Enter Zoom Meeting


Regional hydrological change: advances from observations to models and management in the Mediterranean and in Africa

Water is a strategic issue in the African and Mediterranean regions, mainly because of the scarcity of the available resources in quantity and/or quality. The Mediterranean and African climates and the surface hydrology are characterized by a strong variability in time and space and the importance of extreme events droughts and floods. During the last century, changes of all kinds and intensities, including in the agricultural sector have affected surface and underground reservoirs and water uses. Global and regional hydrological models have recently seen tremendous advances in improved representations of physical processes underpinning these impacts, resulting in better reproductions of observed variables such as streamflow and water extent. As a result, they are increasingly used for predicting socio-economic risks of floods, droughts and water stress in regions around the globe. However, the use of hydroclimatic models for disaster risk reductions in data-sparse regions, while gradually improving, is still limited in comparison.

This session intends to identify and analyse the changes in the Mediterranean and Africa hydrology, in terms of processes, climate and other water-related topics, including environmental and food security. It will gather specialists in observation and modelling of the various water fluxes and redistribution processes within the catchments. Case studies showcasing practical experiments and innovative solutions in decision making under large uncertainty are ncouraged. Contributions addressing the following topics are welcome:

• Spectacular case studies of rapid changes in water resources;
• Using various sources of information for comparing past and present conditions;
• Differentiating climatic and anthropogenic drivers (including GCM reanalysis);
• Modelling hydrological changes (in surface and/or ground water);
• Impacts of extreme events on water systems.

Convener: Lionel Jarlan | Co-conveners: Said Khabba, Fiachra O'Loughlin, María José Polo, Meron Taye, Yves Tramblay, Mehrez Zribi
| Tue, 24 May, 08:30–11:50 (CEST)
Room 2.44

Tue, 24 May, 08:30–10:00

Chairpersons: Lionel Jarlan, Fiachra O'Loughlin, Aaron Boone

Session introduction

Emna Ayari et al.

To ensure food security, the irrigation water demand is increasing with the growth of the population. Therefore, the optimization of irrigation scheduling is compulsory to improve water resources management where soil moisture estimation is an essential component. Over the last decades, remote sensing demonstrated its potential to retrieve soil water content. In this work, we investigate the potential of the Synthetic Aperture Radar (SAR) data in L-band acquired by Advanced Land Observing Satellite-2 (ALOS-2) and C-band data acquired by Sentinel-1 sensor, to estimate soil moisture in heterogenous row crop fields locally irrigated with drips in a semi-arid area in the center of Tunisia.

During SAR data acquisitions, ground data gathering campaigns were carried out over irrigated pepper fields. The in-situ measurements included soil surface parameters such as soil roughness and soil moisture, and pepper biophysical parameters such as vegetation height (H), Leaf Area Index (LAI), and cover fraction (Fc) measurements. Based on the pepper field’s organization and ground observations, we calculated an average soil moisture value per field as the sum of 15% of vegetation row soil moisture and 85% bare soil moisture.

In this context, we suggested the modification of the Water Cloud Model (WCM) to simulate the L-band signal in Horizontal-Horizontal polarization (L-HH) and C-band signal in Vertical-Vertical polarization (C-VV). The total backscattering is simulated as the sum of vegetation row cover contribution weighted by Fc and bare soil contribution weighted by (1-Fc). The vegetation row contribution is calculated as the sum of the scattered signal from pepper seedlings described by vegetation height and bare soil part contribution attenuated by vegetation. The bare soil part is considered as the contribution of two parts where the first is irrigated directly by drips and the second separates two successive pepper seedlings relatively far from water emitters namely the non-irrigated part. The bare soil signal simulations are performed using the Integral Equation model modified by Baghdadi (IEM-B).  

After calibration and validation of the modified WCM using three-folds cross-validation, we investigate the potential of the proposed model by various simulations under constant roughness parameters and different conditions of pepper biophysical parameters and bare soil moisture values. The examination of linear slopes between modeled backscattering and soil moisture measurements highlights that model sensitivity decreases as a function of the increase of pepper vegetation parameters (Fc and H). The sensitivity of the modified WCM is limited where Fc and pepper height are less than 0.4 and 0.5 m, respectively, using L-HH data and lower than 0.3 and 0.3 m using C-VV data. The aforementioned findings revealed the potential of the proposed WCM to simulate SAR signal in heterogeneous context of soil moisture.

How to cite: Ayari, E., Kassouk, Z., Lili-Chabaane, Z., Baghdadi, N., and Zribi, M.: Estimation of soil moisture within drip irrigation context in pepper fields using ALOS-2 and Sentinel-1 data. , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3937, https://doi.org/10.5194/egusphere-egu22-3937, 2022.

Mehrez Zribi et al.

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.

Nadia Ouaadi et al.

Irrigated agriculture is the largest consumer of freshwater in the world, particularly in the South Mediterranean region, that already suffers from water shortages. For a rational and sustainable management of water resources, monitoring the water stress status of plants can contribute to an optimal use of irrigation.

C-band radar data have shown great potential for monitoring soil and vegetation hydric conditions. Over forests, several studies have observed a diurnal cycle in the backscattering coefficient that can reach up to 1 dB between morning and evening measurements acquired by sun-synchronous satellites. This cycle is assumed to be related to the physiological functioning of trees, in particular to the diurnal cycle of the vegetation water content. A recent study also identified a diurnal cycle in the temporal coherence measured over tropical forests. The authors hypothesized that transpiration was the main factor in the decrease in coherence at dawn, especially since winds are almost zero at that time of day. While the diurnal cycle of radar data is well documented over trees, the behavior of annual crops is yet to be investigated. In this context, the objective of this work is to present a preliminary study of this behavior over wheat by assuming that water movement in the plant could lead to a daily cycle of the interferometric coherence and backscattering coefficient.

An experiment funded by LMI TREMA and TOSCA/CNES has been conducted over a winter wheat field in Morocco since January 2020. The experimental setup consists of six C-band antennas installed at the top of a 20 m high tower. It allows the full polarization acquisition of the backscattering coefficient and the interferometric coherence with a 15 minutes time step. The field is also equipped with an eddy covariance and weather stations that allow half-hourly measurements of evapotranspiration and wind speed. In addition to automatic measurements, field campaigns are also carried out to measure soil moisture, surface roughness, vegetation above-ground biomass and cover fraction.

The preliminary analysis of in situ radar acquisitions over the 2020 agricultural season reveals the existence of a diurnal cycle of the interferometric coherence whose amplitude increases with the development of vegetation. In particular, a drop in coherence was observed at dawn. This drop is concomitant with the increase in evapotranspiration, which may indicate that it could be due to the sapflow. On the other hand, low coherence values are recorded at the end of the afternoon, which may be related to wind peaks. For the backscattering coefficient, a good agreement is observed between the evolution of its daily average and the evolution of evapotranspiration. These results, which need to be consolidated, demonstrate the existence of important dependencies between the C-band response and the physiological functioning of wheat, which opens insights for the monitoring of crop water status using radar data acquired at sub-daily timescale. This rather highlights the interest of a future geostationary radar mission.

How to cite: Ouaadi, N., Villard, L., Khabba, S., Frison, P.-L., Ezzahar, J., Kasbani, M., Fanise, P., Chakir, A., Le Dantec, V., Zribi, M., Er-Raki, S., and Jarlan, L.: In situ radar measurements for monitoring the physiological functioning of wheat crops in the semi-arid area, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2768, https://doi.org/10.5194/egusphere-egu22-2768, 2022.

Adnane Chakir et al.

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.

Manel Khlif et al.

With climate change, mainly drought, the situation of water stress in most Mediterranean countries is worsening with the high demand for agricultural water and the scarcity of water resources. Forecasts have found that more than 33 countries, including Tunisia and Spain, will face extremely high water stress by 2040, threatening agriculture and food security. In this study, we analyze the potential of different drought indices to identify drought periods for two regions with different climates: Kairouan in Tunisia, and Lleida in Spain, and we identify the indices that give more accuracy for cereal yield prediction.

To achieve the objectives of this study, satellite data was used: MODIS (NDVI and LST) and SMOS. Spatial resolution enhancement algorithms have been applied, such as DISaggregation based on Physical And Theoretical scale Change (DISPATCh), to improve the spatial resolution of SMOS from 40 km to 1 km. In this study, we focus on two principal parameters to identify agricultural drought: Soil Moisture Anomaly Index (SMAI) calculated from soil moisture DISPATCh data, which gives an idea of the soil water status and Vegetation Anomaly Index (VAI) derived from MOD13Q1, which reflects the vegetative activity. 

Over the past 10 years, from the 2010/2011 agricultural year to 2019/2020, we have identified dry periods of agricultural drought based on VAI and SMAI. The results show that SMAI can detect more dry periods in space and time than VAI. For the study area in Tunisia, the strongest correlation obtained between wheat yield and SMAI is in November (R = 0.71). This result highlights the importance of water during this period. The correlation between wheat yield and SMAI decreased slightly in January (R=0.55), February (R=0.57), and March (R=0.63). However, the vegetation cover started to appear in January. A stronger, but later, correlation with VAI in March (R=0.63). For the second study area in Spain, Lleida, the correlation between drought index and yield anomaly of wheat and barley was studied separately. For barley, the increase in the correlation between grain yield and VAI started in February (R= 0.71), March (R=0.73), and then April where it reached its maximum (R=0.87). A more important correlation is noted in March with the SMAI which is about 0.8. Similarly, for wheat, the best correlation between yield and SMAI is recorded in March (R= 0.88) and with a slightly less important correlation with VAI of the order of 0.51 in March.

In conclusion, this study shows the interest in improving the spatial resolution of soil moisture to better study agricultural drought and its effect on cereal yield.

How to cite: Khlif, M., Chahbi Bellakanji, A., Escorihuela, M. J., Stefan, V.-G., and Lili Chabaane, Z.: Potential of remote sensing data to analyze the effect of drought on wheat yields in the Mediterranean region: study area Kairouan Tunisia and Lleida Spain, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-291, https://doi.org/10.5194/egusphere-egu22-291, 2022.

Aicha Chahbi et al.

Global food security is based on a limited number of species mainly cereals, maize and rice.                                    
In semi-arid region, the availability of cereals on the international market at competitive prices in relation to local production has led to a change in domestic demand in these countries and has affected the capacity of populations to cover their basic food needs. An operational early grain yield prediction system has been needed to assist policy makers in making initial assessments and planning for annual grain imports. In this context, the main objective of this study is to develop a method for the early estimation of grain and grain straw yields based on high spatial resolution optical satellite data and radar data. Thus, we used two lines of research: the first is based on analysing the relationship between vegetation index and the VH/VV ratio with cereals yields measured in situ. The second axis is based on the estimation of the cereal yields based on a combined index. This last is a combination of the radar index VH/VV and an optical index.

For the first axe, a 22 Sentinel-2 and 55 Sentinel-1 images acquired between 01/09/2017 and 31/08/2018 are used. From the optical data, three spectral indices (NDVI, EVI and EVI2) are calculated and from the Radar data, we calculated the VH/VV polarization ratio. At the same time, we realized experimental measurements made on 54 test plots of dry or irrigated cereals carried out in study area during the 2017-2018 agriculture year. The first approach based on a statistical analysis between the NDVI, EVI and EVI2 vegetation indices and the yields measured showed that NDVI is the best optical index allowing an estimate of grain yield from mid-March with a correlation coefficient R2 = 69.22% for the average weight of the grains and R2 = 72.38% for the average weight of the straw. Validation of estimates obtained by remote sensing shows that this approach is robust, with an error of 1.79qx/ha and 1.21 qx/ha, respectively, for seed and straw yields. The evolution of yields as a function of the VH/VV ratio was then studied for different dates. The analysis allows that an early estimate can be made the 10th of March based on this ratio with a correlation coefficient R2 = 53.79% for the average weight of the seeds and R2 = 56% for the average weight of the straw.

For the second axe, a combined index was developed based on the combination of the radar index VH/VV and the optical index. The results show that the most suitable combination is the one between the Radar Index and the NDVI where correlations R2 = 63.64% for the average seed weight and R2 = 64.03% for the average straw weight. The validation of the estimates obtained by this combined index is made with an error equal to 1.97 qx/ha and 1.31 qx/ha, respectively for the seed and straw yields.

How to cite: Chahbi, A., Zribi, M., Shil, E., and Lili-Chabaane, Z.: Characterization of cereals in a semi-arid context based on remote sensing indicators from high spatial resolution images from the Sentinel 1 and Sentinel 2 satellite in central Tunisia, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9150, https://doi.org/10.5194/egusphere-egu22-9150, 2022.

Antonio Jodar et al.


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.


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.

Hafsa Bouamri et al.

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.

Sofyan Sbahi et al.

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.

Zhenyu Zhang et al.

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.

Ana Andreu et al.

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.

Eva Contreras Arribas et al.

In Mediterranean areas the high seasonal and annual variability in precipitation produces large changes in the reservoir water availability. However, the state of these water bodies is not only subjected to the weather and the natural hydrology of this kind of system, but is often modified on one hand by the water demands and on the other hand, by the land uses upstream which have serious effects on the water quality of the river contributions. Remote sensing and GIS methods are currently emerging as an alternative to traditional methods like field survey (usually laborious, time consuming and expensive) to analyse the evolution of the state of these water bodies in terms of the free-water reservoir surface.

In this paper, the Guadalquivir River Basin (southwest Spain), where the gradual and intense development of large irrigated areas (which has increased in the last 50 years by more than 50%) leads to an increase in the storage capacity in the basin (which doubles during the next 40 years), was taken as a research object. The Global Surface Water (GSWE) online machine, combined with historical, hydrological, meteorological and water quality data, were used to spatially quantify free-water reservoir surface during the period 1984-2020. This allowed us, through a water balance approach on a monthly basis, the estimation of water inputs and outputs to analyse the hydrological changes in terms of seasonality, but also considering the effects of the dam operations and the changes in water quality in terms of sediments loads in those reservoirs where turbidity data series are available. 

The results show the increase of the free-water reservoir surface along the study period, which is consistent with the dramatic decrease of the contribution of the water flowing into the last receiver of the network of reservoirs (Alcalá del Río dam). This also implies the storage of associated substances such as sediments (mainly from the extensive olive groves areas located upstream) that produce the filling of the reservoirs, and turbidity episodes in flood events, which was verified with field measurements in the main control points of the basin.

This work has been funded by the project Integrated Management for the control of water inputs and sediments in reservoir systems in the Guadalquivir basin, 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: Contreras Arribas, E., Pimentel, R., Aguilar, C., Aparicio, J., and Polo, M. J.: Assessing annual and seasonal changes in the free-water reservoir surface state and turbidity conditions: implications for dam management in the Guadalquivir River Basin (Spain), EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12963, https://doi.org/10.5194/egusphere-egu22-12963, 2022.

Jean-Martial Cohard et al.

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.

Aicha Moumni and Abderrahman Lahrouni

Due to the water shortage and poor management of limited water resources in semi-arid region, the improvement of irrigation efficiency became crucial. In this context, the objective of this work is to estimate water content and evapotranspiration using the HYDRUS-1D model. 

The study was carried out over wheat fields of the R3 perimeter (located in the Haouz plain of Marrakesh-Safi region, Morocco) for the growing season of 2003/2004. Four types of data have been used, namely: data related to the soil, data related to the plant, data related climatic parameters (recorded in a station close to the study site), and data related to the local agricultural practice.

We firstly used the inverse method, available in HYDRUS-1D, in order to estimate the hydrodynamic parameters of cultivated soil. The analysis of the convergence and consistency of this method showed that for correct calibration of the model, it is necessary to take into account the vertical heterogeneity of the soil. Therefore, we proceeded to the manual calibration of the model by testing different choices of initial parameters and taking into account the soil  vertical heterogeneity. The calibration carried out concerned mainly the water content of the soil and the evapotranspiration of the surface.

The simulations of the real evapotranspiration (ET) were carried out using the inputs obtained for the manual calibration. The results obtained by the HYDRUS-1D model gave an overestimation of the soil water content. This underestimation can be explained either by an underestimation of the LAI inputs or by the root extraction module that needs to be readjusted.

In the present work, the HYDRUS-1D model was tested, for the first time, over an area of Haouz plain in central Morocco.  The obtained results are not yet final. The model needs to be tested sufficiently over a wide spatio-temporal range. The HYDRUS-1D model is widely used in different regions of the world and the extensive literature reports a good score on the consistency and robustness of the model. Thus we are convinced that, overall, HYDRUS-1D seems to be an adequate model to estimate with acceptable accuracy the water content and the real ET under semi-arid conditions. It is also a promising tool for planning and decision support in the field of water and agro-environmental research.

How to cite: Moumni, A. and Lahrouni, A.: Towards a calibration of the HYDRUS-1D model on a wheat crop in the semi-arid conditions of Haouz region, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3121, https://doi.org/10.5194/egusphere-egu22-3121, 2022.

Tue, 24 May, 10:20–11:50

Chairpersons: Fiachra O'Loughlin, Lionel Jarlan, Aaron Boone

el houcine el moussaoui et al.

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.

Youness Ouassanouan et al.

Piedmonts around the Mediterranean are important hydro-agro-systems bridging between the mountains (upstream) where streamflow is generated, and the adjacent plains (downstream) where water is used. In Morocco, the piedmonts of the High-Atlas Mountains host secular irrigation channels (seguia) that divert the streamflow for irrigating a traditional agriculture since hundreds of years. These traditional hydro-agro-systems might be threatened by the effects of global change that requires in-depth study to identify the main causes and propose better sustainable management. The present study was carried out in the semi-arid piedmont of the High-Atlas mountains. A detailed analysis of hydro-climatological data was performed between 1965 and 2018 together with associated agricultural trends over the period 1984-2020. Statistical tests (Mann-Kendall and Pettitt) were used to assess whether there were significant trends or not in the long-term evolution of water resources. The findings revealed a significant decrease of the surface water and groundwater resource. The SPI meteorological drought index delineated three main droughts during 1982-1986, 1998-2008 and 2013-2017. Paradoxically, the scarcity and decrease trends in water resources are associated with an agricultural change from seasonal crops (cereals) to perennial crops (trees). The subsequent growing agricultural water demand exacerbates the water shortage and worsen the groundwater depletion.

How to cite: Ouassanouan, Y., Fakir, Y., Simonneaux, V., Kharrou, M. H., Bouimouass, H., and Chehbouni, A.: Sustainability issues of a Mediterranean semiarid irrigated piedmont inferred frommulti-decadal trends of water resources and land use, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4725, https://doi.org/10.5194/egusphere-egu22-4725, 2022.

Benoit Huet et al.

The basal crop coefficient (Kcb) is the ratio of crop evapotranspiration that primarily corresponds to transpiration. A comparison of different approaches using remote sensing observations for the estimation of Kcb of grapevines is carried out. The study is done over a cv.Tempranillo vineyard located in Catalunya, Spain from March to July 2021.

The different approaches tested are the following: 1- a linear relation between NDVI and Kcb(Campos et al., 2010), 2 and 3 - the two different approaches proposed in (Allen and Pereira, 2009), where Kcb is estimated thanks to a density factor. The first version lies on an exponential of Leaf Area Index (LAI), the second version lies on the tree height and the fraction of effective exposed area. 4 and 5- an intercepted photosynthetic radiation (fiPAR) model (Oyarzun et al., 2007) using inferred crop height and width is related to Kcb through the (Lebon et al., 2003) and (Picón-Toro et al., 2012) proposals. 6- The generic tabulated approach proposed by (Allen et al., 1998) is also used to compare to a reference, however it must be remembered that those tabulations are only indicative.

The different approaches are compared to the actual Kcb retrieved from a flux tower and the reference evapotranspiration of a nearby weather station. The resulting Kcb are injected into a water budget and daily evapotranspirations are finally compared to actual measurements.

The simple linear method did not transfer well on this particular vineyard. The "Allen& Pereira LAI" and the "Oyarzun/Picon" had the best performance with a respective r2, RMSE of 0.57, 0.60 and 0.54 0.62 mm.day-1 on evapotranspiration estimates. However, the former approach through LAI does not seem really operational. The later method only needs to be parameterized with some easy to retrieve descriptions of the plot and plantation. In any case, a drawback of these NDVI based methods is the possible appearance of adventices, or the presence of a inter-row crop. Those must be withdrawn from the NDVI signal of the grapevine.

How to cite: Huet, B., Le Page, M., Tous, D., Fanise, P., Duthoit, S., and Bellvert, J.: A comparison of different NDVI based methods for grapevines Kcb, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10231, https://doi.org/10.5194/egusphere-egu22-10231, 2022.

Mohsen Amini et al.

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

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.

Myriam Benkirane et al.

Mediterranean mountainous regions are strongly affected by flash flood events causing many damages. The vulnerability to flooding in the Moroccan High Atlas, especially in the Tensift basin, has been increasing over the last decades. Rainfall-runoff models can be very useful for flash flood forecasting. However, event-based models require a reduction of their uncertainties related to the estimation of initial moisture conditions before a flood event. Soil moisture may strongly modulate the magnitude of floods and is thus a critical parameter to be considered in flood modeling.

Indeed, several studies have assimilated satellite soil moisture observations into rainfall-runoff models to improve their flood forecasting capabilities.

In order to have a better representation of the watershed states which leads to a better estimation of the streamflow. By exploiting the strong physical connection between soil moisture dynamics and precipitation, it has been shown that satellite soil moisture observations can also be used to improve the quality of precipitation observations.

The aim of this study is to compare daily soil moisture measurements obtained by time domain reflectometry (TDR) at Sidi Rahal station with satellite soil moisture products (European Space Agency Climate Change Initiative, ESA-CCI), in order to estimate the initial soil moisture conditions for each event. The systematic bias between soil moisture products and in situ measurements was corrected using a bias correction method. The correlations between soil moisture products and in situ observations are about 0.77 after the correction.  

However, a modeling approach based on rainfall-runoff observations of 30 sample flood events have been applied, from (2011 to 2018), in the Ghdat basin were extracted and modeled by an event-based rainfall-runoff model (HEC-HMS) which is based on the Soil Conservation Service (SCS-CN), loss model, and a Clark unit hydrograph was developed for simulation and calibration of the 10-minute rainfall runoff.

A similar approach could be implemented in other watersheds in this region for further operational purposes. This method is very satisfactory for reproducing rainfall-runoff events in this small Mediterranean mountainous watershed, the same approach could be implemented in other watersheds in this region. The results of this study indicate that the remote sensing data are theoretically useful for estimating soil moisture conditions in data-sparse watersheds in arid Mediterranean regions.

Keywords: Soil moisture; Floods; Remote sensing; Hydrological modelling, CN method, Mediterranean basin.

How to cite: Benkirane, M., Laftouhi, N.-E., and Khabba, S.: Impact of initial soil moisture on the hydrological response: Application for flood forecasting in the Mediterranean mountainous watershed., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3786, https://doi.org/10.5194/egusphere-egu22-3786, 2022.

Lorenzo Alfieri et al.

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.

Kaoutar Oukaddour et al.

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.

Behnam Mirgol et al.

Climate change, as one of the most significant challenges that humans currently face, is defined as a shift in climate patterns in response to increasing greenhouse gas emissions in the atmosphere. Notably, climate change has been associated with global warming temperature, regional changes in rainfall patterns and extreme events. Such changes in climate are emerging at a time of rapid growth for many economies in the southern Mediterranean region, stressing the need to understand their impacts on sectors better. In addition, unlike other regions, very little research has been undertaken to understand how climate has changed (and will change) over the area and how such changes may affect the agricultural sector. Here, using trend analysis and the non-stationary generalized extreme value (GEV) model, we examine whether the probability of extreme agrometeorological risks has changed over the last 60 years in response to the globally warming temperature. We then quantify the magnitude of such changes over different phenological stages for wheat, maize and rice, highlighting the most vulnerable areas to extreme conditions in the southern Mediterranean region. Extreme agrometeorological risks are estimated using multiple state-of-the-art observational and reanalyzed daily datasets (REGEN, BERKELEY, CHIRPS, ERA5 and ERA5-land), and using multiple drought indices (standardized precipitation-evapotranspiration index [SPEI], standardized antecedent precipitation-evapotranspiration index [SAPEI], frequency and duration of dry spells) and heat stress indices (wet-bulb globe temperature [WBGT], effective temperature, discomfort index, heat index, frequency and duration of hot and cold spells). As such, this study, identifying areas in which crop growth and productivity are becoming particularly threatened by the increasing frequency and duration of extremes, provides vital evidence for climate change adaptation and mitigation plans in the southern Mediterranean region. 

How to cite: Mirgol, B., Dieppois, B., Northey, J., Eden, J., Jarlan, L., Tramblay, Y., and Mahé, G.: Recent changes in the probability of agrometeorological risks over the southern Mediterranean region, and potential impacts on crop growth , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8677, https://doi.org/10.5194/egusphere-egu22-8677, 2022.

Md Abdul Muktadir et al.

Land use and land cover change significantly influence regional energy budgets, and hydrological and biogeochemical cycles which may occur from both anthropogenic and natural disturbances. Likewise, vegetation may also respond dynamically to climate. In the past decades, the Horn of Africa has been hit by several droughts and heatwaves causing severe economic, environmental, and social damage. To evaluate and mitigate such impacts, it is necessary to establish and quantify the linkage between land cover change and regional climate. This study presents an observational analysis of recent (2001–2019) historical changes in land cover and land use and their relation to climate in the Horn of Africa. 

Firstly, we evaluate changes in land cover using the Moderate Resolution Imaging Spectrometer (MODIS) dataset. Results indicate steady expansion of grasslands (net gain is 1.2% of total area) and an opposite pattern for open shrublands during the period 2001–2016. Importantly, deforestation of evergreen broadleaf forest (0.3% of the total area) is also noticeable in continuous fractional vegetation cover (FVC) analysis. Next, the Global Database of Historical Yields (GDHY) is explored to identify the yield trends for two main cereals: maize and wheat.  Wheat yield shows increasing trends in the northern and southern parts, while maize yields increase in Ethiopia and mildly decrease in Kenya. To quantify the adverse impact of drought on yields, three drought indices are used: (a) Standardized Precipitation Evapotranspiration Index (SPEI), (b) self-calibrating Palmer Drought Severity Index (scPDSI), and (c) Standard Evapotranspiration Deficit Index (SEDI). The analysis identifies SPEI12 as arguably the best performing drought index for monitoring and forecasting impacts on yields in this region. 

Finally, a Conditional Spectral Granger Causality (CSGC) algorithm is employed for understanding the influence of climate variability on vegetation dynamics. Although the influence of climatic factors (i.e., precipitation, temperature, and solar energy radiation) on vegetation dynamics is heterogeneous, given the wide spectrum of climate regimes in the region, an overall increased influence of temperature on vegetation dynamics is revealed. In conclusion, the observational evidence indicates that climate plays an important role as a driver of both crop and natural vegetation change in the Horn of Africa. 

How to cite: Muktadir, M. A., Koppa, A., Claessen, J., MacLeod, D. A., Singer, M., and Miralles, D. G.: Links between land cover change and climate in the Horn of Africa, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10577, https://doi.org/10.5194/egusphere-egu22-10577, 2022.

Akash Koppa et al.

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.


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.

Serena Sirigu et al.

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.

Stefan Liersch and Hagen Koch

To feed the growing population, achieve the Sustainable Development Goals, and fulfil the commitments of the Paris Agreement, West African countries need to invest in agriculture and renewable energy, among other sectors. Irrigated agriculture, feeding millions of people, and hydropower, which generates clean electricity, both depend on the availability of water. We have investigated the extent to which synergies and trade-offs exist between simulated water demand and supply of three planned irrigation sites in the Volta basin and the hydropower potential at four dams using an eco-hydrological model. The impacts in terms of changes in the water balance and availability were attributed to single projects (irrigation site or dam).

We found that without upstream reservoirs, the naturally intermittent flow regime of the Black and White Volta Rivers either limits or makes dry-season irrigation impossible, depending on the location (climate) in the basin. The planned additional irrigated area of 104,000 ha could feed about half a million people but relies on upstream dams transforming the intermittent to a permanent flow regime. Irrigation withdrawals would be at the expense of hydropower potential, which decreased by 139 GWh/a. The 182 GWh/a of the planned Pwalugu dam thus contribute only 24% of its potential. Moreover, our process-based simulations revealed that solely the transformation from intermittent to permanent flow regime caused accumulating transmission losses downstream, which can be substantial.

Simulated future crop water requirements did not increase under climate change projections using an ensemble of 8 bias-adjusted global climate models, because the higher evaporative demand was outbalanced by increasing precipitation.

How to cite: Liersch, S. and Koch, H.: Recent and future developments in the Volta River basin from a Nexus perspective: Synergies and trade-offs between different water uses under climate change, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12416, https://doi.org/10.5194/egusphere-egu22-12416, 2022.

Soufiane Taia et al.

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.