Hydrological Processes最新文献

{"title":"Diagnosis of the Past, Present and Future Hydrology of a Glaciated High Mountain Headwater Basin in Central Asia","authors":"Okan Aygün,&nbsp;Zhihua He,&nbsp;Alain Pietroniro,&nbsp;John W. Pomeroy","doi":"10.1002/hyp.70283","DOIUrl":"https://doi.org/10.1002/hyp.70283","url":null,"abstract":"<p>This study used the Canadian physically based hydrological land surface scheme MESH for a comprehensive representation of high mountain hydrological processes such as glacier energy balance and ablation, blowing snow, energy balance snowmelt and frozen ground in Kyrgyzstan's partly glacierised basin Ala-Archa. Historical and future changes in the basin's hydrology were diagnosed through inter-comparisons of the hydrological processes in three periods of past (1961–1980), current (1991–2010) and future (2081–2100), with respect to the dynamics in climate and glacier coverage. Glacier maps from 1970 and 2000 were used for glacier configurations of the model in the past and present periods, respectively. Impacts of future glacier changes were evaluated through a static assumption to a fully retreated assumption. For historical and present simulations, the MESH model was forced by the EM-Earth (0.1°) and ERA-5 (0.25°) reanalysis data, whilst for the future simulation, monthly perturbations in temperature and precipitation were applied to the observations in 1991–2010 using the average delta changes derived from outcomes of an RCP 8.5 scenario in the CMIP5-AR5 subset (40 GCMs). Results show that the annual peak SWE has declined by 25% from the 1960s to the 2010s, whilst that in the future would show a much smaller decrease (5%). However, the timing of peak SWE in the 2100s is predicted to advance about 1 month and the snow cover duration to decline by 2 months in comparison to the 2010s. The timing of peak streamflow is expected to advance from July to June, and the annual and summer streamflow volume would decrease by 52% and 67%, respectively, under the fully retreated glacier assumption. These results underline the need for renewed diagnostic assessments of water supply in high mountain headwaters of Central Asia to inform adaptation to climate change.</p>","PeriodicalId":13189,"journal":{"name":"Hydrological Processes","volume":"39 10","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hyp.70283","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145228017","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Is Forest Change Confounding the Influence of Climate on Canada's Reference Hydrometric Network?","authors":"Jason A. Leach,&nbsp;Danielle T. Hudson,&nbsp;Joanne C. White,&nbsp;Txomin Hermosilla,&nbsp;Michael A. Wulder","doi":"10.1002/hyp.70274","DOIUrl":"https://doi.org/10.1002/hyp.70274","url":null,"abstract":"<p>Climate change is altering streamflow regimes with potential impacts to water resources, drinking water supply, and aquatic ecosystems. Monitoring hydrologic response to climate variability is crucial for informing effective management and adaptation strategies. In Canada, the Water Survey of Canada (WSC) maintains the Reference Hydrometric Basin Network (RHBN), a subset of gauged basins selected for their minimal human impacts and long streamflow records, which are routinely used for assessing hydrologic response to climate change. The WSC states that changes in forest cover, such as those caused by timber harvesting, were not considered in the selection of reference basins. However, changes in forest cover can have a profound influence on hydrologic processes and accounting for potential forest change could be important for identifying and drawing robust conclusions about climate change effects on streamflow regimes. We quantified the amount of stand-replacing forest change for 454 RHBN watersheds across Canada during the period of 1984–2019 and analysed whether forest change could have influenced long-term trends in annual water yield. Overall, these basins have seen an average change in percent forest cover of <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mo>±</mo>\u0000 </mrow>\u0000 <annotation>$$ pm $$</annotation>\u0000 </semantics></math>9% and some basins have experienced up to a <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mo>±</mo>\u0000 </mrow>\u0000 <annotation>$$ pm $$</annotation>\u0000 </semantics></math>50% change. For many basins included in the RHBN, variability and trends in annual water yield can be primarily accounted for by climate; however, we estimated that streamflow trends for as much as 15% of the watersheds may have been strongly influenced by forest change. Our results highlight that forest cover within many of the RHBN watersheds across Canada is more dynamic than was assumed when the reference basins were selected. These changes in forest cover may attenuate or amplify streamflow responses to climate change and must therefore be considered in tandem with climate change effects.</p>","PeriodicalId":13189,"journal":{"name":"Hydrological Processes","volume":"39 10","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hyp.70274","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145228098","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dissolved Phosphorus Leaching Reflects the Dynamic Interaction Between Hydrology and Soil Phosphorus Kinetics","authors":"Rose C. K. Mumbi,&nbsp;Mark R. Williams,&nbsp;William I. Ford,&nbsp;James J. Camberato,&nbsp;Chad J. Penn","doi":"10.1002/hyp.70285","DOIUrl":"https://doi.org/10.1002/hyp.70285","url":null,"abstract":"<div>\u0000 \u0000 <p>Hydrologic processes and soil phosphorus adsorption/desorption kinetics affect subsurface nutrient transport; however, their interaction is not well understood. In this study, we investigated the effect of hydrologic variables including flow rate, preferential flow, soil–water contact time, rainfall intensity, and soil moisture on dissolved reactive phosphorus (DRP) leaching. Ten undisturbed soil columns (30 × 30 × 30 cm) were collected from an agricultural field in Indiana, USA. Seven rainfall simulations were conducted under varying rainfall intensity and soil moisture conditions to create an array of subsurface flow rates. Results showed that leachate flow rates, preferential flow, soil–water contact time, and DRP concentration varied substantially among soil columns and rainfall simulations, with both connectivity and soil adsorption/desorption kinetics controlling DRP transport. Leachate comprised of either &gt; 90% or &lt; 10% event water had the lowest DRP flow-weighted mean concentration (FWMC; 0.12–0.85 mg L⁻¹). This suggests that minimal and maximum soil–water interaction yielded small DRP desorption from the surface soil and large DRP adsorption in subsoils, respectively. Leachate that was comprised of a mixture of water sources tended to have the greatest DRP FWMC (0.97–3.11 mg L⁻¹) resulting in a parabolic relationship between water source/soil contact time and DRP. Rainfall infiltration and interaction with surface soil promoted DRP desorption, with subsequent matrix-derived preferential flow facilitating the transport of DRP-rich water through the subsoil. Quantifying the connection between hydrology and phosphorus kinetics provides new insights into the impact of preferential flow on DRP leaching and is essential for predicting DRP transport and developing management practices for decreasing DRP loss.</p>\u0000 </div>","PeriodicalId":13189,"journal":{"name":"Hydrological Processes","volume":"39 10","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145228093","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modelling Electrical Conductivity Variation in the Intermittent, High-Salinity Scotts Creek Catchment, South-Eastern Australia Using a Travel Time Distribution Approach","authors":"Zahra Riazi,&nbsp;Andrew William Western","doi":"10.1002/hyp.70266","DOIUrl":"https://doi.org/10.1002/hyp.70266","url":null,"abstract":"<p>Focusing on water travel time as an important characteristic of water transport through a catchment provides an important underpinning for modelling of solute transport and water quality. This concentrates effort on a key catchment feature instead of trying to model all complexities. Past assessments of the travel time approach have focussed on relatively small perennial catchments and have not considered intermittent catchments. To address this gap, the Scotts Creek catchment in SW Victoria, Australia, was modelled. In this analysis, a 20-year, high-frequency electrical conductivity record was used to assess the performance of a travel time-based EC model. The EC data presents a complex pattern of response. Behaviour includes positive EC-discharge correlations early in the runoff season after flow commences and is still at very low discharge levels, while for the majority of the runoff season more typical dilution effects dominate. A time-variant StorAge Selection (SAS) function was applied within a modified version of the Tran-SAS. SAS function parameters were determined by selecting periods of time with consistent EC-discharge variations, reflecting probable changes in EC transport processes. EC concentration was modelled with an age-based concentration model. By varying the relationship between SAS function parameters and discharge under different flow conditions and including a high salinity source for part of the year, the simulation of complicated EC dynamics in Scotts Creek's catchment was improved, particularly for very low flow conditions. The effect of different patterns of interannual variability—either continuously dry or alternating dry and wet years—was explored, demonstrating that the hydroclimatological conditions in previous years affect EC response. The behaviour of simulated travel time distributions and residence time distributions for ten time points across the typical annual pattern of variation is also explored. The final outcomes present good consistency with the existing hydrogeological conceptual model of this catchment. An important learning is that EC appeared to behave non-conservatively in some parts of the year, and it is important to account for this when fitting the model.</p>","PeriodicalId":13189,"journal":{"name":"Hydrological Processes","volume":"39 9","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hyp.70266","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145146560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Machine Learning Approach for Snow Depth Estimation From Temperature Sensors","authors":"Madison Gunn,&nbsp;James S. Mills,&nbsp;Michael Mahoney,&nbsp;Colin Beier,&nbsp;Tao Wen,&nbsp;Samuel E. Tuttle","doi":"10.1002/hyp.70273","DOIUrl":"https://doi.org/10.1002/hyp.70273","url":null,"abstract":"<p>Snow is an effective, natural insulator and the differences in its internal temperature dynamics compared to soil and atmosphere allow for estimation of snow depth from snow temperature measurements. We use temperature sensor profiles to estimate snow depth for monitoring multiple winter seasons in a remote 1.3 km² (130 ha) forested watershed in the Adirondack Mountains, New York, United States. Vertical temperature sensor profiles were installed in a grid pattern in 2019 to monitor snow energy state and soil microclimate. Each profile consists of iButton temperature sensors enclosed in PVC pipe at 20 cm vertical spacing, of which eight profiles were paired with trail cameras and snow stakes for daily snow depth estimation starting in November 2021. An additional four temperature profiles with sensors exposed directly to the snow at 10 cm vertical sensor spacing were added in November 2022. We use photographs paired with temperature profiles to train random forest (RF) machine learning models to estimate snow depth from snow temperature profiles and landscape properties. Comparison of our RF model predictions versus camera-derived snow depths shows that we can accurately infer snow depth with a root mean squared error (RMSE) between 1.8 and 6.5 cm, which is lower than or comparable to existing methods. Our random forest method demonstrated effectiveness in an area with a shallow snowpack and frequent midwinter melt events, and showed little sensitivity to sensor mounting method, vertical sensor spacing, or time of day.</p>","PeriodicalId":13189,"journal":{"name":"Hydrological Processes","volume":"39 9","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hyp.70273","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145146281","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Complementary Precipitation Isotope Models Reveal Young and New Water Fractions in New Zealand Rivers","authors":"Bruce D. Dudley,&nbsp;Andy McKenzie,&nbsp;Jacob S. Diamond,&nbsp;Alice F. Hill","doi":"10.1002/hyp.70265","DOIUrl":"https://doi.org/10.1002/hyp.70265","url":null,"abstract":"<p>Improved knowledge of catchment transit times can enhance our understanding of hydrological and biogeochemical processes occurring in the subsurface, and thus prediction of catchment responses to land use and global change. However, a lack of suitable precipitation tracer data in many areas worldwide hinders transit time assessment at large spatial scales. We evaluated variation in young water fractions (F_yw—the fraction of streamflow less than 2.3 ± 0.8 months old) across 79 New Zealand catchments representing ~46% of New Zealand's total river discharge. F_yw was calculated using two precipitation isotope models: a seasonal kriging model and a machine learning model (PINZ) trained to predict seasonal and non-seasonal variation. We also used data from PINZ to estimate monthly new water fractions (F_new—the fraction of streamflow derived from precipitation that fell within the past month) using ensemble hydrograph separation. Our primary goal was to assess the reliability of the two precipitation isotope models for transit time estimation across New Zealand, where non-seasonal variation in precipitation stable isotope values is prominent in some regions. To evaluate whether F_yw and F_new derived from the two precipitation isotope models captured meaningful variation in catchment hydrology, we tested for consistency of their associations with two established predictors of storage in the subsurface: catchment geology and baseflow recession constants. Our results across all sites indicate that an average of 18% of river flow was younger than ~2.3 months, with 11% younger than 1 month. F_yw and F_new were similarly related to catchment geology and gradients of baseflow recession constants. Kriging provided more accurate F_yw estimates than PINZ, which tended to underestimate extreme precipitation isotope values, leading to overestimates of F_yw. However, the PINZ model offered reliable estimates of F_new when robust estimation was used to reduce the influence of outliers; this held for sites where seasonal cycles were poorly defined, highlighting the potential for machine learning precipitation isotope models to support transit time estimation in regions with weak seasonal isotope cycles (e.g., in tropical or marine climates).</p>","PeriodicalId":13189,"journal":{"name":"Hydrological Processes","volume":"39 9","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hyp.70265","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145101979","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Near-Surface Drying of a Continuous Permafrost Hillslope With Water Tracks Following Ground Collapse","authors":"Sarah G. Evans,&nbsp;Clara C. Chew,&nbsp;Sarah E. Godsey","doi":"10.1002/hyp.70269","DOIUrl":"https://doi.org/10.1002/hyp.70269","url":null,"abstract":"<p>Increasing air temperatures in the Arctic cause permafrost to thaw, releasing carbon dioxide and methane into the atmosphere. Carbon in thawing permafrost is released approximately three times more readily when soils are unsaturated versus saturated. Therefore, understanding if the Arctic is wetting or drying as permafrost thaws is crucial to predicting soil carbon emissions. In upland permafrost regions, near-surface soil moisture is influenced by unchannelized curvilinear zones of enhanced saturation known as water tracks. The ground underneath water tracks can collapse into thermoerosional gullies, altering their thaw depth and seasonal saturation. Water tracks and thermoerosional gullies frequently occur together on upland hillslopes but exhibit heterogeneous saturation dynamics. Thus, understanding saturation states in water tracks and gullies is crucial to predicting soil carbon emissions. In this study, we quantify saturation across water tracks and a gully and examine changes in near-surface saturation metrics over time by leveraging ~30 years of meteorological data and remotely sensed wetness indices from Landsat (1994–2023) and PlanetScope (2017–2023) imagery for a permafrost hillslope on the North Slope of Alaska, USA. Results suggest that the studied water tracks are drying following the ground collapse event, decreasing the overall saturated area proximal to the collapse, but that the water tracks still have relatively high mean Normalised Difference Water Index (NDWI) values for all rainfall magnitudes. Given the importance of soil saturation for predicting carbon emissions, the results of this work may provide tools for improving estimates of carbon release from thawing continuous permafrost hillslopes.</p>","PeriodicalId":13189,"journal":{"name":"Hydrological Processes","volume":"39 9","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hyp.70269","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145101615","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Predominant Role of Stochastic Processes in Bacterial Community Assembly Across Varied Hydrological Connectivity of Watershed Surface Water","authors":"X. D. Hu,&nbsp;Y. W. Deng,&nbsp;S. X. Yu,&nbsp;L. Wang,&nbsp;J. Q. Huang,&nbsp;W. Y. Huang,&nbsp;H. B. Xiao,&nbsp;J. Wang,&nbsp;Z. H. Shi","doi":"10.1002/hyp.70270","DOIUrl":"https://doi.org/10.1002/hyp.70270","url":null,"abstract":"<div>\u0000 \u0000 <p>Microbial community assembly processes are closely related to the composition, structure and distribution of microbes. The changes in environmental conditions and species dispersal capacity induced by hydrological connectivity may significantly impact the microbial community assembly process in surface water, but the mechanisms remain unclear. To reveal how hydrological connectivity affects microbial community assembly processes, surface water samples were collected from the study watershed during periods of low, intermediate and high hydrological connectivity. An integrated 16S rRNA amplicon sequencing technology and phylogenetic null model approach were used to identify the assembly processes of the bacterial communities. The results showed an inverse relationship between hydrological connectivity and environmental heterogeneity, with the highest environmental heterogeneity observed at low connectivity levels. Bacterial alpha diversity under high hydrological connectivity gradients significantly exceeded those under low and intermediate hydrological connectivity. Beta diversity exhibited a trend towards biotic homogenisation as hydrological connectivity increased. The co-occurrence network of bacterial communities under low hydrological connectivity was characterised by robust clustering and intricate interactions, whereas those under intermediate hydrological connectivity tended to form a more straightforward network. Furthermore, stochastic processes play a crucial role in bacterial community assembly, accounting for approximately 80% of the observed patterns. This was substantiated by piecewise structural equation modelling, which showed that environmental factors and biotic interactions exerted minimal influence on the bacterial community assembly. As hydrological connectivity increases, the assembly process shaping the bacterial community appears more stochastic. Moreover, the contributions of drift and heterogeneous selection in assembly processes were found to increase with hydrological connectivity, while the impact of dispersal limitation and homogeneous selection diminished. These insights provide a deeper understanding of the ecological mechanisms that govern microbial distribution patterns and succession in watershed surface water.</p>\u0000 </div>","PeriodicalId":13189,"journal":{"name":"Hydrological Processes","volume":"39 9","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145101614","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mapping and Modelling Specific Sediment Yield and Future Soil Erosion Trends in the Jhelum Catchment, India","authors":"Shahid Ul Islam,&nbsp;Ravi Raj,&nbsp;Epari Ritesh Patro,&nbsp;Manabendra Saharia,&nbsp;Sumedha Chakma","doi":"10.1002/hyp.70262","DOIUrl":"https://doi.org/10.1002/hyp.70262","url":null,"abstract":"<div>\u0000 \u0000 <p>Soil erosion management is a crucial component of sustainable soil and water management, especially in regions where agricultural productivity is at risk and areas that are more vulnerable to the impacts of climate change, such as the Himalayan region. This study explores soil erosion dynamics in the Jhelum Catchment, India, using advanced mapping and modelling techniques to analyse and predict trends of potential soil loss from 2020 to 2090. The study integrates the RUSLE model with projected climate to assess the impact of climate change on soil erosion and rainfall erosivity. The InVEST SDR model is used to quantify sediment transport and specific sediment yield, enhancing our understanding of the hydrological processes that drive soil erosion and sediment mobilisation in the Jhelum Catchment. The RUSLE, along with advanced climate modelling, land-use data, and spatial analysis, is used in this study to predict trends in soil erosion. Climate data from the Coupled Model Intercomparison Project Phase 6 (CMIP6) is combined with data from the India Meteorological Department (IMD) to project rainfall erosivity (<i>R</i>). <i>R</i>, along with soil erodibility (<i>K</i>), slope length and steepness (LS), land cover (<i>C</i>), and support practices (<i>P</i>) factors, are mapped and applied in the Revised Universal Soil Loss Equation (RUSLE) model, which evaluates the potential for soil erosion. This study forecasts soil loss trends by combining climate data, land-use information, and spatial analysis from 2020 to 2090 under two scenarios [SSP245 (moderate emissions) and SSP585 (high emissions)]. Results indicate escalating soil loss, particularly in less severe areas in 2020, highlighting the dynamic threat. The mean value of soil loss for SSP245 exhibits a continuous rise from 46.17 t/ha/year in 2030 to 51.54 t/ha/year in 2090. SSP585 shows a more severe trend, peaking at 71.67 t/ha/year in 2090. The study also classifies potential soil loss into severity classes, observing a decrease in the percentage area of less severe classes over time. Soil erosion class-wise projections from 2020 to 2090, based on LULC and soil type, reveal trends across various categories of land use, including Agriculture, Forest, Built-up Areas, and Grass/Grazing Land, as well as soil types like Cambisols, Lithosols, Glaciers, and Inland Water. These results highlight the urgent need for proactive interventions, offering practical insights for sustainable land management and providing actionable guidance for strategic planning and policy development focused on sustainable agricultural practices and climate change adaptation. This novel approach integrates advanced modelling and GIS-based analysis, making it applicable to other catchments with similar climate and land-use challenges. The study's findings directly apply to informing land management strategies, making the research highly relevant and practical.</p>\u0000 </div>","PeriodicalId":13189,"journal":{"name":"Hydrological Processes","volume":"39 9","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145101732","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Geospatial Assessment of Soil Erosion and Sedimentation Using RUSLE, AHP, and GIS","authors":"Manel Yakhlefoune,&nbsp;Chaouki Benabbas,&nbsp;Florina Grecu,&nbsp;Abdeldjalil Belkendil,&nbsp;Takki-Eddine Kharchi,&nbsp;Rebouh N. Yacer,&nbsp;Hela Elmannai,&nbsp;Aqil Tariq","doi":"10.1002/hyp.70263","DOIUrl":"https://doi.org/10.1002/hyp.70263","url":null,"abstract":"<div>\u0000 \u0000 <p>This study aims to assess and quantify soil erosion risk by integrating the Revised Universal Soil Loss Equation (RUSLE) with the Analytical Hierarchy Process (AHP) within a Geographic Information System (GIS) environment. The RUSLE model evaluates soil loss by combining five key factors: rainfall erosivity (R), soil erodibility (K), length of slope (LS), cover-management factor (C), and support practices factor (P). In parallel, the AHP framework incorporates nine geo-environmental parameters to refine the erosion hazard assessment through multi-criteria decision analysis. The integrated approach enables the generation of spatially explicit erosion risk maps, helping to identify vulnerable zones within the watershed. A primary focus of the study is the Dam, where sedimentation due to upstream erosion poses a critical threat. The outcomes of this research aim to inform soil conservation strategies and contribute to the sustainable management of a vital non-renewable resource, aligning with broader sustainable development goals (SDGs). The sediment delivery ratio (SDR) calculated shows that much soil will reach the basin and contribute to dam siltation. The final soil loss map established by the RUSLE model shows a maximum soil loss rate of 556.1 t ha⁻¹ year⁻¹ contributed over the entire watershed and an average of 49.77 t ha⁻¹ year⁻¹. The sediment delivery ratio is 0.53. A cross-section of different geo-environmental parameters shows that 37.51% of the watershed area is high to very highly vulnerable to erosion. The most dominant factors that take the maximum weight in the AHP matrix are the rainfall erosivity factor, the soil texture factor, the vegetation cover factor, and the slope.</p>\u0000 </div>","PeriodicalId":13189,"journal":{"name":"Hydrological Processes","volume":"39 9","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145101492","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}