A global-scale evaluation of extreme event uncertainty in the eartH2Observe project

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

Disaster risk, climate change, and poverty: assessing the global exposure of poor people to floods and droughts

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

The potential of global reanalysis datasets in identifying flood events in Southern Africa

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

Education, financial aid, and awareness can reduce smallholder farmers' vulnerability to drought under climate change

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

Education, financial aid, and awareness can reduce smallholder farmers' vulnerability to drought under climate change

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

A Spatially Explicit Assessment of Growing Water Stress in China From the Past to the Future

International audienceIn 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 (WSI R), to natural streamflow (WSI Q), and to natural streamflow minus upstream consumptive water withdrawals (WSI C), are used for the assessment. At the basin level, WSI R 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 WSI R (WSI Q) estimates higher (lower) water stress compared to WSI C. Based on the WSI C estimates, 368 million people (nearly one third of the total population) are affected by severe water stress annually during the historical period, while WSI R and WSI Q suggest 595 and 340 million, respectively. Future projections of WSI C 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

Measuring compound flood potential from river discharge and storm surge extremes at the global scale

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

Water shortages worsened by reservoir effects

The expansion of reservoirs to cope with droughts and water shortages is hotly debated in many places around the world. We argue that there are two counterintuitive dynamics that should be considered in this debate: supply–demand cycles and reservoir effects. Supply–demand cycles describe instances where increasing water supply enables higher water demand, which can quickly offset the initial benefits of reservoirs. Reservoir effects refer to cases where over-reliance on reservoirs increases vulnerability, and therefore increases the potential damage caused by droughts. Here we illustrate these counterintuitive dynamics with global and local examples, and discuss policy and research implications.</p

Impact of precipitation and increasing temperatures on drought trends in eastern Africa

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.ISSN:2190-4987ISSN:2190-497

Dependence between high sea-level and high river discharge increases flood hazard in global deltas and estuaries

When river and coastal floods coincide, their impacts are often worse than when they occur in isolation; such floods are examples of ‘compound events’. To better understand the impacts of these compound events, we require an improved understanding of the dependence between coastal and river flooding on a global scale. Therefore, in this letter, we: provide the first assessment and mapping of the dependence between observed high sea-levels and high river discharge for deltas and estuaries around the globe; and demonstrate how this dependencemay influence the joint probability of floods exceeding both the design discharge and design sea-level. The research was carried out by analysingthe statistical dependence between observed sea-levels (and skew surge) from the GESLA-2 dataset, and river discharge using gauged data from the Global Runoff Data Centre, for 187 combinations of stations across the globe. Dependence was assessed using Kendall’s rank correlation coefficient (휏)and copula models. We find significant dependence for skew surge conditional on annual maximum discharge at 22% of the stations studied, and for discharge conditional on annual maximum skew surge at 36% of the stations studied. Allowing a time-lag between the two variables up to 5 days, we find significant dependence for skew surge conditional on annual maximum discharge at 56% of stations, and for discharge conditional on annual maximum skew surge at 54% of stations. Using copula models, we show that the joint exceedance probability of events in which both the design discharge and design sea-level are exceeded can be several magnitudes higher when the dependence is considered, compared to when independence is assumed. We discuss several implications, showing that flood risk assessments in these regions should correctly account for these joint exceedance probabilities.Water Resource