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The hydrological budgets of the Volga basin (VB) and the Caspian Sea (CS) have been analysed. The components of the water balance for the CS were calculated for the period 1993 to 2010 with emphasis on summer 2010 when a severe drought developed over European Russia. A drop in precipitation over the VB in July 2010 occurs simultaneously with a decrease in evaporation for the same area, an increase of evaporation over the CS itself and a drop of the Caspian Sea level (CSL). The drop in the precipitation over the VB cannot lead to an instantaneous drop of the CSL because the precipitated water needs some months to reach the CS. The delay is estimated here to be 1 to 3 months for excessive precipitation in summer, longer for deficient precipitation and for winter cases. However, the evaporation over the CS itself is considered to be responsible for a simultaneous drop of the CSL from July to September 2010. The impact on the CSL from the precipitation deficit over the VB occurs in the months following the drought. The water deficit from July to September 2010 calculated from the anomalous precipitation minus evaporation over the VB would decrease the CSL by 22 cm, of which only 2 cm had been observed until the end of September (observed Volga River discharge anomaly). So the remaining drop of 20 cm can be expected in the months to follow if no other anomalies happen. In previous studies the precipitation over the VB has been identified as the main cause for CSL changes, but here from a 10 cm drop from beginning of July to end of September, 6 cm can be directly assigned to the enhanced evaporation over the CS itself and 2 cm due to reduced precipitation over the CS. Further periods with strong changes of the CSL are also investigated, which provide some estimates concerning the accuracy of the analysis data. The investigation was possible due to the new ECMWF interim reanalysis data which are used to provide data also for sensitive quantities like surface evaporation and precipitation. The comparison with independent data and the consistency between such data for calculating the water budget over the CS gives a high confidence in the quality of the data used. This investigation provides some scope for making forecasts of the CSL few months ahead to allow for mitigating societal impacts.

Surface waters are under pressure from diffuse pollution from agricultural activities, and groundwater is known to be a connection between the agricultural fields and streams. This paper is one of the first to calculate long-term in-stream concentrations of tritium, chloride, and nitrate using dynamic groundwater travel time distributions (TTDs) derived from a distributed, transient, 3D groundwater flow model using forward particle tracking. We tested our approach in the Springendalse Beek catchment, a lowland stream in the east of the Netherlands, for which we collected a long time series of chloride and nitrate concentrations (1969–2018). The Netherlands experienced a sharp decrease in concentrations of solutes leaching to groundwater in the 1980s due to legislations on the application of nitrogen to agricultural fields. Stream measurements of chloride and nitrate showed that the corresponding trend reversal in the groundwater-fed stream occurred after a time lag of 5–10 years. By combining calculated TTDs with the known history of nitrogen and chloride inputs, we found that the variable contribution of different groundwater flow paths to stream water quality reasonably explained the majority of long-term and seasonal variation in the measured stream nitrate concentrations. However, combining only TTDs and inputs underestimated the time lag between the peak in nitrogen input and the following trend reversal of nitrate in the stream. This feature was further investigated through an exploration of the model behaviour under different scenarios. A time lag of several years, and up to decades, can occur due to (1) a thick unsaturated zone adding a certain travel time, (2) persistent organic matter with a slow release of N in the unsaturated zone, (3) a long mean travel time (MTT) compared to the rate of the reduction in nitrogen application, (4) areas with a high application of nitrogen (agricultural fields) being located further away from the stream or drainage network, or (5) a higher presence of nitrate attenuating processes close to the stream or drainage network compared to the rest of the catchment. By making the connection between dynamic groundwater travel time distributions and in-stream concentration measurements, we provide a method for validating the travel time approach and make the step towards application in water quality modelling and management.

Soil erosion/sedimentation is an immense problem that has threatened water resources development in the Nile river basin, particularly in the Eastern Nile (Ethiopia, Sudan and Egypt). An insight into soil erosion/sedimentation mechanisms and mitigation methods plays an imperative role for the sustainable water resources development in the region. This paper presents daily sediment yield simulations in the Upper Blue Nile under different Best Management Practice (BMP) scenarios. Scenarios applied in this paper are (i) maintaining existing conditions, (ii) introducing filter strips, (iii) applying stone bunds (parallel terraces), and (iv) reforestation. The Soil and Water Assessment Tool (SWAT) was used to model soil erosion, identify soil erosion prone areas and assess the impact of BMPs on sediment reduction. For the existing conditions scenario, the model results showed a satisfactory agreement between daily observed and simulated sediment concentrations as indicated by Nash-Sutcliffe efficiency greater than 0.83. The simulation results showed that applying filter strips, stone bunds and reforestation scenarios reduced the current sediment yields both at the subbasins and the basin outlets. However, a precise interpretation of the quantitative results may not be appropriate because some physical processes are not well represented in the SWAT model.

Surface waters are under pressure of diffuse pollution from agricultural activities and groundwater is known to be a connection between the agricultural fields and streams. We calculated in-stream concentrations by coupling input curves for tritium, chloride and nitrate with dynamic groundwater travel time distributions (TTDs) derived from a distributed, transient 3D groundwater flow model using forward particle tracking. We tested our approach in a lowland stream and found that the variable contribution of different groundwater flow paths to stream water quality reasonably explained the majority of long-term and seasonal variation in the measured stream nitrate concentrations. A sensitivity analysis was done to study the breakthrough of agricultural nitrate and it was found that an unsaturated zone, increased mean travel time and a longer distance between agricultural fields and stream cause a lag in the breakthrough of agricultural solutes. Similarly, the recovery of concentrations after measures that aim to reduce the solute inputs is determined by these parameters, with combinations of slow reduction rates and long MTT tending to result in considerable lag times after start of the reductions. We labelled the part of the catchment area where the seepage water infiltrated that contributes to stream discharge at a certain moment in time the groundwater contributing area. This groundwater contributing area was shown to increase and shrink based on wetness conditions within the catchment. Especially the location of agricultural fields in the groundwater contributing area in relation to the catchments’ drainage network was found to be an important factor that largely governs the travel times of the agricultural pollutants. We conclude that groundwater functions as a buffer on the effect of agricultural pollution, by distributing water in time and space and making it possible for different waters to mix.

Availability of in situ river monitoring data, especially of data shared across boundaries, is decreasing, despite growing challenges for water resource management across the entire globe. This is especially valid for the case study of this work, the Brahmaputra Basin in South Asia. Commonly, satellite altimeters are used in various ways to provide information about such river basins. Most missions provide virtual station time series of water levels at locations where their repeat orbits cross rivers. CryoSat-2 is equipped with a new type of altimeter, providing estimates of the actual ground location seen in the reflected signal. It also uses a drifting orbit, challenging conventional ways of processing altimetry data to river water levels and their incorporation in hydrologic–hydrodynamic models. However, CryoSat-2 altimetry data provides an unprecedentedly high spatial resolution. This paper suggests a procedure to (i) filter CryoSat-2 observations over rivers to extract water-level profiles along the river, and (ii) use this information in combination with a hydrologic–hydrodynamic model to fit the simulated water levels with an accuracy that cannot be reached using information from globally available digital elevation models (DEMs) such as from the Shuttle Radar Topography Mission (SRTM) only. The filtering was done based on dynamic river masks extracted from Landsat imagery, providing spatial and temporal resolutions high enough to map the braided river channels and their dynamic morphology. This allowed extraction of river water levels over previously unmonitored narrow stretches of the river. In the Assam Valley section of the Brahmaputra River, CryoSat-2 data and Envisat virtual station data were combined to calibrate cross sections in a 1-D hydrodynamic model of the river. The hydrologic–hydrodynamic model setup and calibration are almost exclusively based on openly available remote sensing data and other global data sources, ensuring transferability of the developed methods. They provide an opportunity to achieve forecasts of both discharge and water levels in a poorly gauged river system.