Lakes are essential components of ecosystems and serve as important indicators of climate change and human impact. This study employed historical remote sensing images and geospatial analysis to examine the dynamics of three significant wetlands (Phewa, Begnas, and Rupa lakes) in the Pokhara Valley of Nepal, which are designated as Ramsar sites. Changes in land use land cover (LULC) and soil erosion within the watersheds of these lakes were also monitored using Landsat images and soil erosion dataset, respectively. Additionally, climatic trends in the Pokhara Valley were analyzed using data from ground-based monitoring stations. The results highlight a notable 11.39 % decline in the surface area of Phewa Lake since 1989, while the surface areas of Begnas and Rupa have remained relatively stable. Changes in LULC show an increase in forest cover (+47 to 64 %) and decrease in croplands (−36 to 59 %) across all watersheds. Urbanization is most pronounced in the Phewa watershed, leading to increased pollution and shoreline encroachment. The decline in cropland may improve water quality by decreasing agricultural runoff. However, soil erosion is most severe in cropland areas, resulting in Phewa lake receiving the highest sediment influx among the three lakes. The lake regions have been experiencing changes in temperature (0.3 °C per decade) and rainfall (insignificant slight increase). Changes in these lakes are primarily driven by watershed dynamics and human activities. These results underscore the necessity for integrated watershed management and further in-depth investigation into the effects of climate change on these ecosystems for regional sustainability.
{"title":"Geospatial analysis of wetland dynamics and watershed monitoring in Pokhara Valley, Nepal","authors":"Krishna Prasad Sigdel , Narayan Prasad Ghimire , Binod Dawadi","doi":"10.1016/j.wsee.2025.06.001","DOIUrl":"10.1016/j.wsee.2025.06.001","url":null,"abstract":"<div><div>Lakes are essential components of ecosystems and serve as important indicators of climate change and human impact. This study employed historical remote sensing images and geospatial analysis to examine the dynamics of three significant wetlands (Phewa, Begnas, and Rupa lakes) in the Pokhara Valley of Nepal, which are designated as Ramsar sites. Changes in land use land cover (LULC) and soil erosion within the watersheds of these lakes were also monitored using Landsat images and soil erosion dataset, respectively. Additionally, climatic trends in the Pokhara Valley were analyzed using data from ground-based monitoring stations. The results highlight a notable 11.39 % decline in the surface area of Phewa Lake since 1989, while the surface areas of Begnas and Rupa have remained relatively stable. Changes in LULC show an increase in forest cover (+47 to 64 %) and decrease in croplands (−36 to 59 %) across all watersheds. Urbanization is most pronounced in the Phewa watershed, leading to increased pollution and shoreline encroachment. The decline in cropland may improve water quality by decreasing agricultural runoff. However, soil erosion is most severe in cropland areas, resulting in Phewa lake receiving the highest sediment influx among the three lakes. The lake regions have been experiencing changes in temperature (0.3 °C per decade) and rainfall (insignificant slight increase). Changes in these lakes are primarily driven by watershed dynamics and human activities. These results underscore the necessity for integrated watershed management and further in-depth investigation into the effects of climate change on these ecosystems for regional sustainability.</div></div>","PeriodicalId":101280,"journal":{"name":"Watershed Ecology and the Environment","volume":"7 ","pages":"Pages 287-298"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144270051","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}
In India, 51 % of the net sown area relies on rainfed agriculture, with 40 % of landholdings unirrigated and 13 % partially irrigated. Rainfed farming produces 40 % of food grains and supports two-thirds of the livestock population but faces challenges like land degradation, low productivity, and biodiversity loss due to erratic monsoons and extreme weather. Additionally, India’s water scarcity is worsening, with per capita availability expected to reduce from 802 cubic meters in 2022 to 677 cubic meters by 2050. Therefore, to meet the diverse food requirements of the burgeoning population of the country, conservation of natural resources, and improving the living standard of the resource-poor small and marginal farmers is imperative. Integrated watershed management (IWM) has emerged as a climate-smart strategy to address these challenges by enhancing soil and water conservation, agricultural productivity, and livelihoods in dryland systems. This study assesses the impact of IWM on dryland agriculture in India by analyzing various interventions such as in-situ and ex-situ water conservation, soil health management, and the use of modern technologies like remote sensing (RS) and geographic information systems (GIS). The results revealed that the adoption of IWM practices has led to significant improvements in soil moisture retention (20–25 %), soil organic carbon (22–32 %) agricultural productivity (30–45 %), and water use efficiency (15–25 %). Additionally, soil conservation techniques have reduced soil loss and runoff by 25–50 % and 50–60 %, respectively. Furthermore, the cultivation of lemon grass (Cymbopogon flexuosus), anjan grass (Cenchrus ciliaris), and bamboo (Bambusa spp.) could be the nature-based solutions for mitigating the impact of climate change due to their soil binding capacity and carbon sequestration potential. Moreover, this review indicates the potential of fast-growing trees (Melia dubia) under the agroforestry system in enhancing carbon sequestration by >100 % over sole cultivation. These results demonstrate that IWM is a sustainable solution to mitigate the adverse effects of climate change on dryland farming systems and improve rural livelihoods. Further, the study suggests that IWM practices helps to achieve sustainable development goals (SDGs) such as zero hunger, no poverty, and climate action etc., particularly in the face of climate change in water-scarce regions.
{"title":"Integrated watershed management for transforming dryland livelihoods: A climate-smart strategy for sustainable dryland agriculture in India","authors":"Ram A. Jat , Dinesh Jinger , Anita Kumawat , Saswat Kumar Kar , Indu Rawat , Suresh Kumar , Venkatesh Paramesh , Vijay Singh Meena , Rajesh Kaushal , Kuldeep Kumar , Hari Singh Meena , S.P. Wani , Rajbir Singh , M. Madhu","doi":"10.1016/j.wsee.2025.03.006","DOIUrl":"10.1016/j.wsee.2025.03.006","url":null,"abstract":"<div><div>In India, 51 % of the net sown area relies on rainfed agriculture, with 40 % of landholdings unirrigated and 13 % partially irrigated. Rainfed farming produces 40 % of food grains and supports two-thirds of the livestock population but faces challenges like land degradation, low productivity, and biodiversity loss due to erratic monsoons and extreme weather. Additionally, India’s water scarcity is worsening, with per capita availability expected to reduce from 802 cubic meters in 2022 to 677 cubic meters by 2050. Therefore, to meet the diverse food requirements of the burgeoning population of the country, conservation of natural resources, and improving the living standard of the resource-poor small and marginal farmers is imperative. Integrated watershed management (IWM) has emerged as a climate-smart strategy to address these challenges by enhancing soil and water conservation, agricultural productivity, and livelihoods in dryland systems. This study assesses the impact of IWM on dryland agriculture in India by analyzing various interventions such as <em>in-situ</em> and <em>ex-situ</em> water conservation, soil health management, and the use of modern technologies like remote sensing (RS) and geographic information systems (GIS). The results revealed that the adoption of IWM practices has led to significant improvements in soil moisture retention (20–25 %), soil organic carbon (22–32 %) agricultural productivity (30–45 %), and water use efficiency (15–25 %). Additionally, soil conservation techniques have reduced soil loss and runoff by 25–50 % and 50–60 %, respectively. Furthermore, the cultivation of lemon grass (<em>Cymbopogon flexuosus</em>), anjan grass (<em>Cenchrus ciliaris</em>), and bamboo (<em>Bambusa spp</em>.) could be the nature-based solutions for mitigating the impact of climate change due to their soil binding capacity and carbon sequestration potential. Moreover, this review indicates the potential of fast-growing trees (<em>Melia dubia</em>) under the agroforestry system in enhancing carbon sequestration by >100 % over sole cultivation. These results demonstrate that IWM is a sustainable solution to mitigate the adverse effects of climate change on dryland farming systems and improve rural livelihoods. Further, the study suggests that IWM practices helps to achieve sustainable development goals (SDGs) such as zero hunger, no poverty, and climate action etc., particularly in the face of climate change in water-scarce regions.</div></div>","PeriodicalId":101280,"journal":{"name":"Watershed Ecology and the Environment","volume":"7 ","pages":"Pages 159-177"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143816974","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}
Understanding hydrochemistry and diatom assemblage is important for assessing the health of aquatic ecosystems. This study has analyzed the water quality and diatom communities in the Dordi River, which is one of the major tributaries of the Marsyangdi River in Nepal. The primary research question being addressed in the study was what is the state of water quality parameters of Dordi River and how do they relate to the distribution and composition of diatoms. The water quality parameters of the river like temperature, pH, electric conductivity (EC), total dissolved solids (TDS), dissolved oxygen (DO), turbidity, and total alkalinity (TA) were measured in-situ, whereas concentrations of major ions (Ca2+, Mg2+, K+, Na+, NH4+, HCO3–, Cl–, SO42–, NO3–, and PO43–), biological oxygen demand (BOD) and chemical oxygen demand (COD) were analyzed in the laboratory by collecting water samples from different parts of the river. Piper plot, Gibbs plot, Mixing plots, redundancy analysis, and principal component analysis were applied for evaluating the spatial variation of anions and cations in water. The results showed alkaline water following the pattern: Ca2+>Mg2+>Na+>K+>NH4+ for cation and HCO3–>Cl–>SO42–>PO43–>NO3– for anion with calcium-bicarbonate dominant lithology in the river. Overall, the results highlight that the drinking and irrigation water qualities of the river were found to be excellent. Additionally, among 75 diatom species observed in the samples, the Bacillariophyceae was the dominant class covering 92% of the species. The results indicated that the diatom species richness declined as elevation increased. The distribution of diatoms was also influenced by the land use types near the water sampling points, tributaries and the main river. Overall, the physico-chemical quality of water showed significant influence on diatom species composition. The findings of this study could be useful for understanding hydrochemistry and association of water quality and diatoms in river basins of the Himalaya.
{"title":"Hydrochemical characteristics, water quality and diatom assemblage in Dordi River, Nepal","authors":"Punam Phuyal , Shraddha Ranabhat , Sanjal Khatri , Nabin Lamichhane , Ramesh Raj Pant , Lal Bahadur Thapa , Ram Kailash Prasad Yadav","doi":"10.1016/j.wsee.2024.12.002","DOIUrl":"10.1016/j.wsee.2024.12.002","url":null,"abstract":"<div><div>Understanding hydrochemistry and diatom assemblage is important for assessing the health of aquatic ecosystems. This study has analyzed the water quality and diatom communities in the Dordi River, which is one of the major tributaries of the Marsyangdi River in Nepal. The primary research question being addressed in the study was what is the state of water quality parameters of Dordi River and how do they relate to the distribution and composition of diatoms. The water quality parameters of the river like temperature, pH, electric conductivity (EC), total dissolved solids (TDS), dissolved oxygen (DO), turbidity, and total alkalinity (TA) were measured <em>in-situ</em>, whereas concentrations of major ions (Ca<sup>2+</sup>, Mg<sup>2+</sup>, K<sup>+</sup>, Na<sup>+</sup>, NH<sub>4</sub><sup>+</sup>, HCO<sub>3</sub><sup>–</sup>, Cl<sup>–</sup>, SO<sub>4</sub><sup>2–</sup>, NO<sub>3</sub><sup>–</sup>, and PO<sub>4</sub><sup>3–</sup>), biological oxygen demand (BOD) and chemical oxygen demand (COD) were analyzed in the laboratory by collecting water samples from different parts of the river. Piper plot, Gibbs plot, Mixing plots, redundancy analysis, and principal component analysis were applied for evaluating the spatial variation of anions and cations in water. The results showed alkaline water following the pattern: Ca<sup>2+</sup>>Mg<sup>2+</sup>>Na<sup>+</sup>>K<sup>+</sup>>NH<sub>4</sub><sup>+</sup> for cation and HCO<sub>3</sub><sup>–</sup>>Cl<sup>–</sup>>SO<sub>4</sub><sup>2–</sup>>PO<sub>4</sub><sup>3–</sup>>NO<sub>3</sub><sup>–</sup> for anion with calcium-bicarbonate dominant lithology in the river. Overall, the results highlight that the drinking and irrigation water qualities of the river were found to be excellent. Additionally, among 75 diatom species observed in the samples, the Bacillariophyceae was the dominant class covering 92% of the species. The results indicated that the diatom species richness declined as elevation increased. The distribution of diatoms was also influenced by the land use types near the water sampling points, tributaries and the main river. Overall, the physico-chemical quality of water showed significant influence on diatom species composition. The findings of this study could be useful for understanding hydrochemistry and association of water quality and diatoms in river basins of the Himalaya.</div></div>","PeriodicalId":101280,"journal":{"name":"Watershed Ecology and the Environment","volume":"7 ","pages":"Pages 23-35"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143158894","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}
Pub Date : 2025-01-01DOI: 10.1016/j.wsee.2025.08.002
Samira Kaddouri , Younes EL Kharim , Kamal Agharroud , Ali Bounab , Youssef El Miloudi , Reda Sahrane , Ahmed Taoufik Ouahabi
The morphology, distribution, and structural control of karst closed depressions in a dolomitic karst landscape are the focus of this study. The study area is the Jbel Dersa Massif (JDM), part of the “Dorsale Calcaire” (DC) unit within the Rif Mountain range in northern Morocco. A combined analysis of geomorphological mapping and structural studies reveal that the Pliocene dismantling phase smoothed the crests of the original imbricate thrust fronts, characteristic feature of the DC unit’s structure. The flattening of the massif’s summit facilitated the dissolution of the rock surface. In addition to the massif’s ruiniform landscape, the observed karstic features include fracture lapies, closed karstic depressions at the summit, and travertine deposits along the structural contacts with the bordering non-karstic units. The 26 identified closed depressions are dissolution dolines. Morphometric analysis indicates that these dolines are primarily located in the endorheic and axial zones of the massif and are preferentially aligned along tectonic faults. Structural, geomorphological, and ERT profile analyses of two sinkholes confirm the structural control over their development and demonstrate that seepage occurs through the fractured material along fault planes. This study highlights the scientific, environmental, and water-supply significance of the JDM. Its karst depressions, serving as primary infiltration zones, play a crucial role in local hydrogeology, providing water sources for several settlements that rely on the massif’s springs.
{"title":"Closed depressions and karst landforms in Rif Alpine Cordillera (Northern Morocco): The case of dolomitic Jbel Dersa Massif","authors":"Samira Kaddouri , Younes EL Kharim , Kamal Agharroud , Ali Bounab , Youssef El Miloudi , Reda Sahrane , Ahmed Taoufik Ouahabi","doi":"10.1016/j.wsee.2025.08.002","DOIUrl":"10.1016/j.wsee.2025.08.002","url":null,"abstract":"<div><div>The morphology, distribution, and structural control of karst closed depressions in a dolomitic karst landscape are the focus of this study. The study area is the Jbel Dersa Massif (JDM), part of the “Dorsale Calcaire” (DC) unit within the Rif Mountain range in northern Morocco. A combined analysis of geomorphological mapping and structural studies reveal that the Pliocene dismantling phase smoothed the crests of the original imbricate thrust fronts, characteristic feature of the DC unit’s structure. The flattening of the massif’s summit facilitated the dissolution of the rock surface. In addition to the massif’s ruiniform landscape, the observed karstic features include fracture lapies, closed karstic depressions at the summit, and travertine deposits along the structural contacts with the bordering non-karstic units. The 26 identified closed depressions are dissolution dolines. Morphometric analysis indicates that these dolines are primarily located in the endorheic and axial zones of the massif and are preferentially aligned along tectonic faults. Structural, geomorphological, and ERT profile analyses of two sinkholes confirm the structural control over their development and demonstrate that seepage occurs through the fractured material along fault planes. This study highlights the scientific, environmental, and water-supply significance of the JDM. Its karst depressions, serving as primary infiltration zones, play a crucial role in local hydrogeology, providing water sources for several settlements that rely on the massif’s springs.</div></div>","PeriodicalId":101280,"journal":{"name":"Watershed Ecology and the Environment","volume":"7 ","pages":"Pages 398-412"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144895242","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}
Water resources management is fundamental to the sustainability of river basins. Water quality is affected by pollution caused by human activities. In this context, the restoration of degraded watersheds helps soil recovery, sustainable water management, reforestation, biodiversity conservation and mitigation of human impacts. Artificial intelligence (AI) innovates data management and analysis processes by optimising decision-making and data analysis in hydrological studies and ecological restoration. This research aims to analyse scientific information related to the integration of AI in studies on hydrogeology and ecological restoration of watersheds by analysing scientific databases for knowledge of the intellectual structure, lines and trends of research. The methodology includes three phases: i) search criteria and data processing (Scopus-Web of Science); ii) analysis of the intellectual and conceptual structure; and iii) application of the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) method. The results indicate that there is a total of 171 records, with a 4.49% growth in scientific production in the last four years, focusing on artificial neural networks (10.53%), artificial intelligence (3.51%), genetic algorithms (1.17%) and machine learning (1.17%). This increase is due to the climatic variation generated in recent years, driven by anthropogenic pressures, especially in the agricultural sector due to the high demand for fertiliser and pesticide pollution. This problem has prompted the search for more far-reaching environmental management technologies, making it a potential niche for study. China (72.51%) and the United States (25.73%) are the most outstanding contributors to production in this area. On the other hand, there is less research in this area in developing countries such as South Africa (2.92%), Colombia (1.17%), and Argentina (0.58%), among others. This analysis identifies opportunities and challenges in applying AI for water resource optimisation and water quality prediction, providing an innovative conceptual framework for sustainable watershed management.
水资源管理是河流流域可持续发展的基础。水质受到人类活动污染的影响。在这方面，恢复退化的流域有助于土壤恢复、可持续水资源管理、重新造林、生物多样性保护和减轻人类影响。人工智能（AI）通过优化水文研究和生态恢复中的决策和数据分析，创新数据管理和分析过程。本研究旨在通过分析科学数据库的知识结构、研究方向和趋势，分析与人工智能在水文地质与流域生态恢复研究中的整合相关的科学信息。该方法包括三个阶段：i)搜索标准和数据处理（Scopus-Web of Science）；Ii)智力和概念结构分析；iii)应用系统评价和荟萃分析（PRISMA）方法的首选报告项目。结果表明，共有171项记录，近四年科学产出增长4.49%，主要集中在人工神经网络（10.53%）、人工智能（3.51%）、遗传算法（1.17%）和机器学习（1.17%）。这种增加是由于近年来人为压力造成的气候变化，特别是在农业部门，由于对化肥和农药污染的高需求。这一问题促使人们寻求影响更深远的环境管理技术，使其成为一个潜在的研究领域。中国（72.51%）和美国（25.73%）是该地区产量贡献最突出的国家。另一方面，发展中国家在这方面的研究较少，如南非（2.92%）、哥伦比亚（1.17%）和阿根廷（0.58%）等。该分析确定了将人工智能应用于水资源优化和水质预测的机遇和挑战，为可持续流域管理提供了创新的概念框架。
{"title":"Artificial intelligence applications in hydrological studies and ecological restoration of watersheds: A systematic review","authors":"Fernando Morante-Carballo , Mirka Arcentales-Rosado , Jhon Caicedo-Potosí , Paúl Carrión-Mero","doi":"10.1016/j.wsee.2025.05.004","DOIUrl":"10.1016/j.wsee.2025.05.004","url":null,"abstract":"<div><div>Water resources management is fundamental to the sustainability of river basins. Water quality is affected by pollution caused by human activities. In this context, the restoration of degraded watersheds helps soil recovery, sustainable water management, reforestation, biodiversity conservation and mitigation of human impacts. Artificial intelligence (AI) innovates data management and analysis processes by optimising decision-making and data analysis in hydrological studies and ecological restoration. This research aims to analyse scientific information related to the integration of AI in studies on hydrogeology and ecological restoration of watersheds by analysing scientific databases for knowledge of the intellectual structure, lines and trends of research. The methodology includes three phases: i) search criteria and data processing (Scopus-Web of Science); ii) analysis of the intellectual and conceptual structure; and iii) application of the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) method. The results indicate that there is a total of 171 records, with a 4.49% growth in scientific production in the last four years, focusing on artificial neural networks (10.53%), artificial intelligence (3.51%), genetic algorithms (1.17%) and machine learning (1.17%). This increase is due to the climatic variation generated in recent years, driven by anthropogenic pressures, especially in the agricultural sector due to the high demand for fertiliser and pesticide pollution. This problem has prompted the search for more far-reaching environmental management technologies, making it a potential niche for study. China (72.51%) and the United States (25.73%) are the most outstanding contributors to production in this area. On the other hand, there is less research in this area in developing countries such as South Africa (2.92%), Colombia (1.17%), and Argentina (0.58%), among others. This analysis identifies opportunities and challenges in applying AI for water resource optimisation and water quality prediction, providing an innovative conceptual framework for sustainable watershed management.</div></div>","PeriodicalId":101280,"journal":{"name":"Watershed Ecology and the Environment","volume":"7 ","pages":"Pages 230-248"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144105700","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}
Pub Date : 2025-01-01DOI: 10.1016/j.wsee.2025.05.005
Zhiyi Li , Lingyan Dong , Liang Xu , Li Wang , Zhe Yuan
Ecological Regulation and Storage (ERS), a crucial natural regulatory mechanism in river basins, is vital in assessing watershed resilience and guiding water resource management. This study establishes a novel tripartite framework (vegetation-wetland-soil) to quantify ERS dynamics in the ecologically fragile Source Region of the Yangtze and Yellow Rivers (SRYY). Integrating multi-source hydrological data (2000–2020) with improved modeling approaches, including a modified SCS-CN method incorporating organic matter dynamics and NDVI-driven vegetation modules, we reveal three key insights: (1) Total ERS exhibited a distinct V-shaped trajectory during 2000–2020, underscoring the system’s resilience and recovery potential; (2) Wetland regulation dominated temporal fluctuations, followed by soil regulation, while canopy interception and litter retention functioned as stabilizing components; (3) Vegetation regulation displayed pronounced seasonal variability, with a robust positive correlation between canopy interception and litter retention (r = 0.94, p = 0.019), revealing synergistic hydrological coordination within the vegetation layer.
生态调节与蓄水（ERS）是一种重要的流域自然调节机制，在评价流域恢复力和指导水资源管理方面具有重要意义。本研究建立了植被-湿地-土壤三方框架来量化长江黄河生态脆弱源区ERS动态。综合多源水文数据（2000-2020年）和改进的建模方法，包括改进的SCS-CN方法，包括有机质动力学和ndvi驱动的植被模块，我们发现了三个关键见解：(1)2000-2020年期间，总ERS呈现出明显的v型轨迹，强调了系统的弹性和恢复潜力；(2)湿地调控主导时间波动，土壤调控次之，冠层截留和凋落物滞留是稳定因子；(3)植被调节表现出明显的季节变异性，冠层截留与凋落物滞留呈显著正相关（r = 0.94, p = 0.019），揭示了植被层内部的协同水文协调作用。
{"title":"Evaluation of vegetation-wetland-soil ecological water retention capacity in the source region of the Yangtze and Yellow rivers (SRYY)","authors":"Zhiyi Li , Lingyan Dong , Liang Xu , Li Wang , Zhe Yuan","doi":"10.1016/j.wsee.2025.05.005","DOIUrl":"10.1016/j.wsee.2025.05.005","url":null,"abstract":"<div><div>Ecological Regulation and Storage (ERS), a crucial natural regulatory mechanism in river basins, is vital in assessing watershed resilience and guiding water resource management. This study establishes a novel tripartite framework (vegetation-wetland-soil) to quantify ERS dynamics in the ecologically fragile Source Region of the Yangtze and Yellow Rivers (SRYY). Integrating multi-source hydrological data (2000–2020) with improved modeling approaches, including a modified SCS-CN method incorporating organic matter dynamics and NDVI-driven vegetation modules, we reveal three key insights: (1) Total ERS exhibited a distinct V-shaped trajectory during 2000–2020, underscoring the system’s resilience and recovery potential; (2) Wetland regulation dominated temporal fluctuations, followed by soil regulation, while canopy interception and litter retention functioned as stabilizing components; (3) Vegetation regulation displayed pronounced seasonal variability, with a robust positive correlation between canopy interception and litter retention (r = 0.94, p = 0.019), revealing synergistic hydrological coordination within the vegetation layer.</div></div>","PeriodicalId":101280,"journal":{"name":"Watershed Ecology and the Environment","volume":"7 ","pages":"Pages 260-273"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144184738","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}
Pub Date : 2025-01-01DOI: 10.1016/j.wsee.2025.05.008
Abreham Berta Aneseyee , Eyasu Elias , Teshome Sorromessa
Sustainable land management is necessary for soil erosion control, vegetation recovery, and land restoration. This study was conducted to identify the soil erosion susceptibility areas in the Winike watershed, upper Omo Gibe Basin of Ethiopia. Analytic Hierarchy Process (AHP) and InVEST modeling combined with GIS were used to generate primary data on soil erosion severity. Land use types, slope, elevation, NDVI, rainfall, drainage density, and soil types were important variables analyzed for soil erosion rate determination. The result shows a significant variation in soil erosion vulnerability among sub-watersheds ranging from low to very high vulnerability. The watershed’s very highly vulnerable eastern part accounts for 108.23 km2 (9.91 %) due to lacks vegetation cover, while the less vulnerable to the western part covers 179.66 km2 (16.46 %). Analysis of the Geo-environmental parameters shows that rainfall (26 %) is the most significant influencing factor, followed by vegetation cover (i.e., land use types), explaining about 23 % of the erosion severity. Comparing soil erosion vulnerability using the AHP and InVEST SDR models was 14.01 % and 16 %, respectively, suggesting insignificant variation between the erosion vulnerability analysis models. The study emphasizes the usefulness of erosion vulnerability modeling for identifying investment priority areas based on soil erosion status for soil conservation intervention, offering a range of decision-making options for land management.
{"title":"Identifying investment priority areas for soil conservation in the Winike watershed, upper Omo Gibe Basin of Ethiopia","authors":"Abreham Berta Aneseyee , Eyasu Elias , Teshome Sorromessa","doi":"10.1016/j.wsee.2025.05.008","DOIUrl":"10.1016/j.wsee.2025.05.008","url":null,"abstract":"<div><div>Sustainable land management is necessary for soil erosion control, vegetation recovery, and land restoration. This study was conducted to identify the soil erosion susceptibility areas in the Winike watershed, upper Omo Gibe Basin of Ethiopia. Analytic Hierarchy Process (AHP) and InVEST modeling combined with GIS were used to generate primary data on soil erosion severity. Land use types, slope, elevation, NDVI, rainfall, drainage density, and soil types were important variables analyzed for soil erosion rate determination. The result shows a significant variation in soil erosion vulnerability among sub-watersheds ranging from low to very high vulnerability. The watershed’s very highly vulnerable eastern part accounts for 108.23 km<sup>2</sup> (9.91 %) due to lacks vegetation cover, while the less vulnerable to the western part covers 179.66 km<sup>2</sup> (16.46 %). Analysis of the Geo-environmental parameters shows that rainfall (26 %) is the most significant influencing factor, followed by vegetation cover (i.e., land use types), explaining about 23 % of the erosion severity. Comparing soil erosion vulnerability using the AHP and InVEST SDR models was 14.01 % and 16 %, respectively, suggesting insignificant variation between the erosion vulnerability analysis models. The study emphasizes the usefulness of erosion vulnerability modeling for identifying investment priority areas based on soil erosion status for soil conservation intervention, offering a range of decision-making options for land management.</div></div>","PeriodicalId":101280,"journal":{"name":"Watershed Ecology and the Environment","volume":"7 ","pages":"Pages 327-337"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144670219","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}
Pub Date : 2025-01-01DOI: 10.1016/j.wsee.2025.03.003
Jill M. Felker, Zachary T. Weagly, Tami H. Mysliwiec
Recreational, agricultural, and industrial utilizations of areas surrounding waterways provide opportunities for collecting chemical and pollutant runoff, which influence the chemical makeup of the waterways and connecting watersheds. Human activities within watersheds can result in conditions that enable pathogenic microorganisms to thrive and allow unique microbial communities to emerge. The study area consisted of three locations at the Blue.
Marsh Watershed in Reading, Pennsylvania, with different surrounding land use and anthropogenic activities. The study areas were monitored monthly during the five-year project to assess seasonal variations in chemical levels and microbial count changes.
Chemical testing included inorganic nitrates, inorganic phosphates, and dissolved oxygen. Additional microbial testing included monthly counts for Escherichia coli and Enterococcus spp. to assess potential pathogenic microbial populations. On most occasions, chemical analyses found nitrate and phosphate concentrations above natural environmental levels.
During the five years, Escherichia coli and Enterococcus spp. concentrations were above the EPA recreational water recommendations 52% and 83% of the time, respectively. These results suggest that recreational, agricultural, and industrial utilization of surrounding waterways may influence chemical and microbial characteristics, including pathogenic microorganisms in the Blue Marsh Watershed.
{"title":"Five-year microbial and chemical assessment of the Blue Marsh Watershed in Reading, Pennsylvania","authors":"Jill M. Felker, Zachary T. Weagly, Tami H. Mysliwiec","doi":"10.1016/j.wsee.2025.03.003","DOIUrl":"10.1016/j.wsee.2025.03.003","url":null,"abstract":"<div><div>Recreational, agricultural, and industrial utilizations of areas surrounding waterways provide opportunities for collecting chemical and pollutant runoff, which influence the chemical makeup of the waterways and connecting watersheds. Human activities within watersheds can result in conditions that enable pathogenic microorganisms to thrive and allow unique microbial communities to emerge. The study area consisted of three locations at the Blue.</div><div>Marsh Watershed in Reading, Pennsylvania, with different surrounding land use and anthropogenic activities. The study areas were monitored monthly during the five-year project to assess seasonal variations in chemical levels and microbial count changes.</div><div>Chemical testing included inorganic nitrates, inorganic phosphates, and dissolved oxygen. Additional microbial testing included monthly counts for <em>Escherichia coli</em> and <em>Enterococcus</em> spp. to assess potential pathogenic microbial populations. On most occasions, chemical analyses found nitrate and phosphate concentrations above natural environmental levels.</div><div>During the five years, <em>Escherichia coli</em> and <em>Enterococcus</em> spp. concentrations were above the EPA recreational water recommendations 52% and 83% of the time, respectively. These results suggest that recreational, agricultural, and industrial utilization of surrounding waterways may influence chemical and microbial characteristics, including pathogenic microorganisms in the Blue Marsh Watershed.</div></div>","PeriodicalId":101280,"journal":{"name":"Watershed Ecology and the Environment","volume":"7 ","pages":"Pages 119-130"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143768638","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}
Pub Date : 2025-01-01DOI: 10.1016/j.wsee.2025.07.001
Son V.T. Dao, Tuan M. Le, Hieu M. Tran, Hung V. Pham, Minh T. Vu, Tuan Chu
As global waste production grows, sustainable waste management (WM) has become an issue for modern societies. This paper explores the integration of Artificial Intelligence (AI), particularly Machine Learning (ML) and Deep Learning (DL), to improve waste management (WM) systems by enhancing automation, classification accuracy, operational efficiency, and real-time decision-making. Current trends and potential future directions are identified with bibliometric and scientometric analysis, which assess methodologies and data in the field. By automating processes such as waste classification, sorting, and transportation, AI-driven models have the potential to optimize operational efficiency and reduce environmental impact. A comprehensive review of recent AI research in WM is presented, with a focus on their effectiveness, scalability, and limitations. Moreover, in the proposed framework, the data augmentation approach has been utilized to improve the model’s performance by increasing the amount of samples. Furthermore, the MobileNetV3 DL model is employed for feature extraction. Besides, the feature selection method − Harris Hawk Optimization (HHO) is also utilized to choose the best subset of features and reduce the irrelevant features. Then these selected features are fed into Machine Learning algorithms such as Decision Tree (DT), Logistic Regression (LR), and Random Forest (RF). In summary, this review highlights key case studies and research insights, offering a roadmap for future developments in AI-driven WM solutions.
{"title":"Integrating artificial intelligence for sustainable waste management: Insights from machine learning and deep learning","authors":"Son V.T. Dao, Tuan M. Le, Hieu M. Tran, Hung V. Pham, Minh T. Vu, Tuan Chu","doi":"10.1016/j.wsee.2025.07.001","DOIUrl":"10.1016/j.wsee.2025.07.001","url":null,"abstract":"<div><div>As global waste production grows, sustainable waste management (WM) has become an issue for modern societies. This paper explores the integration of Artificial Intelligence (AI), particularly Machine Learning (ML) and Deep Learning (DL), to improve waste management (WM) systems by enhancing automation, classification accuracy, operational efficiency, and real-time decision-making. Current trends and potential future directions are identified with bibliometric and scientometric analysis, which assess methodologies and data in the field. By automating processes such as waste classification, sorting, and transportation, AI-driven models have the potential to optimize operational efficiency and reduce environmental impact. A comprehensive review of recent AI research in WM is presented, with a focus on their effectiveness, scalability, and limitations. Moreover, in the proposed framework, the data augmentation approach has been utilized to improve the model’s performance by increasing the amount of samples. Furthermore, the MobileNetV3 DL model is employed for feature extraction. Besides, the<!--> <!-->feature selection method − Harris Hawk Optimization (HHO) is also utilized to choose the best subset of features and reduce the irrelevant features. Then these selected features are fed into Machine Learning algorithms such as Decision Tree (DT), Logistic Regression (LR), and Random Forest (RF). In summary, this review highlights key case studies and research insights, offering a roadmap for future developments in AI-driven WM solutions.</div></div>","PeriodicalId":101280,"journal":{"name":"Watershed Ecology and the Environment","volume":"7 ","pages":"Pages 353-382"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144702707","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}
Pub Date : 2025-01-01DOI: 10.1016/j.wsee.2025.04.002
Masumi Hisano , Shota Deguchi , Keinosuke Sannoh , Ken Motomura , Da-Li Lin
This study highlights the importance of rice paddies in snow-rich regions of central Japan as habitat for wetland bird species during snow-melting late winter season. During the study period, we recorded seven wetland species, including waders, egrets, and waterfowls. The abundance and richness of these birds were not significantly associated with the patch size of rice paddies. However, bird abundance presented a marginally positive association with the coverage of open water bodies within the landscape, while species richness showed a marginal relationship with the distance to the nearest water body. Our findings suggest that snowmelt-created wetlands may provide functions as critical stopover sites for migratory birds along the East Asian-Australian Flyway, and that enhancing water features in agricultural landscapes may yield greater conservation benefits than simply modifying the patch size of agricultural wetlands.
{"title":"Wetland bird utilisation of ephemerally flooded rice paddies in late winter snowmelt season in central Japan","authors":"Masumi Hisano , Shota Deguchi , Keinosuke Sannoh , Ken Motomura , Da-Li Lin","doi":"10.1016/j.wsee.2025.04.002","DOIUrl":"10.1016/j.wsee.2025.04.002","url":null,"abstract":"<div><div>This study highlights the importance of rice paddies in snow-rich regions of central Japan as habitat for wetland bird species during snow-melting late winter season. During the study period, we recorded seven wetland species, including waders, egrets, and waterfowls. The abundance and richness of these birds were not significantly associated with the patch size of rice paddies. However, bird abundance presented a marginally positive association with the coverage of open water bodies within the landscape, while species richness showed a marginal relationship with the distance to the nearest water body. Our findings suggest that snowmelt-created wetlands may provide functions as critical stopover sites for migratory birds along the East Asian-Australian Flyway, and that enhancing water features in agricultural landscapes may yield greater conservation benefits than simply modifying the patch size of agricultural wetlands.</div></div>","PeriodicalId":101280,"journal":{"name":"Watershed Ecology and the Environment","volume":"7 ","pages":"Pages 178-186"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143865135","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}
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