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Recent studies have assessed the impacts of climate change at specific global temperature targets using relatively short (30 year ) transient time-slice periods which are characterized by a steady increase in global mean temperature with time. The Inter-Sectoral Impacts Model Intercomparison Project Phase 2b (ISIMIP2b) provides trend-preserving bias-corrected climate model datasets over six centuries for four global climate models (GCMs) which therefore can be used to evaluate the potential effects of using time-slice periods from stabilized climate state rather than time-slice periods from transient climate state on climate change impacts. Using the H08 global hydrological model, the impacts of climate change, quantified as the deviation from the pre-industrial era, and the signal-to-noise ( SN ) ratios were computed for five hydrological variables, namely evapotranspiration (EVA), precipitation (PCP), snow water equivalent (SNW), surface temperature (TAR), and total discharge (TOQ) over 20 regions comprising the global land area. A significant difference in EVA for the transient and stabilized climate states was systematically detected for all four GCMs. In addition, three out of the four GCMs indicated that significant differences in PCP, TAR, and TOQ for the transient and stabilized climate states could also be detected over a small fraction of the globe. For most regions, the impacts of climate change toward EVA, PCP, and TOQ are indicated to be underestimated using the transient climate state simulations. The transient climate state was also identified to underestimate the SN ratios compared to the stabilized climate state. For both the global and regional scales, however, there was no indication that surface areas associated with the different classes of SN ratios changed depending on the two climate states ( t -test, p > 0.01). Transient time slices may be considered a good approximation of the stabilized climate state, for large-scale hydrological studies and many regions and variables, as: (1) impacts of climate change were only significantly different from those of the stabilized climate state for a small fraction of the globe, and (2) these differences were not indicated to alter the robustness of the impacts of climate change.

Infiltrating pavements are potentially effective climate adaptation measures to counteract arising challenges related to flooding and drought in urban areas. However, they are susceptible to clogging causing premature degradation. As part of the Dutch Delta Plan, Dutch municipalities were encouraged to put infiltrating pavements into practice. Disappointing experiences made a significant number of municipalities decide, however, to stop further implementation. A need existed to better understand how infiltrating pavements function in practice. Through 81 full-scale infiltration tests, we investigated the performance of infiltrating pavements in practice. Most pavements function well above Dutch and international standards. However, variation was found to be high. Infiltration rates decrease over time. Age alone, however, is not a sufficient explanatory factor. Other factors, such as environmental or system characteristics, are of influence here. Maintenance can play a major role in preserving/improving the performance of infiltrating pavements in practice. While our results provide the first indication of the functioning of infiltrating pavement in practice, only with multi-year measurements following a strict monitoring protocol can the longer-term effects of environmental factors and maintenance actually be determined, providing the basis for the development of an optimal maintenance schedule and associated cost–benefit assessments to the added value of this type of climate adaptation. [ABSTRACT FROM AUTHOR]

Analyses of future agricultural drought impacts require a multidisciplinary approach in which both human and environmental dynamics are studied. In this study, we used the socio-hydrologic, agent-based drought risk adaptation model ADOPT. This model simulates the decisions of smallholder farmers regarding on-farm drought adaptation measures and the resulting dynamics in household vulnerability and drought impact over time. We applied ADOPT to assess the effect of four top-down disaster risk reduction interventions on smallholder farmers' drought risk in the Kenyan drylands: the robustness of additional extension services, lowered credit rates, ex ante rather than ex post cash transfers, and improved early warnings were evaluated under different climate change scenarios. Model results suggest that extension services increase the adoption of newer low-cost drought adaptation measures while credit schemes are useful for measures with a high investment cost, and ex ante cash transfers allow the least wealthy households to adopt low-cost, well-known measures. Early warning systems are shown to be more effective in climate scenarios with less frequent droughts. Combining all four interventions displays a mutually reinforcing effect with a sharp increase in the adoption of on-farm drought adaptation measures, resulting in reduced food insecurity, decreased poverty levels, and drastically lower need for emergency aid, even under hotter and drier climate conditions. These nonlinear synergies indicate that a holistic perspective is needed to support smallholder resilience in the Kenyan drylands. [ABSTRACT FROM AUTHOR]

Analyses of future agricultural drought impacts require a multidisciplinary approach in which both human and environmental dynamics are studied. In this study, we applied the agent-based drought risk model ADOPT to assess the effect of various drought risk reduction interventions on smallholder farmers in the Kenyan drylands. Moreover, the robustness of these (non-)governmental interventions under different climate change scenarios was evaluated. ADOPT simulates water management decisions of smallholder farmers, and evaluates household food insecurity, poverty and emergency aid needs due to drought disasters. Model dynamics were informed by extensive field surveys and interviews from which decision rules were distilled based on bounded rational behaviour theories. Model results suggest that extension services increase the adoption of low-cost, newer drought adaptation measures while credit schemes are useful for cost-effective but expensive measures, and ex-ante cash transfers allow the least wealthy households to adopt low-cost well-known measures. Early warning systems show more effective in climate scenarios with less frequent droughts. Combining all four interventions displays a mutually-reinforcing effect with a sharp increase in the adoption of measures resulting in reduced food insecurity, decreased poverty levels and drastically lower need for emergency aid, even under hotter and drier climate conditions. These nonlinear synergies indicate that a holistic perspective is needed to support smallholder resilience in the Kenyan drylands. [ABSTRACT FROM AUTHOR]

In eastern Africa droughts can cause crop failure and lead to food insecurity. With increasing temperatures, there is an a priori assumption that droughts are becoming more severe. However, the link between droughts and climate change is not sufficiently understood. Here we investigate trends in long-term agricultural drought and the influence of increasing temperatures and precipitation deficits. Using a combination of models and observational datasets, we studied trends, spanning the period from 1900 (to approximate pre-industrial conditions) to 2018, for six regions in eastern Africa in four drought-related annually averaged variables: soil moisture, precipitation, temperature, and evaporative demand (E0). In standardized soil moisture data, we found no discernible trends. The strongest influence on soil moisture variability was from precipitation, especially in the drier or water-limited study regions; temperature and E0 did not demonstrate strong relations to soil moisture. However, the error margins on precipitation trend estimates are large and no clear trend is evident, whereas significant positive trends were observed in local temperatures. The trends in E0 are predominantly positive, but we do not find strong relations between E0 and soil moisture trends. Nevertheless, the E0 trend results can still be of interest for irrigation purposes because it is E0 that determines the maximum evaporation rate. We conclude that until now the impact of increasing local temperatures on agricultural drought in eastern Africa is limited and we recommend that any soil moisture analysis be supplemented by an analysis of precipitation deficit. [ABSTRACT FROM AUTHOR]

The extent and impact of climate‐related extreme events depend on the underlying meteorological, hydrological, or climatological drivers as well as on human factors such as land use or population density. Here we quantify the pure effect of historical and future climate change on the exposure of land and population to extreme climate impact events using an unprecedentedly large ensemble of harmonized climate impact simulations from the Inter‐Sectoral Impact Model Intercomparison Project phase 2b. Our results indicate that global warming has already more than doubled both the global land area and the global population annually exposed to all six categories of extreme events considered: river floods, tropical cyclones, crop failure, wildfires, droughts, and heatwaves. Global warming of 2°C relative to preindustrial conditions is projected to lead to a more than fivefold increase in cross‐category aggregate exposure globally. Changes in exposure are unevenly distributed, with tropical and subtropical regions facing larger increases than higher latitudes. The largest increases in overall exposure are projected for the population of South Asia. Plain Language Summary: Global warming changes the frequency, intensity, and spatial distribution of extreme events. We analyze computer simulations of river floods, tropical cyclones, crop failure, wildfires, droughts, and heatwaves under past, present‐day, and potential future climate conditions. Our results show that global warming increases the number of people around the world that are affected by these events each year, both for all event types combined and each type individually. Changes in the chance of being affected by extreme events are unevenly distributed in space. Particularly large increases are simulated for tropical and subtropical regions. Key Points: We quantify the pure effect of climate change on the exposure to extreme climate impact events, for both historical and future time periodsGlobal warming increases the global population exposure to river floods, tropical cyclones, crop failure, wildfires, droughts, and heatwavesThe largest increases in exposure are projected for tropical and subtropical regions [ABSTRACT FROM AUTHOR]

We investigate hydrology during a past climate slightly warmer than the present: the last interglacial (LIG). With daily output of preindustrial and LIG simulations from eight new climate models we force hydrological model PCR‐GLOBWB and in turn hydrodynamic model CaMa‐Flood. Compared to preindustrial, annual mean LIG runoff, discharge, and 100‐yr flood volume are considerably larger in the Northern Hemisphere, by 14%, 25%, and 82%, respectively. Anomalies are negative in the Southern Hemisphere. In some boreal regions, LIG runoff and discharge are lower despite higher precipitation, due to the higher temperatures and evaporation. LIG discharge is much higher for the Niger, Congo, Nile, Ganges, Irrawaddy, and Pearl and lower for the Mississippi, Saint Lawrence, Amazon, Paraná, Orange, Zambesi, Danube, and Ob. Discharge is seasonally postponed in tropical rivers affected by monsoon changes. Results agree with published proxies on the sign of discharge anomaly in 15 of 23 sites where comparison is possible. Plain Language Summary: It is still uncertain how the water cycle will respond to a warmer climate in the coming decades. To increase our understanding of the relationships between climate and hydrology, we study the past climate of the last interglacial, which was slightly warmer than the present. We present the results of a modeling approach, showing that while Northern Hemisphere precipitation was higher during the last interglacial, discharge of rivers was even higher, and floods were even larger. On the contrary, in the Southern Hemisphere precipitation, discharge and floods were lower. We show that, for some regions, precipitation, discharge, and floods do not have the same direction of change. The seasonal timing of discharge also changes for some large basins of the Northern Hemisphere. Finally, for 23 sites, we compare our results to geological evidence. These results form a useful term of comparison to both projections of the future and geological studies of past hydrology. Key Points: We present the first modeling of hydrology and floods for the last interglacialBoreal precipitation and runoff are higher than preindustrial, and boreal river discharge and flood volume are (in %) even higherMost of the discharge occurs later in the year in large river basins of the Northern Hemisphere [ABSTRACT FROM AUTHOR]

Various transboundary river basins are facing increased pressure on water resources in near future. However, little is known ab out the future drivers globally, namely, changes in natural local runoff and natural inflows from upstream parts of a basin, as well as local and upstream water consumption. Here we use an ensemble of four global hydrological models forced by five global climate models and the latest greenhouse‐gas concentration (RCP) and socioeconomic pathway (SSP) scenarios to assess the impact of these drivers on transboundary water stress in the past and future. Our results show that population under water stress is expected to increase by 50% under a low population growth and emissions scenario (SSP1‐RCP2.6) and double under a high population growth and emission scenario (SSP3‐RCP6.0), compared to the year 2010. As changes in water availability have a smaller effect when water is not yet scarce, changes in water stress globally are dominated by local water consumption—managing local demand is thus necessary in order to avoid future stress. Focusing then on the role of upstream changes, we identified upstream availability (i.e., less natural runoff or increased water consumption) as the dominant driver of changes in net water availability in most downstream areas. Moreover, an increased number of people will be living in areas dependent on upstream originating water in 2050. International water treaties and management will therefore have an increasingly crucial role in these hot spot regions to ensure fair management of transboundary water resources. Key Points: Water stress will mostly intensify in areas already under stress in all future scenarios for most transboundary river basinsChanges in water stress are dominated by local water consumption—managing local demand is thus a key strategy to alleviate future stressLess natural runoff or increased water consumption in upstream areas is the dominant driver of changes in downstream net water availability [ABSTRACT FROM AUTHOR]

Since 1990, natural hazards have led to over 1.6 million fatalities globally, and economic losses are estimated at an average of around USD 260–310 billion per year. The scientific and policy communities recognise the need to reduce these risks. As a result, the last decade has seen a rapid development of global models for assessing risk from natural hazards at the global scale. In this paper, we review the scientific literature on natural hazard risk assessments at the global scale, and we specifically examine whether and how they have examined future projections of hazard, exposure, and/or vulnerability. In doing so, we examine similarities and differences between the approaches taken across the different hazards, and we identify potential ways in which different hazard communities can learn from each other. For example, there are a number of global risk studies focusing on hydrological, climatological, and meteorological hazards that have included future projections and disaster risk reduction measures (in the case of floods), whereas fewer exist in the peer-reviewed literature for global studies related to geological hazards. On the other hand, studies of earthquake and tsunami risk are now using stochastic modelling approaches to allow for a fully probabilistic assessment of risk, which could benefit the modelling of risk from other hazards. Finally, we discuss opportunities for learning from methods and approaches being developed and applied to assess natural hazard risks at more continental or regional scales. Through this paper, we hope to encourage further dialogue on knowledge sharing between disciplines and communities working on different hazards and risk and at different spatial scales. [ABSTRACT FROM AUTHOR]

The interaction between physical drivers from oceanographic, hydrological, and meteorological processes in coastal areas can result in compound flooding. Compound flood events, like Cyclone Idai and Hurricane Harvey, have revealed the devastating consequences of the co-occurrence of coastal and river floods. A number of studies have recently investigated the likelihood of compound flooding at the continental scale based on simulated variables of flood drivers, such as storm surge, precipitation, and river discharges. At the global scale, this has only been performed based on observations, thereby excluding a large extent of the global coastline. The purpose of this study is to fill this gap and identify regions with a high compound flooding potential from river discharge and storm surge extremes in river mouths globally. To do so, we use daily time series of river discharge and storm surge from state-of-the-art global models driven with consistent meteorological forcing from reanalysis datasets. We measure the compound flood potential by analysing both variables with respect to their timing, joint statistical dependence, and joint return period. Our analysis indicates many regions that deviate from statistical independence and could not be identified in previous global studies based on observations alone, such as Madagascar, northern Morocco, Vietnam, and Taiwan. We report possible causal mechanisms for the observed spatial patterns based on existing literature. Finally, we provide preliminary insights on the implications of the bivariate dependence behaviour on the flood hazard characterisation using Madagascar as a case study. Our global and local analyses show that the dependence structure between flood drivers can be complex and can significantly impact the joint probability of discharge and storm surge extremes. These emphasise the need to refine global flood risk assessments and emergency planning to account for these potential interactions. [ABSTRACT FROM AUTHOR]

Knowledge of how uncertainty propagates through a hydrological land surface modelling sequence is of crucial importance in the identification and characterisation of system weaknesses in the prediction of droughts and floods at global scale. We evaluated the performance of five state-of-the-art global hydrological and land surface models in the context of modelling extreme conditions (drought and flood). Uncertainty was apportioned between the model used (model skill) and also the satellite-based precipitation products used to drive the simulations (forcing data variability) for extreme values of precipitation, surface runoff and evaporation. We found in general that model simulations acted to augment uncertainty rather than reduce it. In percentage terms, the increase in uncertainty was most often less than the magnitude of the input data uncertainty, but of comparable magnitude in many environments. Uncertainty in predictions of evapotranspiration lows (drought) in dry environments was especially high, indicating that these circumstances are a weak point in current modelling system approaches. We also found that high data and model uncertainty points for both ET lows and runoff lows were disproportionately concentrated in the equatorial and southern tropics. Our results are important for highlighting the relative robustness of satellite products in the context of land surface simulations of extreme events and identifying areas where improvements may be made in the consistency of simulation models. [ABSTRACT FROM AUTHOR]

In this study, we examine the spatial and temporal characteristics of water stress in China for the historical (1971–2010) and the future (2021–2050) periods using a multimodel simulation approach. Three water stress indices (WSIs), that is, the ratios of water withdrawals to locally generated runoff (WSIR), to natural streamflow (WSIQ), and to natural streamflow minus upstream consumptive water withdrawals (WSIC), are used for the assessment. At the basin level, WSIR estimates generally match the reported data and indicate severe water stress in most northern basins. At the grid cell level, the WSIs show distinct spatial patterns of water stress wherein WSIR (WSIQ) estimates higher (lower) water stress compared to WSIC. Based on the WSIC estimates, 368 million people (nearly one third of the total population) are affected by severe water stress annually during the historical period, while WSIR and WSIQ suggest 595 and 340 million, respectively. Future projections of WSIC indicate that more than 600 million people (43% of the total) might be affected by severe water stress, and half of China's land area would be exposed to stress. The found aggravating water stress conditions could be partly attributed to the elevated future water withdrawals. This study emphasizes the necessity of considering explicit upstream and downstream relations with respect to both water availability and water use in water stress assessment and calls for more attention to increasing levels of water stress in China in the coming decades. Plain Language Summary: Severe water stress in China has been widely reported, but its time evolution and spatial patterns are rarely assessed. We examine the spatial and temporal change patterns of water stress in China by using multimodel simulations and three different water stress indices (WSIs). Results suggest that different WSIs imply distinct spatial patterns of water stress over China. The WSIs indicate that water stress conditions in northern China are quite distinct from that in southern China. During the past decades (1971–2010), severe water stress is found in northern areas while little is found in southern areas. In the future (2021–2050), however, water‐stressed areas might expand in southern China and water stress levels might aggravate in urban areas, putting considerably more people exposed to severe water stress. This assessment provides useful information for regional water planning/management within the context of future climate change and socioeconomic development in China. Key Points: Water stress estimates can be much different with the consideration of upstream water withdrawal and consumptionSevere water stress conditions are found in northern China in the pastWater‐stressed areas significantly expand over southern China in the future [ABSTRACT FROM AUTHOR]

The interaction between physical drivers from oceanographic, hydrological, and meteorological processes in coastal areas can result in compound flooding. Compound flood events, like Cyclone Idai and Hurricane Harvey, have revealed the devastating consequences of the co-occurrence of coastal and river floods. A number of studies have recently investigated the likelihood of compound flooding at the continental scale based on simulated variables of flood drivers such as storm surge, precipitation, and river discharges. At the global scale, this has only been performed based on observations, thereby excluding a large extent of the global coastline. The purpose of this study is to fill this gap and identify potential hotspots of compound flooding from river discharge and storm surge extremes in river mouths globally. To do so, we use daily time-series of river discharge and storm surge from state-of-the-art global models driven with consistent meteorological forcing from reanalysis datasets. We measure the compound flood potential by analysing both variables with respect to their timing, joint statistical dependence, and joint return period. We find many hotspot regions of compound flooding that could not be identified in previous global studies based on observations alone, such as: Madagascar, Northern Morocco, Vietnam, and Taiwan. We report possible causal mechanisms for the observed spatial patterns based on existing literature. Finally, we provide preliminary insights on the implications of the bivariate dependence behaviour on the flood hazard characterisation using Madagascar as a case study. Our global and local analyses show that the dependence structure between flood drivers can be complex and can significantly impact the joint probability of discharge and storm surge extremes. These emphasise the need to refine global flood risk assessments and emergency planning to account for these potential interactions. [ABSTRACT FROM AUTHOR]

A growing number of countries are reforming their water allocation regimes through the use of economic instruments. This article analyzes the performance of economic instruments in water allocation reforms compared against their original design objectives in five European countries: England, France, Italy, Spain and the Netherlands. We identify the strengths of, barriers to and unintended consequences of economic instruments in the varying socio-economic, legal, institutional and biophysical context in each case study area, and use this evidence to draw out underlying common guidelines and recommendations. These lessons will help improve the effectiveness of future reforms while supporting more efficient water resources allocation. [ABSTRACT FROM AUTHOR]

In eastern Africa droughts can cause crop failure and lead to food insecurity. With increasing temperatures, there is an a priori assumption that droughts are becoming more severe, however, the link between droughts and climate change is not sufficiently understood. In the current study we focus on agricultural drought and the influence of high temperatures and precipitation deficits on this. Using a combination of models and observational datasets, we studied trends in six regions in eastern Africa in four drought-related annually averaged variables – soil moisture, precipitation, temperature and, as a measure of evaporative demand, potential evapotranspiration (PET). In standardized soil moisture data, we find no discernible trends. Precipitation was found to have a stronger influence on soil moisture variability than temperature or PET, especially in the drier, or water-limited, study regions. The error margins on precipitation-trend estimates are however large and no clear trend is evident. We find significant positive trends in local temperatures. However, the influence of these on soil moisture annual trends appears limited as evaporation is water limited. The trends in PET are predominantly positive, but we do not find strong relations between PET and soil moisture trends. Nevertheless, the PET-trend results can still be of interest for irrigation purposes as it is PET that determines the maximum evaporation rate. We conclude that, until now, the impact of increasing local temperatures on agricultural drought in eastern Africa is limited and recommend that any soil moisture analysis be supplemented by analysis of precipitation deficit. [ABSTRACT FROM AUTHOR]

Knowledge of how uncertainty propagates through a hydrological land surface modelling sequence is of crucial importance in the identification and characterisation of system weaknesses in the prediction of droughts and floods at global scale. We evaluated the performance of five state-of-the-art global hydrological and land surface models in the context of modelling extreme conditions (drought and flood). Uncertainty was apportioned between model used (model skill) and also the satellite-based precipitation products used to drive the simulations (forcing data variability) for extreme values of precipitation, surface runoff and evaporation. We found in general that model simulations acted to augment uncertainty rather than reduce it. In percentage terms, the increase in uncertainty was most often less than the magnitude of the input data uncertainty, but of comparable magnitude in many environments. Uncertainty in predictions of evapotranspiration lows (drought) in dry environments was especially high, indicating that these circumstances are a weak point in current modelling system approaches. We also found that high data and model uncertainty points for both ET lows and runoff lows were disproportionately concentrated in the equatorial and southern tropics. Our results are important for highlighting the relative robustness of satellite products in the context of land surface simulations and identifying areas where improvements may be made in the consistency of simulation models. [ABSTRACT FROM AUTHOR]

This study presents the development of a new bottom‐up large‐scale hydroeconomic model, Extended Continental‐scale Hydroeconomic Optimization (ECHO), that works at a subbasin scale over a continent. The strength of ECHO stems from the integration of a detailed representation of local hydrological and technological constraints with regional and global policies, while accounting for the feedbacks between water, energy, and agricultural sectors. In this study, ECHO has been applied over Africa as a case study with the aim of demonstrating the benefits of this integrated hydroeconomic modeling framework. Results of this framework are overall consistent with previous findings evaluating the cost of water supply and adaptation to global changes in Africa. Moreover, results provide critical assessments of future investment needs in both supply‐ and demand‐side water management options, economic implications of contrasting future socioeconomic and climate change scenarios, and the potential trade‐offs among economic and environmental objectives. Overall, this study demonstrates the capacity of ECHO to address challenging research questions examining the sustainability of water supply and the impacts of water management on energy and food sectors and vice versa. As such, we propose ECHO as useful tool for water‐related scenario analysis and management options evaluation. Key Points: A new large‐scale hydroeconomic model (ECHO) is developedECHO is used to evaluate the water management adaptation pathways in Africa under various socioeconomic and climate futuresFuture scenario simulations highlight the capacity of ECHO to address challenging research questions related to water‐energy‐land nexus [ABSTRACT FROM AUTHOR]

Sufficient and accurate hydro-meteorological data are essential to manage water resources. Recently developed global reanalysis datasets have significant potential in providing these data, especially in regions such as Southern Africa that are both vulnerable and data poor. These global reanalysis datasets have, however, not yet been exhaustively validated and it is thus unclear to what extent these are able to adequately capture the climatic variability of water resources, in particular for extreme events such as floods. This article critically assesses the potential of a recently developed global Water Resources Reanalysis (WRR) dataset developed in the European Union's Seventh Framework Programme (EU-FP7) eartH2Observe (E2O) project for identifying floods, focussing on the occurrence of floods in the Limpopo River basin in Southern Africa. The discharge outputs of seven global models and ensemble mean of those models as available in the WRR dataset are analysed and compared against two benchmarks of flood events in the Limpopo River basin. The first benchmark is based on observations from the available stations, while the second is developed based on flood events that have led to damages as reported in global databases of damaging flood events. Results show that, while the WRR dataset provides useful data for detecting the occurrence of flood events in the Limpopo River basin, variation exists amongst the global models regarding their capability to identify the magnitude of those events. The study also reveals that the models are better able to capture flood events at stations with a large upstream catchment area. Improved performance for most models is found for the 0.25° resolution global model, when compared to the lower-resolution 0.5° models, thus underlining the added value of increased-resolution global models. The skill of the global hydrological models (GHMs) in identifying the severity of flood events in poorly gauged basins such as the Limpopo can be used to estimate the impacts of those events using the benchmark of reported damaging flood events developed at the basin level, though this could be improved if further details on location and impacts are included in disaster databases. Large-scale models such as those included in the WRR dataset are used by both global and continental forecasting systems, and this study sheds light on the potential these have in providing information useful for local-scale flood risk management. In conclusion, this study offers valuable insights in the applicability of global reanalysis data for identifying impacting flood events in data-sparse regions. [ABSTRACT FROM AUTHOR]

Drought is a natural hazard that occurs at many temporal and spatial scales and has severe environmental and socioeconomic impacts across the globe. The impacts of drought change as drought evolves from precipitation deficits to deficits in soil moisture or streamflow. Here, we quantified the time taken for drought to propagate from meteorological drought to soil moisture drought and from meteorological drought to hydrological drought. We did this by cross-correlating the Standardized Precipitation Index (SPI) against standardized indices (SIs) of soil moisture, runoff, and streamflow from an ensemble of global hydrological models (GHMs) forced by a consistent meteorological dataset. Drought propagation is strongly related to climate types, occurring at sub-seasonal timescales in tropical climates and at up to multi-annual timescales in continental and arid climates. Winter droughts are usually related to longer SPI accumulation periods than summer droughts, especially in continental and tropical savanna climates. The difference between the seasons is likely due to winter snow cover in the former and distinct wet and dry seasons in the latter. Model structure appears to play an important role in model variability, as drought propagation to soil moisture drought is slower in land surface models (LSMs) than in global hydrological models, but propagation to hydrological drought is faster in land surface models than in global hydrological models. The propagation time from SPI to hydrological drought in the models was evaluated against observed data at 127 in situ streamflow stations. On average, errors between observed and modeled drought propagation timescales are small and the model ensemble mean is preferred over the use of a single model. Nevertheless, there is ample opportunity for improvement as substantial differences in drought propagation are found at 10% of the study sites. A better understanding and representation of drought propagation in models may help improve seasonal drought forecasting as well as constrain drought variability under future climate scenarios. [ABSTRACT FROM AUTHOR]

People living in poverty are particularly vulnerable to shocks, including those caused by natural disasters such as floods and droughts. This paper analyses household survey data and hydrological riverine flood and drought data for 52 countries to find out whether poor people are disproportionally exposed to floods and droughts, and how this exposure may change in a future climate. We find that poor people are often disproportionally exposed to droughts and floods, particularly in urban areas. This pattern does not change significantly under future climate scenarios, although the absolute number of people potentially exposed to floods or droughts can increase or decrease significantly, depending on the scenario and region. In particular, many countries in Africa show a disproportionally high exposure of poor people to floods and droughts. For these hotspots, implementing risk-sensitive land-use and development policies that protect poor people should be a priority. [ABSTRACT FROM AUTHOR]

Sufficient and accurate hydro-meteorological data are essential to manage water resources. Recently developed global re-analysis datasets have significant potential in providing these data, especially in regions such as Southern Africa that are both vulnerable and data poor. These global re-analysis datasets have, however, not yet been exhaustively validated and it is thus unclear to what extent these are able to adequately capture the climatic variability of water resources, in particular for extreme events such as floods. This article critically assesses the potential of a recently developed global Water Resource Re-analysis (WRR) dataset developed in the EU FP7 eartH2Observe project for identifying floods, focussing on the occurrence of floods in the Limpopo River basin in Southern Africa. The discharge outputs of seven global models and ensemble mean of those models as available in the WRR dataset are analysed and compared against two benchmarks of flood events in the Limpopo River basin. The first benchmark is based on observations from the available stations, while the second is developed based on flood events that have led to damages as reported in global databases of damaging flood events. Results show that while the WRR dataset provides useful data for detecting the occurrence of flood events in the Limpopo River basin, variation exists amongst the global models regarding their capability to identify the magnitude of those events. The study also reveals that the models are better able to capture flood events at stations with a large upstream catchment area. Improved performance for most models is found for the 0.25 degrees resolution global model, when compared to the lower resolution 0.5 degrees models, thus underlining the added value of increased resolution global models. The skill of the global hydrological models in identifying the severity of flood events in poorly gauged basins such as the Limpopo can be used to estimate the impacts of those events using the benchmark of reported damaging flood events developed at the basin level, though could be improved if further detail on location and impacts are included in disaster databases. Large-scale models such as those included in the WRR dataset are used by both global and continental forecasting systems, and this study sheds light on the potential these have in providing information useful for local scale flood risk management. In conclusion, this study offers valuable insights in the applicability of global re-analysis data for identifying impacting flood events in data sparse regions. [ABSTRACT FROM AUTHOR]

Most flood early warning systems have predominantly focused on forecasting floods with lead times of hours or days. However, physical processes during longer timescales can also contribute to flood generation. In this study, we follow a pragmatic approach to analyse the hydrometeorological pre-conditions of 501 historical damaging floods from 1980 to 2010 in sub-Saharan Africa. These are separated into (a) weather timescale (0-6 days) and (b) seasonal timescale conditions (up to 6 months) before the event. The 7-day precipitation preceding a flood event (PRE7) and the standardized precipitation evapotranspiration index (SPEI) are analysed for the two timescale domains, respectively. Results indicate that high PRE7 does not always generate floods by itself. Seasonal SPEIs, which are not directly correlated with PRE7, exhibit positive (wet) values prior to most flood events across different averaging times, indicating a relationship with flooding. This paper provides evidence that bringing together weather and seasonal conditions can lead to improved flood risk preparedness. [ABSTRACT FROM AUTHOR]

With 70 percent of its population living in coastal areas and low-lying deltas, Vietnam is highly exposed to riverine and coastal flooding. This paper examines the exposure of the population and poor people in particular to current and future flooding in Vietnam and specifically in Ho Chi Minh City, using new high-resolution flood hazard maps and spatial socioeconomic data. The national-level analysis finds that a third of today's population is already exposed to a flood, which occurs once every 25 years, assuming no protection. For the same return period flood under current socioeconomic conditions, climate change may increase the number exposed to 38 to 46 percent of the population. Climate change impacts can make frequent events as important as rare ones: the estimates suggest a 25-year flood under future conditions can expose more people than a 200-year flood under current conditions. Although poor districts are not found to be more exposed to floods at the national level, the city-level analysis of Ho Chi Minh City provides evidence that slum areas are highly exposed. The results of this paper show the benefits of investing today in flood risk management, and can provide guidance as to where future investments may be targeted. [ABSTRACT FROM AUTHOR]

Climate change and changing land use challenge the livability and flood safety of Dutch cities. One option cities have to become more climate-proof is to increase infiltration of stormwater into soil through permeable pavement and thus reduce discharge of stormwater into sewer systems. To analyze the market receptivity for permeable pavements in the Netherlands, this article focuses on the perception of end-users towards key transition factors in the infrastructure transformation processes. Market receptivity was studied on two levels: (1) on the system level, by analyzing 20 key factors in the Dutch urban water sector that enable wider application of permeable pavements; and (2) on the technology level, by analyzing 12 key factors that explain why decision makers select permeable pavements or not. Results show that trust between cooperating partners was perceived as the system level key factor that needs to be improved most to facilitate the wider uptake of permeable pavements. Additionally, the association of end-users with permeable pavement, particularly their willingness to apply these technologies and their understanding of what kinds of benefits these technologies could bring, was regarded the most important receptivity attribute. On the technology level, the reliability of permeable pavement was regarded as the most important end-user consideration for selecting this technology. [ABSTRACT FROM AUTHOR]

Droughts are a persistent and costly hazard impacting human and environmental systems. As climate variability continues to increase and socioeconomic development influences the distribution of wealth and people, drought risk is expected to increase in many parts of the world. The unique characteristics of droughts—namely their slow onset, large spatiotemporal extent, human‐influenced propagation, delayed impacts and teleconnection potential—make it difficult to correctly assess drought impact and calculate risk. Further complicating this calculation is the capacity for humans to make adaptive decisions before, during, and after a drought event, which in turn alters expected impacts. In this sense, droughts are equally a social and hydroclimatic issue. Risk perception is one of the main factors driving adaptation decisions, yet most models neglect how humans view and respond to risk, and in particular how experiences influence decisions through time. In this overview, we describe a framework that extends the traditional risk modeling approach to include the two‐way feedback between the transient adaptation decisions and drought exposure, vulnerability and hazard. We discuss how a sociohydrologic, agent‐based modeling setup, focused on individual and collective actions, can simulate the adaptive behaviors of different stakeholders to examine how emergent actions might influence projected drought risk. We suggest such an approach can provide a test‐bed for understanding adaptive behaviors in an increasingly drought‐prone world and could allow for better prioritization of drought adaptation strategies; refined understanding of future scenarios; and a vehicle to drive planning and resilience building. This article is categorized under: Science of Water > Water ExtremesEngineering Water > Planning WaterEngineering Water > Methods [ABSTRACT FROM AUTHOR]

Effectively preparing for the long-term challenges posed by future climate change requires decision-makers to have access to relevant climate impact assessments that are based on the best available science and communicated in a clear and consistent manner. By developing an online climate-services portal, the ISIpedia project aims to deliver subcontinental to national-level, state-of-the-art climate impact assessments with broad sector coverage to the varied public of climate adaptation planners (e.g. involved in National Adaptation Plans, NAPs, the Sendai framework, or the SDGs) and practitioners, regional knowledge hubs, trans- and interdisciplinary scientists including climate economists, and regional climate experts from the private sector, such as (re-)insurance companies. The societally and user-relevant climate-impact information generated and communicated through ISIpedia, both its content and form, is the result of an intense and ongoing dialogue – shaped by a series of workshops and a survey - between the ISIpedia project team, scientist involved in the Inter-Sectoral Impact Model Intercomparison Project (www.isimip.org) and its potential end-users. In this contribution, we will describe the current state and latest developments of the ISIpedia portal with a main focus on the global water sector. In doing so, we will show the latest climate impact assessments for the global water sector as developed under the ISIMIP2b simulation round and communicated through ISIpedia and we will demonstrate how they can be of use to a varied group of policy makers and practitioners, for example to (a) assess the potential water-related impacts and risks under climate-change and design adaptation strategies accordingly; (b) evaluate the potential benefits of following a 1.5 degree Celsius climate mitigation pathway compared to the business-as-usual; (c) to evaluate potential co-benefits and trade-offs for alternative climate impact sectors such as agriculture, energy, biodiversity, and health; and (d) to prioritize short- to long-term capacity steering of disaster risk reduction agencies, global investors, and (re-)insurance companies with the aim to foster a robust, sustainable, and risk-resilient development of societies towards the future.Next to presenting the latest scientific results, we will reflect on the lessons learnt from the stakeholder dialogues and the process of co-creation and development of such an online platform with a diverse team consisting of scientists, web-designers, and stakeholders. We will conclude with sharing ideas for further developing its design, functionalities and assessment content and by sketching our envisaged time-line towards full launch of the ISIpedia portal. [ABSTRACT FROM AUTHOR]

Climate change is leading to increased water scarcity and drought in many parts of the world. Agriculture, an important sector for the EU economy, is one of the most climate-sensitive of all economic sectors: crop yield and water use are directly affected by changes in climatological conditions. Although the EU produces most of the agricultural commodities used by its economic sectors, it meets some of its needs by importing. The availability of these imports, particularly those that rely on water, is at risk because many commodities are produced in regions that are potentially sensitive to extreme weather events and climate change. As part of the IMPREX, a Horizon 2020 project, a work package entitled "Water Economy" mapped the EU's global dependency on water resources outside its borders and assessed how increased water scarcity and drought, due to climate change, may disrupt supplies of the key food crops that it imports. This study presents the outcomes of the work package showing how levels of vulnerability will vary under different climate change scenarios. To translate climate impacts into vulnerabilities for the EU economy, we first calculated the global water demand of the EU agri-food based economy. Next, we identified which imported products are key to the EU. Finally, we assessed how water scarcity and drought could disrupt supplies of key food crops that it imports in the years 2030, 2050 and 2085 under the Representative Concentration Pathway (RCP) 2.6 and 6.0 climate change scenarios. The results of our analysis show that climate change impacts outside the EU's borders are expected to escalate and are likely to pose an increasing risk to agri-food importers in EU Member States; greater effort is needed to build adaptive capacity and resilience. The European economy will become significantly more vulnerable to water scarcity and drought conditions under climate change in the future, even under the most optimistic RCP scenario. In the near future, supplies of soybeans, rice, sugar cane, cotton, almonds, pistachios and grapes are most likely to be affected because they come from areas with significant or severe levels of water scarcity. Climate change will significantly increase the risk of disruption to these commodity imports, particularly those from Southeast Asia and the USA. In the longer term, products such as coffee, palm oil, soybean and cocoa are also likely to be impacted by increased drought conditions due to climate change altering rainfall patterns and thereby increasing the risk of drought or other water-related problems in their countries of origin. To assist producers and importers and to increase awareness of the risks that climate change poses to the agri-food business, EU policies and business strategies should consider that the region's economy is highly dependent on goods produced in locations that are vulnerable to the water-related impacts of climate change. [ABSTRACT FROM AUTHOR]