Assessment of historical and future land use land cover change and its impacts in the upper Bagmati River Basin using remote sensing and GIS

Evolving Earth Pub Date : 2026-01-01 Epub Date: 2026-09-09 DOI:10.1016/j.eve.2026.100167
Sushil Subedi, Ramesh Rana, Srijan Thapa, Pradeep Gyawali, Subash Ghimire, Kutubuddin Ansari
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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.
基于遥感和GIS的巴格马提河上游流域历史和未来土地利用、土地覆被变化及其影响评估
评估土地利用和土地覆盖(LULC)变化对河流流量的影响对于制定可持续流域管理战略至关重要,特别是在数据稀缺的喜马拉雅地区。本研究通过整合遥感、QGIS中的土地利用变化评估模块(MOLUSCE)插件和水土评估工具(SWAT),研究了尼泊尔巴格马蒂河上游流域(UBRB)历史和预测的LULC变化对河流流量的影响。使用MOLUSCE插件模拟的2018年LULC地图与当年实际观测的LULC地图比较,结果显示出很强的一致性,模拟结果的Kappa系数为0.87。因此,使用MOLUSCE插件生成2027年、2050年和2100年的未来LULC情景,并将其纳入校准后的SWAT模型中,以评估未来的水文响应。SWAT模型显示出令人满意的性能,在校准期(2002-2005年)和验证期(2006-2009年)的月NSE值分别为0.88和0.80,两次的R2值均为0.89。历史LULC分析显示,建成区面积从2000年的83.78 km2(13.72%)扩大到2018年的147.65 km2(24.18%),而同期农业用地从293.20 km2(48.0%)下降到227.21 km2(37.21%)。未来的预测表明,随着时间的推移,城市的持续扩张和农田和林地的减少将导致地表径流的增加和河流特征的改变。这些发现可以帮助水资源管理者和决策者在快速城市化的喜马拉雅河流域规划可持续流域管理、城市发展和气候适应型土地利用战略。他们还表明,在数据有限的地区,结合遥感、MOLUSCE和SWAT可以很好地评估预计的LULC变化的长期水文影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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