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Precipitation and surface runoff vary strongly in space and time across Morocco. The country's water management is primarily governed at the basin level, following a decentralized approach. However, in some cases, water is shared between basins, which increases the complexity and the potential for conflicts. The current study, conducted at Oum Er Rbia (OER) basin and Moroccan country scales, evaluates the use of novel Earth Observation (EO) products (surface soil moisture and evapotranspiration) combined with global water balance model (PCR-GLOBWB) for basin level surface runoff and country level drought assessment. At the basin level, OER River discharges considerable surface water amounts from the Middle Atlas Mountains to large reservoirs, providing water for various sectors, predominantly irrigated agriculture. The EO based PCR-GLOBWB model yielded satisfactory monthly surface runoff results validated through two OER streamflow gauges. Spatially distributed quarterly annual surface runoff matched well with the simulations achieved through more detailed Soil and Water Assessment Tool (SWAT) modeling. EO data and PCR-GLOBWB model were subsequently used to investigate country scale drought occurrence using various drought indicators (Standardized Precipitation Index (SPI), Standardized Runoff Index (SRI), and Standardized Soil Moisture Index (SSMI)). The study concludes on a foremost local to regional nature of droughts. Consistent assessment of water stress situations, from the basin to the country scale, suggest the good potential of novel EO products and global models to support demand driven water management, especially in data scarce areas. [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]

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]