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<p>Changes in climatic variables like precipitation and the rapid development of anthropogenic activities have the potential to affect both groundwater and surface water. It is specifically observable in the non-perennial river like the Damodar, where, despite the construction of dams, flooding is a recurring problem. This study aims to evaluate the changes in the annual water yield of the DRR using the ‘annual water yield’ module of the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model. The inputs of the model were derived from different remote sensing datasets using the Google Earth Engine (GEE) platform. The results indicate a lower annual water yield in 2023 (mean 1036&#xa0;mm) and a higher yield in 2013 (mean 1426&#xa0;mm), compared to 2003 (mean 1219&#xa0;mm). Reduced vegetation cover (reduced by 5500 km<sup>2</sup>), reduced area of waterbodies (471 km<sup>2</sup>), and increased urbanisation (built-up areas increased by 700 km<sup>2</sup>) were observed between 2003 and 2023 in the DRR. The sensitivity analysis of the model revealed that precipitation is a more influential factor than evapotranspiration when simulating water yield. The effect of changing land use was found to have very little or no effect on the annual water yield. This study also demonstrates a coupled framework for building hydrological resilience in the DRR by integrating three subsystems – namely, the water subsystem, the human subsystem and the socio-hydrological system.</p>

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A modelling approach to assess the impacts of climate dynamics and anthropogenic pressure on water yield in the Damodar River basin

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年11月23日

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  • Jyoti Prakash Hati,
  • Anirban Mukhopadhyay,
  • Rituparna Acharyya,
  • Halina Kaczmarek

摘要

Changes in climatic variables like precipitation and the rapid development of anthropogenic activities have the potential to affect both groundwater and surface water. It is specifically observable in the non-perennial river like the Damodar, where, despite the construction of dams, flooding is a recurring problem. This study aims to evaluate the changes in the annual water yield of the DRR using the ‘annual water yield’ module of the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model. The inputs of the model were derived from different remote sensing datasets using the Google Earth Engine (GEE) platform. The results indicate a lower annual water yield in 2023 (mean 1036 mm) and a higher yield in 2013 (mean 1426 mm), compared to 2003 (mean 1219 mm). Reduced vegetation cover (reduced by 5500 km2), reduced area of waterbodies (471 km2), and increased urbanisation (built-up areas increased by 700 km2) were observed between 2003 and 2023 in the DRR. The sensitivity analysis of the model revealed that precipitation is a more influential factor than evapotranspiration when simulating water yield. The effect of changing land use was found to have very little or no effect on the annual water yield. This study also demonstrates a coupled framework for building hydrological resilience in the DRR by integrating three subsystems – namely, the water subsystem, the human subsystem and the socio-hydrological system.