Geological heterogeneity enhances spreading of solutes and causes transport to be anomalous with much less mixing and reactivity than suggested by dispersion. We propose formal criteria that should be met by effective transport formalisms to represent advection, spreading and mixing. While relevant for dispersion in heterogeneous porous media, mobile–immobile exchange models induce lower but more sustained resistance to mixing.

We assess the impact of future climate change on Dinder River streamflow (Sudan), and infer its relative possible effects on the Dinder National Park (DNP) ecosystem habitats. Four GCMs from CMIP5 and two statistical downscaling approaches combined with SWAT were used. Climate over the basin will become warmer and wetter and streamflow will likely increase; accordingly, the ecosystems in the DNP will be affected positively and promote the ecological restoration of the flora and fauna habitats.

Changes of T, P, Q and sediment fluxes in a semi-arid basin little affected by human activities are analyzed from 40 years of measurements. T increased, P decreased, an earlier onset of first summer rains occurred. The flow regime shifted from perennial to intermittent. Sediment flux almost doubled every decade. The sediment regime shifted from two equivalent seasons of sediment delivery to a single major season regime. The C–Q rating curve ability declined due to enhanced hysteresis effects.

Remote sensing techniques can provide useful large-scale estimates of soil moisture. However, these methods often only sense near-surface soil moisture, whereas many applications require estimates of the entire root zone. In this study we propose and test methods to "depth-scale" the shallow soil moisture measurements obtained using the cosmic-ray neutron probe to represent the entire root zone, thereby improving the applicability of this measurement approach.

Fine-resolution spatio-temporal precipitation data are important as input to urban hydrological models to assess performance issues under all possible conditions. In the present study synthetic data at very fine spatial and temporal resolution are generated using a stochastic model. Data are generated for both present and future climate conditions. The results show that it is possible to generate spatially distributed data at resolutions relevant for urban hydrology.

This study applies artificial neural networks (ANN) to predict the groundwater table variations in a tropical wetland in Singapore. Surrounding reservoir levels and rainfall are selected as ANN inputs. The limited number of inputs eliminates the data-demanding restrictions inherent in the physical-based numerical models. The forecast is made at 4 locations with 3 leading times up to 7 days. The ANN forecast shows promising accuracy with decreasing performance when leading time progresses.

We analyse how stream discharge declines after rain storms. This "recession" behaviour contains information about the capacity of the catchment to hold or release water. Looking at many rivers in Sweden, we were able to link distinct recession regimes to land use and catchment characteristics. Trends in recession behaviour are found to correspond to intensifying agriculture and extensive reforestation. We conclude that both humans and nature reorganizes the soil in order to enhance efficiency.

There has been much recent debate regarding the future of the hydrological sciences, and several publications have voiced opinions on this subject. This opinion paper seeks to comment and expand on some recent publications that have advocated an increased focus on process modeling while de-emphasizing the focus on detailed attention to parameter estimation. In particular, it offers a perspective that emphasizes a more hydraulic approach to development and implementation of hydrological models.

We present an "Earth observation-based" method for estimating root zone storage capacity – a critical parameter in land surface modelling that represents the maximum amount of soil moisture available for vegetation. Variability within a land cover type is captured, and a global model evaporation simulation is overall improved, particularly in sub-humid to humid regions with seasonality. This new method can eliminate the need for unreliable soil and root depth data in land surface modelling.

Seven gridded statistical downscaling methods are tested for strength in simulating climate and hydrologic extremes. A recently developed technique, which is a post-processed version of bias corrected constructed analogues where the final bias correction is based on the bias corrected climate imprint method, is shown to be an especially strong method for hydrologic extremes versus other more commonly applied methods, including the popular bias corrected spatial disaggregation method.

The stem-root flow mechanism was parameterized and incorporated into the Simplified Simple Biosphere model to analyze its impact on soil moisture and land-atmospheric interactions. By testing against the Lien Hua Chih (Taiwan) and HAPEX-Mobilhy (France) measurements, the model shows that stem-root flow reduced the top-soil moisture content and moistened the deeper soil layers. Such soil moisture redistribution results in significant changes in heat flux exchange between land and atmosphere.

This paper describes a model inter-comparison and validation study conducted using sub-meter resolution thermal data from an aircraft. The model inter-comparison is between a physically based model and a very simple empirical model. The strengths and weaknesses of both modeling approaches for high-resolution mapping of water use in vineyards is described. The findings provide significant insight into the utility of complex versus simple models for precise water resources management.

We quantitatively isolated the relative contributions that human activities and climate variability made to decadal streamflow changes in Jinghe basin by three methods. We concluded that the three methods were in good agreement in terms of the dominant contributor, i.e., human activities played a more important role in the streamflow decrease than climate changes. We qualitatively discussed the errors and uncertainties, and will make an attempt for further research on quantitative discussions.

Our study represents the most comprehensive study on the combined effects of environmental change in streamflow using three different hydrological models. It revealed that climate change impacts exceeded land cover change in the 2000s. Considering the effect of climate changes on water supply, some active land management and water resources management options are discussed.

This paper provides a comprehensive review and up-to-date synthesis of the observed changes in air temperature, precipitation, seasonal snow cover, mountain glaciers, permafrost, freshwater ice cover, and river discharge over the interior of western Canada since the mid- or late 20th century. Important long-term observational networks and data sets are described, and qualitative linkages among the changing Earth system components are highlighted.

Flows out of Lake Chad are constrained by a modeling of the hydrological, chemical, and isotopic budgets, based on a review of existing data along with new data. This innovative approach allows one to determine the proportions of evaporation, transpiration, and infiltration out of the lake while the two last flows are often neglected in semi-arid environments. Moreover, it allows to investigate the lake hydrological and chemical regulations under the large climatic changes in Sahel since 1950.

This study provides an important first step towards a better understanding of the hydrology of tropical montane regions and the factors influencing baseflow mean transit times (MTT). Our MTT estimates ranged between 1.2 and 2.7 years, suggesting deep and long subsurface pathways contributing to sustain dry season flows. Our findings showed that topography and subsurface permeability are the key factors controlling baseflow MTTs. Longest MTTs were found in the cloud forest headwater catchments.

Precise and detailed DEMs are essential to accurately predict overland flow in urban areas. In this this study we evaluated whether DEMs generated from UAV imagery are suitable for urban drainage overland flow modelling. Specifically, 14 UAV flights were conducted to assess the influence of four different flight parameters on the quality of generated DEMs. In addition, we compared the best quality UAV DEM to a conventional lidar-based DEM; the two DEMs are of comparable quality.