Hydrological assessment of the Gundlakamma sub-basin through SWAT modeling: integration of land use land cover (LULC) and climate changes

K. V. Sivakumar Babu, Aravindan Achuthan, Shamshaad Ahmad
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Abstract

Gundlakamma sub-basin faces challenges with increasing water demand and climate change impacts, requiring innovative solutions for sustainable water management. The study was conducted to improve the long-term utilization of water resources in Andhra Pradesh. To accomplish this, the study attempts to estimate LULC change detection and its impact on water resources by analyzing the performance of the soil and water assessment tool (SWAT) model. From 2005 to 2021, the amount of cropland decreased while built-up land increased, indicating urban growth. The SWAT model identifies hydrological processes and assesses the temporal and spatial distribution of water resources in the watershed. Statistical parameters results reveal that a good match was found between actual and modeled flows with Nash–Sutcliffe efficiency (NSE) and coefficient of determination (R2) greater than 0.75 for both calibration and validation periods. The area has average annual precipitation, surface runoff, water yield, and actual evapotranspiration of 949.96, 215.6, 469.24, and 429.15 mm, respectively. The SWAT model's fascinating outcomes demonstrate that it could be a promising decision support tool for predicting water balance and water yield in other watersheds of Andhra Pradesh for sustainable water management of water resources where water quality and quantity are critical issues.

通过 SWAT 模型对贡德拉卡马分流域进行水文评估:土地利用、土地覆被 (LULC) 和气候变化的整合
贡德拉卡马(Gundlakamma)分流域面临着水资源需求日益增长和气候变化影响的挑战,需要创新的可持续水资源管理解决方案。本研究旨在改善安得拉邦水资源的长期利用。为此,研究试图通过分析水土评估工具(SWAT)模型的性能来估算 LULC 变化探测及其对水资源的影响。从 2005 年到 2021 年,耕地面积减少,而建筑用地增加,表明城市在发展。SWAT 模型可识别水文过程并评估流域水资源的时空分布。统计参数结果表明,实际流量与模型流量匹配良好,校准期和验证期的纳什-苏克里夫效率 (NSE) 和判定系数 (R2) 均大于 0.75。该地区的年平均降水量、地表径流量、产水量和实际蒸散量分别为 949.96 毫米、215.6 毫米、469.24 毫米和 429.15 毫米。SWAT 模型引人入胜的结果表明,它可以成为一种很有前途的决策支持工具,用于预测安得拉邦其他流域的水平衡和产水量,以实现水资源的可持续管理,因为水质和水量是关键问题。
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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