Delineation of endorheic drainage basins in the MERIT-Plus dataset for 5 and 15 minute upscaled river networks.

The MERIT-Hydro networks re-gridded by the Iterative Hydrography Upscaling (IHU) algorithm do not retain exo- or endorheic basin attributes from the original data. Here we developed methods to assign such attributes to those and any other digital river networks. The motivation is that endorheic inland drainage basins are essential for hydrologic modelling of global and regional water balances, land surface water storage, gravity anomalies, sea level rise, etc. First, we create basin attributes that explicitly label endorheic and exorheic catchments by the criteria of direct or hidden connectivity to the ocean without changing their flow direction grid. In the second step we alter the delineation of endorheic basins by the merging algorithm that eliminates small inland watersheds to the adjacent host basins. The resulting datasets have a significantly reduced number of endorheic basins while preserving the total land portion and topology of the inland basins. The data was validated using the Water Balance Model by comparing volume of endorheic inland depressions with modelled water accumulation in their inland lakes.

Quantifying the link between crop production and mined groundwater irrigation in China.

In response to increasing demand for food, Chinese agriculture has both expanded and intensified over the past several decades. Irrigation has played a key role in increasing crop production, and groundwater is now an important source of irrigation water. Groundwater abstraction in excess of recharge (which we use here to estimate groundwater mining) has resulted in declining groundwater levels and could eventually restrict groundwater availability. In this study we used a hydrological model, WBMplus, in conjunction with a process based crop growth model, DNDC, to evaluate Chinese agriculture's recent dependence upon mined groundwater, and to quantify mined groundwater-dependent crop production across a domain that includes variation in climate, crop choice, and management practices. This methodology allowed for the direct attribution of crop production to irrigation water from rivers and reservoirs, shallow (renewable) groundwater, and mined groundwater. Simulating 20 years of weather variability and circa year 2000 crop areas, we found that mined groundwater fulfilled 20%-49% of gross irrigation water demand, assuming all demand was met. Mined groundwater accounted for 15%-27% of national total crop production. There was high spatial variability across China in irrigation water demand and crop production derived from mined groundwater. We find that climate variability and mined groundwater demand do not operate independently; rather, years in which irrigation water demand is high due to the relatively hot and dry climate also experience limited surface water supplies and therefore have less surface water with which to meet that high irrigation water demand.

Joint analysis of stressors and ecosystem services to enhance restoration effectiveness.

With increasing pressure placed on natural systems by growing human populations, both scientists and resource managers need a better understanding of the relationships between cumulative stress from human activities and valued ecosystem services. Societies often seek to mitigate threats to these services through large-scale, costly restoration projects, such as the over one billion dollar Great Lakes Restoration Initiative currently underway. To help inform these efforts, we merged high-resolution spatial analyses of environmental stressors with mapping of ecosystem services for all five Great Lakes. Cumulative ecosystem stress is highest in near-shore habitats, but also extends offshore in Lakes Erie, Ontario, and Michigan. Variation in cumulative stress is driven largely by spatial concordance among multiple stressors, indicating the importance of considering all stressors when planning restoration activities. In addition, highly stressed areas reflect numerous different combinations of stressors rather than a single suite of problems, suggesting that a detailed understanding of the stressors needing alleviation could improve restoration planning. We also find that many important areas for fisheries and recreation are subject to high stress, indicating that ecosystem degradation could be threatening key services. Current restoration efforts have targeted high-stress sites almost exclusively, but generally without knowledge of the full range of stressors affecting these locations or differences among sites in service provisioning. Our results demonstrate that joint spatial analysis of stressors and ecosystem services can provide a critical foundation for maximizing social and ecological benefits from restoration investments.