HS2.1.1

Water resource management is a key issue in climate change conditions, considering the increasing number of drought events, as well as the increase in water use for irrigation in Mediterranean region. In this context, different decision tools have been developed to optimize water use for irrigation. One crucial question for managers is the precise identification of irrigated areas. Remote sensing has shown great potential for irrigation mapping. This study aims to propose an operational approach to map irrigated areas based on the synergy of Sentinel-1 and Sentinel-2 data. An application is proposed at two study sites in Mediterranean region, in Spain and in Italy, with two climatic contexts, semiarid and humid respectively. Several classifiers are proposed to separate irrigated and rainfed areas. They are based on statistical variables from Sentinel-1 and Sentinel-2 time series data at the agricultural field scale, as well as on the contrasted behavior between the field scale and the 5-km surroundings. Support Vector Machine (SVM) classification approach is tested with different options to evaluate the robustness of the proposed methodologies. The optimal number of metrics found is five. The highest accuracy of the classifications, approximately equal to 85%, is based on training dataset with mixed reference fields from the two study sites. In addition, the accuracy is consistent at the two study sites.

How to cite: Zribi, M., Le page, M., Jarlan, L., Baghdadi, N., Brocca, L., Modanesi, S., Dari, J., Quintana Segui, P., and Elwan, E.: Irrigation mapping using Sentinel-1 and Sentinel-2 data, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8060, https://doi.org/10.5194/egusphere-egu22-8060, 2022.

This work deals with crop monitoring in a semi-arid environment, the Mediterranean region, where up to 80-90% of already over-exploited water resources are used for irrigation. To help sustainable use of water resources in agriculture, more efforts have to be made to water use through a better assessment of crop water stress, evapotranspiration, and soil moisture at the plot scale on large areas.

This study is focused on the diurnal and seasonal variation of the backscatter coefficient and the interferometric coherence over an olive orchard, located in the Chichaoua region (central Morocco), that has an area of 2.4ha, irrigated by drip system, with olives trees of 20-years-old. The study site was equipped, since May-2019, with a radar device consisting of 7 C-band horn-antennas at the top of a 20m-high-tower, that collects measurements at 4-polarizations allowing radar acquisitions in high temporal frequency with a timestep of 15min.  An Eddy-covariance system has been also installed for measuring energy balance and the physiological functioning of olives trees with sapflow and dendrometer sensors on olives trunks. The study site is visible at the intersection of three different sentinel-1 orbit passes allowing to have six acquisitions every 10days to compare them with in-situ radar measurements at different incidence angles.

Both the backscattering coefficient s⁰  and the interferometric coherences are analyzed. At a seasonal scale, all s⁰  polarizations show a low temporal frequency profile with amplitude lower than 3dB. For VV-polarization, in 2021, it is quite constant, with a slight decrease of 1 dB during the summer, while for 2020, an increase of 2dB is observed at the end of the spring. At HV-polarization no particular seasonal behavior can be seen. On the contrary, a marked diurnal profile is observed at VV-polarization, which is closely correlated with plant activity, with daily amplitude varying between 3dB in winter to 5dB in summer. The diurnal s⁰  signature is low during night, increases from 6AM, reaches its maximum during 2 to 6PM, and then decreases to recover its low value around midnight.

Concerning the interferometric coherence r, similar behavior to the one observed over tropical forest is noted. The r daily evolution shows a clear diurnal cycle, with amplitude varying between 0.3 in winter to 0.7 in summer. During this latter, r is high (~0.9) at night when the wind and vegetation activity are low, and begins to decrease at 7AM, with vegetation activity start, before the wind picks up at 8AM, reaching minimum value at 7PM (~0,4). It then follows a rapid increase to reach its maximum value (0.9) at midnight. A high sensitivity to rainy events is also noted, corresponding to very low r values. It is worth noticing than r estimated between measurements separated by 6 days, show similar diurnal profiles, with r lower amplitude (0.2 to 0.4), suggesting it can be characterized by Sentinel-1 morning and evening observations. Additional work as to be carried on to relate this radar diurnal cycle to water cycle, that would be good omen to monitor water stress from spaceborne C-band radar sensors.

How to cite: Chakir, A., Frison, P.-L., Khabba, S., Villard, L., Ouaadi, N., Zribi, M., Le-dantec, V., Ezzahar, J., Erraki, S., and Jarlan, L.: Diurnal and seasonal behavior observed by C-band radar measurements at high temporal frequencies over an olive orchard in a Mediterranean region, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4151, https://doi.org/10.5194/egusphere-egu22-4151, 2022.

Abstract:

Hydrological modelling in karst environments is a difficult task due to the inherent complexity of the karst system and the usual lack of information about its geometrical description. The hydrological processes of karst systems in Mediterranean semiarid environments are particularly difficult to simulate mathematically due to the pattern of long dry periods and short wet periods. In this study, we tested the ability of the open-source SWAT hydrologic modelling code to simulate the behaviour and hydrologic output of a karstic watershed in a Mediterranean semiarid environment (SE Spain). Calibration and first validation were accomplished using a 20-year and 10-year record of stream water discharge, respectively, at the catchment outlet. Additional testing of the model was accomplished using groundwater discharge data from four natural springs in the watershed and by comparing the results of the SWAT model with the SIMPA model (a hydrological model used by the Spanish national water authority to simulate the water balance among others). Likewise, an adapted form of the Nash-Sutcliffe Efficiency (NSE) index for arid environments, ANSE, is presented. Based on results, the simulated behaviour was good and very good (with ANSE values of 0.96 and 0.78 for the calibration and validation periods respectively). SWAT and SIMPA results provide spatial distributions of the main hydrological processes of the watershed, such as aquifer recharge, actual evapotranspiration, and surface runoff, being verified as useful tools for water policy managers in karstic environments.

Keywords:

Water balance; karst aquifer springs; SWAT; SIMPA; ANSE index; Mediterranean karstic catchment.

How to cite: Jodar, A., Palacios - Cabrera, T., Bailey, R. T., Melgarejo - Moreno, P., Legua - Murcia, P., and Hussein, E. E.: Evaluation of the water response in a Mediterranean karstic catchment (SE Spain) with the SIMPA and SWAT models, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1390, https://doi.org/10.5194/egusphere-egu22-1390, 2022.

In the Atlas Mountains range, streamflow is largely generated from meltwater supplied by the snowpack during spring and early summer. In this manner, snow is considered an important factor which determining water availability in semi-arid and arid mountains. This substantial part of freshwater stored in the form of snow contributes significantly to mountainous runoff. However, the contribution of snow and rain to the annual and multi-annual water balance remain largely unknown. Hydrological modeling is needed to support water resource assessment and management in the Atlas range. As meteorological data is often scarce, the models must be able to simulate the spatiotemporal heterogeneity of forcing variables while maintaining a low data input requirement.

In this study, the performance of the snowmelt runoff model (SRM) is assessed to simulate and forecast daily runoff essentially from snowmelt and rainfall at the Rheraya watershed in the Moroccan High Atlas range over the 2010 - 2016 period. The SRM runoff simulation is tested under two forcing inputs: (i) four snowmelt rates previously estimated by a classical temperature-index model (TI) and three enhanced temperature index models that respectively include the potential clear-sky direct radiation (HTI), the incoming solar radiation (ETI-A), and net solar radiation (ETI-B); (ii) calculated snowmelt from the snow cover area (SCA) products of Moderate-Resolution Imaging Spectroradiometer (MODIS).

All SRM simulated runoff were subjected to calibration and validation through the measured runoff in the Tahanaout weather station. The sensibility of recession coefficients was also evaluated. The SRM simulations results over the validation period show an acceptable performance.

Keywords: Runoff, SRM, snowmelt, SCA, temperature index model; enhanced degree-day models, MODIS, semi-arid climate, Rheraya, High Atlas, Morocco.

How to cite: Bouamri, H., Boudhar, A., and Kinnard, C.: A comparative study of snowmelt runoff modelling at Rheraya watershed in the Moroccan High Atlas Mountains, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3894, https://doi.org/10.5194/egusphere-egu22-3894, 2022.

Excess phosphorus (P) in wastewater can produce eutrophication, posing a serious risk to the safety of water resources and ecosystems. Therefore, effective pollutant removal including P from wastewater is the key strategy to save the environment and public health. Multi-soil-layering (MSL) is a promising nature-based technology that mainly relies on a soil mixture containing iron to remove P-pollution from wastewater. Fifteen water quality parameters were monitored in the MSL influent to determine which ones have the strongest relationship with total phosphorus (TP) removal. The influence of hydraulic loading rate (HLR) and climatic variables on the removal of TP was investigated. Three data-driven methods including multiple linear regression (MLR), k-nearest neighbors (KNN), and random forest (RF) were conducted to predict TP removal at the MSL system outlet. In contrast to climatic variables, the results reveal that the HLR has a significant impact (p <0.05) on TP removal (47%-90%) in the MSL system. Furthermore, using a feature selection technique, the HLR, pH, orthophosphate, and TP were suggested as the relevant input variables affecting TP removal in the MSL system, while an examination of accuracy shows that the RF model achieves good prediction accuracy (R² = 0.94).

How to cite: Sbahi, S., Ouazzani, N., Hejjaj, A., Lahrouni, A., and Mandi, L.: Total phosphorus removal in multi-soil-layering nature-based technology: assessment of influencing factors and prediction by data driven methods, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4125, https://doi.org/10.5194/egusphere-egu22-4125, 2022.

Due to the high variability of climate variables under climate change, the assessment of the climate impacts on water management, ecosystems restoration, as well as climate change adaptation requires very detailed climate information regionally and ideally at a local scale. State-of-the-art coupled land-atmosphere numerical models incorporate the water and energy exchange processes in the soil–vegetation–atmosphere continuum in a physically consistent way, thereby their simulations capture the complete evolution of state variables and provide the complex linkages across compartmental boundaries in the Earth system. As an effort to contribute to climate- and water-related research in South Africa, we present a high spatial and temporal resolution climatological atmosphere–land surface–hydrology analysis dataset covering the period 2000-2020. This analysis dataset is dynamically downscaled from ERA5 reanalysis using the Weather Research and Forecasting Model Hydrological modeling system (WRF-Hydro). This dataset covers the territory of South Africa with a grid resolution of 4 km and a time interval of 1 hour.

As a result, a comprehensive analysis dataset is provided, including the land surface and atmosphere state conditions, as well as the water flux components for the joint atmospheric-terrestrial water balance. The model performance is evaluated based on in-situ measurement records and remote sensing results. For instance, we evaluate the soil moisture and soil temperature using continuous in-situ measurement over six South Africa locations following a climate gradient, and the spatiotemporal trends of soil moisture are further evaluated using a newly developed radar-retrieved Surface Moisture Index (SurfMI). Biases of simulation results have been identified that should be taken into account in any application.

How to cite: Zhang, Z., Laux, P., Arnault, J., Baade, J., Urban, M., Schmullius, C., and Kunstmann, H.: Presentation of a high-resolution present-day joint atmosphere-land surface-hydrology simulation dataset for South Africa, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10349, https://doi.org/10.5194/egusphere-egu22-10349, 2022.

Mediterranean mountain areas are hotspots when evaluating vulnerability towards global warming. Future hydro-climatic scenarios present a probable situation of high alteration of these systems, mainly conditioned by an increase of extreme events frequency (e.g., heatwaves and droughts). Dehesas are one of these characteristic landscapes. They result from the co-evolution of autochthonous ecosystems and human settlement in a sustainable balance, with high relevance from the environmental (biodiversity) and socioeconomic (livestock farming, including the Iberian pork food industry) view. They have a complex vegetation cover structure formed by isolated trees, mainly holm oak, cork oak, and oak, Mediterranean shrubs, and pastures, with specific phenological cycles. This complexity conditions the partitioning of water fluxes, shifting their importance along the year. 

This work proposes to quantify the actual role of the vegetation in the water fluxes partitioning over mountain Mediterranean areas. Specifically, this study is conducted in the Martin Gonzalo watershed upstream of the Martin Gonzalo dam, located within the Cardeña-Montoro Natural Park (southern Spain). The vegetation role is assessed by comparing three different hydrological model simulations conducted using the distributed and physically-based hydrological model WiMMed (Watershed Integrated Model for Mediterranean Areas): i) non-vegetation, in which no vegetation is included in the modelling; ii) static vegetation, in which vegetation is defined in the model using the official land cover maps from the regional authorities; and iii) dynamical vegetation, in which vegetation information is provided by a dynamical spectral mixture analysis using Sentinel-2. All water fluxes in the water balance are quantified and compared between the three simulations. Results highlight, on the one hand, the key role of vegetation in controlling water partitioning and, on the other hand, the importance of considering the yearly phenological changes to model water partitioning accurately.  

This work has been funded by project SIERRA Seguimiento hIdrológico de la vEgetación en montaña mediteRránea mediante fusión de sensores Remotos en Andalucía, with the economic collaboration of the European Funding for Rural Development (FEDER) and the Office for Economy, Knowledge, Enterprises and University of the Andalusian Regional Government.

How to cite: Andreu, A., Pimentel, R., Torralbo, P., Aparicio, J., González-Dugo, M. P., and Polo, M. J.: Quantifying the importance of vegetation in water fluxes partitioning over Mediterranean mountain areas: a study case in Cardeña-Montoro Natural Park (Spain), EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11403, https://doi.org/10.5194/egusphere-egu22-11403, 2022.

West Africa is undergoing a drastic transition in climate, demography and land use. This has a strong impact on the development capacities of every country in the region. While regional trends in each of these three key areas are relatively well known, decision makers scientists are often lacking a proper vision of how climate and land use are evolving at spatial and temporal scales that count most for the living of populations. Moreover, the hydrological implications of these climate and land use evolutions are hardly documented, while models have still difficulties in reproducing them. It is therefore of utmost importance to rely on combined observation-modeling strategies to better apprehend the ongoing transition and explore possible future trajectories in terms of water resources, hydrological risks and food security. To that end, the regional long-term observatory AMMA-CATCH aims at monitoring the impacts of global changes on the continental water cycle and the functioning of the critical zone in West Africa, through a combination of mesoscale observations, data analyses and local to regional modeling. Three main issues are currently guiding our observation strategy: (1) Multi-decadal trends of hydro-climatic hazards (past, current and projected); (2) Dynamics of vegetation, land use and their interactions with the water cycle; (3) Trajectories of water resources. This strategy is supported by metrology, technology watch and innovation. The AMMA-CATCH observatory has been collecting data since 1990 on four highly instrumented sites (each of the roughly covering 10000 to 20000 km²), staggered from North to South of West Africa, in order to measure the latitudinal gradient in different eco-climatic zones (Benin, Niger, Mali), and since 2016, from complementary sites in Senegal and Niger, to assess the longitudinal variability in the Sahelian area. It is part of the OZCAR French Critical Zone observatory network and supported by French research institutions with long term engagement.

This presentation aims at highlighting recent results obtained by analyzing the data of the AMMA-CATCH observatory covering a large range of hydrology/land use related issues, such as tipping points in hydrology, rainfall intensification, infrastructure design norms, soil restoration, local and regional hyper-resolution hydrological modeling, …. This presentation also aims at encouraging a African-European structuration of socio-hydro-climate observations in this region in order to provide a strong science-based foundation for the elaboration of adaptation policies.

How to cite: Cohard, J.-M., Grippa, M., Lawin, E., Peugeot, C., Assanou, B., Boucher, M., Chaffard, V., Diawara, M., Etchanchu, J., Faye, G., Galle, S., Mainassara, I., Malam-Abdou, M., Mamadou, O., Mariscal, A., Mougin, E., Moumouni, S., Panthou, G., and Lebel, T.: The AMMA-CATCH observatory : a platform to address scientific and societal issues in West-Africa, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12616, https://doi.org/10.5194/egusphere-egu22-12616, 2022.

The hydraulic basin of Tensift is a concrete example of diversification and increase of pollutants discharged without treatment into the natural environment. This issue strongly threatens the water resources of this basin and makes it extremely sensitive to pollution, including groundwater that is a strategic resource in this area. The purpose of this study is to simulate two phenomena, which are hydrodynamic operation and leaching of solute in the conditions of the Haouz region.

The study was conducted on the R3 perimeter. It is an irrigated agricultural sector in the region of Sidi Rahal, about 40 km east of Marrakech city, Morocco. To carry out this work, the VS2DI model was chosen for the following reasons: accessibility, reliability, and free of charge. This model popularly uses Cartesian or radial coordinates and allows solving the Richards equation to model the water transfer and the convection-dispersion equation to model the transport of solutes and heat in a porous and variably saturated medium. Our research team collects the data needed for the VS2DI model during the agricultural season of 2002/2003. The collected data is related to climatic conditions, soil, plant, and cultivation practice. 

The results obtained showed that for the scenarios studied the moisture of the upper layers increases and tends towards saturation depending on the value of the flux imposed on the surface. However, the deep layers remain unsaturated for a long time because of drainage. Thus, after one day and for a flux of 12 cm/d, the first 40cm of the soil is saturated. For the 4 cm/d flow, the saturation, during 24h, did not exceed the 30 cm depth. Knowing that these upper layers are subject to strong thermal gradients and root extractions. On the other hand, in the simulations of solute transport, we try to describe the evolution of the degree of contamination of a layer after a period of one day as a function of the imposed water flow and the concentration of solute on the surface.

The results obtained by these simulations show that at 20cm depth the solute concentration starts to change only after a period of 4h and that the rate of change of the concentration is almost linear with time for each given water flux. Beyond 4h, the rate of change of the solute at this depth decreases in a non-linear way with the increase of the water flux imposed on the surface. From these first tests, we can say that this model performs water balances in an acceptable way. It has also been proved that the saturation rate of the soil increases with the increase of the imposed flux and of the moisture of this layer. Finally, it was found that the rate of change of the solute at a given depth decreases non-linearly with the imposed water flux at the surface.

How to cite: el moussaoui, E. H., Moumni, A., and Lahrouni, A.: Simulation study of water balance and solute transport in agricultural soil in Haouz region, Morocco, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3201, https://doi.org/10.5194/egusphere-egu22-3201, 2022.

One of the most deterministic aspects of water consumption in Mediterranean ecosystems is
evapotranspiration, which accounts for returning a large fraction of precipitation into the atmosphere.
Pine trees as an indigenous species play an important role in the soil water balance in these ecosystems.
The main objective of this study is to simulate the contribution of evapotranspiration components of pine
(Pinus brutia) in the water balance. The research includes a comprehensive sensitivity analysis and model
calibration. The field study is located in Athalassa Forest Park in Cyprus. The 10-ha field is covered by a
combination of seasonal vegetation and indigenous trees and shrubs, with a 5 to 6-m planting distance.
The site is relatively flat with a mean slope of 4% and an average annual rainfall of 315 mm.
Pine tree evapotranspiration components were modeled using a one-dimensional NOAH-MP land surface
model (one grid cell). Due to incomplete knowledge about the extent of the tree roots (root zone area),
we modeled the grid cell in three different scenarios according to tree density (the distance between
trunks, 5-6 m), tree canopy area (7.5 m2 on average), and leaf area index (LAI = 2.5 on average) to
represent our field study in the model. We analyzed the sensitivity of all modeled water balance
components, namely, evapotranspiration (evaporation from bare soil, transpiration, and evaporation
from the canopy), runoff (surface and subsurface runoff), soil moisture change of the soil column to all
related soil and vegetation input parameters, using a local sensitivity analysis. We also examined the
impact of the number of soil layers with roots, different soil layers thicknesses, and the slope of the area
on the model outputs (water balance components). The results showed that NOAH-MP is capable of 
representing a semi-arid Mediterranean ecosystem.

This research has received financial support from the PRIMA MED (2018 Call) SWATCH Project and the
Water JPI (Joint Call 2018) FLUXMED Project, both funded through the Cyprus Research and Innovation
Foundation.

How to cite: Amini, M., Djuma, H., Sofokleous, I., Eliades, M., and Bruggeman, A.: Evapotranspiration components of pine (Pinus brutia) trees in a Mediterranean ecosystem, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-13496, https://doi.org/10.5194/egusphere-egu22-13496, 2022.

Every year Africa is affected by extreme weather related hazards which, combined with high levels of vulnerability and increasing population exposure, result in considerable impacts to people and assets. Here we present recent activities in the development of an African Multi Hazard Early Warning System for disaster risk reduction, a multi-year project funded by the Italian Government through the United Nations Office for Disaster Risk Reduction. After a brief introduction on the main project goals, the presentation will give insights on one of its key activities, focused on strengthening impact-based flood monitoring and forecasting capabilities for the Greater Horn of Africa region. This ongoing activity foresees the implementation of a probabilistic impact-based flood forecasting system based on the Flood PRObabilistic Operative Forecasting System (Flood-PROOFS) developed by CIMA Foundation and run routinely in several world regions. Flood-PROOFS has as its core the Continuum distributed hydrological model, which takes as input meteorological variables and several other static and dynamic data to simulate the hydrological processes in the focus region. For this application, Continuum was set up at hourly time step on 17 hydrologically consistent domains, with grid resolutions ranging between 250m and 3.3km, ultimately covering a surface of 6.82 million km². Given the relative scarcity of in situ data, model calibration is based on observed river discharges at 130+ river gauging stations, as well as on GLEAM satellite evaporation and soil moisture products. A 40-year continuous hydrological reanalysis is produced by forcing the model with ERA5 atmospheric reanalysis bias corrected for precipitation and temperature. Daily runs include model updates with satellite precipitation estimates and 5-day forecasts forced by the Global Forecast System. Ongoing activities are expanding the current deterministic setup to ensemble forecasts, as well as coupling hydrological forecasts in real time with state of the art global inundation maps, to estimate impact-based flood warnings by integrating information on exposure, vulnerability and coping capacity. Such information is used in the operational monitoring and early preparedness versus impending disasters, as well as to design prevention and mitigation measures, which is fundamental to prioritize and optimize the use of available resources for disaster response.

How to cite: Alfieri, L., Libertino, A., Campo, L., Ghizzoni, T., Masoero, A., Menchise, C., Poletti, M. L., Gabellani, S., Rossi, L., Rudari, R., Rossi, L., Mouakkid Soltesova, K., Gatkuoth, K., Ouma, J., Amdihun, A., Nshimirimana, G., Tramblay, Y., and Massabò, M.: Developing an operational impact-based flood forecasting system for the Greater Horn of Africa region, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8680, https://doi.org/10.5194/egusphere-egu22-8680, 2022.

Droughts can be defined as a climatic phenomenon in which periods of low precipitation may generate water shortages in various parts of the whole of the hydrological cycle. Droughts are natural hazards that usually have severe negative impacts on the economy, society, and environment. Meteorological drought is generally described by the magnitude and duration of the precipitation deficit. Therefore, precipitation is the primary variable often used in the calculation of drought indices, such as the Standardized Precipitation Index (SPI). The SPI is particularly useful for drought monitoring, allowing the identification of different drought types and their impacts on different systems.

Nevertheless, the sparse network of observation stations data-scarce regions, especially in developing countries, is often an obstacle to drought monitoring. To overcome this limitation, remote sensing observations of precipitation are increasingly used over large-scale regions. Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) data are of particular interest. The CHIRPS monthly precipitation product at 0.05° spatial resolution, for the period 1981 to 2020, and the SPI have been used to study the intensity, duration, and spatial extent of meteorological droughts in Morocco at different time-scales (monthly, seasonal, and annual). The use of several time scales allowed us to highlight the spatial occurrence, temporal characteristics, and impacts of drought on different hydrological and agricultural landscapes of Morocco. Based on a threshold level of SPI, drought event statistics (number of events, duration, severity, and magnitude) over 39 years were derived at the watershed scale to highlight regional differences at multiple time scales. The results of this study allow existing water and agricultural strategies to be adapted to different types of drought. The results will also open perspectives for the development of drought monitoring and early warning systems in Morocco and over Africa.

How to cite: Oukaddour, K., Fakir, Y., and Le Page, M.: Analysis and assessment of meteorological droughts in Morocco using CHIRPS data., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4049, https://doi.org/10.5194/egusphere-egu22-4049, 2022.

The Horn of Africa drylands (HAD) are highly vulnerable to hydroclimatic extremes, with droughts and floods frequently leading to famines, crop losses, and significant humanitarian crises. However, development of robust mitigation measures has been hindered by the lack of understanding of the drivers of the two main rainfall seasons in the region: the long (March–May) and short (October–December) rains. In particular, the inter-annual variability of the long rains has been subject of much debate; a significant amount of research has attempted to diagnose the drivers of the observed decline in the long rains. Given the ecological and socio-economic importance of the two rain seasons for the HAD region, understanding the major moisture sources and their variability in both space and time is essential. Such an analysis can help disentangle the causes of temporal variability in rainfall, especially the long rains, improve forecasts, and build ecosystem and community resilience against hydroclimatic extremes.

To trace the origin of rainfall over the HAD region, we use global simulations of the FLEXPART version 9.01, forced with the ERA-Interim reanalysis for a period of 37 years (1980–2016). The FLEXPART outputs include the properties of the air parcels at 3-hourly time steps, which are then post-processed to identify the source regions of rainfall using the Heat and Moisture Tracking Framework (HAMSTER v1.2.0) described by Keune et al. (2021). Using this framework, we first trace the rainfall occurring over the HAD region during the long and short rain seasons to their terrestrial and oceanic sources spatially. Then, we track the changes in the contributions of ocean and land evaporation to HAD rainfall in time over the 37-year period. 

Preliminary results show that around 80% of HAD rainfall originates from Indian Ocean evaporation, for both seasons. For both seasons the contribution of evaporation from land is relatively low compared to the oceanic contribution. For the long rains, a similar amount of moisture originates from recycling (local) and remote sources (10.9% and 10.5% respectively). On the other hand the short rains show a larger proportion of local recycling (13.8%) relative to remote land evaporation (9.4%). The larger contribution of remote land sources for the long rains arises from the Indian subcontinent and Southeast Asia. Further, we shed light on the trends and anomalies in source regions for the two rain seasons, with particular focus on the anomalies in moisture sources that are characteristic of extreme dry and wet conditions.

References:

Keune, J., Schumacher, D. L., and Miralles, D. G.: A holistic framework to estimate the origins of atmospheric moisture and heat using a Lagrangian model, Geosci. Model Dev. Discuss. [preprint], in review, 2021.

How to cite: Koppa, A., Keune, J., MacLeod, D. A., Singer, M., and Miralles, D. G.: Unraveling the Origin of Rainfall over Horn of Africa Drylands, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5330, https://doi.org/10.5194/egusphere-egu22-5330, 2022.

Over the past century, climate change has been affecting precipitation regimes across the world (Giorgi et al., 2008). In the Mediterranean regions, there is a persistent declining trend of precipitation and runoff decreases (Martinez-Fernandez et al.2013), contributing to a desertification process with dramatic consequences for agricultural and water resources sustainability.

The position of the island of Sardinia, in the center of the western Mediterranean basin, with its low level of both urbanization and human activity, its complex orography with many mountains and alluvial valleys, and its strong correlation with North Atlantic Oscillation index makes Sardinia a primary reference for the investigation of climate change effects on Mediterranean ecosystems.

Two contrasting basins are investigated, the Rio Fluminimaggiore basin and Rio Flumendosa basin, which are different for position in the island (west side vs. east side), size (83km2 vs. 934  km2) and land covers (Rio Fluminimaggiore is mainly covered by forest while Rio Flumendosa land cover is mixed). These are basin are crucial for the water resources system of Sardinia, because include dams. In particular, two large dams, the Flumendosa Dam at Nuraghe and the Mulargia Dam at Monte Su Rei, are in the Flumendosa basin with a total reservoir of 600 million of cubic meter. Long database of hydrologic data (runoff, precipitation, temperature) are available for both basins from 1925, and in both basins eddy covariance towers are installed in representative field sites.

A distributed hydrological model at basin scale has been developed, which predicts runoff, soil water storage, evapotranspiration and grass and tree leaf area index (LAI). The model has been successfully calibrated for runoff estimation. An alarming historical decreasing trend of runoff and winter precipitation has been detected in both basins. We used the future climate scenarios predicted by Global climate models (GCM) in the Fifth Assessment report of the Intergovernmental Panel on Climate Change (IPCC). Hydro-meteorological scenarios are generated using a weather stochastic generator that allows simulation of hydrometeorological variables from GCM future scenarios. The use of the model allowed to predict soil water balance and vegetation dynamics for the generated hydrometeorological scenarios. Results demonstrated that tree dynamics are strongly influenced by the inter-annual variability of atmospheric forcing, with tree density changing according to seasonal rainfall. At the same time the tree dynamics affected the soil water balance. We demonstrated that future warmer scenarios will impact forest, which could be not able to adapt to the increasing droughts. The decrease of tree cover will affect water resources of the Sardinian basins. In the Flumendosa basin future scenarios predict a reduction of the runoff, which is crucial for the dam reservoir recharge. The water resources system planning needs to carefully takes into account the effect of future climate change on water resources and vegetation dynamics.

How to cite: Sirigu, S., Corona, R., and Montaldo, N.: Climate change impact on water resources and forest sustainability of two Sardinian basins, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11918, https://doi.org/10.5194/egusphere-egu22-11918, 2022.

High Atlas is considered as one of the major reservoirs of freshwater for crop yield and hydropower production in the plains of central Morocco. Nevertheless, snowmelt and discharge in this region have been reported very vulnerable to climate variability, which threaten the sustainability and development of socio-economic activities in this region. Thus, there’s a strong need to understand the spatio-temporal variability of water cycle in addition to the impact of the changing climate on the main hydrological components.  This work focuses on the application of SWAT model in the mountainous watershed of Oued Al Abid river, which is potentially threatened by climate and anthropogenic forcings. The study is based on two main axes: (i) the implementation of SWAT to model the snowmelt discharge processes over this watershed taking into consideration the karst structure of this area, (ii) the projection of climate change has been also analyzed by forcing SWAT model using three simulations of Regional Climate Model RCA4. Results showed that SWAT model performed satisfactory to very good in reproducing discharge and reservoir inflow. According to the results, the hydrological components showed a significant variability, particularly in snowmelt, infiltration and surface runoff. Furthermore, negative variation and peak shift in the projected inflows to the dam have been demonstrated by this study.

How to cite: Taia, S., Erraioui, L., Chao, J., Scozzari, A., and El Mansouri, B.: Using SWAT model to evaluate the plausible changes in a karst snow-fed watershed in the Moroccan High Atlas, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-13351, https://doi.org/10.5194/egusphere-egu22-13351, 2022.