{"title":"Assessment of historical and future land use land cover change and its impacts in the upper Bagmati River Basin using remote sensing and GIS","authors":"Sushil Subedi, Ramesh Rana, Srijan Thapa, Pradeep Gyawali, Subash Ghimire, Kutubuddin Ansari","doi":"10.1016/j.eve.2026.100167","DOIUrl":null,"url":null,"abstract":"<div><div>Evaluating land use and land cover (LULC) change impacts on river flow is essential for developing sustainable watershed management strategies, mainly in data scarce Himalayan regions. This study examines the influence of historical and projected LULC changes on river flow in the Upper Bagmati River Basin (UBRB), Nepal, by integrating remote sensing, the Modules for Land Use Change Evaluation (MOLUSCE) plugin in QGIS, and the Soil and Water Assessment Tool (SWAT). The comparison between simulated LULC map using MOLUSCE plugin for 2018 and observed LULC map for that year reveals a strong agreement, further supported by Kappa coefficient of 0.87 for simulated result. Therefore, MOLUSCE plugin was used to generate future LULC scenarios for 2027, 2050, and 2100<strong>,</strong> which were included into the calibrated SWAT model to evaluate future hydrological responses. The SWAT model revealed satisfactory performance, with monthly Nash-Sutcliffe Efficiency (NSE) values of 0.88 in the calibration (2002-2005) period and 0.80 in validation (2006-2009) periods and R<sup>2</sup> values of 0.89 in both times. Historical LULC analysis showed that built-up areas expanded from 83.78 km<sup>2</sup> (13.72%) in 2000 to 147.65 km<sup>2</sup> (24.18%) in 2018, while agricultural land declined from 293.20 km<sup>2</sup> (48.0%) to 227.21 km<sup>2</sup> (37.21%) over the same period. Future projections indicate continued urban expansion and declining agricultural and forest land, leading to increased surface runoff and altered streamflow characteristics over time. These findings can help water resource managers and policymakers plan sustainable watershed management, urban development, and climate resilient land use strategies in Himalayan River basins that are urbanizing quickly. They also show that combining remote sensing, MOLUSCE, and SWAT works well for assessing the long term hydrological effects of projected LULC change in areas with limited data.</div></div>","PeriodicalId":100516,"journal":{"name":"Evolving Earth","volume":"4 ","pages":"Article 100167"},"PeriodicalIF":0.0000,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Evolving Earth","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2950117226000634","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2026/9/9 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Evaluating land use and land cover (LULC) change impacts on river flow is essential for developing sustainable watershed management strategies, mainly in data scarce Himalayan regions. This study examines the influence of historical and projected LULC changes on river flow in the Upper Bagmati River Basin (UBRB), Nepal, by integrating remote sensing, the Modules for Land Use Change Evaluation (MOLUSCE) plugin in QGIS, and the Soil and Water Assessment Tool (SWAT). The comparison between simulated LULC map using MOLUSCE plugin for 2018 and observed LULC map for that year reveals a strong agreement, further supported by Kappa coefficient of 0.87 for simulated result. Therefore, MOLUSCE plugin was used to generate future LULC scenarios for 2027, 2050, and 2100, which were included into the calibrated SWAT model to evaluate future hydrological responses. The SWAT model revealed satisfactory performance, with monthly Nash-Sutcliffe Efficiency (NSE) values of 0.88 in the calibration (2002-2005) period and 0.80 in validation (2006-2009) periods and R2 values of 0.89 in both times. Historical LULC analysis showed that built-up areas expanded from 83.78 km2 (13.72%) in 2000 to 147.65 km2 (24.18%) in 2018, while agricultural land declined from 293.20 km2 (48.0%) to 227.21 km2 (37.21%) over the same period. Future projections indicate continued urban expansion and declining agricultural and forest land, leading to increased surface runoff and altered streamflow characteristics over time. These findings can help water resource managers and policymakers plan sustainable watershed management, urban development, and climate resilient land use strategies in Himalayan River basins that are urbanizing quickly. They also show that combining remote sensing, MOLUSCE, and SWAT works well for assessing the long term hydrological effects of projected LULC change in areas with limited data.