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Peru is already facing a number of challenges related to climate change, including retreating glaciers and more severe droughts and floods. Therefore, a countrywide analysis of current and future hydroclimatic conditions is crucial to formulate adaptation strategies in water resource development. This study aims to evaluate the effects of climate change on the distribution of water budget components and streamflow variability across Peru. For that, we bias-adjusted and statistically downscaled CMIP6 climate projections of 10 climate models under two Shared Socioeconomic Pathways (SSP1-2.6 and SSP5-8.5) to obtain a range of possible future regional climatic conditions. These selected scenarios span a range of possible future options from the sustainable pathway (SSP1-2.6, with 2.6 W/m2 by the year 2100) to fossil-fueled development (SSP5-8.5, with 8.5 W/m2 by the year 2100). The adjusted climate data were fed into the hydrological model, Soil and Water Assessment Tool (SWAT), to simulate and analyze future hydroclimatic conditions. SWAT was calibrated and validated at 72 discharge stations against mean, high and low water flows. Climate projections suggest a warmer climate and diverging changes in precipitation, with a drier response over the lowlands of the Upper Amazon related to a substantial reduction in precipitation during June-November and a wetter response over the tropical Andes due to precipitation increases during September-March. Projected changes in hydrological conditions show lower water availability over lowlands and higher water availability along the Andean basins in the future. The projections for hydrological extremes indicate that Peru might face excessive water exposure during floods along the Andean catchments and water scarcity during droughts over the Amazon lowlands in the future, particularly under the fossil-fueled development (SSP5-8.5) scenario. The results of this study provide information to planners and decision-makers for formulating adaptation strategies for sustainable water management under climate change in Peru. Keywords: water resources, climate change, CMIP6, hydrological extremes, Peru, Andes, Amazon

Most hydrological studies rely on a model calibrated using discharge alone. However, judging the model reliability based on such calibration is problematic, as it does not guarantee the correct representation of internal hydrological processes. This study aims (a) to develop a comprehensive multi-objective calibration framework using remote sensing vegetation data and hydrological signatures (flow duration curve���FDC, and baseflow index) in addition to discharge, and (b) to apply this framework for calibration of the Soil and Water Assessment Tool (SWAT) in a typical Andean catchment. Overall, our calibration approach outperformed traditional discharge-based and FDC signature-based calibration strategies in terms of vegetation, streamflow, and flow partitioning simulation. New hydrological insights for the region are the following: baseflow is the main component of the streamflow sustaining the long dry-season flow, and pasture areas offer higher water yield and baseflow than other land-cover types. The proposed approach could be used in other data-scarce regions with complex topography. �� 2020 IAHS.

Burundi is one of the poorest countries in the world with about 65% of the population living below the poverty line and suffering from alarming food insecurity. Its population is highly dependent on rain-fed agriculture, which makes them extremely sensitive to climate variability and extremes for their subsistence. During the last decades, heavy rains, floods, and landslides suffered by Burundi’s population have led to severe famines, death, conflicts, and internal displacement among other fatalities, indicating the high vulnerability of this region to extreme events. Therefore, it is of vital importance to provide detailed information about the potential impacts of climate change in order to enhance adaptation options and preparedness in a country for which little information about climate projections and hydro-climatic impacts is available.In this work, we investigated the changes in future climate over Burundi projected by a set of 13 regional climate models, for two future periods, under RCP4.5 and RCP8.5. The projections from CORDEX models have been used as forcing climate for the eco-hydrological Soil and Water Integrated Model (SWIM) in order to assess future changes in mean and extreme river discharge and water availability across Burundi.Our results indicate that unabated climate change will lead to faster and more severe warming over Burundi than the global mean. Precipitation will increase in the north of Burundi despite a possible prolongation of the dry season, and will decrease in the south, with the exception of the months core of the rainy season that show the highest rise along the year and across the country. The increase in the frequency, magnitude, and intensity of extreme climate events (daily temperature, dry and wet events) will characterize the future climate in this region according to CORDEX models.These changes get translated into increases of discharge in North Burundi across the whole year in all future scenarios and periods (up to 196% in annual streamflow in small catchments and 40% in larger ones), and slight decreases in the south from February to October (up to 7%). The increase of daily and annual extreme river discharges, their probabilities of exceedance, and the decrease in their recurrence intervals implies a higher risk of floods in magnitude and frequency.These findings indicate the critical importance of adaptation of land and water management to changing hydro-climatic conditions in Burundi to improve food security and support its development.

Changes in weather persistence are of particular concern in the context of climate change as periods of longer persistence can reinforce weather extremes. In our study we apply structural image recognition methods to global ERA5 reanalysis data to identify when, where and how long isolines of atmospheric geopotential height fields run in similar tracks. We identify regions and episodes around the world in which, retrospectively, unusually long-lasting weather patterns repeatedly occurred. Concerning the temperature and precipitation meteorological fields, we derive a connection between the occurrence of weather persistence and hydro-climatic extreme events.Based on our new method we find that weather persistence has been particularly increasing in Northern Hemisphere mid-latitudes in summer confirming earlier studies. Here, highly populated regions like Central Europe have experienced long-term increases in persistent weather conditions of up to 4-5% between 1981 and 2019 amplifying the risk of prolonged heat waves and droughts. Further, we show that climate models tend to have difficulties in capturing the dynamics of weather persistence and thus may severely underestimate the frequency and magnitude of future extremes events in their climate projections.

Recent studies have shown that hydro-climatic extremes have increased significantly in number and intensity in the last decades. In the Northern Hemisphere such events were often associated with long lasting persistent weather patterns. In 2018, hot and dry conditions prevailed for several months over Central Europe leading to record-breaking temperatures and severe harvest losses. The underlying circulation processes are still not fully understood and there is a need for improved methodologies to detect and quantify persistent weather conditions. Here, we propose a new method to detect, compare and quantify persistence through atmosphere similarity patterns by applying established image recognition methods to day to day atmospheric fields. We find that persistent weather patterns have increased in number and intensity over the last decades in Northern Hemisphere mid-latitude summer, link this to hydro-climatic risks and evaluate the extreme summers of 2010 (Russian heat wave) and of 2018 (European drought). We further evaluate the ability of climate models to reproduce long-term trend patterns of weather persistence and the result is a notable discrepancy to observed developments.

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 region-specific 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.

Many renewable resources for the generation of electricity, such as hydropower and wind power, are dependent on climatic factors. Reservoirs have been created to overcome the stochastic nature of river flows and to make water supply more reliable. However, reservoirs are affecting the ecological status of river ecosystems, e.g., by modifying the flow regime, triggering discussions regarding the discharge of reservoirs. In Brazil’s northeast region, the installed capacity for wind power generation has increased substantially in recent years. Setting up a modeling system for simulating wind power and hydropower generation in this study, it is analyzed whether wind power generation, peaking in the dry season, can help to achieve a more environmentally oriented flow regime in the Sub-middle and Lower Sao Francisco River Basin. Simulated higher discharges from reservoirs during the rainy season and lower discharges during the dry season, representing a more natural flow regime, will reduce hydropower generation in the dry season. Under recent conditions, the resulting gap in electricity generation can only be partially covered by wind power. A large share needs to be generated by thermal power plants or be imported from other regions in Brazil. The planned future increase in installed wind power capacity can change this picture; the demand for electricity generated by thermal power plants and imported will decrease. Adopting an integrated approach for hydropower and wind power generation, the flow regime in the Sub-middle and Lower Sao Francisco River Basin can be modified to improve the ecological status of the river system.

An impact assessment of food-securing upgrading strategies (UPS) can be performed to assess actual and potential UPS effects at the local level. We developed an assessment framework that integrates the main components of the food value chain (FVC), including natural resources, food production, processing, marketing, and consumption. The framework provides a generic template in which different impact assessment approaches can be complementarily integrated and was tested for a case study in Tanzania. The framework employs a structured sequence of steps: (1) context analysis and the development of UPS, (2) the selection and application of assessment approaches and (3) the establishment of food security criteria and UPS effects. To illustrate the flexibility and use of the framework, the inputs of three different impact assessment approaches were considered. First, data from a household survey was applied to provide baseline information at the local level. Second, scientific knowledge was employed to systematically assess the selected UPS. Third, local stakeholder knowledge was considered to identify the local food security constraints and preferences and provide assessments of potential UPS effects. The Framework for Participatory Impact Assessment (FoPIA) approach was utilized to conduct local focus group discussions, and the Scaling Up Assessment Tool for Food Security (ScalA-FS) was employed to gather scientific knowledge about specific UPS impacts. Based on the preliminary results from the framework testing, diverse stakeholder participation was found to be essential for considering local preferences and to engage stakeholders in the assessment process, whereas scientific knowledge and monitoring data were needed to complement the “local picture” with more quantifiable results. The strengths and shortcomings of the framework are discussed.

CONTEXT Crop rotations considerably affect the hydrological regime of river basins used for agricultural production and are key for sustainable land and water management. However, eco-hydrological modelling usually neglects crop rotations. OBJECTIVE In this paper, we present a Crop Generator to reproduce the stochastic characteristics of crop rotations at regional scale. METHODS The Crop Generator emulates farmers’ decision making on crop rotation planning. We combined the Crop Generator with the eco-hydrological Soil and Water Integrated Model to show the hydrological relevance of considering crop rotations in a study region in central Europe including the Elbe River basin. RESULTS AND CONCLUSIONS A spatial validation showed that the Crop Generator reproduced the given cropping patterns well. Higher daily discharge, runoff and groundwater seepage and lower evapotranspiration were simulated based on crop rotations compared with a simplified representation of cropping patterns. The Crop Generator is a solution to simulate more realistic cropping patterns in large-scale eco-hydrological modelling. It closes the gap between aggregated agricultural statistics and the requirement of representing crop rotations in a realistic way in eco-hydrological modelling. SIGNIFICANCE The Crop Generator enables smart projections of future adjustments in crop rotations in view of climate and socio-economic changes as a basis for improving eco-hydrological projections and designing more sustainable agricultural systems.

To bridge the gap between 1D and 2D hydraulic models for regional scale assessment and global river routing models, we coupled the CaMa-Flood (Catchment-based Macro-scale Floodplain) model and the regional hydrological model SWIM (Soil and Water Integrated Model) as a tool for large-scale flood risk assessments. As a proof-of-concept study, we tested the coupled models in a meso-scale catchment in Germany. The Mulde River has a catchment area of ca. 6,171 km2 and is a sub-catchment of the Elbe River. The modified CaMa-Flood model routes the sub-basin-based daily runoff generated by SWIM along the river network and estimates the river discharge as well as flood inundation areas. The results show that the CaMa-Flood hydrodynamic algorithm can reproduce the daily discharges from 1991 to 2003 well. It outperforms the Muskingum flow routing method (the default routing method in the SWIM) for the 2002 extreme flood event. The simulated flood inundation area in August 2002 is comparable with the observations along the main river. However, problems may occur in upstream areas. The results presented here show the potential of the coupled models for flood risk assessments along large rivers.

Conventional water management strategies, that serve solely socio-economic demands and neglect changing natural conditions of the river basins, face significant challenges in governing complex human-hydrological systems, especially in the areas with constrained water availability. In this study we assess the possibility to harmonize the inter-sectoral water allocation scheme within a highly altered human-hydrological system under reduction in water availability, triggered by projected climate change applying scenario-based approach. The Tagus River Basin headwaters, with significant disproportion in the water resources allocation between the environmental and socio-economic targets were taken as a perfect example of such system out of balance. We propose three different water allocation strategies for this region, including two conventional schemes and one imposing shift to sustainable water management and environmental restoration of the river. We combine in one integrated modelling framework the eco-hydrological process-based Soil and Water Integrated Model (SWIM), coupled with the conceptual reservoir and water allocation modules driven by the latest bias-corrected climate projections for the region and investigate possible water allocation scenarios in the region under constrained water availability in the future. Our results show that the socio-economic demands have to be re-considered and lowered under any water allocation strategy, as the climate impacts may significantly reduce water availability in the future. Further, we show that a shift to sustainable water management strategy and river restoration is possible even under reduced water availability. Finally, our results suggest that the adaptation of complex human-hydrological systems to climate change and a shift to a more sustainable water management are likely to be parts of one joint strategy to cope with climate change impacts.

This paper introduces the Special Issue “Hydrological Model Intercomparison for Climate Impact Assessment”. We describe the river basins used as case studies, the input data, the hydrological models, and the climate scenarios applied in the multi-model framework. We also summarize the main results of the papers contained in this Special Issue.

Study region Eight river catchments within Central Asia. Study focus The limited amount of water resources is already an issue in the Central Asian region, and climate change may be crucial for water availability and development of countries in the region. This study investigates potential climate change impacts on water resources in Central Asia to the end of the century by focusing on eight river catchments with diverse natural conditions located in different countries. The eco-hydrological model SWIM was setup, calibrated and validated for all selected catchments under study. Scenarios from five bias-corrected GCMs under Representative Concentration Pathways 4.5 and 8.5 were used to drive the hydrological model. New hydrological insights for the region The results show an increase of mean annual temperature in all catchments for both RCPs to the end of the century. The projected changes in annual precipitation indicate a clear trend to increase in the Zhabay and to decrease in the Murghab catchments, and for other catchments, they were smaller. The projected trends for river discharge are similar to those of precipitation, with an increase in the north and decrease in the south of the study region. Seasonal changes are characterized by a shift in the peak of river discharge up to one month, shortage of snow accumulation period, and reduction of discharge in summer months.

Understanding of future climate change impacts and successful planning of adaptation measures are of vital importance for Central Asia given the region's economic vulnerability, dependence on scarce water resources, and observed above global average warming rates. This paper analyses how impacts of climate change on the hydrological regimes and temperature patterns could affect the irrigated agricultural production in two case study areas, the Aspara and Isfara river basins. The methodology applied is based on analysis of temperature indicators and current cropping calendars in target locations combined with hydrological simulations by the process-based Soil and Water Integrated Model (SWIM) of the two river basins. The selected climate change projections comprise the moderate and high emissions scenarios - RCP4.5 and RCP8.5. The results reveal that climate change will create unfavourable conditions for irrigated spring crops, due to decrease of discharge during the vegetation period. On the other hand, the projected shift of peak discharge to an earlier date offers benefits for irrigated winter cereals, providing more water for irrigation in spring. Results suggest that, there is an opportunity to adapt the irrigated agricultural production in the selected regions by fitting the cropping calendars to changing vegetation periods and to the timing of peak discharges.

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.

One of the key inputs of a hydrological model is the potential evapotranspiration (PET), which sets an upper limit to evapotranspirative water demand. However, limited data availability often challenges the choice of a PET estimation method, which in turn affects the PET estimates as well as the water balance (WB) components. The objectives of this research are (1) to evaluate the use of different sources of weather input data to derive PET: Climate Forecast System Reanalysis (CFSR) data, Water and Global Change (WATCH) data, and data generated by the weather generator of the soil and water assessment tool (SWAT) (SWAT–WG); and (2) to investigate the effects of the Penman–Monteith and Hargreaves (HG) methods on WB components using a SWAT-based model for the Upper Mara Catchment (Kenya). It is shown that PET estimations using the CFSR, WATCH, and SWAT–WG data sets compare well with the average annual and seasonal PET estimates from local observations over a period of 20 years. This shows the potential of global reanalysis climate data sources for the computation of PET in data-limited catchments. The SWAT models forced by these data sets and by gauged rainfall show a modified Nash–Sutcliffe (NSmNSm) efficiency ranging from 0.6 to 0.72 for the simulation of the flow, depending on the selected PET estimation method. Unlike water yield, the other WB components simulated by the SWAT models (ET, deep aquifer loss, and reevaporation from the shallow aquifer) vary in magnitude, depending on the data and methods being used. The sensitivity analysis and the calibration results show that the model parameters are sensitive to the choice of the PET estimation method. Therefore, for catchments where parameterization is a challenge owing to data scarcity, it is crucial to consider the appropriate PET estimation method for a realistic modeling of the hydrological processes. In our case study, the HG method gives more robust and realistic ET estimations. - See more at: http://ascelibrary.org/doi/abs/10.1061/(ASCE)HE.1943-5584.0001305#sthash.BLe6Dfi1.dpuf

In our first study on possible flood damages under climate change in Germany, we reported that a considerable increase in flood-related losses can be expected in a future warmer climate. However, the general significance of the study was limited by the fact that outcome of only one global climate model (GCM) was used as a large-scale climate driver, while many studies report that GCMs are often the largest source of uncertainty in impact modelling. Here we show that a much broader set of global and regional climate model combinations as climate drivers show trends which are in line with the original results and even give a stronger increase of damages.

The choice of the baseline period, intentionally chosen or not, as a reference for assessing future changes of any projected variable can play an important role for the resulting statement. In regional climate impact studies, well-established or arbitrarily chosen baselines are often used without being questioned. Here we investigated the effects of different baseline periods on the interpretation of discharge simulations from eight river basins in the period 1960–2099. The simulations were forced by four bias-adjusted and downscaled Global Climate Modelsunder two radiative forcing scenarios (RCP 2.6 and RCP 8.5). To systematically evaluate how far the choice of different baselines impacts the simulation results, we developed a similarity index that compares two time series of projected changes. The results show that 25% of the analyzed simulations are sensitive to the choice of the baseline period under RCP 2.6 and 32% under RCP 8.5. In extreme cases, change signals of two time series show opposite trends. This has serious consequences for key messages drawn from a basin-scale climate impact study. To address this problem, an algorithm was developed to identify flexible baseline periods for each simulation individually, which better represent the statistical properties of a given historical period.

The aim of the study is to analyze and discuss possible climate change impacts on flood damages in Germany. The study was initiated and supported by the German insurance sector whereby the main goal was to identify general climate-related trends in flood hazard and damages and to explore sensitivity of results to climate scenario uncertainty. The study makes use of climate scenarios regionalized for the main river basins in Germany. A hydrological model (SWIM) that had been calibrated and validated for the main river gauges, was applied to transform these scenarios into discharge for more than 5000 river reaches. Extreme value distribution has been fitted to the time series of river discharge to derive the flood frequency statistics. The hydrological results for each river reach have been linked using the flood statistics to related damage functions provided by the German Insurance Association, considering damages on buildings and small enterprises. The result is that, under the specific scenario conditions, a considerable increase in flood related losses can be expected in Germany in future, warmer, climate.

This study addresses the increasing flood risk in the Niger basin and assesses the damages that arise from flooding. Statistics from three different sources (EM-DAT, Darthmouth Flood Observatory, NatCat Munich RE) on people affected by floods show positive trends for the entire basin beginning in the 1980s. An assessment of four subregions across the Niger basin indicates even exponential trends for the Sahelian and Sudanian regions. These positive trends for flooding damage match up to a time series of annual maximum discharge (AMAX): the strongest trends in AMAX are detected in the Sahelian and Sudanian regions, where the population is also increasing the fastest and vulnerability generally appears to be very high. The joint effect of these three factors can possibly explain the exponential increase in people affected by floods in these subregions. In a second step, the changes in AMAX are attributed to changes in precipitation and land use via a data-based approach within a hypothesis-testing framework. Analysis of rainfall, heavy precipitation and the runoff coefficient shows a coherent picture of a return to wet conditions in the basin, which we identify as the main driver of the increase in AMAX in the Niger basin. The analysis of flashiness (using the Richards–Baker Index) and the focus on the "Sahel Paradox" of the Sahelian region reveal an additional influence of land-use change, but it seems minor compared to the increase in precipitation.

Globally, there is increased concern about the potential impacts of extreme climate events, including their impact on loss and damage to people, assets an property. The Global Insurance Sector is a...

Central Europe, the focus region of this study, is a region in transition, climatically from maritime to continental and politically from formerly more planning-oriented to more market-oriented management regimes, and in terms of climate change from regions of increasing precipitation in the west and north of Europe to regions of decreasing precipitation in central and southern Europe. The Elbe basin, a trans-boundary catchment flowing from the Czech Republic through Germany into the North Sea, was selected to investigate the possible impacts of global change on crop yields and water resources in this region. For technical reasons, the paper has been split into two parts, the first showing the overall model concept, the model set-up for the agricultural sector, and first results linking eco-hydrological and agro-economic tools for the German part of the basin. The second part describes the model set-up for simulating water supply and demand linking eco-hydrological and water management tools for the entire basin including the Czech part.

This study aims to assess the potential alterations in the hydrological regime attributed to projected climate change in one of the largest rivers in the Carpathian Area, the Mures River, and to estimate associated threats to riverine ecosystem. The eco-hydrological model, Soil and Water Integrated Model (SWIM), was applied on the Mures River basin, calibrated and validated against records at a gauging station in Alba-Julia town. A set of nine future projections for climatic parameters under one emissions scenario A1B over the period 1971–2100 were fed into the SWIM model. To provide functional link between hydrological regimes and riverine ecosystems, each of the nine simulated discharge time series were introduced into the IHA (Indicators of Hydrological Alterations) tool. Triggered changes in hydrological patterns of the Mures River were assessed at the basin and sub-basin scales. The obtained results present a strong agreement through all nine climate projections, suggesting an increase in the discharge of Mures River for the winter season, a decrease in summer and prolongation of the low flow periods by the end of the century. Anticipated changes would pose threats to aquatic ecosystems, altering normal life-cycles, and depleting natural habitats of species.

In this study, scenarios of changes in land-use patterns, agricultural production and climate, and their effects on water demand and availability in the São Francisco river basin (Brazil) are analysed. The global driver population growth, economic development, and trade liberalization are included. Using the regionalized version of a global agro-economic land- and water use model, impacts are analysed for two scenarios: a regionalized world with slow economic development, high population growth, and little awareness of environmental problems (A2), and a globalized world with low population growth, high gross domestic product (GDP) growth, and environmental sustainability (B1). A regional ecohydrological model is used to analyse the effect of these scenarios on water demand and availability. The climate scenarios in general show a wetter future (years 2021 – 2050), with wetter rainy seasons and drier dry seasons. The water availability for irrigated agriculture is high, while hydropower generation is declining by 3.2% (A2) and 1.7% (B1) compared to the reference.

Climate variability and change affect electricity generation in several ways. Electricity generation is directly dependent on climate/weather parameters like wind (wind power generation) or air temperature and resulting water temperature (thermal power plants). River discharge as a result of precipitation and temperature, the latter being one main factor influencing evapotranspiration, is important for hydro power generation and cooling of thermal power plants. In this study possible effects of climate variability and change on electricity generation in Germany are analyzed. Considered is electricity generation by thermal power plants, wind power plants and hydro power plants. While hydro power plants and thermal power plants are affected negatively due to declining river discharge or higher water temperatures, for wind power generation no clear tendency was found. The reduction for hydro power generation could be leveled out by a slight increase in installed capacity and modernization of turbines and generators. By a replacement of old once-through cooling systems by closed-circuit cooling systems for new thermal power plants the negative impacts on electricity generation can be reduced significantly. The planned increase of installed capacity for wind power generation clearly surpasses the changes arising from climate change.

Aim of our study is to quantify the impacts of climate change on hydrology in the large river basins in Germany (Rhine, Elbe, Danube, Weser and Ems) and thereby giving the range of impact uncertainty created by the most recent regional climate projections. The study shows mainly results for the A1B SRES (Special Report on Emission Scenario) scenario by comparing the reference period 1981–2010 and the scenario periods 2031–2060 and 2061–2090 and using climate projections of a combination of 4 Global Climate Models (GCMs) and 12 Regional Climate Models (RCMs) as climate driver. The outcome is compared against impacts driven by a more recent RCP (Representative Emission Pathways) scenario by using data of a statistical RCM. The results indicate that more robust conclusions can be drawn for some river basins, especially the Rhine and Danube basins, while diversity of results leads to higher uncertainty in the other river basins. The results also show that hydrology is very sensitive to changes in climate and effects of a general increase in precipitation can even be over-compensated by an increase in evapotranspiration. The decrease of runoff in late summer shown in most results can be an indicator for more pronounced droughts under scenario conditions.

The Soil and Water Integrated Model (SWIM) is a continuous-time semi-distributed ecohydrological model, integrating hydrological processes, vegetation, nutrients and erosion. It was developed for impact assessment at the river basin scale. SWIM is coupled to GIS and has modest data requirements. During the last decade SWIM was extensively tested in mesoscale and large catchments for hydrological processes (discharge, groundwater), nutrients, extreme events (floods and low flows), crop yield and erosion. Several modules were developed further (wetlands and snow dynamics) or introduced (glaciers, reservoirs). After validation, SWIM can be applied for impact assessment. Four exemplary studies are presented here, and several questions important to the impact modelling community are discussed. For which processes and areas can the model be used? Where are the limits in model application? How to apply the model in data-poor situations or in ungauged basins? How to use the model in basins subject to stro...

We present one of the first climate change impact assessments on river runoff that utilises an ensemble of global hydrological models (Glob-HMs) and an ensemble of catchment-scale hydrological models (Cat-HMs), across multiple catchments: the upper Amazon, Darling, Ganges, Lena, upper Mississippi, upper Niger, Rhine and Tagus. Relative changes in simulated mean annual runoff (MAR) and four indicators of high and low extreme flows are compared between the two ensembles. The ensemble median values of changes in runoff with three different scenarios of global-mean warming (1, 2 and 3 °C above pre-industrial levels) are generally similar between the two ensembles, although the ensemble spread is often larger for the Glob-HM ensemble. In addition the ensemble spread is normally larger than the difference between the two ensemble medians. Whilst we find compelling evidence for projected runoff changes for the Rhine (decrease), Tagus (decrease) and Lena (increase) with global warming, the sign and magnitude of change for the other catchments is unclear. Our model results highlight that for these three catchments in particular, global climate change mitigation, which limits global-mean temperature rise to below 2 °C above preindustrial levels, could avoid some of the hydrological hazards that could be seen with higher magnitudes of global warming. © 2016 The Author(s) BMBF/01LS1201A Beijing Natural Science Foundation National Natural Science Foundation of China National Science and Technology Major Project Norwegian Research council Islamic Development Bank

Ideally, the results from models operating at different scales should agree in trend direction and magnitude of impacts under climate change. However, this implies that the sensitivity to climate variability and climate change is comparable for impact models designed for either scale. In this study, we compare hydrological changes simulated by 9 global and 9 regional hydrological models (HM) for 11 large river basins in all continents under reference and scenario conditions. The foci are on model validation runs, sensitivity of annual discharge to climate variability in the reference period, and sensitivity of the long-term average monthly seasonal dynamics to climate change. One major result is that the global models, mostly not calibrated against observations, often show a considerable bias in mean monthly discharge, whereas regional models show a better reproduction of reference conditions. However, the sensitivity of the two HM ensembles to climate variability is in general similar. The simulated climate change impacts in terms of long-term average monthly dynamics evaluated for HM ensemble medians and spreads show that the medians are to a certain extent comparable in some cases, but have distinct differences in other cases, and the spreads related to global models are mostly notably larger. Summarizing, this implies that global HMs are useful tools when looking at large-scale impacts of climate change and variability. Whenever impacts for a specific river basin or region are of interest, e.g. for complex water management applications, the regional-scale models calibrated and validated against observed discharge should be used.

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

Flusshochwasser werden in lokale und plotzliche Sturzfluten und in Hochwasser an groseren Flussen unterschieden. Fur verschiedene Hochwasserindikatoren und Flusseinzugsgebiete ergeben sich erhebliche Unterschiede, wobei sowohl uberwiegend aus Regen als auch uberwiegend aus Schmelzwasser gespeiste Hochwasserereignisse betrachtet werden. Besondere Aufmerksamkeit finden Hochwasserereignisse an Rhein, Elbe, Weser und Ems sowie die Entwicklung von Sturzfluten infolge von Extremniederschlagen kurzer Dauer, wobei die Beobachtungen und Trends zu Modellierungsergebnissen in Beziehung gesetzt werden. Auch die Notwendigkeit von Anpassungsmasnahmen aufgrund uberwiegend positiver Trends wird diskutiert.

Past and the projected future climate change in Afghanistan has been analyzed systematically and differentiated with respect to its different climate regions to gain some first quantitative insights into Afghanistan’s vulnerability to ongoing and future climate changes. For this purpose, temperature, precipitation and five additional climate indices for extremes and agriculture assessments (heavy precipitation; spring precipitation; growing season length (GSL), the Heat Wave Magnitude Index (HWMI); and the Standardized Precipitation Evapotranspiration Index (SPEI)) from the reanalysis data were examined for their consistency to identify changes in the past (data since 1950). For future changes (up to the year 2100), the same parameters were extracted from an ensemble of 12 downscaled regional climate models (RCM) of the Coordinated Regional Climate Downscaling Experiment (CORDEX)-South Asia simulations for low and high emission scenarios (Representative Concentration Pathways 4.5 and 8.5). In the past, the climatic changes were mainly characterized by a mean temperature increase above global level of 1.8 °C from 1950 to 2010; uncertainty with regard to reanalyzed rainfall data limited a thorough analysis of past changes. Climate models projected the temperature trend to accelerate in the future, depending strongly on the global carbon emissions (2006–2050 Representative Concentration Pathways 4.5/8.5: 1.7/2.3 °C; 2006–2099: 2.7/6.4 °C, respectively). Despite the high uncertainty with regard to precipitation projections, it became apparent that the increasing evapotranspiration is likely to exacerbate Afghanistan’s already existing water stress, including a very strong increase of frequency and magnitude of heat waves. Overall, the results show that in addition to the already extensive deficiency in adaptation to current climate conditions, the situation will be aggravated in the future, particularly in regard to water management and agriculture. Thus, the results of this study underline the importance of adequate adaptation to climate change in Afghanistan. This is even truer taking into account that GSL is projected to increase substantially by around 20 days on average until 2050, which might open the opportunity for extended agricultural husbandry or even additional harvests when water resources are properly managed.

Climate change is expected to become an important driver influencing biodiversity. To protect biological diversity in the long term, nature conservationists must include potential climate change impacts in their management decisions. In order to incorporate effective climate change adaption strategies in the management of protected areas, potential threats of climate change need to be identified. In this study, climate model projections have been evaluated to derive information about the future exposure of nature parks to climate change. Indicators reflecting climate boundary conditions were selected in a cooperative process, considering both scientifically reliable climate scenario analysis and the requirements of park managers. The evaluation exhibits large uncertainties depending on the indicator. While for temperature, a warming trend is projected for all the regions, future projections for precipitation show the largest inter-model uncertainties. The Climatic Water Balance reflects the potential water availability and aids clarification to stakeholders, as it incorporates the temperature trend. The analysis robustly indicates a prolongation for the climatic growing season. The main challenges related to climate model information for decision-making are the uncertainties, different scales of climate and ecosystem processes and the finding of a common communication level for knowledge transfer. The results are useful for climate-influenced decision-making and provide one part of evidence for making adaptation decisions.

In highly developed countries electricity generation is one of the largest water users. Water is mainly used in the cooling processes of thermal power plants. In as yet less developed countries, electricity requirements are also increasing in step with increasing production and standard of living. Renewable electricity generation is gaining more attention in both highly and less developed economies. However, many types of renewable electricity generation, e.g. wind or solar, are still unreliable due to their dependence on weather conditions. This is why electricity generation by thermal power plants will remain a substantial component of the overall energy system for the next decades. An approach is applied here for analysing links between water availability and water temperature, air temperature and electricity generation by power plants. A highly disaggregated level is used combining a power plant model and hydrological models. It is applied to analyse effects of climate change on 17 nuclear power plants in Germany. Although even under baseline conditions reduced electricity generation can be observed, any further increase in air temperatures reduces electricity output of almost all nuclear power plants. The different technological and environmental conditions of each plant site mean that specific models are necessary for the simulations.