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Geomorphologists have long debated the relative importance of disturbance magnitude, duration and frequency in shaping landscapes; for channel change during single floods, it is thought that flood duration, rather than magnitude, matters most. However, studies of flood-induced channel change have often drawn upon small datasets. By using satellite data to track channel adjustment during floods, we can now query these classic hypotheses with large datasets, and we do so here by combining 7 years of Sentinel-2 images with daily flow data from laterally active rivers. Using Earth Engine, we apply automated algorithms to map river planforms and detect their lateral shifting, and we generate a large dataset to quantify channel change during ~1000 flood events in gauged rivers across New Zealand and the Americas. We draw upon this dataset to evaluate how characteristics of the flood hydrograph (including magnitude, duration, and integrated sediment transport) correlate with the degree of geomorphic change observed. Finally, we examine the potential of predictive models for geomorphic change during floods, and consider the variables that moderate this relation between flood character and geomorphic change.

River bifurcations, multi-thread rivers and artificial channels are not commonly included in global river networks, as they defy the gravity flow assumption elevation-derived networks are based on (e.g. HydroSheds, MERIT Hydro). Yet, these natural and artificial river divergences are important features of the global river drainage system and matter greatly at local to regional scales for various riverine risk assessments. For example, large river deltas are often highly populated regions, in part because of the rivers’ many distributaries. Representing these diverging flows in global river networks will greatly improve the accuracy of many river-based geoscience applications, such as flood forecasting, water availability and quality simulations, or riverine habitat mapping. We developed a vector-based, global river network that not only represents the tributary components of the global drainage network but also the distributary ones, including multi-thread rivers, canals and delta distributaries. We achieve this by merging a 30m, Landsat-based river mask with elevation-generated streams to ensure a homogeneous drainage density outside of the river mask (rivers narrower than approx. 30m). Crucially, this is the first global hydrography derived from a global 30m digital terrain model (FABDEM, based on Copernicus DEM) that shows greater accuracy over the traditionally used SRTM derivatives. OpenStreetMap river centrelines are used to increase the accuracy of the network outside of the river mask. After vectorisation and pruning, directionality is assigned by a combination of elevation, flow angle and continuity approaches. The new global network and its attributes are validated using gauging stations, reference river networks and randomised manual checks. The new network represents ~18 million km of streams and rivers with drainage areas greater than 50km2 and includes ~58 thousand. bifurcations in rivers wider than 30m. The hydrography includes vector river segments, sub-1km reaches and catchments as well as 30m flow direction and accumulation rasters. With the advent of hyper-resolution modelling in the geosciences at the regional and global scale, we expect this river network to be relevant to a broad range of applications in flood protection, hydrology, ecology, fluvial geomorphology and others. The network has been developed as part of the NERC-funded EvoFlood project and will be used to improve global flood models.

Geomorphologists have long debated the relative importance of disturbance magnitude, duration and frequency in shaping landscapes. For river-channel adjustment during floods, some argue that cumulative flood ‘power’, rather than magnitude or duration, matters most. However, studies of flood-induced river-channel change often draw upon small datasets. Here, we combine Sentinel-2 imagery with flow data from laterally-active rivers to address this question using a larger dataset. We apply automated algorithms in Google Earth Engine to map rivers and detect their lateral shifting; we generate a large dataset to quantify channel change during 160 floods across New Zealand, Russia, and South America. Widening during these floods is best explained by their duration and cumulative hydrograph. We use a random forest regression model to predict flood-induced channel widening, with potential applications for hazard management. Ultimately, better global data on sediment supply and caliber would help us to understand flood-driven change to river planforms.

This study was conducted within the project SuMaRiO (Sustainable Management of River Oases along the Tarim River; http://www.sumario.de/), funded by the German Federal Ministry of Education and Research (BMBF grants 01LL0918J, 01LL0918I and 01LL0918B). T. Bolch acknowledges funding by Deutsche Forschungsgemeinschaft (DFG, BO3199/2–1). Open Access funding enabled and organized by Projekt DEAL. Glacierised river catchments are highly sensitive to climate change, while large populations may depend on their water resources. The irrigation agriculture and the communities along the Tarim River, NW China, strongly depend on the discharge from the glacierised catchments surrounding the Taklamakan Desert. While recent increasing discharge has been beneficial for the agricultural sector, future runoff under climate change is uncertain. We assess three climate change scenarios by forcing two glacio-hydrological models with output of eight general circulation models. The models have different glaciological modelling approaches but were both calibrated to discharge and glacier mass balance observations. Projected changes in climate, glacier cover and river discharge are examined over the twenty-first century and generally point to warmer and wetter conditions. The model ensemble projects median temperature and precipitation increases of + 1.9–5.3 °C and + 9–24%, respectively, until the end of the century compared to the 1971–2000 reference period. Glacier area is projected to shrink by 15–73% (model medians, range over scenarios), depending on the catchment. River discharge is projected to first increase by about 20% in the Aksu River catchments with subsequent decreases of up to 20%. In contrast, discharge in the drier Hotan and Yarkant catchments is projected to increase by 15–60% towards the end of the century. The large uncertainties mainly relate to the climate model ensemble and the limited observations to constrain the glacio-hydrological models. Sustainable water resource management will be key to avert the risks associated with the projected changes and their uncertainties. Publisher PDF

The conveyance capacity of rivers is a key uncertainty in regional and global flood models. Most models resort to assumptions of uniform discharge recurrence of 1-2 years, using modelled discharge. While this assumption may hold on average, reach-scale bankfull discharge has been shown to vary significantly at the global scale. To improve this key boundary condition in large-scale hydrodynamic models, we have coupled emerging understanding of the hydrological and geomorphological drivers of bankfull discharge with recent advances in remote sensing products and machine learning. Using measured bankfull discharge values derived from stage-discharge and width-discharge relationships as reference, we construct a data-driven model to estimate bankfull discharge globally at the reach scale (30m centreline pixels and sub-kilometre vector reaches). Various remote sensing products are used as predictor variables that pertain to either catchment-wide or reach-specific attributes. This includes river geometry and floodplain metrics derived from Landsat water masks that have also been used to construct the underlying river network. This novel river network was designed to be as DEM-independent as possible, allowing for multi-thread channels, bifurcations and canals. Early results indicate good agreement between predicted and independent reference values.The new dataset will be used to improve the parametrisation of a state-of-the-art global flood model as part of the EvoFlood research project (NERC, UK), but is also expected to be useful for other hydrological and hydrodynamic models as well as investigations at regional to global scales.

This study was conducted within the project SuMaRiO (Sustainable Management of River Oases along the Tarim River; http://www.sumario.de/), funded by the German Federal Ministry of Education and Re- search (BMBF grants 01LL0918J and 01LL0918B). T. Bolch acknowledges funding by Deutsche Forschungs- gemeinschaft (DFG, Code BO3199/2-1). The authors gratefully acknowledge the European Regional Devel- opment Fund (ERDF), the German Federal Ministry of Education and Research and the Land Brandenburg for supporting this project by providing resources on the high performance computer system at the Potsdam Institute for Climate Impact Research. Glacierised river catchments have been shown to be highly sensitive to climate change, while large populations depend on the water resources originating from them. Hydrological models are used to aid water resource management, yet their treatment of glacier processes is either rudimentary in large-scale applications or linked to fully distributed glacier models that prevent larger model domains. Also, data scarcity in mountainous catchments has hampered the implementation of physically based approaches over entire river catchments. A fully integrated glacier dynamics module was developed for the hydrological model SWIM (SWIM-G) that takes full account of the spatial heterogeneity of mountainous catchments but keeps in line with the semi-distributed disaggregation of the hydrological model. The glacierised part of the catchment is disaggregated into glaciological response units that are based on subbasin, elevation zone and aspect classes. They seamlessly integrate into the hydrological response units of the hydrological model. Robust and simple approaches to ice ow, avalanching, snow accumulation and metamorphism as well as glacier ablation under consideration of aspect, debris cover and sublimation are implemented in the model, balancing process complexity and data availability. The fully integrated model is also capable of simulating a range of other hydrological processes that are common for larger mountainous catchments such as reservoirs, irrigation agriculture and runoff from a diverse soil and vegetation cover. SWIM-G is initialised and calibrated to initial glacier hypsometry, glacier mass balance and river discharge. While the model is intended to be used in medium to large river basins with data-scarce and glacierised headwaters, it is here validated in the data-scarce catchment of the Upper Aksu River, Kyrgyzstan/NW China and in the relatively data-abundant catchment of the Upper Rhone River, Switzerland. Postprint

The study is based on results of the project Sustainable Management of River Oases along the Tarim River (SuMARiO) supported by the German Ministry of Science and Education (Bunderministerium für Bildung und Forschung, BMBF, Code 01 LL0918 A-K). 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. Publisher PDF

Extreme precipitation events often lead to flash floods, in particular in urban environments dominated by impervious surfaces. Likewise, excessive rainfall over an extended period or heavy snowmelt may lead to extreme river floods, which historically have caused loss of many lives, extensive damages to human and natural systems, and displacement of millions of people. Risk assessments generally consider the potential hazards from pluvial and fluvial floods as separate events. This can lead to a significant underestimation of the risks. Thus, the physical processes (e.g. precipitation) that drive these extreme events may interact and/or exhibit a spatial or temporal dependency, which could lead to an intensification of the hazard or modify the associated vulnerability and/or exposure. This is, e.g., the case of Budapest, where the urban drainage system relies on gravity flows. At about 3 m above the normal water level, rain water is not able to drain into the river without pumping, changing the operational conditions of the drainage system and potentially increasing the risk of urban flooding if this is coincident with an extreme precipitation event.Here, we analyse the coincidence of compound pluvial and fluvial flood events for both a current and future climate, including the potential physical links between extreme precipitations events, and larger scale rainfall in the Danube catchment. For this analysis, we use the Future Danube Model (FDM), representing a full catastrophe model compliant with the insurance industry standards. The model considers four members of the Euro-CORDEX regional climate model ensemble and their historical and future simulations- 30-year time slices (e.g. 2071-2100) are extracted from each simulation, which are first bias-corrected and then statistically inflated using the IMAGE weather generator to yield spatially distributed daily time series covering 10.000 model years with the same overall statistical properties as the underlying Euro-CORDEX model but with an enhanced representation of rare (precipitation) extremes across the entire catchment of the Danube. This time series feed into a detailed hydrological/ hydrodynamic model for the river catchment, based on a combination of the SWIM eco-hydrological model and a modified version of the CaMa-Flood hydrodynamic model, from where we estimate the discharge levels and fluvial flood risk at the location of the city of Budapest. For the pluvial flood modelling, we use a modified version of the approach described in Kaspersen et al. (2017), forced by the same four Euro-CORDEX models as used in the SWIM hydrological model, to infer recurrence periods and intensities for present and future heavy to extreme rainfall events. Considering the seasonality of the pluvial and fluvial flood risk, respectively, we find a significantly enhanced risk of compound events happening during the summer period, and that for most periods the compound risk is exacerbated by climate change. Given that the urban drainage system in Budapest already today is worn down and lacking the necessary capacity to deal with major flash floods, this suggests that new potentially nature-based approaches for dealing with storm water should be considered and that significant investments in updated urban drainage infrastructure is urgently needed.

The results presented in this contribution demonstrate the value of climate services for the planned construction of the new Wastewater Treatment Plant (WWTP) in Novi Sad, Serbia. In this case, climate services provided added value for the decision-making processes, in terms of enhanced effectiveness, optimized technological opportunities and minimized risks and by serving as the means of involving and better-informing end-users and stakeholders. The specific goal of the research was to improve climate change resilience of the WWTP and to facilitate better overall hygienic conditions in Novi Sad and to safeguard the potable water resources and the quality of the environment in the areas located downstream and under the influence of the Danube River.In order to achieve it, preliminary activities were oriented on analyzing the current climate and hydrological conditions, engaging the relevant data providers, stakeholders and policy makers and evaluating what relevant local data would be useful for the study. The data collected was applied in the testing and for improving the Future Danube Multi-hazard, Multi-risk Model (FDM), a catastrophe model implemented in the OASIS Loss Modeling Framework (Oasis-LMF). The FDM is implemented for the entire Danube Basin. High-resolution components for pluvial flood risks were further implemented to the city of Novi Sad, Serbia, after successful testing in the Budapest region. Observations and model results were used in a climate change impact assessment with the purpose of identifying adaptation options, appraisal of adaptation options and integration of an adaptation action plan into the Feasibility Study of the WWTP construction. The results of the pluvial flood model for Novi Sad clearly suggested that it is important to consider pluvial flood risks and that protective measures have to be considered as part of the WWTP construction, both under current and future climate conditions. Moreover, novel estimates of drainage water intensities during heavy rains would advise the design of the simultaneously planned pumping station on the banks of the Danube. Combined, this clearly demonstrates the added value of the climate services and risk information delivered by the FDM also beyond the insurance sector, as well as its potential to support adaptation decision making with respect to infrastructural investments in Novi Sad.

Consistent information on fluvial flood risks in large river basins is typically sparse. This is especially true for the Danube River basin covering up to 14 countries and creating a patchwork of flood risk information across a populous and flood-prone region. As climatic changes have shown to increase flooding in the future, consistent basin-scale assessments prove vital to the insurance industry as well as municipal and infrastructural planning. The Future Danube Model (FDM) was designed to fill this gap complying to both insurance industry and climate science standards. That is, allowing for a reasonably detailed model scale (based on a 25m digital elevation model), stochastic sampling to create a large number of extreme events and flood event footprints (10k years), a thorough calibration and validation as well as the use of an ensemble of climate model output to drive the model under scenario conditions. The model is here used to assess the impact on critical infrastructure across the basin. Results indicate a marked increase in flood risk has already occurred when comparing the current climate period (2006-2035) to the reference period (1970-1999). Further increases are projected under a moderate and a business as usual scenario for the next climate period (2020-2049) and the end of the century (2070-2099). In large parts of the basin, the historical 100-year flood level, often used as a critical protection level for infrastructure, is projected to be equalled or exceeded every 50–10 years, while areas with a 100-year flood risk are projected to increase by 6-19%.

Severe hydro-meteorological hazards have been increasing during recent decades and, as a consequence of global change, more frequent and intense events are expected in the future. Climate informed planning of adaptation actions needs both consistent and reliable information about future risks and associated uncertainties, and appropriate tools to support comprehensive risk assessment and management. The Future Danube Model (FDM) is a multi-hazard and risk model suite for the Danube region which provides climate information related to perils such as heavy precipitation, heatwaves, floods and droughts under recent and future climate conditions. FDM has a modular structure with exchangeable components for climate input, hydrology, inundation, risk, adaptation and visualisation. FDM is implemented within the open-source OASIS Loss Modelling Framework, which defines a standard for estimating ground-up loss and financial damage of disaster events or event scenarios. The OASIS lmf implementation of the FDM is showcased for the current and future fluvial flood risk assessment in the Danube catchment. We generate stochastic inundation event sets for current and future climate in the Danube region using the output of several EURO-CORDEX models as climate input. One event set represents 10,000 years of daily climate data for a given climate model, period and representative concentration pathway. With this input, we conduct long term continuous simulations of flood processes using a coupled semi-distributed hydrological and a 1.5D hydraulic model for fluvial floods. Flood losses to residential building are estimated using a probabilistic multi-variable vulnerability model. Effects of adaptation actions are exemplified by scenarios of private precaution. Changes in risk are illustrated with exceedance probability curves for different event sets representing current and future climate on different spatial aggregation levels which are of interest for adaptation planning.

The Upper Tarim River basin, contributing about 85% of the total inflow to the mainstream Tarim River, is heavily influenced by climate change and human interferences. This study is the first integrated assessment of agriculture and water management under climate change scenarios for this arid river basin in Central Asia. It aims to analyze changes in river discharge of the Upper Tarim under 28 climate projections for 3 representative concentration pathways (RCP) and the A1B scenario and 30 combinations of changes in land use (agricultural area) and water saving measures considered as adaptation strategies. Headwater discharge simulations of two hydrological models (SWIM-G and WASA) are used to drive a hydrological model of the lowland area (SWIM-oasis), taking account irrigation and river transmission losses. The projections show that the river discharge of the Upper Tarim River is likely to increase in a warmer climate if the agricultural area is reduced to the level as in 1998 even without any water saving measures. If the agricultural area increases to the 2010 level, strong water saving measures must be applied to ensure sufficient water inflow to the mainstream Tarim under all climate scenarios. If agricultural area continues to expand, there is a risk of decreasing river discharge at the end of this century under the RCP2.6 scenario. The uncertainty of the projections is large, especially in the far future, and it is mainly related to the climate and hydrological models.

Changes in river discharge regimes are regarded as the primary drivers of change of many in-stream ecological processes. While a lot of assessments addressing the hydrological alteration caused by human activities have been conducted for many river basins worldwide, a comprehensive analysis of hydrological alteration over major river basins worldwide under climate change is still limited to date. This study aims to address multi-dimensional hydrological alterations (alterations of multiple river flow characteristics) under climate change for four major rivers on three continents, by means of a consolidated framework consisting of two hydrological models, bias-corrected scenarios from five general circulation models (GCMs), and three Representative Concentration Pathways (RCPs) scenarios. The multi-dimensional hydrological alterations are quantified via the general Indicators of Hydrological Alteration approach (IHA) and two modified IHA methods based on dimensionality reduction. The reliability and advantages for the modified IHA methods are also analyzed. The results show that: (1) A modified IHA method (“NR-IHA method”) where the selected non-redundant IHA indices are basin specific is a valid alternative to the conventional IHA method for evaluating flow regime alteration, in consideration that high agreements in the simulated overall flow regimes alteration degree between it and the conventional IHA method are found during historical and future scenario periods, over four basins (the Upper Yellow River, the Lena River, the Tagus River and the Upper Amazon River). (2) Climate change is expected to remarkably alter overall flow regimes in the Tagus River and Upper Yellow River, especially at the end of the 21st century and under high RCP scenarios, whereas the dominant alteration extent tends to be low in the Lena River and Upper Amazon River in the two future periods. (3) The modified IHA method, preventing double-counting some aspects of the flow regime when assessing alteration degree of overall flow regimes, can save 65 % computation time and is more efficient than the conventional IHA method. It could be beneficial to figure out adaptive countermeasures for water resource management and restoration of eco-environmental systems under climate change.

Recent climate change impact studies studies have presented conflicting results regarding the largest source of uncertainty in essential hydrological variables, especially streamflow and derived characteristics that describe the evolution of drought events. Part of the problem arises from the lack of a consistent framework to address compatible initial conditions for the impact models and a set of standardized historical and future forcings. The ISI-MIP2 project provides a good opportunity to advance our understanding of the propagation of forcing and model uncertainties on to century-long time series of drought characteristics using an ensemble of hydrological model (HM) projections across a broad range of climate scenarios and regions. To achieve this goal, we used six regional preconditioned hydrological models set up in seven large river basins: Upper-Amazon, Blue-Nile, Ganges, Upper-Niger, Upper-Mississippi, Rhine, and Upper-Yellow. These models were forced with bias-corrected outputs from five CMIP5 general circulation models (GCMs) under two extreme representative concentration pathway scenarios (i.e., RCP2.6 and RCP8.5) for the period 1971-2099. The simulated streamflow was transformed into a monthly runoff index (RI) to analyze the attributions of the GCM and HM uncertainties on to drought magnitudes and durations over time. The results indicated that GCM uncertainty mostly dominated over HM uncertainty for the projections of runoff drought characteristics, irrespective of the selected RCP and region. In general, the overall uncertainty increased with time. The uncertainty in the drought characteristics increased as the radiative forcing of the RCP increased, but the propagation of the GCM uncertainty on to a drought characteristic depended largely upon the hydro-climatic regime. Although our study emphasizes the need for multi-model ensembles for the assessment of future drought projections, the agreement between the GCM forcings was still too weak to draw conclusive recommendations.

Mountain precipitation is often strongly underestimated as observations are scarce, biased toward lower-lying locations and prone to wind-induced undercatch, while topographical heterogeneity is large. This presents serious challenges to hydrological modeling for water resource management and climate change impact assessments in mountainous regions of the world, where a large population depends on water supply from the mountains. The headwaters of the Tarim River, covering four remote and highly glacierized Asian mountain ranges, are vital water suppliers to large agricultural communities along the Taklamakan Desert, northwest China. Assessments of future changes to these water towers have been hampered because of the large precipitation uncertainties. In this study, six existing precipitation datasets (observation-based reanalysis datasets, satellite observation datasets, and the output of high-resolution regional climate models) were compared over five headwaters of the Tarim River. The dataset incorporating the highest observation density (APHRODITE) is then corrected by calibrating the glacio-hydrological model Soil and Water Integrated Model–Glacier Dynamics (SWIM-G) to observed discharge, glacier hypsometry, and modeled glacier mass balance. Results show that this form of inverse modeling is able to inform the precipitation correction in such data-scarce conditions. Substantial disagreement of annual mean precipitation between the analyzed datasets, with coefficients of variation in catchment mean precipitation of 68% on average, was found. The model-based precipitation estimates are on average 1.5–4.3 times higher than the APHRODITE data, but fall between satellite-based and regional climate model results.

An intercomparison of climate change impacts projected by nine regional-scale hydrological models for 12 large river basins on all continents was performed, and sources of uncertainty were quantified in the framework of the ISIMIP project. The models ECOMAG, HBV, HYMOD, HYPE, mHM, SWAT, SWIM, VIC and WaterGAP3 were applied in the following basins: Rhine and Tagus in Europe, Niger and Blue Nile in Africa, Ganges, Lena, Upper Yellow and Upper Yangtze in Asia, Upper Mississippi, MacKenzie and Upper Amazon in America, and Darling in Australia. The model calibration and validation was done using WATCH climate data for the period 1971–2000. The results, evaluated with 14 criteria, are mostly satisfactory, except for the low flow. Climate change impacts were analyzed using projections from five global climate models under four representative concentration pathways. Trends in the period 2070–2099 in relation to the reference period 1975–2004 were evaluated for three variables: the long-term mean annual flow and high and low flow percentiles Q10 and Q90, as well as for flows in three months high- and low-flow periods denoted as HF and LF. For three river basins: the Lena, MacKenzie and Tagus strong trends in all five variables were found (except for Q10 in the MacKenzie); trends with moderate certainty for three to five variables were confirmed for the Rhine, Ganges and Upper Mississippi; and increases in HF and LF were found for the Upper Amazon, Upper Yangtze and Upper Yellow. The analysis of projected streamflow seasonality demonstrated increasing streamflow volumes during the high-flow period in four basins influenced by monsoonal precipitation (Ganges, Upper Amazon, Upper Yangtze and Upper Yellow), an amplification of the snowmelt flood peaks in the Lena and MacKenzie, and a substantial decrease of discharge in the Tagus (all months). The overall average fractions of uncertainty for the annual mean flow projections in the multi-model ensemble applied for all basins were 57% for GCMs, 27% for RCPs, and 16% for hydrological models. Intercomparison of regional-scale hydrological models and climate change impacts projected for 12 large river basins worldwide—a synthesis

The projected increase in temperature is expected to intensify the hydrological cycle, and thus more intense precipitation is likely to increase hydro-meteorological extremes and flood hazard. However to assess the future dynamics of hazard and impact induced by these changes it is necessary to consider extreme events and to take a spatially differentiated perspective. The Future Danube Model is a multi-hazard and risk model suite for the Danube region which has been developed in the OASIS project. The model comprises modules for estimating potential perils from heavy precipitation, heat-waves, floods, droughts, and damage risk considering hydro-climatic extremes under current and climate change conditions. Web-based open Geographic Information Systems (GIS) technology allows customers to graphically analyze and overlay perils and other spatial information such as population density or assets exposed. The Future Danube Model combines modules for weather generation, hydrological and hydrodynamic processes, and supports risk assessment and adaptation planning support. This contribution analyses changes in flood hazard in the Danube basin and in flood risk for the German part of the Danube basin. As climate change input, different regionalized climate ensemble runs of the newest IPCC generation are used, the so-called Representative Concentration Pathways (RCPs). They are delivered by the CORDEX initiative (Coordinated Downscaling Experiments). The CORDEX data sample is extended using the statistical weather generator (IMAGE) in order to also consider extreme events. Two time slices are considered: near future 2020-2049 and far future 2050-2079. This data provides the input for the hydrological, hydraulic and flood loss model chain. Results for RCP4.5 and RCP8.5 indicate an increase in intensity and frequency of peak discharges and thus in flood hazard for many parts of the Danube basin.

The River Aksu is the principal tributary to the River Tarim, providing about three quarters of its discharge. It originates in Kyrgyzstan and flows into the arid areas of the Xinjiang Uyghur Autonomous Region in China, where an extensive irrigated agriculture has been developed in the river oases. The aim of the present contribution is to review the current trends in temperature, precipitation, and river discharge and links between these variables. The temperature in the region and the river discharge have been rising. Changes were studied using multiple trend analyses with different start and end years. Correlations between daily temperature and discharge are high and statistically significant for two headwater subcatchments of the Aksu for most of the time. However, there are episodes in late summer or beginning of autumn when correlations between temperature and discharge for the Xiehela station are absent. This can only be explained by Glacial Lake Outburst Floods from the Lake Merzbacher that are not routinely monitored. On an annual time scale, changes in summer discharge in the highly glacierized Xiehela subcatchment are dominated by changes in temperature. In contrast, in the subcatchment Shaliguilanke, variations in summer streamflow are more strongly influenced by variations in precipitation. A comparison of links between climatic variables and streamflow at different temporal scales is offered. Perspectives for seasonal forecasting are examined.

Glacial lake outburst floods (GLOF) often have a significant impact on downstream users. Including their effects in hydrological models, identifying past occurrences and assessing their potential impacts are challenges for hydrologists working in mountainous catchments. The regularly outbursting Merzbacher Lake is located in the headwaters of the Aksu River, the most important source of water discharge to the Tarim River, northwest China. Modelling its water resources and the evaluation of potential climate change impacts on river discharge are indispensable for projecting future water availability for the intensively cultivated river oases downstream of the Merzbacher Lake and along the Tarim River. The semi-distributed hydrological model SWIM was calibrated to the outlet station Xiehela on the Kumarik River, by discharge the largest tributary to the Aksu River. The glacial lake outburst floods add to the difficulties of modelling this high-mountain, heavily glaciated catchment with poor data coverage and quality. The aims of the study are to investigate the glacier lake outburst floods using a modelling tool. Results include a two-step model calibration of the Kumarik catchment, an approach for the identification of the outburst floods using the measured gauge data and the modelling results and estimations of the outburst flood volumes. Results show that a catchment model can inform GLOF investigations by providing ‘normal’ (i.e. without the outburst floods) catchment discharge. The comparison of the simulated and observed discharge proves the occurrence of GLOFs and highlights the influences of the GLOFs on the downstream water balance. © 2013 The Authors. Hydrological Processes Published by John Wiley & Sons Ltd.

Glacierised river catchments have been shown to be highly sensitive to climate change, while large populations depend on the water resources originating from them. Hydrological models are used to aid water resource management, yet their treatment of glacier processes is either rudimentary in large applications or linked to fully distributed glacier models that prevent larger model domains. Also, data scarcity in mountainous catchments has hampered the implementation of physically based approaches over entire river catchments. A fully integrated glacier dynamics module was developed for the eco-hydrological model SWIM (SWIM-G) that takes full account of the spatial heterogeneity of mountainous catchments but keeps in line with the semi-distributed disaggregation of the hydrological model. The glacierised part of the catchment is disaggregated into glaciological response units that are based on subbasin, elevation zone and aspect classes. They seamlessly integrate into the hydrological response units of the hydrological model SWIM. Robust and simple approaches to ice flow, avalanching, snow accumulation and metamorphism as well as glacier ablation under consideration of aspect, debris cover and sublimation are implemented in the model, balancing process complexity and data availability. The fully integrated is also capable of simulating a range of other hydrological processes that are common for larger mountainous catchments such as reservoirs, irrigation agriculture and runoff from a diverse soil and vegetation cover. SWIM-G is initialised and calibrated to initial glacier hypsometry, glacier mass balance and river discharge. While the model is intended to be used in medium to large river basins with data-scarce and glacierised headwaters, it is here validated in the data-abundant catchment of the Upper Rhone River, Switzerland and the data-scarce catchment of the Upper Aksu River, Kyrgyzstan/NW China.

The Tarim River basin, located in Xinjiang, NW China, is the largest endorheic river basin in China and one of the largest in all of Central Asia. Due to the extremely arid climate, with an annual precipitation of less than 100 mm, the water supply along the Aksu and Tarim rivers solely depends on river water. This is linked to anthropogenic activities (e.g., agriculture) and natural and semi-natural ecosystems as both compete for water. The ongoing increase in water consumption by agriculture and other human activities in this region has been enhancing the competition for water between human needs and nature. Against this background, 11 German and 6 Chinese universities and research institutes have formed the consortium SuMaRiO (Sustainable Management of River Oases along the Tarim River; http://www.sumario.de), which aims to create a holistic picture of the availability of water resources in the Tarim River basin and the impacts on anthropogenic activities and natural ecosystems caused by the water distribution within the Tarim River basin. On the basis of the results from field studies and modeling approaches as well as from suggestions by the relevant regional stakeholders, a decision support tool (DST) will be implemented that will then assist stakeholders in balancing the competition for water, acknowledging the major external effects of water allocation to agriculture and to natural ecosystems. This consortium was formed in 2011 and is funded by the German Federal Ministry of Education and Research. As the data collection phase was finished this year, the paper presented here brings together the results from the fields from the disciplines of climate modeling, cryology, hydrology, agricultural sciences, ecology, geoinformatics, and social sciences in order to present a comprehensive picture of the effects of different water availability schemes on anthropogenic activities and natural ecosystems along the Tarim River. The second objective is to present the project structure of the whole consortium, the current status of work (i.e., major new results and findings), explain the foundation of the decision support tool as a key product of this project, and conclude with application recommendations for the region. The discharge of the Aksu River, which is the major tributary of the Tarim, has been increasing over the past 6 decades. From 1989 to 2011, agricultural area more than doubled: cotton became the major crop and there was a shift from small-scale to large-scale intensive farming. The ongoing increase in irrigated agricultural land leads to the increased threat of salinization and soil degradation caused by increased evapotranspiration. Aside from agricultural land, the major natural and semi-natural ecosystems are riparian (Tugai) forests, shrub vegetation, reed beds, and other grassland, as well as urban and peri-urban vegetation. Within the SuMaRiO cluster, focus has been set on the Tugai forests, with Populus euphratica as the dominant tree species, because these forests belong to the most productive and species-rich natural ecosystems of the Tarim River basin. At sites close to the groundwater, the annual stem diameter increments of Populus euphratica correlated with the river runoffs of the previous year. However, the natural river dynamics cease along the downstream course and thus hamper the recruitment of Populus euphratica. A study on the willingness to pay for the conservation of the natural ecosystems was conducted to estimate the concern of the people in the region and in China's capital. These household surveys revealed that there is a considerable willingness to pay for conservation of the natural ecosystems, with mitigation of dust and sandstorms considered the most important ecosystem service. Stakeholder dialogues contributed to creating a scientific basis for a sustainable management in the future.

Climate variability and change play a crucial role in the vulnerable system of the Aksu River basin located in Kyrgyzstan and northwest China, providing precious water resources for the intense oasis agriculture of the Xinjiang Province (China). Ubiquitous warming and increase in precipitation (in the lower part of the basin) have been detected. Glaciers in the region are retreating. Seasonal trends in river discharge show an increase. A clear link could be demonstrated between daily temperature and lagged river discharge at two headwater stations in summer. However, the correlation breaks over short periods in the end of summer or beginning of autumn at the Xiehela station, when the high (over 95th percentile) flow peaks caused by the glacier lake outburst floods of the Merzbacher Lake occur. This feature is a challenge for the climate impact assessment in the region, as these regular outbursts have to be represented in the projections for the future as well.Editor D. Koutsoyiannis