Scholarlink

<p>Assessing the combined impacts of climate change and land use transitions is important to understanding catchment hydrology. This study presents a unique modeling framework, integrating a General Circulation Model (GCM) ensemble model with land use land cover (LULC) forecasts. The model selection for ensembling was done through a multi-criteria ranking framework using the modified Technique for Order Preference by Similarity to Ideal Solution (mTOPSIS) and LULC scenarios were developed using a combined Multi-Layer Perceptron Neural Network (MLPNN) and Cellular Automata (CA)-Markov method. This study explores a flood-prone sub-basin of the Upper Krishna River by employing the Soil and Water Assessment Tool (SWAT), integrated with GCM ensemble projections and projected LULC scenarios for mid-century and end-century. The climate projections show significant increases in both temperature and precipitation. These climatic shifts are accompanied by substantial hydrological responses. The mean annual surface runoff increases from 422.5&#xa0;mm to 723.07&#xa0;mm under SSP5-8.5, and water yield rises from 559.2&#xa0;mm to 1016.89&#xa0;mm. Evapotranspiration (ET) also shows a steady rise, from 419.5&#xa0;mm in 2021 to 431.1&#xa0;mm by 2100. Streamflow forecasts for the Arjunwad and Almatti stations reveal concerning trends. In years like 2029 under SSP2-4.5 scenarios and years 2051, 2080, and 2082 under SSP5-8.5, extreme discharge events surpassing 10,000 cumec and reaching up to 15,000 cumec are anticipated, with over 10 straight days exceeding the 8000 cumec mark. These outcomes highlight how warming and urban growth together intensify flood threats in the study area. These insights provided are important for planning basin-wide adaptation strategies in response to environmental and human-induced pressures.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Simulating Streamflow Scenarios Using Hydrological Modeling Integrated with Future Land Use and CMIP6 Climate Projections

  • 期刊论文

  • 发表日期：

    2026年2月6日

查看全文
  • Preetam Choudhary,
  • C P Devatha,
  • Adani Azhoni

摘要

Assessing the combined impacts of climate change and land use transitions is important to understanding catchment hydrology. This study presents a unique modeling framework, integrating a General Circulation Model (GCM) ensemble model with land use land cover (LULC) forecasts. The model selection for ensembling was done through a multi-criteria ranking framework using the modified Technique for Order Preference by Similarity to Ideal Solution (mTOPSIS) and LULC scenarios were developed using a combined Multi-Layer Perceptron Neural Network (MLPNN) and Cellular Automata (CA)-Markov method. This study explores a flood-prone sub-basin of the Upper Krishna River by employing the Soil and Water Assessment Tool (SWAT), integrated with GCM ensemble projections and projected LULC scenarios for mid-century and end-century. The climate projections show significant increases in both temperature and precipitation. These climatic shifts are accompanied by substantial hydrological responses. The mean annual surface runoff increases from 422.5 mm to 723.07 mm under SSP5-8.5, and water yield rises from 559.2 mm to 1016.89 mm. Evapotranspiration (ET) also shows a steady rise, from 419.5 mm in 2021 to 431.1 mm by 2100. Streamflow forecasts for the Arjunwad and Almatti stations reveal concerning trends. In years like 2029 under SSP2-4.5 scenarios and years 2051, 2080, and 2082 under SSP5-8.5, extreme discharge events surpassing 10,000 cumec and reaching up to 15,000 cumec are anticipated, with over 10 straight days exceeding the 8000 cumec mark. These outcomes highlight how warming and urban growth together intensify flood threats in the study area. These insights provided are important for planning basin-wide adaptation strategies in response to environmental and human-induced pressures.