No abstract

Migration is often seen as an adaptive human response to adverse socioenvironmental conditions, such as water scarcity. A rigorous assessment of the causes of migration, however, requires reliable information on the migration in question and related variables, such as, unemployment, which is often missing. This study explores the causes of one such type of migration, from rural to urban areas, in the Jiangsu province of China. A migration model is developed to fill a gap in the understanding of how rural to urban migration responds to variations in inputs to agricultural production including water availability and labor and how rural population forms expectations of better livelihood in urban areas. Rural to urban migration is estimated at provincial scale for period 1985-2013 and is found to be significantly linked with rural unemployment. Further, migration reacts to a change in rural unemployment after 2-4 years with 1% increase in rural unemployment, on average, leading to migration of 16,000 additional people. This implies that rural population takes a couple of years to internalize a shock in employment opportunities before migrating to cities. The analysis finds neither any evidence of migrants being pulled by better income prospects to urban areas nor being pushed out of rural areas by water scarcity. Corroborated by rural-urban migration in China migration survey data for 2008 and 2009, this means that local governments have 2-4 years of lead time after an unemployment shock, not necessarily linked to water scarcity, in rural areas to prepare for the migration wave in urban areas. This original analysis of migration over a 30-year period and finding its clear link with unemployment, and not with better income in urban areas or poor rainfall, thus provides conclusive evidence in support of policy interventions that focus on generating employment opportunities in rural areas to reduce migration flow to urban areas.

Understanding the rate and process of land-use/land-cover (LULC) change in a watershed is essential for managing natural resources and achieving sustainable development. Therefore, this study aims to analyze historical LULC change from 1980 to 2010 and project future changes in 2030, 2060, and 2090 in the Guanting Reservoir Basin (GRB), China, a critical water-supplying watershed for China’s capital Beijing, through scenario-based simulations. Two LULC scenarios, ‘business-as-usual’ and ‘governance’ (Gov), were projected using the Cellular Automata-Markov (CA–Markov) model. Historical LULC trend analysis shows that built-up land increased from 2.6% in 1980 to 5.26% in 2010, while cropland, grassland, and water body decreased. LULC conversion analysis indicates that, in general, grassland, cropland, and woodland were converted to built-up area from 1980 to 2010. The BAU scenario projects a dramatic increase in built-up area, rising from 2296.98 km2 (5.26%) in 2010 to 11,757.35 km2 (26.93%) in 2090 at the expense of cropland and grassland areas. Conversely, the Gov scenario predicts an increase in water body, woodland, and grassland, encouraging sustainable development. Overall, these results provide useful inputs to the LULC planners and water resources managers to elaborate on eco-friendly policies and regulations for GRB.

Streamflow simulation of the headwater catchment of the Yellow River basin (HCYRB) in China is important for water resources management of the Yellow River basin. A statistical‐dynamical model, combining regular vine copulas with an optimization method for structure estimation, is presented with an application for simulating the monthly streamflow with local climate drivers at HCYRB. Local climate drivers for streamflow in every month are analyzed using rank‐based correlation. Precipitation, evaporation, and temperature generally show strong associations with streamflow. Winter streamflows relate to total precipitation of the wet season and total evaporation of October and November, while unfrozen‐month streamflows are correlated with evaporation and precipitation of current month and previous 1 month in the wet season. Both canonical vine and D‐vine copulas are applied to develop different conditional quantile functions for streamflows in different months with their dynamical covariates. The covariates are selected from historical streamflows and climate drivers with appropriate lags using partial correlations. The optimal vine trees are selected using the sequential maximum spanning tree algorithm with the weight based on both dependence and goodness of fit. The model demonstrates higher skill than existing vine‐based models and the seasonal autoregressive integrated moving average model. The enhanced skill of the hybrid statistical‐dynamical model comes from an improved capability of capturing nonlinear correlation and tail dependence of streamflow and climate drivers with the optimization of vine structure selection. The model provides an effective advance to enhance water resources planning and management for HCYRB and the whole basin.

Water resources are very important to support the socio-economic development and maintain environmental health, which is a typical issue in water resources management. In this study, we developed an optimal allocation model for a large complex system of water resources by considering both water supply and river ecological benefits. The water supply benefit is defined as the minimum water deficit for different water users, while the ecological benefit involves making the reservoir release as close as possible to the natural streamflow. To solve this problem, the combination of decomposition-coordination (DC) and discrete differential dynamic programming (DDDP) methods were proposed. The proposed methods first decomposed a large system with multi-objective programming into subsystems, and the optimal solution of each subsystem was accomplished by the DDDP method to solve the system efficiently. Then the subsystems’ solutions were coordinated to figure out the near global optimal solution. The proposed models were tested in the Lingui and Yongfu County, Guilin City in China. Results show that the optimal reservoir release is close to the natural flow regime and there is a slight water deficit ratio in both level years. The water supply objective is more sensitive to the system model compared with the ecological objective, and the result of water allocation is optimized when the reservoir release is as close as possible to the natural flow based on the minimum water deficit. The proposed system model could facilitate sustainable water use and provide technical support for water resources management in economic development.