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A novel approach for estimating precipitation patterns is developed here and applied to generate a new hydrologically corrected daily precipitation dataset, called RAIN4PE (Rain for Peru and Ecuador), at 0.1° spatial resolution for the period 1981–2015 covering Peru and Ecuador. It is based on the application of 1) the random forest method to merge multisource precipitation estimates (gauge, satellite, and reanalysis) with terrain elevation, and 2) observed and modeled streamflow data to first detect biases and second further adjust gridded precipitation by inversely applying the simulated results of the ecohydrological model SWAT (Soil and Water Assessment Tool). Hydrological results using RAIN4PE as input for the Peruvian and Ecuadorian catchments were compared against the ones when feeding other uncorrected (CHIRP and ERA5) and gauge-corrected (CHIRPS, MSWEP, and PISCO) precipitation datasets into the model. For that, SWAT was calibrated and validated at 72 river sections for each dataset using a range of performance metrics, including hydrograph goodness of fit and flow duration curve signatures. Results showed that gauge-corrected precipitation datasets outperformed uncorrected ones for streamflow simulation. However, CHIRPS, MSWEP, and PISCO showed limitations for streamflow simulation in several catchments draining into the Pacific Ocean and the Amazon River. RAIN4PE provided the best overall performance for streamflow simulation, including flow variability (low, high, and peak flows) and water budget closure. The overall good performance of RAIN4PE as input for hydrological modeling provides a valuable criterion of its applicability for robust countrywide hydrometeorological applications, including hydroclimatic extremes such as droughts and floods. Significance Statement: We developed a novel precipitation dataset RAIN4PE for Peru and Ecuador by merging multisource precipitation data (satellite, reanalysis, and ground-based precipitation) with terrain elevation using the random forest method. Furthermore, RAIN4PE was hydrologically corrected using streamflow data in watersheds with precipitation underestimation through reverse hydrology. The results of a comprehensive hydrological evaluation showed that RAIN4PE outperformed state-of-the-art precipitation datasets such as CHIRP, ERA5, CHIRPS, MSWEP, and PISCO in terms of daily and monthly streamflow simulations, including extremely low and high flows in almost all Peruvian and Ecuadorian catchments. This underlines the suitability of RAIN4PE for hydrometeorological applications in this region. Furthermore, our approach for the generation of RAIN4PE can be used in other data-scarce regions. [ABSTRACT FROM AUTHOR]

Droughts and resulting low flows are a threat for society, economy, and ecosystems. Droughts are natural phenomena, but anthropogenic water use can increase the pressure on water resources. To analyze the effects of changing land-use or water management and climate variability/change on water resources, models integrating the most important hydrological processes are needed. These models must account for natural processes and water resources management at different spatial and temporal scales, e.g., reservoir operation, water withdrawals. Low flow indices are analyzed for observed and simulated flows for the highly managed São Francisco river basin in Brazil, showing that during wet, normal, and moderately dry years, the existing reservoir system is able to augment low flows while during strong droughts the system reaches its limits. This effect is also represented in the simulations using the eco-hydrological model SWIM, which was adapted to account for regionspecific characteristics of land-use and water management. While good to very good performance was achieved for calibration and validation for most gauges, for some gauges at tributaries only insufficient quantitative criteria are reached. The reasons for the deviation between observations and simulation results are discussed. Overall, the model is able to represent natural discharges and observed, managed discharges. [ABSTRACT FROM AUTHOR]

The Tagus River basin is an ultimately important water source for hydropower production, urban and agricultural water supply in Spain and Portugal. Growing electricity and water supply demands, over-regulation of the river and construction of new dams, as well as large inter-basin and intra-basin water transfers aggravated by strong natural variability of climate in the catchment, have already imposed significant pressures on the river. The substantial reduction of discharge is observed already now, and projected climatic change is expected to alter the water budget of the catchment further.In this study, we address the effects of projected climate change on the water resources availability in the Tagus River basin and influence of potential changes on hydropower generation of the three important reservoirs in the basin. The catchment-scale, process-based eco-hydrological model soil and water integrated model was set up, calibrated and validated for the entire Tagus River basin, taking into account 15 large reservoirs in the catchment. The future climate projections were selected from those generated within the Inter-Sectoral Impact Model Intercomparison Project. They include five bias-corrected climatic datasets for the region, obtained from global circulation model runs under two emissions scenario - moderate and extreme ones - and covered the whole century. The results show a strong agreement among model runs in projecting substantial decrease of discharge of the Tagus River discharge and, consequently, a strong decrease in hydropower production under both future climate scenarios. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Information about the potential impacts of climate change on river runoff is needed to prepare efficient adaptation strategies. This study presents scenario projections for the future hydrological runoff regime in the Danube River Basin. The eco-hydrological watershed model Soil and Water Integrated Model (SWIM) was applied for the entire Danube River catchment, considering 1224 subbasins. After calibration and validation of the model, a set of high-resolution climate projections (bias-corrected and non-bias-corrected) served as meteorological drivers with which future daily river discharge under different climate warming scenario conditions was simulated. Despite existing uncertainties, robust trends could be identified. In the next 30 years, the seasonal stream-flow regime of the Danube and its tributaries is projected to change considerably. Our results show a general trend towards a decrease in summer runoff for the whole Danube basin and, additionally, in autumn runoff for the Middle and Lower Danube basin, aggravating the existing low flow periods. For the winter and early spring seasons, mainly January-March, an increase in river runoff is projected. Greater uncertainties show up in particular for winter runoff in the Dinaric Alps and the Lower Danube basin. The existing trends become very distinct until the end of the 21st century, especially for snow-influenced river regimes. [ABSTRACT FROM AUTHOR]

The present study is aimed to: (a) project future low flow conditions in the five largest river basins in Germany, and (b) to account for the projections uncertainties. The eco-hydrological model SWIM was driven by different regional climate models (REMO, CCLM, and Wettreg) to simulate daily river discharges in each study basin. The 50-year low flow was estimated for the period 1961 to 2000, and its return period was assessed for two scenario periods, 2021-2060 and 2061-2100, using the generalized extreme value distribution. The 50-year low flow is likely to occur more frequently in western, southern, and parts of central Germany after 2061, as suggested by more than or equal to 80% of the model runs. The current low flow period (from August to September) may be extended until late autumn at the end of this century. The return period of 50-year deficit volume shows a similar temporal and spatial pattern of change as for the low flow, indicating slightly less severe conditions with lower confidence. When compared with flood projections for the same area using the same models, the severer low flows projected in this study appear more pronounced, consistent, and have lower uncertainty. [ABSTRACT FROM AUTHOR]

A spatially differentiated, management-revised projection of natural water availability up to 2053 was requested for a basin-wide scenario study about the impact of global change in the Elbe River basin. Detailed discharge and weather information of the recent years 1951-2003 were available for model calibration and validation. However, the straightforward 'classic' approach of calibrating a hydrological model on observed data and running it with a climate scenario could not be taken, because most observed river runoffs in Central Europe are modified by human management. This paper reports how the problem was addressed and how a major projection bias could be avoided. The eco-hydrological model SWIM was set up to simulate the discharge dynamics on a daily time step. The simulation area of 134,890 km² was divided into 2,278 sub-basins that were subdivided into more than 47,500 homogeneous landscape units (hydrotopes). For each hydrotope, plant growth and water fluxes were simulated while river routing calculation was based on the sub-basin structure. The groundwater module of SWIM had to be extended for accurate modelling of low flow periods. After basin-scale model calibration and revisions for known effects of lignite mining and water management, evapotranspiration and groundwater dynamics were adjusted individually for more than 100 sub-areas largely covering the entire area. A quasi-natural hydrograph was finally derived for each sub-area taking into account management data for the years 2002 (extremely wet) and 2003 (extremely dry). The validated model was used to access the effect of two climate change scenarios consisting of 100 realisations each and resembling temperature increases of 2 and 3 K, respectively. Additionally, four different land use scenarios were considered. In all scenario projections, discharge decreases strongly: The observed average discharge rate in the reference period 1961-1990 is 171 mm/a, and the scenario projections for the middle of the twenty-first century give 91-110 mm/a, mainly depending on the climate scenario. The area-averaged evapotranspiration increases only marginally within the scenario period, e.g., from about 570 to about 580 mm/a for the temperature increase of 2 K, while potential evapotranspiration increases considerably from about 780 to more than 900 mm/a. Both discharge and evapotranspiration changes vary strongly within the basin, correlating with elevation. The runoff coefficient that globally decreases from 0.244 to 0.160 in the 2 K scenario is locally governed primarily by land use; 68% of the variance of the decreases can be attributed to this factor. [ABSTRACT FROM AUTHOR]