Suchergebnisse

Abstract. Soil moisture is a key variable for drought monitoring, but soil moisture
measurements networks are very scarce. Land-surface models can provide a
valuable alternative for simulating soil moisture dynamics, but only a few
countries have such modelling schemes implemented for monitoring soil
moisture at high spatial resolution. In this study, a soil moisture accounting model (SMA) was regionalized over the Iberian Peninsula, taking
as a reference the soil moisture simulated by a high-resolution land-surface model. To estimate the soil water holding capacity, the sole parameter required to run the SMA model, two approaches were compared: the direct estimation from European soil maps using pedotransfer functions or an indirect estimation by a machine learning approach, random forests, using as predictors altitude, temperature, precipitation, potential evapotranspiration and land use. Results showed that the random forest model estimates are more robust, especially for estimating low soil moisture levels. Consequently, the proposed approach can provide an efficient way to simulate daily soil moisture and therefore monitor soil moisture droughts, in contexts where high-resolution soil maps are not available, as it relies on a set of covariates that can be reliably estimated from global databases.

Abstract. In Morocco, socio-economic activities are highly vulnerable to extreme weather events. This study investigates trends in mean and extreme rainfall, run-off and temperature, as well as their relationship with large-scale atmospheric circulation. It focuses on two Moroccan watersheds: the subhumid climate region of Bouregreg in the north and the semi-arid region of Tensift in the south, using data from 1977 to 2003. The study is based on a set of daily temperature, precipitation and run-off time series retrieved from weather stations in the two regions. Results do not show a homogeneous behaviour in the two catchments; the influence of the large-scale atmospheric circulation is different and a clear spatial dependence of the trend analysis linked to the distance from the coast and the mountains can be observed. Overall, temperature trends are mostly positive in the studied area, while weak statistically significant trends can be identified in seasonal rainfall, extreme rainfall events, average run-off and extreme run-off events.

Purpose
The purpose of this paper is to identify vulnerable areas for flood hazard and to analyze stakes exposed in touristic valley of Morrocan mountains. The three goals are: methodological (low-cost diagnosis without starting data), operational (to show the risk and identify avenues of prevention in Ourika) and incentive (to reproduce this on other sectors in Morocco).


Design/methodology/approach
The vulnerability of three areas of the Ourika valley (the most frequented) was assessed by a hydro-geomorphological study, human frequentation surveys and risk indices at the building scale.


Findings
Surveys carried out in the field allowed the identification of areas with high risk, the evaluation of the buildings' vulnerability and the frequentation of the valley. Evacuation plans, allowing easy access to potential refuges in case of flood, were finally proposed.


Originality/value
The reproducible, inexpensive and relevant nature of the approach (integrated and spatialized) helps in decision making and facilitating dialogue for prevention.

Abstract. To define a dry day, the most common approach is to identify a fixed threshold below which precipitation is considered equivalent to zero. This fixed threshold is usually set to account for measurement errors and precipitation losses due to the atmospheric evaporation demand. Yet, this threshold could vary in time according to the seasonal cycle and in the context of long-term trends, such as the increase in temperature due to climate change. In this study, we compare extreme dry spells, defined either with a fixed threshold for a dry day (1 mm) or with a time-varying threshold estimated from reference evapotranspiration (ET0), for a large database of 160 rain gauges covering large parts of the Mediterranean basin. Results indicated positive trends in ET0 during summer months (June, July and August) in particular. However, these trends do not imply longer dry spells since the daily precipitation intensities remain higher than the increase in the evaporative demand. Results also indicated a seasonal behavior: in winter the distribution of extreme dry spells is similar when considering a fixed threshold (1 mm) or a time-varying threshold defined with ET0. However, during summer, the extreme dry-spell durations estimated with a 1 mm threshold are strongly underestimated in comparison to extreme dry spells computed with ET0. We stress the need to account for the atmospheric evaporative demand instead of using fixed thresholds for defining a dry day when analyzing dry spells, with respect to agricultural impacts in particular.

Abstract. Floods are the primary natural hazard in the French Mediterranean area, causing damages and fatalities every year. These floods are triggered by heavy precipitation events (HPEs) characterized by limited temporal and spatial extents. A new generation of regional climate models at the kilometer scale have been developed, allowing an explicit representation of deep convection and improved simulations of local-scale phenomena such as HPEs. Convection-permitting regional climate models (CPMs) have been scarcely used in hydrological impact studies, and future projections of Mediterranean floods remain uncertain with regional climate models (RCMs). In this paper, we use the CNRM-AROME CPM (2.5 km) and its driving CNRM-ALADIN RCM (12 km) at the hourly timescale to simulate floods over the Gardon d'Anduze catchment located in the French Mediterranean region. Climate simulations are bias-corrected with the CDF-t method. Two hydrological models, a lumped and conceptual model (GR5H) and a process-based distributed model (CREST), forced with historical and future climate simulations from the CPM and from the RCM, have been used. The CPM model confirms its ability to better reproduce extreme hourly rainfall compared to the RCM. This added value is propagated on flood simulation with a better reproduction of flood peaks. Future projections are consistent between the hydrological models but differ between the two climate models. Using the CNRM-ALADIN RCM, the magnitude of all floods is projected to increase. With the CNRM-AROME CPM, a threshold effect is found: the magnitude of the largest floods is expected to intensify, while the magnitude of the less severe floods is expected to decrease. In addition, different flood event characteristics indicate that floods are expected to become flashier in a warmer climate, with shorter lag time between rainfall and runoff peak and a smaller contribution of base flow, regardless of the model. This study is a first step for impact studies driven by CPMs over the Mediterranean.

Abstract. The Mediterranean region is characterized by intense
rainfall events giving rise to devastating floods. In Maghreb countries such
as Morocco, there is a strong need for forecasting systems to reduce the
impacts of floods. The development of such a system in the case of ungauged
catchments is complicated, but remote-sensing products could overcome the
lack of in situ measurements. The soil moisture content can strongly
modulate the magnitude of flood events and consequently is a crucial
parameter to take into account for flood modeling. In this study, different
soil moisture products (European Space Agency Climate Change Initiative, ESA-CCI; Soil Moisture and Ocean Salinity, SMOS; Soil Moisture and Ocean Salinity by the Institut National de la Recherche Agronomique and Centre d'Etudes Spatiales de la Biosphère, SMOS-IC; Advanced Scatterometer, ASCAT; and
ERA5 reanalysis) are compared to in situ measurements and one continuous
soil-moisture-accounting (SMA) model for basins located in the High Atlas
Mountains, upstream of the city of Marrakech. The results show that the
SMOS-IC satellite product and the ERA5 reanalysis are best correlated with
observed soil moisture and with the SMA model outputs. The different soil
moisture datasets were also compared to estimate the initial soil moisture
condition for an event-based hydrological model based on the Soil
Conservation Service curve number (SCS-CN). The ASCAT, SMOS-IC, and ERA5
products performed equally well in validation to simulate floods,
outperforming daily in situ soil moisture measurements that may not be
representative of the whole catchment soil moisture conditions. The results
also indicated that the daily time step may not fully represent the
saturation state before a flood event due to the rapid decay of soil
moisture after rainfall in these semiarid environments. Indeed, at the
hourly time step, ERA5 and in situ measurements were found to better
represent the initial soil moisture conditions of the SCS-CN model by
comparison with the daily time step. The results of this work could be used
to implement efficient flood modeling and forecasting systems in semiarid
regions where soil moisture measurements are lacking.

Abstract. Every year Africa is hit by extreme floods which, combined with high levels of vulnerability and increasing population exposure, often result in humanitarian crises and population displacement. Impact-based forecasting and early warning for natural hazards is recognized as a step forward in disaster risk reduction, thanks to its focus on people, livelihoods, and assets at risk. Yet, the majority of the African population is not covered by any sort of early warning system. This article describes the setup and the methodological approach of Flood-PROOFS East Africa, an impact-based riverine flood forecasting and early warning system for the Greater Horn of Africa (GHA), with a forecast range of 5 d. The system is based on a modeling cascade relying on distributed hydrological simulations forced by ensemble weather forecasts, link to inundation maps for specific return period, and application of a risk assessment framework to estimate population and assets exposed to upcoming floods. The system is operational and supports the African Union Commission and the Disaster Operation Center of the Intergovernmental Authority on Development (IGAD) in the daily monitoring and early warning from hydro-meteorological disasters in eastern Africa. Results show a first evaluation of the hydrological reanalysis at 78 river gauging stations and a semi-quantitative assessment of the impact forecasts for the catastrophic floods in Sudan and in the Nile River basin in summer 2020. More extensive quantitative evaluation of the system performance is envisaged to provide its users with information on the model reliability in forecasting extreme events and their impacts.

We present a long-term assessment of precipitation trends in Southwestern Europe (1850-2018) using data from multiple sources, including observations, gridded datasets and global climate model experiments. Contrary to previous investigations based on shorter records, we demonstrate, using new long-term, quality controlled precipitation series, the lack of statistically significant long-term decreasing trends in precipitation for the region. Rather, significant trends were mostly found for shorter periods, highlighting the prevalence of interdecadal and interannual variability at these time-scales. Global climate model outputs from three CMIP experiments are evaluated for periods concurrent with observations. Both the CMIP3 and CMIP5 ensembles show precipitation decline, with only CMIP6 showing agreement with long term trends in observations. However, for both CMIP3 and CMIP5 large interannual and internal variability among ensemble members makes it difficult to identify a trend that is statistically different from observations. Across both observations and models, our results make it difficult to associate any declining trends in precipitation in Southwestern Europe to anthropogenic forcing at this stage. ; This work was supported by the research projects CGL2017-82216-R, CGL2017-83866-C3-3-R and PCI2019-103631, financed by the Spanish Commission of Science and Technology and FEDER; CROSSDRO project financed by the AXIS (Assessment of Cross(X) - sectoral climate Impacts and pathways for Sustainable transformation), JPI-Climate co-funded call of the European Commission and INDECIS which is part of ERA4CS, an ERA-NET initiated by JPI Climate, and funded by FORMAS (SE), DLR (DE), BMWFW (AT), IFD (DK), MINECO (ES), ANR (FR) with co-funding by the European Union (Grant 690462).