Use of geomatics, Simulating the Impact of Future Land Use and Climate Change on Soil Erosion in the Tigrigra watershed (Azrou region, Middle Atlas, Morocco)

Soil losses need to be quantified in watersheds to implement erosion protection measures. The main objective of this work is to quantify soil loss in the Tigrigra watershed over the reference period 1985-2020 and two future periods 2050-2070, A Revised Universal Soil Loss Equation (RUSLE) model supported by geographic information systems (GIS) and remote sensing was used. GIS’s model generator can automate various operations of creating thematic layers of model parameters. For future climatic periods (2050-2070), precipitation was produced using a classical statistical downscaling model (SDSM). On the other hand, Automata/Markov models (CA Markov) are used to characterize future land use through modeling in Idrisi software. Over the two periods, the results showed that annual erosivity varies decreases, or increases. The annual soil loss maps showed that 50% of our study area was in the very low class (80 t/ha/year). These fluctuations are primarily due to the effects of climate change and deforestation/reforestation in the region. This leads to changes in soil erosion due to the important role played by these two factors

Use of geomatics and multi-criteria methods to assess water erosion in the Tigrigra watershed (Azrou region, Morocco)

In Morocco, the capacity of dam reservoirs has decreased in recent years due to water erosion. This study aims to identify the sub-watersheds most vulnerable to soil erosion in the Tigrigra watershed by utilizing morphometric analysis of linear, landscape, and shape parameters and various multi-criteria decision models. These approaches allow for the prioritization of areas or sub-watersheds at high erosion risk. In the study area, erosion assessment is conducted using multi-criteria decision support models (MCDM) such as MOORA, VIKOR, TOPSIS, COPRAS, WASPAS, and SAW within a GIS environment. This approach highlights the significant role of morphometric parameters and multi-criteria methods in identifying sub-watersheds susceptible to erosion. Overall, the results indicate that morphometric parameters are highly effective in identifying erosion-prone areas. The Tigrigra watershed generally exhibits low to medium sensitivity to erosion, except for certain sub-watersheds. Subcatchment 28 showed significant erosion in most methods used

Predicting Nitrate Levels in the Saïss Water Table: A Comparative Study of Machine Learning Methods

The main goal of this study is to predict nitrate (NO3-) levels in the Saiss basin water table as a function of various physicochemical parameters. To accomplish this, three machine learning approaches were utilized: multiple linear regression (MLR), super vector regression (SVR), and artificial neural networks (ANN). The independent variables were composed of six water quality parameters, including Ca2+, Na2+, EC, Cl-, HCO3-, and SO42-. The study utilized a dataset of 389 water samples collected between 1991 and 2017. The artificial neural network (ANN) was trained using the Levenberg-Marquardt (LM) algorithm, which was selected from various optimization algorithms. Additionally, during the training of the SVR model, it was observed that the RBF kernel outperformed the other kernels (linear, polynomial, and sigmoid kernel). The results were analyzed by the coefficient of determination (R2) and the mean square error (MSE). The results of the MLR method revealed R2 (0.523) and MSE (757.34). The ANN model with architecture [6-20-1] performed better than RLM with R2 = 0.836, MSE= 0.023 The SVR model result confirms what has been proved by ANN concerning the performance, with R2=0.902 and MSE= 4,364

Assessment of physicochemical and microbiological quality using the SEQ-Eau approach for groundwater in the Saïss basin (Fez-Meknes region, Morocco)

The Saïss water table is one of Morocco's major agricultural regions. Its water resources satisfy domestic, agricultural, industrial, and tourist needs. The present work focuses on the technique used to detect spatiotemporal variations in the overall physicochemical, microbiological, and heavy metal quality of groundwater in the Saïss basin, as assessed by the SEQ-Eau water quality system. A total of 28 samples were collected during high and low water periods, respectively. The results show that 25% of the stations present average quality during the dry season, and are located mainly in the southern part of the Meknes plateau in the El Hajeb, Boufekrane, and Agouray regions, while this pollution is reduced during the wet season with a percentage of 7.14%. However, the poor quality of groundwater indicates that 75% and 92.85% occupy almost the entire rest of the basin during the dry and wet seasons. Mapping of nitrate pollution of groundwater indicates that the lowest nitrate concentrations were recorded in the southwest part of the aquifer. The highest values were recorded in the center of the study area, with a maximum value of 118 mg/l, which exceeds the Moroccan standard due to the anthropogenic impact of agriculture and water use

Modeling and Spatiotemporal Mapping of Water Quality through Remote Sensing Techniques: A Case Study of the Hassan Addakhil Dam

With its high water potential, the Ziz basin is one of the most important basins in Morocco. This paper aims to develop a methodology for spatiotemporal monitoring of the water quality of the Hassan Addakhil dam using remote sensing techniques combined with a modeling approach. Firstly, several models were established for the different water quality parameters (nitrate, dissolved oxygen and chlorophyll a) by combining field and satellite data. In a second step, the calibration and validation of the selected models were performed based on the following statistical parameters: compliance index R2, the root mean square error and p-value. Finally, the satellite data were used to carry out spatiotemporal monitoring of the water quality. The field results show excellent quality for most of the samples. In terms of the modeling approach, the selected models for the three parameters (nitrate, dissolved oxygen and chlorophyll a) have shown a good correlation between the measured and estimated values with compliance index values of 0.62, 0.56 and 0.58 and root mean square error values of 0.16 mg/L, 0.65 mg/L and 0.07 µg/L for nitrate, dissolved oxygen and chlorophyll a, respectively. After the calibration, the validation and the selection of the models, the spatiotemporal variation of water quality was determined thanks to the multitemporal satellite data. The results show that this approach is an effective and valid methodology for the modeling and spatiotemporal mapping of water quality in the reservoir of the Hassan Addakhil dam. It can also provide valuable support for decision-makers in water quality monitoring as it can be applied to other regions with similar conditions

Diachronic mapping and evaluation of soil erosion rates using RUSLE in the Bouregreg River Watershed, Morocco

Soil erosion has been severely affecting soil and water resources in semi-arid areas like the Mediterranean. In Morocco, this natural process is accelerated by anthropogenic activities, such as unsustainable soil management, overgrazing, and deforestation. With a drainage area of 395,600 ha, the Bouregreg River Watershed extends from the Middle Atlas Range (Jebel Mtourzgane) to the Sidi Mohamed Ben Abdellah (SMBA) dam reservoir south-east of Rabat. Its contrasted eco-geomorphological landscapes make it susceptible to unprecedented soil erosion due to climate change. Resulting changes in erosive dynamics led to huge amounts of solid loads transported to the catchment outlet and, thus, jeopardised the SMBA dam lifespan due to siltation. The research aims to quantify the average annual soil losses in this watershed using the Revised Universal Equation of Soil Losses (RUSLE) within a GIS environment. To highlight shifts in land use/land cover patterns and their effects on erosional severity, we have resorted to remote sensing through two Landsat 8 satellite images captured in 2004 and 2019. The C factor was combined with readily available local data regarding major erosion factors, e.g. rainfall aggressiveness (R), soil erodibility (K), topography (LS), and conservation practices (P). The helped to map the erosion hazard and determine erosion prone areas within the watershed where appropriate water and conservation measures are to be considered. Accordingly, from 2004 to 2019, average annual soil losses increased from 11.78 to 18.38 t∙ha-1∙y-1, as the watershed area affected by strong erosion (>30 t∙ha-1∙y-1) evolved from 13.57 to 39.39%

Groundwater Hydrochemical and Isotopic Evolution from High Atlas Jurassic Limestones to Errachidia Cretaceous Basin (Southeastern Morocco)

International audienceThe objective of this research was to determine the recharge of the Cretaceous aquifers by the High Atlas, as well as the interaction and possible mixing phenomena between the waters of the different aquifers, by investigating the hydrochemical and isotopic evolution of groundwater flow paths from the limestone karst systems of the High Atlas to the Cretaceous basin of Errachidia. Geological techniques were used to investigate and confirm the chemical and isotopic characteristics of the waters. Although the Gibbs diagram shows that water–rock interaction is the dominant hydrochemical process, some water samples in the Cretaceous basin are influenced by both evaporation and water–rock interaction, indicating a mixture of rainfall and deep waters. A saturation index study indicated that limestone minerals were supersaturated in parts of the groundwater samples (calcite and dolomite). This result was confirmed by isotope data. Indeed, some Cretaceous basin samples show isotopic similarities to those from the Jurassic High Atlas. The geological cross-sections illustrate that the High Atlas Jurassic limestones are in direct contact with the Cretaceous basin’s permeable rocks, allowing groundwater to circulate from the High Atlas to Errachidia’s Cretaceous basin

Proposal of a Big data System for an Intelligent Management of Water Resources

Today, advanced technologies like Big Data, IoT, and Cloud Computing can provide new opportunities and applications in all sectors. In the water sector, water scarcity has become a common concern of different institutions and actors worldwide. In this context, several approaches and systems have been proposed and developed, using these technologies, allowing intelligent water resources management. Internet of Things can be used for assisting the Water Industry to collect data, manage and monitor the water infrastructures using smart devices. Big Data is a strategic technology for analyzing and interpreting collected data into valuable and helpful information for better decision making. This paper presents Big Data and Internet of Things technologies. It addresses theirs uses in some use cases such as municipal water losses, water pollution in agriculture, water Leak detection, etc., to provide new systems and innovative solutions for intelligent water resources management. Based on this study, we propose a Big Data and IoT architecture for intelligent water resources management

Water Erosion Monitoring and Prediction in Response to the Effects of Climate Change Using RUSLE and SWAT Equations: Case of R’Dom Watershed in Morocco

Soil erosion is an increasingly issue worldwide, due to several factors including climate variations and humans’ activities, especially in Mediterranean ecosystems. Therefore, the aim of this paper is: (i) to quantify and to predict soil erosion rate for the baseline period (2000–2013) and a future period (2014–2027), using the Revised Universal Soil Loss Equation (RUSLE) and the Soil and Water Assessment Tool (SWAT) model in the R’Dom watershed in Morocco, based on the opportunities of Remote Sensing (RS) techniques and Geographical Information System (GIS) geospatial tools. (ii) we based on classical statistical downscaling model (SDSM) for rainfall prediction. Due to the lack of field data, the model results are validated by expert knowledge. As a result of this study, it is found that both agricultural lands and bare lands are most affected by soil erosion. Moreover, it is showed that soil erosion in the watershed was dominated by very low and low erosion. Although the area of very low erosion and low erosion continued to decrease. Hence, we hereby envisage that our contribution will provide a more complete understanding of the soil degradation in this study area and the results of this research could be a crucial reference in soil erosion studies and also may serve as a valuable guidance for watershed management strategies

Isotopic Characterization of Rainwater for the Development of a Local Meteoric Water Line in an Arid Climate: The Case of the Wadi Ziz Watershed (South-Eastern Morocco)

International audienceFor any hydrological or hydrogeological system, the arrival of new rains is the input signal to the system. This isotopic signature of precipitation is of major interest in understanding the recharge processes of the aquifer system. On the scale of a given basin, staged stations at different altitudes and spread out in space allow this input signal to be well characterized and to draw the local meteoric water line. In south-eastern Morocco, specifically, in the Errachidia region, several chemical and isotopic studies of the waters of the various aquifers have been carried out. In the absence of a local meteoric water line, these studies were based on the use of the global meteoric water line (GMWL). Thus, the objective of this work is the isotopic characterization and the elaboration of the local meteoric water line of the rainwater of the Ziz watershed. This characterization of the input signal in the study area is based on 41 measurements of stable isotopes (δ18O and δ2H) relating to the precipitations collected during the period from December 2019 to November 2020 in four staged stations at different altitudes and spread over the space from upstream to downstream of the watershed. The linear relationship of δ2H as a function of δ18O describes the local meteoric water line (LMWL) by equation δ2H = 7.5 ± 0.3 δ18O + 4.6 ± 1.7; R2 = 0.93. This equation displays evaporation confirmed by the arrival of continental currents in an arid environment. The variation in precipitation δ18O as a function of the sampling altitudes for the rains highlighted the relationship δ18O = −0.0026 ∗ Z − 1.67, with R2 = 0.93, which means an altitudinal gradient of −0.26‰ per 100 m of altitude. In this regard, the development of the local meteoric water line and the determination of the altitudinal gradient for the first time in this arid to semi-arid region of the watershed will be of great use to researchers and water resource managers; for example, to help determine the groundwater recharge areas, determine the exchanges between surface water and groundwater, and analyze many other hydrological problems