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The study deals with assessing the influence of the changing climate on water availability over mountain communities in Central Himalaya. Precipitation variability causes fluctuations in the hydrological regimes which have a cascading effect on the natural resources, especially the water, forest, and agricultural resources, severely impacting the mountain people and their environment. The demand for natural resources has increased recently, placing tremendous pressure on the limited supply, making it imperative to assess the status of the resources in the context of climate change. The present study attempts to estimate the resource vulnerability in response to precipitation variability and provides adaptation strategies. The precipitation trend analysis using various statistical tests was performed and fourteen indicators for natural and human resources were identified based on sensitivity due to exposure to precipitation variability. The study provides insights into the critical quadrants and vulnerable regions that require quadrant-specific natural resource management and policy. With climate change and precipitation variability, the ripple effects on dwindling water resources are critical and cannot be overlooked. The study employs a novel methodology to assess the surface and sub-surface interaction of water. The coupling of two hydrological models, namely, the Soil Water Assessment Tool (SWAT) and the MIKE Hydro NAM model, was done to quantify the spatial variations in surface and sub-surface discharge for an ungauged watershed. Utilizing the data decomposition method and innovative trend analysis, the trends in surface and sub-surface discharge were assessed, and the findings indicate significant trends in the spatio-temporal domain due to changes in land practices and future precipitation behaviour at watershed or sub-catchment scale. The study reveals that sub-surface discharge is declining, which impacts the agricultural practices that rely on spring-fed water in Uttarakhand.
Since agriculture is the mainstay of the economy in Central Himalaya, the land use land cover dynamics due to changes in surface and sub-surface water were assessed based on current and future climate scenarios. The Multi-Layer Perceptron Artificial Neural Network (MLP ANN) based geospatial modelling was performed for quantifying the future land practices from 2019 to 2050 under RCP 4.5 and RCP 8.5 climate scenarios. The study identified seventeen potential drivers that influence land use and land cover changes. The most noticeable changes were estimated in agricultural classes of crop and fallow land in all the districts of Uttarakhand. The present study is aimed to investigate the different stakeholders’ perceptions of climate change and its associated impacts on natural resources. In this context, questionnaire surveys were conducted and the climate and hydrological changes were cross-examined with the perceptions of local people and tribal communities, as well as the water resource managers. The socio-economic and biophysical characteristics of the stakeholders were shown to have a significant influence on their perception of climate change and its impact on their livelihood. The findings of the study will undoubtedly aid water specialists, resource managers, and policy makers in strengthening adaptive capacity and improving the resilience of vulnerable people across the Himalayan region.
Keywords: Climate change; Agriculture; Hydrological Modelling; Ungauged watershed; LULC dynamics; Indigenous communities.
