Forecasting at the seasonal timescale aims to answer questions such as the following: how much water do we have next summer? Is next winter going to be extremely cold? Constrained by computer power, earth system models (ESMs) do not resolve all environmental variables of interest. Our study tests a method to refine the output of such an ESM for streamflow forecasting in the Rhine basin. The results show that the method is able to translate skill at different spatial scales.

The paper proposes a dimensionless framework to investigate the impact of the rainfall event structure on the runoff peak. A set of analytical expressions are derived from a constant hyetograph to assess the maximum runoff peak for a given event structure irrespective of the specific catchment. A catchment application is discussed to point out the dimensionless procedure implications and to provide some numerical examples of the rainfall structures with respect to observed rainfall events.

In global water resource allocation, robust tools are required to establish environmental flows. In addition, tools should characterize past, present and future consequences of altered flows and non-flow variables to social and ecological management objectives. PROBFLO is a risk assessment method designed to meet best practice principles for regional-scale holistic E-flow assessments. The approach has been developed in Africa and applied across the continent.

This study explores the relationship between drip water and rainfall in a SW Australian karst, where both intra- and interannual hydrological variations are strongly controlled by seasonal variations in recharge. The hydrological behavior of cave drips is examined at daily resolution with respect to mean discharge and the flow variation. We demonstrate that the analysis of the time series produced by cave drip loggers generates useful hydrogeological information that can be applied generally.

A new product (Global Forcing Data, GFD) that provides bias-adjusted meteorological forcing data for impact models, such as hydrological models, is presented. The main novelty with the product is the near-real time updating of the data which allows more up-to-date impact modeling. This is performed by combining climatological data sets with climate monitoring data sets. The potential in using the data to initialize hydrological forecasts is further investigated.

Fractal models of regular triangle arrangement (RTA) and square pitch arrangement (SPA) are developed in this study. Results suggest RTA can cause more groundwater contamination and make remediation more difficult. In contrast, the cleanup of contaminants in aquifers with SPA is easier. This study demonstrates how microscale arrangements control contaminant migration and remediation, which is helpful in designing successful remediation schemes for subsurface contamination.

Hydrological low flows are affected under different levels of future global warming (i.e. 1.5, 2, and 3 K). The multi-model ensemble results show that the change signal amplifies with increasing warming levels. Low flows decrease in the Mediterranean, while they increase in the Alpine and Northern regions. The changes in low flows are significant for regions with relatively large change signals and under higher levels of warming. Adaptation should make use of change and uncertainty information.

Polish Institute of Meteorology and Water Management – State Research Institute (IMGW-PIB) has been conducting research on the use of river absorption capacity (RAC) for 5 years. The research focuses on combining mathematical modelling with traditional RAC calculations. For this purpose, the Macromodel DNS (discharge–nutrient–sea) was developed in the IMGW-PIB, along with the Soil Water Assessment Tool (SWAT). The study was conducted on a selected fragment of one of the largest rivers in Poland.

In this study, a screening approach was applied on a set of streamflow records for which various human influences are indicated to identify streamflow records that have drought characteristics that deviate from those expected under pristine conditions. Prolonged streamflow drought duration, a weaker correlation between streamflow and precipitation, and changes in streamflow drought occurrence over time were related to human influences such as groundwater abstractions or reservoir operations.

For a large beach nourishment called the Sand Engine we have examined the impact of groundwater recharge, tides, storm surges, and geomorphological changes on the growth of the fresh groundwater resources between 2011 and 2016. With detailed model simulations of these coastal processes we were able to get a good match with field measurements, and demonstrated the importance of wave runup and coastal erosion in studies on fresh groundwater in such dynamic coastal environments.

The study examined dynamics of DOC export from a permafrost peatland catchment located in northeastern China. The findings indicated that the DOC export is a transport-limited process and the DOC load was significant for the net carbon balance in the studied catchment. The flowpath shift process is key to observed DOC concentration, resources and chemical characteristics in discharge. Permafrost degradation would likely elevate the proportion of microbe-originated DOC in baseflow.

For realistic flood predictions, it is necessary to have accurate rainfall estimates. The Weather Research and Forecasting (WRF) model is often used to correctly simulate heavy rainfall events, but setting up the model over a region is a challenging task. In this study, the sensitivity of the WRF model is assessed for physics schemes, parameterization options, land surface models and downscaling ratios, by simulating several extreme rainfall events in the Ganges basin.

The following study extends existing irrigation maps based on official reports. The main idea was to extend the reported irrigated areas using agricultural suitability data and compare them with remote sensing information about plant conditions. The analysis indicates an increase in irrigated land by 18 % compared to the reported statistics. The additional areas are mainly identified within already known irrigated regions where irrigation is more dense than previously estimated.

This paper is motivated by the need for more precise evaporation rates from the Dead Sea (DS) and methods to estimate and forecast evaporation. A new approach to measure lake evaporation with a station located at the shoreline, also transferable to other lakes, is introduced. The first directly measured DS evaporation rates are presented as well as applicable methods for evaporation calculation. These results enable us to further close the DS water budget and to facilitate the water management.

This article presents predictability analyses of snow accumulation for the upcoming winter season. The results achieved using two coupled atmosphere–ocean general circulation models and a water balance model show that the tendency of snow water equivalent anomalies (i.e. the sign of anomalies) is correctly predicted in up to 11 of 13 years. The results suggest that some seasonal predictions may be capable of predicting tendencies of hydrological model storages in parts of Europe.

River water-quality time series often exhibit fractal scaling, which here refers to autocorrelation that decays as a power law over some range of scales. This paper provides a comprehensive overview of the various approaches for quantifying fractal scaling in irregularly sampled data and provides new understanding and quantification of the methods’ performances. More generally, the findings and approaches may be broadly applicable to irregularly sampled data in other scientific disciplines.

Water flows through soils with more difficulty when the soil is dried out. Scant rainfall in deserts may therefore result in a seemingly wet soil, but the water will often not penetrate deeply enough to replenish the groundwater. We compared the mathematical functions that describe how well different soils hold their water and found that only a few of them are realistic. The function one chooses to model the soil can have a large impact on the estimate of groundwater recharge.

We investigate the impact of wildfire on watershed flow regimes, examining responses across the western United States. On a national scale, our results confirm the work of prior studies: that low, high, and peak flows typically increase following a wildfire. Regionally, results are more variable and sometimes contradictory. Our results may be significant in justifying the calibration of watershed models and in contributing to the overall observational analysis of post-fire streamflow response.

This study analyzes the influence of local and regional meteorological factors on the isotopic composition of precipitation. The impact of the different factors on the isotopic condition was quantified by multiple linear regression of all factor combinations combined with relative importance analysis. The proposed approach might open a pathway for the improved reconstruction of paleoclimates based on isotopic records.

In this paper, stochastically generated rainfall and corresponding evapotranspiration time series, generated by means of vine copulas, are used to force a simple conceptual hydrological model. The results obtained are comparable to the modelled discharge using observed forcing data. Yet, uncertainties in the modelled discharge increase with an increasing number of stochastically generated time series used. Still, the developed model has great potential for hydrological impact analysis.

Agrivoltaism is the association of agricultural and photovoltaic energy production on the same land area, coping with the increasing pressure on land use and water resources while delivering clean and renewable energy. This paper shows how to operate the tilting-angle solar panels tested above the cultivated plots to remedy the often unexplored rain redistribution issues, by which large parts of the plot are sheltered, whereas concentrated fluxes are redirected on a few locations.

Satellite data offer great opportunities to improve spatial model predictions by means of spatially oriented model evaluations. In this study, satellite images are used to observe spatial patterns of evapotranspiration at the land surface. These spatial patterns are utilized in combination with streamflow observations in a model calibration framework including a novel spatial performance metric tailored to target the spatial pattern performance of a catchment-scale hydrological model.

We present a new global ET dataset and associated uncertainty with monthly temporal resolution for 2000–2009 and 0.5 grid cell size. Six existing gridded ET products are combined using a weighting approach trained by observational datasets from 159 FLUXNET sites. We confirm that point-based estimates of flux towers provide information at the grid scale of these products. We also show that the weighted product performs better than 10 different existing global ET datasets in a range of metrics.

This paper reviews a relevant social science that links cultural factors to environmental decision-making and assesses how to better incorporate its insights to enhance sociohydrological (SH) models and the knowledge gaps that remain to be filled. The paper concludes with a discussion of challenges and opportunities in terms of generalization of SH models and the use of available data to facilitate future prediction and allow model transfer to ungauged basins.

In an effort to apply cloud-tolerant microwave data to satellite-based monitoring of evapotranspiration (ET), this study reports on an experiment where microwave-based land surface temperature is used as the key diagnostic input to a two-source energy balance method for the estimation of ET. Comparisons of this microwave ET with the conventional thermal infrared estimates show widespread agreement in spatial and temporal patterns from seasonal to inter-annual timescales over Africa and Europe.

This study investigates the use of a nonparametric model for combining multiple global precipitation datasets and characterizing estimation uncertainty. Inputs to the model included three satellite precipitation products, an atmospheric reanalysis precipitation dataset, satellite-derived near-surface daily soil moisture data, and terrain elevation. We evaluated the technique based on high-resolution reference precipitation data and further used generated ensembles to force a hydrological model.

This work quantifies how future land-use and climate change may affect the hydrology of the Upper Ganges basin. Three sets of modelling experiments are run for the period 2000–2035, considering (1) only climate change, (2) only land-use change and (3) both climate and land-use change. Results point towards a severe increase in high flows. The changes are greater in the combined land-use and climate change experiment. We also show that future winter water demands in the region may not be met.

Due to the effects of wind, precipitation gauges typically underestimate the amount of precipitation that occurs as snow. Measurements recorded during a World Meteorological Organization intercomparison of precipitation gauges were used to evaluate and improve the adjustments that are available to address this issue. Adjustments for specific types of precipitation gauges and wind shields were tested and recommended.

In this study, we integrate free, global Earth observations in a user-friendly and flexible model to reliably characterize an otherwise unmonitored river basin. The proposed model is the best baseline characterization of the Ogooué basin in light of available observations. Furthermore, the study shows the potential of using new, publicly available Earth observations and a suitable model structure to obtain new information in poorly monitored or remote areas and to support user requirements.

Citizens can contribute to science by providing data, analysing them and as such contributing to decision-making processes. For example, citizens have collected water levels from gauges, which are important when simulating/forecasting floods, where data are usually scarce. This study reviewed such contributions and concluded that integration of citizen data may not be easy due to their spatio-temporal characteristics but that citizen data still proved valuable and can be used in flood modelling.

Backward erosion piping is the cause of a significant percentage of failures and incidents involving dams and river embankments. In the past 20 years fibre-optic Distributed Temperature Sensing (DTS) has proved to be effective for the detection of leakages and internal erosion in dams. This work investigates the effectiveness of DTS for monitoring backward erosion piping in river embankments. Data from a large-scale piping test performed on an instrumented dike are presented and discussed.

The paper aims to infer the bulk electrical conductivity distribution in the root zone from EMI readings. TDR measurements were used as ground-truth data to evaluate the goodness of the estimations by EMI inversion. The approach is based on the mean and standard deviation of the EMI and TDR series. It looks for the physical reasons for the differences between EMI- and TDR-based electrical conductivity and provides a correction of the bias based on the statistical sources of the discrepancies.

In changing environments, extreme low-flow events are expected to increase. Frequency analysis of low-flow events considering the impacts of changing environments has attracted increasing attention. This study developed a frequency analysis framework by applying 11 indices to trace the main causes of the change in the annual extreme low-flow events of the Weihe River. We showed that the fluctuation in annual low-flow series was affected by climate, streamflow recession and irrigation area.

Understanding water infiltration in karst regions is crucial as the aquifers they host provide drinkable water for a quarter of the world's population. We present a non-invasive tool to image hydrological processes in karst systems. At our field site, the injection of electrical current in the ground, repeated daily over a 3-year period, allowed imaging changes in the groundwater content. We show that specific geological layers control seasonal to rainfall-triggered water infiltration dynamics.

Climate change effects on snow, glaciers, and hydrology are investigated for the Ötztal Alps region (Austria) using a hydroclimatological model driven by climate projections for the RCP2.6, RCP4.5, and RCP8.5 scenarios. The results show declining snow amounts and strongly retreating glaciers with moderate effects on catchment runoff until the mid-21st century, whereas annual runoff volumes decrease strongly towards the end of the century.

Rainfall forecasts from dynamical global climate models (GCMs) require post-processing before use in hydrological models. Existing methods generally lack the sophistication to achieve calibrated forecasts of both daily amounts and seasonal accumulated totals. We develop a new statistical method to post-process Australian GCM rainfall forecasts for 12 perennial and ephemeral catchments. Our method produces reliable forecasts and outperforms the most commonly used statistical method.

This article tackles the problem of finding the origin of groundwater in basin aquifers adjacent to mountains. In particular, we aim to determine whether the recharge occurs predominantly through stream infiltration along the mountain front or through subsurface flow from the mountain. To this end, we discuss the use of routinely measured variables: hydraulic head, chloride and electrical conductivity. A case study from Australia demonstrates the approach.