence morphology (Blanc et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), structural controls may better explain observed variations.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003ePetrographic observations revealed tuffs at locations a, b, c, and d, occurring as volcanic breccia matrices and single lithology. Schmidt (1981) classified these tuffs into three categories: crystal tuff at locations a and c (middle), vitric tuff at locations b and d, and lithic tuff at location c (top). Petrographic analysis shows that the crystal tuff at location a (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003ea) contains 2% quartz, 3% clinopyroxene, 50% feldspar, 40% volcanic glass, and 5% opaque minerals. The vitric tuff at location b (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003eb) contains 2% quartz, 2% orthopyroxene, 7% feldspar, 60% volcanic glass, 28% lithic fragments, and 1% opaque minerals. The lithic tuff at location c (top) (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003ec) contains 1% quartz, 2% orthopyroxene, 50% lithic fragments, 12% feldspar, 34% volcanic glass, and 1% opaque minerals. Meanwhile, the crystal tuff at location c (middle) (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003ed) contains 4% quartz, 4% clinopyroxene, 1% hornblende, 45% feldspar, 42% volcanic glass, and 4% opaque minerals.\u003c/p\u003e\u003cp\u003eUnlike most rocks, volcanic rocks form rapidly. Two main stages occur: the ejection of fragments during eruptions (tuffs) and the cooling or sedimentation of volcanic ash. Pyroclastic material, from fine sand to clay-sized ash and pumice, forms the tuff matrix. Rapid cooling results in incomplete crystallization, leaving sharp, angular fragments in a poorly consolidated matrix. This creates complex pore networks with distinct macro- and microporosities that strongly influence weathering (Wedekind et al. \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). High volcanic glass content further promotes alteration to zeolites and clays. Vitric tuffs typically show high porosity, large pores, and water absorption of 15\u0026ndash;31 wt%, whereas crystal tuffs have lower porosity, smaller pores, and absorption of 6\u0026ndash;16 wt%. Crystal tuffs also contain swelling clays and zeolites, reducing vapor permeability but increasing expansion. In the study area, volcanic breccia matrices show weathering, loosening fragments that accumulate in channels.\u003c/p\u003e\u003cp\u003ePlutonic rocks at locations b and c (bottom), occurring as volcanic breccia fragments, were classified as basalts following Streckeisen (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e1976\u003c/span\u003e). At location b (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003ee), basalt consists of quartz, 5% orthopyroxene, 3% opaque minerals, 45% plagioclase, 4% clinopyroxene, 23% groundmass, and 20% vesicles. At location c (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003ef), it contains 2% quartz, 55% plagioclase, 5% clinopyroxene, 2% orthopyroxene, 2% opaque minerals, and 34% groundmass. Compared with the matrix, volcanic breccia fragments are more resistant to erosion. When the matrix weathers, basalt clasts remain and accumulate in channels. These coarse, erosion-resistant fragments are difficult to transport, explaining the relative stability of channel and point bars in the upper reach as shown in GEE imagery. Erosion here is therefore limited mainly to weathering of the breccia matrix, while basalt persists in the channels. Limestone at locations e and f was petrographically classified, following Dunham and Ham (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e1962\u003c/span\u003e), as wackestone. At location e (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003eg), wackestone contains 2% quartz, 3% opaque minerals, 35% fossils, 1% glauconite, and 59% clay carbonate. At location f (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003eh), it consists of 2% quartz, 1% opaque minerals, 50% fossils, 4% glauconite, and 43% clay carbonate. Wackestone is mud-supported with \u0026gt;\u0026thinsp;10% bioclasts, fully cemented by lime mud, which prevents reservoir space development (Qi et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Carbonate grains float in lime mud, typically\u0026thinsp;\u0026gt;\u0026thinsp;20 microns in size (Smith \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Due to clay content, pressure-solution seams often form (Zepu et al. \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eClay carbonate minerals, acting as cement, occur abundantly in both samples, with authigenic minerals precipitating in pores and around grains during diagenesis. Detrital quartz and feldspar are commonly replaced by carbonate cement. Glauconite precipitates along grain surfaces or fractures and may fully replace feldspar, muscovite, or clays (Baiyegunhi et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). These limestones represent altered lithologies with significant mineral replacement. Evidence of advanced alteration at location f corresponds with greater weathering and erosion observed in the middle reach in GEE imagery.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003eThe impacts of climatic on the river morphological changes\u003c/h2\u003e\u003cp\u003eThree representative points of the study area were selected to analyze the impact of climate on river morphological changes (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003ea). Annual precipitation (2002\u0026ndash;2022) and riverbank erosion at each point were examined (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003eb). Regression analysis between annual precipitation and erosion produced p-values of 0.724 (upper reach), 0.704 (middle reach), and 0.983 (lower reach), with R\u0026sup2; values of 0.0067, 0.0078, and 0.00002, respectively. These results indicate a weak negative correlation between precipitation and riverbank erosion. High erosion events often occurred during years of low rainfall (e.g., 2011 in the upper reach, 2015 in the middle and lower reaches), while low erosion or net accretion coincided with higher rainfall (e.g., 2014 at all points). Overall, annual rainfall remained relatively stable, and its influence on erosion was not significant.\u003c/p\u003e\u003cp\u003eThe study area lacks extreme weather events such as typhoons, making rainfall variability a limited driver of morphological change. Several factors explain the weak correlation:(1) Annual precipitation does not always correspond to runoff or infiltration in the Progo River, as runoff characteristics determine erosion more than rainfall itself (Mart\u0026iacute;nez-Murillo et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2013\u003c/span\u003e); (2) heavy rainfall may weaken bank material, but erosion may only occur later when thresholds are exceeded, as in 2019 when erosion doubled despite reduced rainfall compared to 2018; (3) LULC strongly influences runoff, with forested areas contributing less sediment than bare land or settlements; and (4) rainfall partly influences erosion, but anthropogenic factors, such as quarrying and dam construction, play a larger role (Ferrier et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Prasetya et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In conclusion, climatic factors affect river morphology, but the Progo River shows limited direct response to precipitation, as anthropogenic and geological controls are more dominant.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003eThe impacts of anthropogenic activities on the river morphological changes\u003c/h2\u003e\u003cp\u003eAn anthropogenic map (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003e) illustrates human activities influencing Progo River morphology. Quarrying, dam construction, and LULC changes increase sediment supply to the channel, enhancing river accretion and altering morphological dynamics.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\u003ch2\u003eImpacts of quarrying activities\u003c/h2\u003e\u003cp\u003eThere is no definitive record of when quarrying began on the Progo River, though interviews with miners suggest activity since 1978. Current practices include large-scale extraction of boulders, gravel, and sand using heavy equipment, alongside small-scale community quarrying with simple tools, both legal and illegal. Interviews were conducted at two sites: location b represents small-scale quarrying, where workers extract gravel and sand manually, producing about 3 m\u0026sup3; per day (two trucks, 1.5 m\u0026sup3; each). Location c represents mechanized quarrying, with heavy equipment extracting up to 120 m\u0026sup3; daily (15 trucks, 8 m\u0026sup3; each). Morphological analysis (2018\u0026ndash;2022, Fig.\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e12\u003c/span\u003e) shows erosion at location b reached 0.18 ha, compared to 1.96 ha at location c, confirming that high extraction volumes cause greater riverbank erosion.\u003c/p\u003e\u003cp\u003eQuarrying alters river morphology in three main ways: (1) reducing sediment load, which lowers bed levels and disrupts transport; (2) altering grain-size distribution, as selective extraction of medium-to-coarse sand accelerates bed coarsening and erosion; and (3) steepening bed slopes, as quarry pits deepen channels, increasing velocity and localized erosion (Bhattacharya and Das Chatterjee \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Abandoned pits along riverbanks further contribute to long-term geomorphic instability.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec22\" class=\"Section2\"\u003e\u003ch2\u003eImpacts of dam construction\u003c/h2\u003e\u003cp\u003eConstructed between 2016 and 2018, Kamijoro Dam (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003ee) is located in the middle reach of the Progo River, providing irrigation for 2,370 ha and serving as a public space for recreation and sports (Kementerian PUPR \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). GEE images were used to analyze downstream morphology before, during, and after dam construction (Fig.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e13\u003c/span\u003e). In 2016, no construction was visible, serving as a baseline. By 2017, during the initial stage, accretion of 9.39 ha appeared downstream of the construction site. In 2018, at the final stage, accretion reached 8.02 ha. These changes were likely caused by sediment from land clearing, channel widening, and dredging activities. In 2019, after completion, no new accretion was observed; instead, erosion occurred at several points. Dams can trap large volumes of sediment, altering natural sediment transport and causing \u0026ldquo;hungry water\u0026rdquo; conditions downstream, which erode riverbeds and banks. Additionally, dams reduce flood peaks and modify flow characteristics, leading to significant morphological adjustments in downstream reaches of rivers (Vu et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv id=\"Sec23\" class=\"Section3\"\u003e\u003ch2\u003eImpacts of land use and land cover change\u003c/h2\u003e\u003cp\u003eThe NDVI of the Progo River was analyzed to assess the impacts of land use and land cover (LULC) on river morphology from 2002 to 2022. Figure\u0026nbsp;\u003cspan refid=\"Fig14\" class=\"InternalRef\"\u003e14\u003c/span\u003ea\u0026ndash;c shows NDVI maps for 2002 and 2022, vegetation\u0026ndash;erosion\u0026ndash;accretion trends, and regression results. Soil and vegetation pixel ranges were 0.0938\u0026ndash;0.364 and 0.312\u0026ndash;1, respectively. In 2002, bare and wet land dominated riverbanks, but by 2022 forests had become the main cover. Vegetation decline occurred in several years (2005, 2006, 2009, 2011, 2012, 2016, 2018, and 2019), influencing erosion and accretion (Fig.\u0026nbsp;\u003cspan refid=\"Fig14\" class=\"InternalRef\"\u003e14\u003c/span\u003eb).\u003c/p\u003e\u003cp\u003eRegression analysis indicated a strong positive correlation (R\u0026sup2; = 0.91, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) between vegetation cover, soil erosion, and river accretion (Fig.\u0026nbsp;\u003cspan refid=\"Fig14\" class=\"InternalRef\"\u003e14\u003c/span\u003ec). Increased vegetation reduced erosion and sediment discharge, while vegetation loss intensified channel erosion and deposition. Forests affect hydrology through evapotranspiration, infiltration, and root stabilization. Although afforestation may increase evapotranspiration and lower streamflow, forests generally enhance infiltration, recharge groundwater, stabilize banks, and reduce sediment loads. Streams in forested areas typically show greater stability, with broader, more stable channels, lower discharge, slower velocities, and reduced sediment input. Conversely, vegetation loss decreases infiltration, increases runoff, reduces baseflow, and accelerates peak flows, leading to higher flood volumes, sediment transport, and erosion risks. Forest root systems are essential for binding soil, reducing water deficits, and preventing small landslides, underscoring the critical role of vegetation in maintaining river stability (Kayitesi et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec24\" class=\"Section2\"\u003e\u003ch2\u003eA special event (the impacts of the Merapi Volcano eruption)\u003c/h2\u003e\u003cp\u003eVolcanic events during and after eruptions significantly impact nearby river systems. These impacts include high volcaniclastic sediment inflow, formation and collapse of natural dams, drainage disruptions, changes in slope gradients, lava dome collapse, surface roughness, mass wasting, alterations in channel geometry, and interruptions in river flow. The duration of fluvial system recovery or transition depends on the severity of these disruptions (O\u0026rsquo;Shea 2009; Dipayana et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Merapi Volcano, located upstream of the Progo River (Fig.\u0026nbsp;\u003cspan refid=\"Fig15\" class=\"InternalRef\"\u003e15\u003c/span\u003ea), erupted explosively in October 2010, the largest in over a century. Unlike the typical dome collapses that produce \u0026ldquo;Merapi-type\u0026rdquo; pyroclastic density currents, this eruption generated multiple explosions, ash columns rising to 17 km, and pyroclastic density currents reaching 16 km from the summit. Lava domes extruded at exceptionally high rates, up to 35 m\u0026sup3; s⁻\u0026sup1; (Jousset and Pallister \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Approximately 150\u0026nbsp;million m\u0026sup3; of volcanic material entered rivers draining the volcano, including the Progo River. This material triggered debris flows that caused major morphological changes, particularly in the middle and downstream reaches (Fitriadin et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eFollowing the eruption, the Progo River experienced both bed degradation and aggradation. Bed degradation was the main factor driving riverbank erosion (Harsanto \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). From April to July 2010, before the eruption, erosion and accretion measured 9.72 ha and 14.22 ha, respectively. From July 2010 to March 2011, erosion rose dramatically to 186.23 ha, while accretion decreased to 3.69 ha (Fig.\u0026nbsp;\u003cspan refid=\"Fig15\" class=\"InternalRef\"\u003e15\u003c/span\u003eb). Post-eruption, high discharges carrying debris flows eroded banks significantly, while much of the volcanic material was deposited in channels, filling degraded beds. Debris flows in the central slope altered hydraulic conditions, leading to localized degradation and aggradation. Downstream, sedimentation caused watergate clogging, while simulations suggest that continued sediment supply may reduce further bed degradation (Fitriadin et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv id=\"Sec25\" class=\"Section3\"\u003e\u003ch2\u003eThe timeline of the Progo River\u003c/h2\u003e\u003cp\u003eGeological factors influenced Progo River morphology over long timescales, while climatic factors were not the main drivers of change. In contrast, anthropogenic activities caused significant structural changes within short periods. The timeline (2002\u0026ndash;2022) highlights how each controlling factor shaped river morphology, as summarized in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eThe detailed timeline experienced by the Progo River from 2002 to 2022\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYear\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eControlling factors\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eProgo River\u0026rsquo;s conditions\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2002\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAnthropogenic activity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eQuarrying activities started in 1978 and continue to this day.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2005\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAnthropogenic activity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eLoss of vegetation has increased soil erosion and increased river accretion in the Progo River.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2010\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMerapi Volcano activity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eThe eruption of Merapi Volcano caused significant riverbank erosion in the Progo River.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2012\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAnthropogenic activity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eLoss of vegetation has increased soil erosion and increased river accretion in the Progo River.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2017\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAnthropogenic activity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDuring the initial stage of dam construction in the middle reach area of the Progo River, a significant amount of accretion occurred downstream of the area after the dam construction site due to sedimentary materials from land clearing\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2018\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAnthropogenic activity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eIn the final stage of dam construction, significant accretion occurred due to sedimentary materials from land clearing during dam construction.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2019\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAnthropogenic activity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eThe period after the dam construction was completed did not show any new accretion from the previous year; instead, erosion occurred at several points downstream after the dam construction.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2022\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAnthropogenic activity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eQuarrying activities from previous years resulted in erosion in several locations in the Progo River, both in the upper, middle, and lower reach areas.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eGEE images validated several results from river modeling, highlighting the role of geology in shaping morphology. Grain size and lithology explained the patterns: the upper reach showed minimal erosion due to coarse grains, resistant lithology, and bedrock, while pebble and granule deposits formed cut banks in the middle reach. In contrast, the lower reach, composed of loose sand to clay, was the most eroded section. Accretion was most evident after the confluence of two tributaries in the upper reach, where sediment input and transport increased. However, coarse grains were less mobile, causing localized deposition. Moderate to steep riverbank slopes further influenced erosion\u0026ndash;accretion dynamics. Annual erosion rates from GEE confirmed the dominance of low erosion (yellow), aligning with the model. Stable rainfall, without extreme events, also limited climatic drivers of erosion. Yet, unlike the model, GEE and fieldwork revealed significant accretion in the lower reach. This discrepancy stems from the model\u0026rsquo;s exclusion of lithology, human activities, and marine sediment input. Anthropogenic activities significantly alter the Progo River morphology through quarrying, dam construction, and land use/land cover (LULC) changes. Quarrying, both small- and large-scale, accelerates riverbank erosion, alters sediment load and grain size, and creates unstable pits. The Kamijoro Dam (2016\u0026ndash;2018) modified downstream morphology by trapping sediment, reducing flood peaks, and causing erosion from \u0026ldquo;hungry water\u0026rdquo; conditions. LULC analysis (2002\u0026ndash;2022) revealed strong correlations between vegetation cover, erosion, and accretion, with forested areas stabilizing banks and reducing sediment loads, while vegetation loss increased erosion and flood risk. Collectively, these activities drive long-term geomorphic instability. Overall, geology governs long-term processes, while anthropogenic activities accelerate rapid morphological changes in the Progo River.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAll authors contributed to the idea and design of the study. A.Z. wrote the first draft of the manuscript, F.I.G. created the CAESAR-Lisflood model of the Progo River, and the other authors provided feedback on it. All authors have read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe Southeast Asian Regional Center for Graduate Study and Research in Agriculture (SEARCA) and the Deutscher Akademischer Austauschdienst (DAAD) funded our research. We thank Muhammad Ginong Pratidhina, Dadi Fathoni Wibowo, Haris Nur Eka Prasetya, Ayu Atikha Reinaty, and Alan Prahutama for their technical assistance with this research. We also thank Dr. Jillian Aira Ratio for assessing the material before submission.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAlam AK, Islam MB (2017) Recent changes in Jadukata fan (Bangladesh) in response to Holocene tectonics. Quatern Int 462:226\u0026ndash;235. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.quaint.2017.08.014\u003c/span\u003e\u003cspan address=\"10.1016/j.quaint.2017.08.014\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAswathy MV, Vijith H, Satheesh R (2008) Factors influencing the sinuosity of Pannagon River, Kottayam, Kerala, India: An assessment using remote sensing and GIS. 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Int J Appl Earth Obs Geoinf 69:175\u0026ndash;185. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jag.2017.12.006\u003c/span\u003e\u003cspan address=\"10.1016/j.jag.2017.12.006\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"river morphology, river dynamics, human-river interaction, river characterization and monitoring","lastPublishedDoi":"10.21203/rs.3.rs-7415481/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7415481/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study investigates the geologic, climatic, and anthropogenic factors controlling morphological changes along the Progo River in Daerah Istimewa Yogyakarta (DIY), Indonesia. The CAESAR-Lisflood model was applied to assess the relative effects of climate and geology on watershed morphology and sediment discharge, with validation using Google Earth Engine (GEE). Datasets including GEE imagery, a geological map, Shuttle Radar Topography Mission Digital Elevation Model (SRTM DEM), field observations, and petrographic analysis were integrated to identify morphologic changes related to geological conditions. Comparison of GEE images from 2002 and 2022 produced a morphology change map that highlighted erosion and accretion zones over two decades. Normalized Difference Vegetation Index (NDVI) analysis, combined with rainfall data, was used to evaluate climatic impacts, while fieldwork and community interviews provided insights into human influences. Results indicate that lithology, geological structure, slope, and grain size strongly influence river morphology. Larger boulders and resistant bedrock limit erosion, whereas fine-grained and weakly consolidated sediments in lower reaches erode rapidly, especially under heavy rainfall. Limestone exhibits lower resistance to erosion than volcanic breccia. Annual precipitation data show no significant long-term trend, and seasonal variability could not be assessed, suggesting only a limited climatic role. Anthropogenic factors\u0026mdash;including dam construction, quarrying, and land use changes\u0026mdash;emerge as the most significant drivers of morphological change. Additionally, the 2010 eruption of Mount Merapi contributed large volumes of loose material, temporarily enhancing sediment transport. These findings underscore the combined but unequal influence of natural and human factors on river system dynamics.\u003c/p\u003e","manuscriptTitle":"An Investigation on the Geologic, climatic, and anthropogenic controls on the morphology of the Progo River, Indonesia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-01 10:08:19","doi":"10.21203/rs.3.rs-7415481/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"550bc12a-a243-428e-ab35-346b181464d9","owner":[],"postedDate":"October 1st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-10-31T20:53:22+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-01 10:08:19","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7415481","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7415481","identity":"rs-7415481","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}