To account for complex and diverse water system involving river dry-up, groundwater degradation, agricultural/urban water use, and dam/canal effects in heavily irrigated Yellow River Basin, this study coupled NIES Integrated Catchment-based Eco-hydrology (NICE) model series with more complex sub-models involving various factors (NICE-DRY). The model reproduced reasonably evapotranspiration, irrigation water use, groundwater level, and river discharge during spring/winter wheat, summer maize, and summer rice cultivations. Scenario analysis predicted the impact of irrigation on both surface water and groundwater, which had previously been difficult to evaluate. The simulated discharge with irrigation was improved in terms of mean value, standard deviation, and coefficient of variation. Another scenario analysis of conversion from dryland to irrigated fields predicted that the effect of groundwater irrigation was predominant in the middle and downstream and the resultant groundwater degradation predominantly, where surface water was seriously limited. Simulated dry biomasses of wheat and maize were linearly related to Time-Integrated Normalized Difference Vegetation Index (TINDVI) estimated from satellite images. Temporal gradient of TINDVI during 1982-1999 showed spatially heterogeneous distribution and increasing trends in the wheat and maize fields, indicating that the production increases were related to irrigation water and the resultant hydrologic changes. This integrated approach could help to estimate a close relationship between crop production, hydrologic cycle, and water availability, and predict heterogeneous vulnerability of water resources. Because this region experienced substantial river dry-up and groundwater degradation at the end of the 20th century, this approach would help to overcome substantial pressures of increasing food demand and declining water availability, and to decide on appropriate measures for whole water resources management to achieve sustainable development under sound socio-economic conditions.
