Watershed Ecology and the Environment最新文献

{"title":"GIS and remote sensing based spatial analysis of dominant RUSLE factors and the corresponding influence on soil loss in Werie Agricultural Landscape: An agro-ecological approach","authors":"Abrha Asefa ,&nbsp;Mitiku Haile ,&nbsp;Melaku Berhe ,&nbsp;Amanuel Zenebe","doi":"10.1016/j.wsee.2026.01.001","DOIUrl":"10.1016/j.wsee.2026.01.001","url":null,"abstract":"<div><div>This study quantified the dominant soil erosion factors across in Werie Watershed. The study employed the Revised Universal Soil Loss Equation and Geographic Information System framework, and individual RUSLE factor<!--> <!-->were normalized. Zonal statistics were then applied to quantify area dominance across Agro-Ecological Zones. Finding revealed that mean soil loss was highest in Kolla at 22.83ton/ha/year, significantly exceeding Weina Dega (8.77 ton/ha/year) and Dega (7.64 ton/ha/year). Spatially, Rainfall Erosivity (R-factor) dominated the largest areas, covering 228.96 km² in Kolla (57.89%) and 1874.61 km² in Weina Dega (40.50%). Cover-Management (C-factor) was also dominating 161.77 km² in Kolla (40.90%) and 1410.73 km² in Weina Dega (30.48%). In Dega, Soil Erodibility (K-factor) was most prominent, dominating 143.30 km² (41.45%), while R-factor dominated 128.59 km² (37.19%). The Slope Length-Gradient (LS-factor) exhibited minimal areal dominance, covering 0.005 km² across all AEZs. However, the P-factor was not identified as a dominant factor in the watershed. Average normalized R-factor values were consistently high across all AEZs, ranging from 0.52 to 0.64. In contrast, K-factor averages remained very low ranging from 0.001 to 0.003. This study quantified the varying influences of erosion factors across AEZs and provided data-driven insights for designing tailored soil conservation strategies in Werie Watershed.</div></div>","PeriodicalId":101280,"journal":{"name":"Watershed Ecology and the Environment","volume":"8 ","pages":"Pages 142-153"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146172613","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Vegetation loss of the muni coastal lagoon: Implications for ecosystem services and climate impacts","authors":"Alexander Nii Adjei Sowah","doi":"10.1016/j.wsee.2025.07.002","DOIUrl":"10.1016/j.wsee.2025.07.002","url":null,"abstract":"<div><div>Coastal lagoons are highly productive ecosystems protected under laws of conservations. They provide extensive ecosystem services including fisheries, aquaculture, storm protection and tourism. In spite of the ecological, social, economic and cultural values of coastal lagoons, they suffer multiple pressures that threaten their ecological integrity and function. Population growth and its attendant increased demand for resources, expansion of the built environment to the fringes of such ecosystems and the production of waste are placing coastal lagoons’ ecosystems at the risk of collapse. Relying on Landsat satellite images of Land Cover of the Muni lagoon catchment of the Effutu Municipality of Ghana from 1993 to 2023 alongside field observations, the paper examines vegetation loss and land cover changes and how the observed changes influence/affects the lagoon’s ability to function and provide its ecological and socio-economic services. It was observed that apart from grassland which has steadily increased over the last three decades, marshes and mangroves have consistently reduced in size, from 21% of the total land cover in 1993 to 11% in 2003 and 10% in 2013 to 7% in 2023. A projected analysis of the different land cover for the next decade [2023–2033] indicated further shrinking of the mangrove and size of the lagoon itself. While the lagoon remains viable regarding some of the services it provides, losing mangroves, marshes and swamps have implications for the lagoon’s water holding capacity and ecosystem services it provides. This is especially against the backdrop of dangers posed to coastal communities by sea encroachment arising from climate-induced sea level rise.</div></div>","PeriodicalId":101280,"journal":{"name":"Watershed Ecology and the Environment","volume":"8 ","pages":"Pages 100-109"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145684502","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rejuvenation of Kalyani River, Uttar Pradesh (India): A Study using Geospatial Modeling","authors":"Akash Pal ,&nbsp;Neeraj Kumar ,&nbsp;Shakti Suryavanshi ,&nbsp;Krishan Tyagi ,&nbsp;Jagadeesh Menon ,&nbsp;Deepak Lal ,&nbsp;Arnab Kundu ,&nbsp;Neeraj Kumar Sharma ,&nbsp;Easterlily Shylla ,&nbsp;Mukesh Kumar","doi":"10.1016/j.wsee.2025.09.001","DOIUrl":"10.1016/j.wsee.2025.09.001","url":null,"abstract":"<div><div>Rivers play a crucial role in maintaining ecological balance and providing essential resources; however, many are facing significant degradation, particularly in India, where urbanization and population growth exacerbate water scarcity. This study focuses on the Kalyani River, located in Barabanki district, Uttar Pradesh (India), which spans approximately 69.65 km and is vital for local communities. We employed an integrated approach combining geospatial technology, the HEC-RAS (Hydrologic Engineering Centers-River Analysis System) model, and field verification to assess river conditions and identify restoration needs. Our analysis revealed critical challenges affecting the Kalyani River, including siltation and blockages that hinder flow and contribute to flooding. The results indicate a recommended excavation length of approximately 22.37 km in the Nindora block, along with a total cleaning length of around 47.28 km for both Nindora and Fatehpur blocks. These findings underscore the necessity for immediate eco-restoration efforts to rejuvenate the river ecosystem and mitigate the impacts of human-induced changes. Furthermore, we mapped critical zones requiring intervention, emphasizing the need for community engagement in conservation initiatives. This study highlights the importance of not only addressing the physical restoration of the river but also fostering long-term ecological health through sustainable management practices. By comparing our findings with established river restoration projects, we contextualize the significance of our approach to enhance the resilience of the Kalyani River. Ultimately, this research offers valuable insights and actionable recommendations that can aid local authorities and stakeholders in implementing effective river management strategies, contributing to improved water security and ecological sustainability in the region.</div></div>","PeriodicalId":101280,"journal":{"name":"Watershed Ecology and the Environment","volume":"8 ","pages":"Pages 13-22"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145222213","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing sediment-induced storage capacity loss in the Hisorak Reservoir, Uzbekistan","authors":"Khojiakbar Khasanov,&nbsp;Masharif Bakiev","doi":"10.1016/j.wsee.2025.10.004","DOIUrl":"10.1016/j.wsee.2025.10.004","url":null,"abstract":"<div><div>This study examines the long-term sedimentation dynamics and their impact on the storage capacity of the Hisorak Reservoir over 42 years (1980–2022). Sedimentation rates, capacity loss, and spatial volume changes were analyzed by comparing the original design data with bathymetric surveys conducted in 2003 and 2022. Four interpolation techniques—Inverse Distance Weighting (IDW), Radial Basis Function (RBF), Ordinary Kriging (OK), and Empirical Bayesian Kriging (EBK)—were applied to process bathymetric data and evaluated using RMSE, MAE, R², and SDpred. Among them, OK provided the highest accuracy (RMSE = 1.13, MAE = 0.008, R² = 0.996). The resulting spatial model enabled precise capacity calculations, showing a reduction of 39.4 Mm³ (23.2 %) in reservoir storage due to sedimentation. Between 2003 and 2022, sediment accumulated at an average rate of 0.88 Mm³ yr⁻¹, more than three times the design estimate of 0.272 Mm³ yr⁻¹. A Surface Difference Map revealed concentrated deposition in upstream zones and erosion along reservoir boundaries. These findings demonstrate that sedimentation is progressing faster than anticipated, causing accelerated storage loss. The study highlights the usefulness of geostatistical methods and surface difference analysis for assessing reservoir sedimentation and supports the development of more effective management and sediment-control strategies in arid-region reservoirs such as Hisorak.</div></div>","PeriodicalId":101280,"journal":{"name":"Watershed Ecology and the Environment","volume":"8 ","pages":"Pages 23-35"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145519502","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The structure, factors and analytical frameworks of microbial food webs in aquatic ecosystems","authors":"Yueyun Yang,&nbsp;Zhengzhu Dang,&nbsp;Guodong Ji","doi":"10.1016/j.wsee.2026.03.004","DOIUrl":"10.1016/j.wsee.2026.03.004","url":null,"abstract":"<div><div>Rivers and lakes are fundamental to global biogeochemical cycles and aquatic ecosystem stability. The health of these systems is largely governed by microbial food web (MFW) dynamics, which regulate energy transfer and nutrient cycling. However, existing methodologies remain largely descriptive, lacking the capacity to quantitatively link MFW structure to ecosystem function—a critical gap that limits predictive understanding of how these systems respond to environmental change. To address this gap, we propose an advanced analytical framework grounded in ecological trophic networks that integrates taxonomic identification, functional annotation, and trophic interaction inference. By explicitly reconstructing trophic architecture and quantifying energy flow pathways, this framework enables mechanistic assessment of material cycling and reveals how MFWs adapt along environmental gradients. This approach thus provides both a robust tool for aquatic ecosystem health assessment and a scientific basis for conservation and sustainable management strategies.</div></div>","PeriodicalId":101280,"journal":{"name":"Watershed Ecology and the Environment","volume":"8 ","pages":"Pages 208-220"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147797817","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Recent trends and future directions in artificial intelligence (AI) applications for coastal ecosystems Conservation: Insights from a bibliometric analysis","authors":"Sylvester T. Cortes","doi":"10.1016/j.wsee.2025.11.004","DOIUrl":"10.1016/j.wsee.2025.11.004","url":null,"abstract":"<div><div>Coastal ecosystems, such as mangroves, seagrass beds, and coral reefs, provide essential ecological, economic, and social services. However, their capacity to deliver these services is diminishing due to increasing ecosystem disturbances, resource exploitation, and the impacts of climate change. In response, the integration of artificial intelligence (AI) tools into conservation efforts has led to a surge in scholarly publications, highlighting the need for a bibliometric analysis to systematically examine emerging trends and identify future directions in this rapidly evolving and interdisciplinary field. Bibliometric data were sourced from the Scopus database, covering a ten-year period from 2015 to June 2025. The analysis was conducted using Bibliometrix and VOSviewer, complemented by OpenRefine, Microsoft Excel, RStudio, and OriginPro for data cleaning and visualization. Results revealed an annual publication growth rate of 6.61% in the field. The institutions from China and the United States are at the forefront of research outputs and international collaborations, indicating their strong investment and leadership in the application of AI to coastal ecosystem conservation. Keyword co-occurrence analysis identified thematic clusters around AI tools such as remote sensing, machine learning, and deep learning, highlighting a transition from traditional environmental sensing toward real-time monitoring and predictive modeling. There is also a growing presence of multiple countries based on the keyword co-occurrence networks. It indicates increasing global participation, collaboration, and interest in applying AI to ecosystem conservation. Collectively, these findings point to a maturing research landscape with a promising trajectory toward the development of globally adaptive conservation strategies driven by artificial intelligence.</div></div>","PeriodicalId":101280,"journal":{"name":"Watershed Ecology and the Environment","volume":"8 ","pages":"Pages 88-99"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145684500","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sectoral divergences in industrial effluent quality and risk in Bangladesh: Insights from tobacco and non-tobacco industries","authors":"Anupam Roy ,&nbsp;Md. Golam Mostafa","doi":"10.1016/j.wsee.2026.04.001","DOIUrl":"10.1016/j.wsee.2026.04.001","url":null,"abstract":"<div><div>This study presents the first comparative assessment of tobacco and non-tobacco industrial effluents in Bangladesh, emphasizing irrigation potential and ecological risks (<em>ER</em>) through multi-index evaluations. Eighteen tobacco effluents were analyzed for twenty-eight physicochemical, ionic, and heavy metal (HM) parameters, while secondary raw data from published articles were analyzed for major non-tobacco Bangladeshi industries. Results revealed clear sectoral divergences. Tannery effluents were the most hazardous, exceeding limits for nearly all parameters, whereas tobacco showed moderate pollution. Across industries, turbidity, total suspended solids, biochemical/chemical oxygen demand, K⁺, NO₃-N, and PO₄-P were key drivers of effluent degradation. Sodium hazards were confined to the tannery and sugar. HM analysis identified tannery as the dominant Cr polluter and tobacco with elevated Cd. FTIR Spectroscopy of tobacco effluents revealed diverse organic and metal-linked compounds. The Water Quality Index rated all effluents very poor. The Water Health Index classified tannery and textile-dyeing as extremely poor, while tobacco and most others were comparatively better. HM Pollution and <em>ER</em> Indices illustrated tannery, textile-dyeing, and pharmaceutical as high-risk due to Cr, Cd, Pb, and Mn. These findings highlight both risks and opportunities for nutrient-rich effluent reuse, offering a pollution ranking framework to guide targeted treatment, sustainable irrigation, and ecosystem protection.</div></div>","PeriodicalId":101280,"journal":{"name":"Watershed Ecology and the Environment","volume":"8 ","pages":"Pages 221-238"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147797813","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quantifying ecosystem services and analyzing trade-offs under a rapid land cover change: the case of Northwestern Ethiopian Highlands","authors":"Temesgen Bogale ,&nbsp;Shimeles Damene ,&nbsp;Assefa Seyoum ,&nbsp;Nigussie Haregeweyn","doi":"10.1016/j.wsee.2026.02.001","DOIUrl":"10.1016/j.wsee.2026.02.001","url":null,"abstract":"<div><div>Rapid land use/land cover (LULC) change in the Northwestern Ethiopian Highlands is intensifying pressures on ecosystem services. However, empirical evidence on the magnitude and nature of trade-offs among these services remains limited. This study aimed at quantifying and valuing ecosystem services and their trade-offs associated with high-intensity LULC change between 2010 and 2020, to provide insights for sustainable land management. We applied the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model to assess carbon storage, sediment retention, seasonal water yield, crop yield, and plantation revenue. Rigorous data processing steps such as watershed delineation, image preprocessing, land use classification, accuracy validation and trade-offs analysis were undertaken. Changes in ecosystem services were valued in terms of net present values to facilitate comparison across services and among watersheds by using a common unit of account −USD. LULC change was dominated by a 297% expansion of plantation forests, accompanied by an increase in carbon stock (39.57 to 45.93 t ha⁻¹). In contrast, sediment retention declined from 68.32 to 48.63 t ha⁻¹ yr⁻¹, and seasonal water yield decreased by 9.8%. Meanwhile, annual gross-margin from crop yields rose by 39.7%, and plantation income more than tripled. The net present value of ecosystem service changes included USD 4.27 million from carbon storage, USD 27.92 million from avoided dredging costs, and USD 78.99 million from crop production. Trade-offs were observed between crop yield and regulating services, while synergies occurred between plantation income and carbon sequestration. High-intensity LULC change improves provisioning services at the expense of regulating services. However, balanced land allocation, as observed in Timble watershed, can reduce trade-offs and even create synergies among services. The findings offer actionable evidence for policymakers and land managers to design strategies that balance agricultural production with long-term ecosystem sustainability.</div></div>","PeriodicalId":101280,"journal":{"name":"Watershed Ecology and the Environment","volume":"8 ","pages":"Pages 154-173"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147649930","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A systematic review of flood prediction (2018–2025): Flood categories, input features, and Machine Learning, Deep Learning and hybrid approaches","authors":"Saif Tasnim Chowdhury ,&nbsp;Farzana Yasmin ,&nbsp;Most Mahbuba Pervin Tanni ,&nbsp;Mizanur Rahman ,&nbsp;Hasan Sarwar ,&nbsp;Ting Tin Tin","doi":"10.1016/j.wsee.2026.03.002","DOIUrl":"10.1016/j.wsee.2026.03.002","url":null,"abstract":"<div><div>Floods continue to pose a significant global threat, resulting in substantial human, infrastructural, and economic losses each year. Although floods cannot be entirely prevented, advancements in modern technologies, particularly data-driven approaches, offer significant potential to mitigate their impacts through accurate prediction. This paper conducts a <em>Systematic Literature Review (SLR)</em> of flood prediction research published between 2018 and 2025. The review focuses on four primary aspects: (1) the classification and geographical distribution of different flood types; (2) the key hydrological, meteorological, and geographical parameters utilized in flood prediction; (3) the range of innovative technologies applied, including traditional statistical approach, Machine Learning (ML), Deep Learning (DL), and hybrid models; and (4) the challenges associated with training ML models using historical and geographical datasets. The findings reveal a clear trend toward the adoption of advanced ML and ensemble-based methods due to their improved prediction accuracy and adaptability across diverse geographical contexts. The review also emphasizes the critical role of feature selection in enhancing model performance and highlights the growing importance of integrating real-time data streams for timely flood forecasting. Despite the progress, significant challenges persist, particularly the scarcity of comprehensive historical datasets in many regions, which affects model generalizability and robustness. This paper outlines potential future research directions, including leveraging transfer learning, data augmentation, and integrating heterogeneous data sources to develop more reliable and context-aware flood prediction systems.</div></div>","PeriodicalId":101280,"journal":{"name":"Watershed Ecology and the Environment","volume":"8 ","pages":"Pages 185-207"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147649937","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Examining the role of Indonesian major fishing ports on contributing to ocean macroplastic pollution","authors":"Tri Yuwono ,&nbsp;Mutiara Rachmat Putri ,&nbsp;Susanna Nurdjaman ,&nbsp;Sakti Wahyu Trenggono ,&nbsp;Kamaluddin Kasim","doi":"10.1016/j.wsee.2025.03.001","DOIUrl":"10.1016/j.wsee.2025.03.001","url":null,"abstract":"<div><div>Plastic pollution in marine environments remains a critical global challenge, with Indonesia playing a significant role due to its extensive fisheries sector. Fishing ports contribute substantially to this issue through waste generated from vessel operations, fish processing, port activities, and riverine pollution. This study examines macro plastic waste production and its sources at four major Indonesian fishing ports—PPS Nizam Zachman (Jakarta), PPN Cilacap, PPN Kejawanan (Cirebon), and PPN Sibolga (North Sumatra)—by integrating field surveys and stakeholder discussions. The results indicate that plastic waste generation varies significantly across ports, with PPS Nizam Zachman producing the highest amount at an average of 700 kg per month, followed by PPN Cilacap (170 kg) and PPN Kejawanan (72 kg). Additionally, riverine plastic pollution plays a critical role in plastic accumulation, particularly at ports near urban river systems. Despite existing regulatory frameworks, including MMAF Decree No. 130 of 2023, challenges persist in waste management due to financial constraints, weak enforcement, and inadequate infrastructure. Based on the research findings, the most effective strategies for mitigating plastic pollution at fishing ports include expanding and institutionalizing waste retrieval programs by linking vessel permits (Surat Layak Operasi/SLO) to waste management compliance, improving waste management infrastructure through public–private partnerships, and strengthening multi-stakeholder collaboration among port authorities, regulatory bodies, and local governments. Additionally, integrating riverine waste management into coastal strategies—such as installing floating trash barriers and enhancing upstream waste collection—is crucial to reducing plastic influx into fishing ports. Community engagement and education initiatives, including waste bank programs and awareness campaigns targeting fishers and port workers, are also essential for long-term sustainability. The findings emphasize the urgent need for an integrated waste management system that aligns regulatory enforcement, infrastructure development, and community participation to promote sustainability in Indonesia’s fisheries sector. Addressing these challenges through coordinated government and stakeholder action is paramount to reducing plastic waste leakage into the marine environment and ensuring long-term ecological and economic sustainability.</div></div>","PeriodicalId":101280,"journal":{"name":"Watershed Ecology and the Environment","volume":"7 ","pages":"Pages 74-83"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143600162","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}