Global environmental change has implications for the spatial and temporal distribution of water resources, but quantifying its effects remains a challenge. The impact of vegetation responses to increasing atmospheric CO2 concentrations on the hydrologic cycle is particularly poorly constrained1, 2, 3.

This paper presents an inverse modeling method based on wavelet analysis, devoted to assessment of the impacts of climate change on the groundwater resources of a con- fined coastal multi-layer aquifer, located in the south of France (Pyrénées-Orientales). The hydraulic behavior of the aquifer is described based on the results of a model calibrated to simulate the groundwater dynamics observed on two representative piezometers. The relative contributions of the climate and pumping forcings to the piezometric variations are quantified.

With the rapid population growth, ecological pressure caused by human activities on rivers is growing. Decision makers are often faced with the dilemma of how to maintain economic growth while also maintaining the resources of a river and its environment. In this study, a model has been proposed for the assessment of river–human relationship. The method establishes a complete index system to quantify the abstraction of river–human relationship and evaluation.

Managing freshwater resources sustainably under future climatic and hydrological uncertainty poses novel challenges. Rehabilitation of ageing infrastructure and construction of new dams are widely viewed as solutions to diminish climate risk, but attaining the broad goal of freshwater sustainability will require expansion of the prevailing water resources management paradigm beyond narrow economic criteria to include socially valued ecosystem functions and services.

Wetlands are globally important ecosystems that provide critical services for natural communities and human society. Montane wetland ecosystems are expected to be among the most sensitive to changing climate, as their persistence depends on factors directly influenced by climate (e.g. precipitation, snowpack, evaporation). Despite their importance and climate sensitivity, wetlands tend to be understudied due to a lack of tools and data relative to what is available for other ecosystem types.

We here demonstrate that we can resolve the seasonality of the hydrologic cycle in the Amazon using an approach, opposite to general circulation models, in which we resolve convection and parameterize large-scale circulation as a function of the resolved convection. The results emphasize the key role of cloud albedo feedback and, in particular, of the morning fog layer in determining the diurnal course of surface heat fluxes and seasonality of the surface and atmospheric heat and water cycles.