Increased grazing and agricultural production, industrialization, population growth, and consequent land use land cover (LULC) changes considerably increase water consumption. Global climate change exaggerates the uncertainty of water sources and supplies. Unfortunately, most current examinations are either confined within disciplinary silos or not integrated for considering wide-ranging socioenvironmental, management, and policy factors. The paper develops an integrated regional water environment modeling framework, examining how climate, LULC, socioenvironmental, and policy factors interact with the water environment. It also adopts a block-based econometric panel data analysis to quantify this framework. The paper extracts seasonal water area and LULC data through image processing from 2000 to 2014 in the Hulun-Buir watershed, Inner Mongolia of China. The paper quantitatively analyzed the interactions between seasonal water changes and major driving factors, such as climatic, land-use, socioeconomic, policy, space, and time. Many of these driving factors were interacting with the seasonal water environment and showing long-term causal relationships. The socioeconomic variables explained 71% of the variance of seasonal water change, the environmental and climatic factors about 9%, the regional disparities around 13%, and the yearly differences about 4%. The findings confirm that it is critical to carry out a time-series examination of causal relationships between seasonal water change and its manifold driving factors at the scale of regional watershed studies. This integrated watershed modeling framework is suitable for adaptation in other geographic areas or for integrated studies of other socio-environmental systems.
Keywords: Integrated socioenvironmental and spatiotemporal system; data blocks; panel data analysis; regional water environment; seasonal water change.
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