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Environmental flows are unanimously considered to be one of the most comprehensive indicators of the rivers health and their capacities to provide ecosystem goods and services. In this study, the objective was to predict the response of environmental flow components in a typical North African rivers network to future climate change. The study watershed is Bouregreg watershed (BW) in Morocco. To achieve this objective, a hybrid approach was build based on the semi-distributed model Soil and Water Assessment Tool (SWAT) and the Indicators of Hydrologic Alteration program (IHA). Data of two emissions scenarios (RCP4.5 and RCP8.5) from a downscaled Global Circulation Model were used to force the hybrid SWAT-IHA to calculate modifications of BW's environmental flow components in 2085-2100 period. Results showed that BW will experience climatic changes under both scenarios. Most of the environmental flow attributes will be modified within the study period: loss of natural flow variability due to shift in exceedance probability of low flows (up to 40%), decrease of monthly low flows, forward shift in high flow timing (up to 50%), and alteration of both the duration and the rise rates of floods. BW's streams responded unequally to the simulated changes in terms of the altered attributes as well as the degree of the alteration. This study confirmed the ability of the developed modeling approach to monitor environmental flow parameters for the first time in Morocco, and contributed in highlighting the necessity of proactive long term strategies to protect riverine ecosystems in North Africa watersheds. [ABSTRACT FROM AUTHOR]

The recent Sixth Assessment Report of the IPCC posits that across Africa, temperatures will continue to rise in almost all regions, while precipitation will decline in North and Southern parts of Africa and increase in the Sahel and most of sub-Saharan Africa. Vulnerability to these stressors is expected to increase across Africa due mainly to declining adaptive capacities. There is therefore a need to develop novel ways of assessing and monitoring the adaptive capacity of populations and communities across regions and countries of Africa. This work, therefore, aims at developing and testing a new adaptive capacity index based on two key inversely related proxies of adaptive capacity which are literacy and poverty rates. The data for these proxies were collected for the period 1991–2021 from the Readiness Index Database on figshare, the World Bank Group and Macro Trends. The historical data were analysed using the newly developed adaptive capacity index. Regionally, the results show that North Africa and Southern Africa have the highest adaptive capacity indices while West Africa, Middle and East Africa have the lowest adaptive capacity indices. Nationally, Sao Tome and Principe and Seychelles record the highest adaptive capacity indices. Generally, the indices at the country level as well as at the regional level are within the low-range scale, depicting a generally low level of adaptive capacity when compared to other regions of the world. The index suggested here will serve as a tool for bench-marking adaptive capacity at various scales as it is easily applicable in various contexts. • Africa is more vulnerable to climate change due to its low adaptive capacity. • This work develops and test a new adaptive capacity index in Africa. • Regionally, North and Southern Africa record higher adaptive capacity indices. • Nationally, Sao Tome and Principe and Seychelles record higher adaptive capacity indices. • Generally, the level of adaptive capacity across all African regions is low. [ABSTRACT FROM AUTHOR]

• Crop production at various scales is constrained by climatic and non-climatic variables. • In Morocco wheat stands out as the most studied crop. • AquaCrop process-based crop model and regression-based models are the most frequently calibrated crop models. • Precipitation, temperature, soil properties, irrigation, and fertilization are frequently calibrated indicators. • Empirical models aptly integrate climatic and socioeconomic variables. • Process-based models focus on mostly climatic and biophysical variables. Agriculture is an important sector of the Moroccan economy, employing a huge portion of the Moroccan population and contributing about 14 - 20% to the country's GDP. Unfortunately, agricultural production in Morocco is impacted by climatic, non-climatic, biophysical, and non-biophysical stressors. Researchers have employed various crop models to understand how different crops respond to different environmental conditions such as temperature, precipitation, soil properties, fertilization, and irrigation. Unfortunately, there are no studies that provide a summary and a holistic perspective of the most frequently used models and their calibration inputs in Morocco. This work, therefore, seeks to fill these knowledge gaps by providing a summary of the most calibrated crop models, their calibration input data, the most frequently studied crops, how the studies are published (peer-review or grey literature), and the affiliations of the lead authors. This is achieved through a systematic review of the primary peer review and grey literature. A total of 68 relevant peer review and grey literature papers were considered. The results show that most of the authors are affiliated with Moroccan universities/organizations while wheat is the most studied crop. In addition, the AQUACROP and the regression-based models are the most used crop models. Additionally, most of the models are calibrated in order of importance with variables such as temperature, precipitation, soil properties, irrigation, and fertilizers. On the other hand, there is an observed increase in the use of non-climatic indicators such as poverty, farm income, and literacy levels to fit empirical models. It is still unclear how process-based models will integrate socio-economic indicators. This work has implications for future research as it provides a holistic picture of the key models that are currently used and their calibration. This information can be used by other projects to select methods to use, and crops to study based on the available data when working on crop models in Morocco, and North Africa. These results underscore the leading role in research funding offered by the government of Morocco and other organizations such as UM6P and OCP Africa in research valorization in Morocco and Africa. [ABSTRACT FROM AUTHOR]

During the last decades, the coastal areas of Morocco have witnessed an intense socioeconomic development associated with a continuous population growth and urban extension. This has led to an overexploitation of coastal aquifers leading to a degradation of their water quality. In order to obtain large scale overview on the quality status of Morocco's coastal aquifers (MCA) to assist national water managers to make informed decisions, a comprehensive scrutinization of the MCA against common indicators and using unified methods is essential. In this study, databases from thirteen MCA were analyzed, using multivariate statistical approaches and graphical methods in order to investigate the degree of mineralization in each aquifer and to identify the main salinization processes prevailing in groundwater. The results showed that the dominant groundwater types are Na–Cl, Ca–Mg–Cl, Ca–Mg–SO 4 , Ca–Mg–HCO 3 and Ca–HCO 3 –Cl. The Gibbs diagram and the seawater contribution (0–37%) indicate that the mineralization is mainly due to the seawater intrusion and water-rock interaction. The salinity degree diagram illustrates that almost all groundwater samples are located in the moderate to very saline zone, indicating that MCA are recharged by water from variable sources. The groundwater quality assessment shows a deterioration, particularly by seawater intrusion and significant nitrate pollution. The temporal evolution confirm that the MCA are influenced by seawater namely in the Atlantic part. The Wilcox and USSL diagram indicate that the majority of sampled water are unsuitable for irrigation uses. In addition, and by referring to the WHO and the Moroccan standards for water potability, large number of samples from the groundwaters of the MCA is not fully adequate for drinking purposes. A set of management actions (e,g., artificial recharge) are proposed in order to mitigate the effect of groundwater overexploitation and seawater intrusion to ensure the sustainability of MCA. [Display omitted] • Both seawater intrusion and water rock interaction are the main salinity process in MCA. • A set of management actions, are proposed in order to preserve MCA. [ABSTRACT FROM AUTHOR]

The potential response of flow regimes to future climate has crucial importance for a variety of practical applications, such as sustainable water management and ecological asset preservation. For this study, multi-site investigations of alterations in flow regimes under projected climate change were performed for one of the largest watersheds in Morocco, the Bouregreg Watershed (BW). Future daily streamflow was simulated using the eco-hydrological model Soil and Water Assessment Tool (SWAT) forced by climatic data from CMIP5 model outputs. Simulations were carried out for two periods: 2035–2050 (2040s), and 2085–2100 (2090s) under two emissions scenarios: RCP4.5 and RCP8.5. Future streamflow regimes were examined in accordance with an Indicators of Hydrologic Alteration (IHA) analysis, while being confronted with baseline flow data. Mean temperature has been predicted to increase by up to 2.79 °C in the 2090s (RCP8.5), and a higher variability in rainfall regime is expected. The results indicate that, under future changes in climate patterns, flow regimes in BW will be altered. However, the extent of alteration will be reflected unevenly among the four streams of the study watershed. The IHA analysis revealed that most of the river network will experience both a decrease in monthly flow magnitude (mostly in November and December), and an increase (dominantly in February and March) when compared to baseline. The frequency of flash pulses, and the number of zero-flow days are also expected to increase. Most of the projected alterations were estimated to become very significant in the 2090s under the RCP8.5 scenario. The potential ecological implications were also analysed, and the most sensitive streams of BW were identified to guide local water planning and ecological preservation strategies. • SWAT, CMIP5 data and IHA method used to forecast future flow regimes in Morocco. • Alterations extent will be unevenly distributed over the river network. • Ecological implications are expected due to climate change impact on flow attributes. [ABSTRACT FROM AUTHOR]

Abstract: A deterministic approach for downscaling ∼40 km resolution Soil Moisture and Ocean Salinity (SMOS) observations is developed from 1 km resolution MODerate resolution Imaging Spectroradiometer (MODIS) data. To account for the lower soil moisture sensitivity of MODIS surface temperature compared to that of L-band brightness temperature, the disaggregation scale is fixed to 10 times the spatial resolution of MODIS thermal data (10 km). Four different analytic downscaling relationships are derived from MODIS and physically-based model predictions of soil evaporative efficiency. The four downscaling algorithms differ with regards to i) the assumed relationship (linear or nonlinear) between soil evaporative efficiency and near-surface soil moisture, and ii) the scale at which soil parameters are available (40 km or 10 km). The 1 km resolution airborne L-band brightness temperature from the National Airborne Field Experiment 2006 (NAFE''06) are used to generate a time series of eleven clear sky 40 km by 60 km near-surface soil moisture observations to represent SMOS pixels across the three-week experiment. The overall root mean square difference between downscaled and observed soil moisture varies between 1.4% v/v and 1.8% v/v depending on the downscaling algorithm used, with soil moisture values ranging from 0 to 15% v/v. The accuracy and robustness of the downscaling algorithms are discussed in terms of their assumptions and applicability to SMOS. [Copyright &y& Elsevier]

An accurate estimate of crop coefficient (K c) values at different development stages (K cini , K cmid , and K cend) is crucial for assessing crop water requirements in semi-arid regions. The objectives of this study were first to quantify the reference evapotranspiration (ET o) and to calculate the actual evapotranspiration (ET a) over citrus in a semi-arid climate under drip irrigation. For this purpose, a site of a citrus orchard in Souss-Massa, planted with the Esbal variety of clementine, was equipped with an Eddy-Covariance (EC) system, and sensors to measure radiation, soil heat flux, and micrometeorological forcing data, during 2020 and 2021 seasons. Also, the soil moisture content at various soil depths in the root zone near the EC tower was monitored. The energy balance closure (EBC) approach was adopted for flux assessment to ensure a quality check for the EC measurements. The obtained EBCs were about 82% and 79% for the daily measurements in 2020 and 2021, respectively, which can be considered acceptable considering the nature of the citrus orchard (relatively tall and sparse). Second, the study aimed to estimate actual K c act values for citrus under the same irrigation strategy. The derived values were compared to different recommended K c values in the literature. In the third stage, this work aimed to offer an alternative plan to sustainable irrigation management by elaborating an irrigation schedule for citrus crops in the region using the FAO-56 simple approach to avoid water stress and deep percolation (i.e., K s = 1 and DP = 0). Eventually, an irrigation schedule was drawn following the crop's phenological stages. The seasonal mean citrus evapotranspiration (ET a) values are 1.68, 3.02, and 1.86 mm/day for the initial, mid, and end-season. The seasonal actual K c act values were 0.64, 0.58, and 0.64 for K cini , K cmid , and K cend , respectively. Additionally, the application of the water balance equation revealed that a large quantity of water is lost through deep percolation (52% of total water supplied). The study focuses on Citrus trees being a strategic crop with important socio-economic values in the Souss-Massa region. Thus, the results should support both scientists and farmers in planning and strategy development. • Crop coefficients are adjusted according to agrometeorological conditions. • Citrus crop requires less amount of irrigation water than farmers allocate. • Optimization of irrigation water reduces losses to evaporation and deep percolation. [ABSTRACT FROM AUTHOR]

Accurate estimation of evapotranspiration (ET) is of crucial importance in water science and hydrological process understanding especially in semi-arid/arid areas since ET represents more than 85% of the total water budget. FAO-56 is one of the widely used formulations to estimate the actual crop evapotranspiration (ET c act) due to its operational nature and since it represents a reasonable compromise between simplicity and accuracy. In this vein, the objective of this paper was to examine the possibility of improving ET c act estimates through remote sensing data assimilation. For this purpose, remotely sensed soil moisture (SM) and Land surface temperature (LST) data were simultaneously assimilated into FAO-dualK c. Surface SM observations were assimilated into the soil evaporation (E s) component through the soil evaporation coefficient, and LST data were assimilated into the actual crop transpiration (T c act) component through the crop stress coefficient. The LST data were used to estimate the water stress coefficient (K s) as a proxy of LST (LST proxy). The FAO-Ks was corrected by assimilating LST proxy derived from Landsat data based on the variances of predicted errors on K s estimates from FAO-56 model and thermal-derived K s. The proposed approach was tested over a semi-arid area in Morocco using first, in situ data collected during 2002–2003 and 2015–2016 wheat growth seasons over two different fields and then, remotely sensed data derived from disaggregated Soil Moisture Active Passive (SMAP) SM and Landsat-LST sensors were used. Assimilating SM data leads to an improvement of the ET c act model prediction: the root mean square error (RMSE) decreased from 0.98 to 0.65 mm/day compared to the classical FAO-dualK c using in situ SM. Moreover, assimilating both in situ SM and LST data provided more accurate results with a RMSE error of 0.55 mm/day. By using SMAP-based SM and Landsat-LST, results also improved in comparison with standard FAO and reached a RMSE of 0.73 mm/day against eddy-covariance ET c act measurements. • Improved FAO evapotranspiration (ET) estimates through data assimilation technique. • Assimilating land surface temperature (LST) & soil moisture (SM) to improve wheat ET. • Landsat-LST and Soil Moisture Active Passive (SMAP) SM sensors were used. • Evaluated with ET measurements from two sites. [ABSTRACT FROM AUTHOR]

Crop evapotranspiration (ET) is a fundamental component of the hydrological cycle, especially in arid/semi-arid regions. The FAO-56 offers an operational method for deriving ET from the reduction (dual crop coefficient K c) of the atmospheric evaporative demand (ET 0). The dual coefficient approach (FAO-2Kc) is intended to improve the daily estimation of ET by separating the contribution of bare soil evaporation (E) and crop transpiration components. The FAO-2Kc has been a well-known reference for the operational monitoring of crop water needs. However, its performance for estimating the water use efficiency is limited by uncertainties in the modeled evaporation/transpiration partitioning. This paper aims at improving the soil module of the FAO-2Kc by modifying the E reduction coefficient (K r) according to soil texture information and state-of-the-art formulations, hence, to amend the mismatch between FAO-2Kc and field-measured data beyond standard conditions. In practice this work evaluates the performance of two evaporation models, using the classical Kr (K r,FAO) and a new texture-based Kr (K r,text) over 33 bare soil sites under different evaporative demand and soil conditions. An offline validation is investigated by forcing both models with observed soil moisture (θ s) data as input. The K r,text methodology provides more accurate E estimations compared to the K r,FAO method and systematically reduces biases. Using K r,text allows reaching the lowest root means square error (RMSE) of 0.16 mm/day compared to the K r,FAO where the lowest RMSE reached is 0.88 mm/day. As a step further in the assessment of the proposed methodology, ET was estimated in three wheat fields across the entire agricultural season. Both approaches were thus inter-compared in terms of ET estimates forced by SM estimated as a residual of the water balance model (online validation). Compared to ET measurements, the new formulation provided more accurate results. The RMSE was 0.66 mm/day (0.71 mm/day) and the R2 was 0.83 (0.78) for the texture-based (classical) Kr. • New K r formula is proposed based on the soil texture information using a new pedo-transfer function. • Implementation of the new texture-based Kr into the FAO-2Kc formalism to retrieve soil evaporation. • Approach was evaluated against soil evaporation measurements collected over 33 bare soil fields with different soil textures. • Crop evapotranspiration was retrieved over three wheat sites as a complementary assessment of the new evaporation formula. [ABSTRACT FROM AUTHOR]