2021, Bolch, Tobias, Duethmann, Doris, Wortmann, Michel, Liu, Shiyin, Disse, Markus

Tarim River basin is the largest endorheic river basin in China. Due to the extremely arid climate the water supply solely depends on water originating from the glacierised mountains with about 75% stemming from the transboundary Aksu River. The water demand is linked to anthropogenic (specifically agriculture) and natural ecosystems, both competing for water. Ongoing climate change significantly impacts the cryosphere. The mass balance of the glaciers in Aksu River basin was clearly negative since 1975. The discharge of the Aksu headwaters has been increasing over the last decades mainly due to the glacier contribution. The average glacier melt contribution to total runoff is 30–37% with an estimated glacier imbalance contribution of 8–16%. Modelling using future climate scenarios indicate a glacier area loss of at least 50% until 2100. River discharge will first increase concomitant with glacier shrinkage until about 2050, but likely decline thereafter. The irrigated area doubled in the Aksu region between the early 1990s and 2020, causing at least a doubling of water demand. The current water surplus is comparable to the glacial runoff. Hence, even if the water demand will not grow further in the future a significant water shortage can be expected with declining glacial runoff. However, with the further expansion of irrigated agriculture and related industries, the water demand is expected to even further increase. Both improved discharge projections and planning of efficient and sustainable water use are necessary for further socioeconomic development in the region along with the preservation of natural ecosystems.

2020, Ismail, Muhammad Fraz, Naz, Bibi S., Wortmann, Michel, Disse, Markus, Bowling, Laura C., Bogacki, Wolfgang

This study performs a comparison of two model calibration/validation approaches and their influence on future hydrological projections under climate change by employing two climate scenarios (RCP2.6 and 8.5) projected by four global climate models. Two hydrological models (HMs), snowmelt runoff model + glaciers and variable infiltration capacity model coupled with a glacier model, were used to simulate streamflow in the highly snow and glacier melt–driven Upper Indus Basin. In the first (conventional) calibration approach, the models were calibrated only at the basin outlet, while in the second (enhanced) approach intermediate gauges, different climate conditions and glacier mass balance were considered. Using the conventional and enhanced calibration approaches, the monthly Nash-Sutcliffe Efficiency (NSE) for both HMs ranged from 0.71 to 0.93 and 0.79 to 0.90 in the calibration, while 0.57–0.92 and 0.54–0.83 in the validation periods, respectively. For the future impact assessment, comparison of differences based on the two calibration/validation methods at the annual scale (i.e. 2011–2099) shows small to moderate differences of up to 10%, whereas differences at the monthly scale reached up to 19% in the cold months (i.e. October–March) for the far future period. Comparison of sources of uncertainty using analysis of variance showed that the contribution of HM parameter uncertainty to the overall uncertainty is becoming very small by the end of the century using the enhanced approach. This indicates that enhanced approach could potentially help to reduce uncertainties in the hydrological projections when compared to the conventional calibration approach. © 2020, The Author(s).

2022, Gädeke, Anne, Wortmann, Michel, Menz, Christoph, Islam, AKM Saiful, Masood, Muhammad, Krysanova, Valentina, Lange, Stefan, Hattermann, Fred Fokko

The densely populated delta of the three river systems of the Ganges, Brahmaputra and Meghna is highly prone to floods. Potential climate change-related increases in flood intensity are therefore of major societal concern as more than 40 million people live in flood-prone areas in downstream Bangladesh. Here we report on new flood projections using a hydrological model forced by bias-adjusted ensembles of the latest-generation global climate models of CMIP6 (SSP5-8.5/SSP1-2.6) in comparison to CMIP5 (RCP8.5/RCP2.6). Results suggest increases in peak flow magnitude of 36% (16%) on average under SSP5-8.5 (SSP1-2.6), compared to 60% (17%) under RCP8.5 (RCP2.6) by 2070-2099 relative to 1971-2000. Under RCP8.5/SSP5-8.5 (2070-2099), the largest increase in flood risk is projected for the Ganges watershed, where higher flood peaks become the ‘new norm’ as early as mid-2030 implying a relatively short time window for adaptation. In the Brahmaputra and Meghna rivers, the climate impact signal on peak flow emerges after 2070 (CMIP5 and CMIP6 projections). Flood peak synchronization, when annual peak flow occurs simultaneously at (at least) two rivers leading to large flooding events within Bangladesh, show a consistent increase under both projections. While the variability across the ensemble remains high, the increases in flood magnitude are robust in the study basins. Our findings emphasize the need of stringent climate mitigation policies to reduce the climate change impact on peak flows (as presented using SSP1-2.6/RCP2.6) and to subsequently minimize adverse socioeconomic impacts and adaptation costs. Considering Bangladesh’s high overall vulnerability to climate change and its downstream location, synergies between climate change adaptation and mitigation and transboundary cooperation will need to be strengthened to improve overall climate resilience and achieve sustainable development.

2018, Hattermann, Fred F., Wortmann, Michel, Liersch, Stefan, Toumi, Ralf, Sparks, Nathan, Genillard, Christopher, Schröter, Kai, Steinhausen, Max, Gyalai-Korpos, Miklós, Máté, Kinga, Hayes, Ben, del Rocío Rivas López, María, Rácz, Tibor, Nielsen, Marie R., Kaspersen, Per S., Drews, Martin

Major river and flash flood events have accumulated in Central and Eastern Europe over the last decade reminding the public as well as the insurance sector that climate related risks are likely to become even more damaging and prevalent as climate patterns change. However, information about current and future hydro-climatic extremes is often not available. The Future Danube Model (FDM) is an end-user driven multi-hazard and risk model suite for the Danube region that has been developed to provide climate services related to perils such as heavy precipitation, heat waves, floods, and droughts under recent and scenario conditions. As a result, it provides spatially consistent information on extreme events and natural resources throughout the entire Danube catchment. It can be used to quantify climate risks, to support the implementation of the EU framework directives, for climate informed urban and land use planning, water resources management, and for climate proofing of large scale infrastructural planning including cost benefit analysis. The model suite consists of five individual and exchangeable modules: a weather and climate module, a hydrological module, a risk module, an adaptation module, and a web-based visualization module. They are linked in such a way that output from one module can either be used standalone or fed into subsequent modules. The utility of the tool has been tested by experts and stakeholders. The results show that more and more intense hydrological extremes are likely to occur under climate scenario conditions, e.g. higher order floods may occur more frequently.