This paper demonstrates an approach to spatial discretization for analyzing green infrastructure (GI) using SWMM. Besides DCIA, pervious buffers should be identified for GI modeling. Runoff contributions from different spatial components and flow pathways would impact GI performance. The presented approach can reduce the number of calibration parameters and apply scale–independently to a watershed scale. Hydrograph separation can add insights for developing GI scenarios.

We calculated hourly new snow densities from automated measurements. This time interval reduces the influence of settling of the freshly deposited snow. We found an average new snow density of 68 kg m⁻³. The observed variability could not be described using different parameterizations, but a relationship to temperature is partly visible at hourly intervals. Wind speed is a crucial parameter for the inter-station variability. Our findings are relevant for snow models working on hourly timescales.

Spatial patterns of snow and frozen ground within watersheds can impact the volume and timing of runoff. Commonly used snow and frozen ground simulation methods were modified to better account for the effects of topography and land cover on the spatial patterns of snow and frozen ground. When tested using a watershed in Vermont the modifications resulted in more accurate temporal and spatial simulation of both snow and frozen ground.

To ensure a sustainable supply of groundwater, scientific information about what is going into the system as recharge and what is taken out of the system via pumping is essential. This study identified the most influential factors in groundwater recharge and developed an empirical global recharge model. The meteorological and vegetation factors were the most important factors, and the long-term global average recharge was 134 mm per year. This model will aid in groundwater policy-making.

A new comprehensive dataset of annual maximum rainfall depths recorded in 1 to 24 consecutive hours in Italy is presented. More than 4500 stations are considered, spanning the period between 1916 and 2014. For the first time, a national dataset of annual maxima allows for an updated characterization of rainstorms in Italy, getting rid of the regional borders. The spatio-temporal analyses of the highest rainstorms represent a robust starting point for the assessment of the extreme rainfall risk.

In this study we show the relevance of an interdisciplinary study for improving restoration within the framework of a European LIFE+ project on the French side of the Upper Rhine (Rohrschollen Island). Our results underscore the advantage of combining functional restoration with detailed knowledge of past trajectories in complex hydrosystems. We anticipate our approach will expand the toolbox of decision-makers and help orientate functional restoration actions in the future.

We estimated a probability distribution of nitrogen loading rates for crop and land-use groups from regional groundwater data. Water & natural land use had the lowest estimated rates, while dairy land use had the highest. Most results compare favorably to previous estimates, though mass balance estimates for several crop groups were higher than our model estimates. The information can provide a better assessment of land-use impacts to water quality absent information on farm nutrient management.

We developed a model experiment and distributed different rainfall patterns over a mountain river basin. For each rainfall scenario, we computed the flood losses with a model chain. The experiment shows that flood losses vary considerably within the river basin and depend on the timing of the flood peaks from the basin's sub-catchments. Basin-specific characteristics such as the location of the main settlements within the floodplains play an additional important role in determining flood losses.

In recent decades, evapotranspiration estimation has been improved by remote sensing methods as well as by hydrological models. However, comparing these methods shows differences of up to 31 % at a spatial resolution of 1 km². Land cover differences and catchment averaged climate data in the hydrological model were identified as the principal causes of the differences in results. The implication is that water management will have to deal with large uncertainty in estimated water balances.

An analytical framework is developed drawing on ideas of regime shifts from resilience literature to understand the transition between cases where water scarcity is or is not experienced depending on whether water from upstream is or is not available. The analysis shows 386 million people dependent on upstream water to avoid possible stress and 306 million people dependent on upstream water to avoid possible shortage. This provides insights into implications for negotiations between sub-basins.

Two optical disdrometers, OTT Parsivel² disdrometer and Thies Clima laser precipitation monitor (LPM), are compared. Analysis of 2 years of one-minute replicated data showed significant differences. Thies LPM recorded a larger number of particles than Parsivel² and a higher proportion of small particles, resulting in higher rain rates and amounts and differences in radar reflectivity and kinetic energy. Possible causes for these differences, and their practical consequences, are discussed.

The Magdalena River basin has great hydropower potential. A number of large dams are proposed in the upstream reaches of the two largest rivers that converge in the lowland floodplains. While these dams are expected to more than double national electricity production, the implications for the wetlands and the people that depend on them are highly uncertain. Our assessment of these implications provides insights to guide basin-level infrastructure development and ecosystem conservation projects.

Daily GRACE gravity field solutions have been evaluated against daily river runoff data for major flood events in the Ganges–Brahmaputra Delta in 2004 and 2007. Compared to the monthly gravity field solutions, the trends over periods of a few days in the daily gravity field solutions are able to reflect temporal variations in river runoff during major flood events. This implies that daily gravity field solutions released in near-real time may support flood monitoring for large events.

Evaporation causes the isotopic composition of soil water to become different from that of the original precipitation source. If multiple samples originating from the same source are available, they can be used to reconstruct the original source composition. However, soil water is influenced by seasonal variability in both precipitation sources and evaporation patterns. We show that this variability, if not accounted for, can lead to biased estimates of the precipitation source water.

The spatial runoff is decomposed into a deterministic trend and deviations from it caused by stochastic fluctuations which are described by Budyko method and stochastic interpolation. This coupled method is applied to spatially interpolate runoff in the Huaihe River basin of China. Results show that the coupled method reduces the error in overestimating low runoff and underestimating high runoff suffered by the other two methods, so it improves the prediction accuracy of the mean annual runoff.

Hydrologic modeling methodologies must be developed that are capable of predicting runoff in catchments with changing land cover conditions. This article investigates the efficacy of a recently developed approach that allows for runoff prediction in catchments with unknown land cover changes, through experimentation in a deforested catchment in Vietnam. The importance of key elements of the method in ensuring its success, such as the chosen hydrologic model, is investigated.

Short-term river discharge records hamper assessment of the severity of modern droughts in south-central Chile, making effective water management difficult. To support decision-making, we present a ~300-year tree-ring reconstruction of summer discharge for this region. Results show that since 1980, droughts have become more frequent and are related to a shift in large-scale climate. We argue that water managers should use this long-term view to better allocate water rights.

Impact of upward flow by capillary rise and recirculation on crop yields is often neglected or underestimated. Case studies and model experiments are used to illustrate the impact of this upward flow in the Dutch delta. Neglecting upward flow results in yield reductions for grassland, maize and potatoes. Half of the withheld water behind these yield effects comes from recirculated percolation water as occurs in free-drainage conditions; the other half from increased upward capillary rise.

Hydropower makes up nearly half of Sweden's electrical energy production. Careful reservoir management is required for optimal production throughout the year and accurate seasonal forecasts are essential for this. In this work we develop a seasonal forecast prototype and evaluate its ability to predict spring flood volumes, a critical variable, in northern Sweden. We show that the prototype is better than the operational system on average 65 % of the time and reduces the volume error by ~ 6 %.

The development of sustainable strategies for groundwater resources exploitation in coastal regions is subordinated to the characterization of seawater intrusion (SWI) phenomena. We develop a numerical model tailored to a real coastal aquifer to investigate quantitatively the joint effects of hydraulic properties heterogeneity and pumping configuration on saltwater inland penetration and saltwater–freshwater mixing. Our results allowed identifying efficient scenarios for the reduction of SWI.

This research proposes a generalised hybrid model development framework and applies it to a case study of salinity prediction in a reach of the Murray River. The hybrid model combines five sub-models which describe one process of salt entry each and are developed based on the amount of system knowledge and data that are available to support each individual process. The model demonstrates increased performance over two benchmark models and has implications for future model development processes.

The National Water Economy Database is a new data resource to better understand the human economy's water use impact on the hydrosphere. NWED quantifies and maps a spatially detailed and economically complete blue water footprint for the United States, utilizing several datasets: US Geological Survey, the US Department of Agriculture, the US Energy Information Administration, the US Department of Transportation, the US Department of Energy, and the US Bureau of Labor Statistics.

Streams which may stop flowing are poorly gauged. To improve their characterisation, we use an extended network providing monthly visual observations stating whether streams are flowing or not across France. These observations are combined with discharge and groundwater level in models to predict daily regional probability of drying. This approach allows identification of the most impacted regions by flow intermittence and estimation of the probability of drying dynamics over the last 27 years.

We have developed a method to assess hydrological impacts of future potential global change (GC) scenarios in a coastal aquifer, the Plana Oropesa-Torreblanca aquifer. Quantity and quality issues are simultaneously considered. It includes the generation of potential GC scenarios involving different sources of uncertainty and an integrated modelling framework to assess their impacts. It is a valuable tool to improve our aquifer knowledge and to help in the analysis of management strategies.

The purpose of this research was to detect the effect of plastic film mulching (PFM), a widely applied cultivation method, on soil respiration. We found that soil respiration was not only affected by PFM, but it was also affected by irrigation and precipitation, and whether the PFM increases soil respiration compared to a non-mulched field largely depends on precipitation in the field. The result has an important meaning for agricultural carbon sequestration in the context of global warming.

An ensemble simulation of five RCMs from CORDEX in East Asia was evaluated and used for future regional climate change projection in China. In addition, the contributions of model uncertainty and internal variability are identified. We found that the multi-model ensemble outperforms the individual RCMs in historical climate simulation. The future climate projections show significant inter-RCM differences and the model uncertainty increases with prediction lead time over all subregions.