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KLIMAWANDEL UND FLIESSGEWÄSSERTEMPERATUREN: ANALYSE DER VERÄNDERUNGEN IN DEN LETZTEN 50 JAHREN UND DER FÜR DIE ZUKUNFT ERWARTETEN VERÄNDERUNGEN Die Wassertemperatur ist einer der Schlüsselparameter für aquatische Ökosysteme und flussbezogene Aktivitäten des Menschen. Im Zuge des Klimawandels verändern sich die Wassertemperaturen. Wir präsentieren hier die Ergebnisse von Analysen zur Entwicklung der Fliessgewässertemperaturen in der Schweiz in den letzten 50 Jahren und Prognosen für das 21. Jahrhundert. Diese zeigen, dass die Wassertemperaturen in Schweizer Fliessgewässern bereits deutlich angestiegen sind – mit einem Mittelwert von +0,33 °C pro Jahrzehnt seit 1979 und jeweils einer markanteren Erwärmung im Sommer. Dieser Anstieg wirkte sich bereits nachweisbar auf die Ausbreitung von Fischkrankheiten aus. Zudem wird der gesetzliche Grenzwert, der in der Schweiz für die Verwendung von Wasser zu Kühlzwecken gilt, immer häufiger erreicht. Auch mit den ambitioniertesten Klimaschutzszenarien ist ein durchschnittlicher Anstieg der Flusstemperaturen von knapp über 1 °C bis 2035 unvermeidbar. Ohne Klimaschutzmassnahmen könnte dieser Anstieg bis zum Ende des Jahrhunderts im Jahresdurchschnitt 3,5 °C und in den Alpenflüssen im Sommer bis zu 6 °C betragen. Dieser Artikel fasst die wichtigsten Ergebnisse des BAFU-Forschungsprojekts Hydro-CH2018 und des ergänzenden Moduls «Veränderung der Wassertemperatur in Flüssen und Seen unter dem Einfluss des Klimawandels» [14, 15] zusammen. Ausgewählte Ergebnisse wurden ebenfalls in wissenschaftlichen Fachzeitschriften veröffentlicht [16–19]. Die Ergebnisse einer zweiten Studie, die im Rahmen des BAFU-Forschungsprojekts Hydro-CH2018 im Zusatzmodul «Aktueller Stand und Temperaturentwicklung der Schweizer Lockergesteinsgrundwasservorkommen» durchgeführt wurde, sind im Artikel «Klimawandel und Grundwassertemperaturen» in dieser Ausgabe (S. 7) zusammengefasst., La température des cours d’eau est l’une des variables les plus importantes pour les écosystèmes aquatiques et pour les activités humaines dépendantes des rivières. Dans le contexte actuel de changements climatiques, ces températures évoluent. Nous présentons ici les résultats de travaux portant sur l’évolution de la température des rivières en Suisse durant les 50 dernières années ainsi que sur des projections pour le XXI e siècle.

Spatial rainfall patterns exert a key control on the catchment-scale hydrologic response. Despite recent advances in radar-based rainfall sensing, rainfall observation remains a challenge, particularly in mountain environments. This paper analyzes the importance of high-density rainfall observations for a 13.4 km2 catchment located in the Swiss Alps, where rainfall events were monitored during 3 summer months using a network of 12 low-cost, drop-counting rain gauges. We developed a data-based analysis framework to assess the importance of high-density rainfall observations to help predict the hydrological response. The framework involves the definition of spatial rainfall distribution metrics based on hydrological and geomorphological considerations and a regression analysis of how these metrics explain the hydrologic response in terms of runoff coefficient and lag time. The gained insights on dominant predictors are then used to investigate the optimal rain gauge network density for predicting the streamflow response metrics, including an extensive test of the effect of down-sampled rain gauge networks and an event-based rainfall–runoff model to evaluate the resulting optimal rain gauge network configuration. The analysis unravels that, besides rainfall amount and intensity, the rainfall distance from the outlet along the stream network is a key spatial rainfall metric. This result calls for more detailed observations of stream network expansions and the parameterization of along-stream processes in rainfall–runoff models. In addition, despite the small spatial scale of this case study, the results show that an accurate representation of the rainfall field (with at least three rain gauges) is of prime importance for capturing the key characteristics of the hydrologic response in terms of generated runoff volumes and delay for the studied catchment (0.22 rain gauges per square kilometer). The potential of the developed rainfall monitoring and analysis framework for rainfall–runoff analysis in small catchments remains to be fully unraveled in future studies, potentially also including urban catchments.

This study evaluates the impacts of climate change on water resources of the Volta River basin located in West Africa. In total, 43 combinations of global climate models (GCM) and five regional climate models (RCM) from CORDEX- Africa are considered under three representative concentration pathways (RCP2.6, RCP4.5 and RCP8.5). The R2D2 multivariate bias correction method is applied to the climate datasets before using them as input to the fully distributed Hydrologic Model (mHM) for hydrological projections over the twenty-first century. The mHM model is constrained with a novel multivariate calibration approach based on the spatial patterns of satellite remote sensing data (Dembélé et al., 2020). Results reveal contrasting changes in the seasonality of precipitation depending on the RCPs and the future projection periods (2021-2050, 2051-2080 and 2071-2100) as compared to the historical period (1991-2020), while a clear increase in the seasonality of temperature is expected. A clear intensification of the hydrological cycle during the twenty-first century is expected only under the RCP8.5 scenario. In this case, an increase is foreseen for the long-term annual estimates of precipitation (+6.2%), average temperature (+9.5%) and potential evaporation (+5.0%). These changes in climatic variables will lead to changes in actual evaporation (+4.2%), surface runoff (+42%), streamflow (+84%), groundwater recharge (+37%), soil moisture (+2.3%) and terrestrial water storage (+3.2%). Consequently, recurrent floods and droughts could weaken the water-energy-food security nexus and amplify the vulnerability of the local population to climate change. These findings could serve as a guideline for decision makers, and contribute to the elaboration of adaptation and mitigation strategies to cope with dramatic consequences of climate change on various sectors including agriculture and hydroelectricity, and strengthen the regional socio-economic development. REFERENCES Dembélé, M., M. Hrachowitz, H. H. G. Savenije, G. Mariéthoz, and B. Schaefli (2020b), Improving the Predictive Skill of a Distributed Hydrological Model by Calibration on Spatial Patterns With Multiple Satellite Data Sets, Water Resources Research, 56(1), https://doi.org/10.1029/2019wr026085.

This study evaluates the ability of different gridded rainfall datasets to plausibly represent the spatio-temporal patterns of multiple hydrological processes (i.e. streamflow, actual evaporation, soil moisture and terrestrial water storage) for large-scale hydrological modelling in the predominantly semi-arid Volta River basin (VRB) in West Africa. Seventeen precipitation products based essentially on gauge-corrected satellite data (TAMSAT, CHIRPS, ARC, RFE, MSWEP, GSMaP, PERSIANN-CDR, CMORPH-CRT, TRMM 3B42 and TRMM 3B42RT) and on reanalysis (ERA5, PGF, EWEMBI, WFDEI-GPCC, WFDEI-CRU, MERRA-2 and JRA-55) are compared as input for the fully distributed mesoscale Hydrologic Model (mHM). To assess the model sensitivity to meteorological forcing during rainfall partitioning into evaporation and runoff, six different temperature reanalysis datasets are used in combination with the precipitation datasets, which results in evaluating 102 combinations of rainfall-temperature input data. The model is recalibrated for each of the 102 input combinations, and the model responses are evaluated by using in situ streamflow data and satellite remote-sensing datasets from GLEAM evaporation, ESA CCI soil moisture and GRACE terrestrial water storage. A bias-insensitive metric is used to assess the impact of meteorological forcing on the simulation of the spatial patterns of hydrological processes. The results of the process-based evaluation show that the rainfall datasets have contrasting performances across the four climatic zones present in the VRB. The top three best-performing rainfall datasets are TAMSAT, CHIRPS and PERSIANN-CDR for streamflow; ARC, RFE and CMORPH-CRT for terrestrial water storage; MERRA-2, EWEMBI/WFDEI-GPCC and PGF for the temporal dynamics of soil moisture; MSWEP, TAMSAT and ARC for the spatial patterns of soil moisture; ARC, RFE and GSMaP-std for the temporal dynamics of actual evaporation; and MSWEP, TAMSAT and MERRA-2 for the spatial patterns of actual evaporation. No single rainfall or temperature dataset consistently ranks first in reproducing the spatio-temporal variability of all hydrological processes. A dataset that is best in reproducing the temporal dynamics is not necessarily the best for the spatial patterns. In addition, the results suggest that there is more uncertainty in representing the spatial patterns of hydrological processes than their temporal dynamics. Finally, some region-tailored datasets outperform the global datasets, thereby stressing the necessity and importance of regional evaluation studies for satellite and reanalysis meteorological datasets, which are increasingly becoming an alternative to in situ measurements in data-scarce regions..

Informed water management critically relies on timely quantified and reliable information, which allows decision makers to design and implement sound policies to cope with water scarcity and sustain water security. Water accounting frameworks are useful tools for reporting on water resources availability and uses. Here, we combine the Water Accounting Plus (WA+) framework with hydrological modelling and climate change scenarios to quantify current and future conditions of water resources in the Volta River basin located in West Africa. Hydrological processes derived from the fully distributed mesoscale Hydrologic Model (mHM) are fed into the WA+ framework to provide a comprehensive report on the current state and future trends of water resources. mHM is used to predict water fluxes, stocks and flows for the historical period 1999-2020 and the near future (2021-2050). Climate change projection datasets are obtained from a large ensemble of nine global climate models (GCMs) and four regional climate models (RCMs) under the emission scenario RCP8.5. The WA+ report shows that the long-term net inflow in the basin over the period 1991-2020 is 389 km3/year and is projected to increase by 5% in the near future. However, only 8% of the net inflow is exploitable as “blue water”, while the remainder is consumed as “green water”, mainly in non-managed lands. The available water for various water uses in the basin amounts to 15 km3/year, of which 79% is utilized, while the remainder 21% is utilizable but not consumed. Only 42% of water use is beneficial for the intended purposes, with agriculture responsible for 35% of the beneficial water consumption. Future projections show an increase of 20% in the exploitable water fraction, while the available water fraction is expected to decrease by 5%. These findings show that climate change could disproportionally affect the exploitable and the available water, thereby calling for adaptation measures by the local authorities in the Volta River basin.