In Mongolia, overuse and degradation of groundwater is a serious issue, mainly in the urban and economic hub in Ulaanbaatar, and the Southern Gobi mining hub. The authors have recently applied a process-based eco-hydrology model, NICE (National Integrated Catchment-based Eco-hydrology) to these two contrasting river basins in order to explicitly quantify spatio-temporal variations in water availability. In this study, they further extended the model to couple with inverse method for sensitivity analysis and parameter estimation of anthropogenic water uses (NICE-INVERSE). The model quantified the spatio-temporal variations of livestock water use in these river basins in comparison with the estimated values by aggregating statistical data, GIS data, observation data, and field surveys in their previous studies. The amount of water use by animals were generally small for each soum (district), and could also be heavily returned back to the ecosystems. The result also showed a temporal decreasing trend of unit water use in some typical livestock (cattle, sheep, and goats), suggesting a substantial increase in water stress due to local-regional eco-hydrological degradation by urbanization and mining. These results clarified the substantial increase in water stress of groundwater degradation was mainly caused by urbanization and mining locally in addition to climatic change. Sensitivity analysis and inverse estimation of model parameters helped to improve the accuracy of hydrologic budgets in basins. This methodology is powerful for evaluating spatio-temporal variations of water availability in regions with fewer inventory data on urbanization, mining, and livestock.

在蒙古，地下水的过度使用和退化是一个严重的问题，主要是在乌兰巴托的城市和经济中心以及南部戈壁采矿中心。作者最近将基于过程的生态水文模型 NICE（基于国家综合流域的生态水文）应用于这两个对比鲜明的流域，以明确量化可用水量的时空变化。在这项研究中，他们进一步扩展了模型，以结合逆向方法进行人为用水的敏感性分析和参数估计（NICE-INVERSE）。该模型通过汇总以往研究中的统计数据、GIS 数据、观测数据和实地调查，量化了这些流域牲畜用水的时空变化，并与估计值进行了比较。soum（地区），也可能大量回归生态系统。结果还显示，一些典型牲畜（牛、绵羊和山羊）的单位用水量随时间推移呈下降趋势，表明由于城市化和采矿造成的局部区域生态水文退化，水资源压力显着增加。这些结果表明，除了气候变化外，地下水退化造成的水资源压力大幅增加主要是由当地的城市化和采矿引起的。模型参数的敏感性分析和逆估计有助于提高流域水文预算的准确性。这种方法对于评估城市化、采矿和牲畜清单数据较少的地区的可用水资源时空变化非常有效。