Wyniki wyszukiwania - BazTech

1

Mapping Favorable Groundwater Potential Recharge Areas Using a GIS-Based Analytical Hierarchical Process – A Case Study of Ferkla Oasis, Morocco

Ismail Ait Lahssaine, Lahcen Kabiri, Badre Messaoudi, Badre Essafraoui, Mohamed El Ouali, Lamya Ouali, Jean Albergel, Meryem El Amraoui, Amina Kassou, Essahlaoui Ali

Ecological Engineering & Environmental Technology

|

2024

|

Vol. 25, iss. 3

311--325

EN

In the Ferkla Oasis, much like in numerous other oases across the southeastern region of Morocco, a range of socioeconomic and environmental challenges are intricately linked to the inadequate management of water resources. One proposed remedy to address these concerns is the implementation of artificial aquifer recharge, which stands as an alternative strategy to safeguard the crucial oasis ecosystems. Thus, to evaluate the viability of this method in promoting sustainable water resource usage, it becomes imperative to delineate groundwater recharge potential zones (GRPZs). This study aims to achieve this objective by mapping GRPZs within the Ferkla Oasis, employing a fusion of the analytical hierarchy process (AHP), geospatial information derived from remote sensing (RS), and geographic information system (GIS) technologies. In pursuit of this goal, an array of geological, topographical, pedological, hydrological, and climatic criteria have been meticulously selected, classified, and assigned weights following their relevance to water infiltration suitability. This comprehensive approach culminates in the generation of seven thematic maps: slope, lineament density, lithology, soil type, drainage density, land use/land cover, and rainfall distribution. Through the integration of these aforementioned maps, a tripartite classification of potential GRPZs emerges, comprising low, medium, and high categories. The findings underscore the distribution: 30% of the total study area exhibits a low potential for GRPZs, 50% of the total land area is characterized as having medium potential GRPZs, while the remaining 20% is designated as high potential GRPZs. These outcomes have been substantiated through validation against piezometric levels, which have been ascertained through recent field surveys. Consequently, these results stand as a testament to the efficacy of the presented approach as a robust decision-making tool. The approach effectively facilitates the establishment of conditions conducive to viable artificial recharge, thereby offering a means to safeguard the groundwater reservoirs that sustain the fragile oasis environments.

2

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

Moudden Fouad, El Hafyani Mohammed, El Ouali Anas, Roubil Allal, El Ouali Abdelhadi, Essahlaoui Ali, Brouziyne Youssef

Journal of Water and Land Development

|

2022

|

no. 53

86--99

EN

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%.

3

Modelling and Mapping of Soil Organic Matter in Doukkala Plain, Moroccan Semi-Arid Region

Bel-Lahbib Sanae, Namr Khalid Ibno, El Hafyani Mohammed, Al Masmoudi Yassine, Essahlaoui Ali

Ecological Engineering & Environmental Technology

|

2022

|

Vol. 23, iss. 5

188--197

EN

The Doukkala plains one of the largest irrigated areas in Morocco with a very important agricultural potential. With the integration of new technologies in agriculture, the plain has been subjected to intensive agriculture which has negative impacts on soil quality especially the soil organic matter loss. Therefore, the objective of this study is to combine remote sensing and modelling for monitoring of organic matter content. The obtained results showed that all the examined models showed satisfactory results in the prediction of organic matter with a coefficient of determination R2 ranging from 0.58 to 0.71 and the Root Mean Square Error (RMSE) varied 0.25 and 0.26%. Based on the findings, we can infer that this approach is both efficient and valid for modelling and mapping soil organic matter and may moreover be applied for other areas with same characteristics.

4

Weather drought index prediction using the support vector regression in the Ansegmir Watershed, Upper Moulouya, Morocco

Bekri My Hachem, El Hmaidi Abdellah, Ousmana Habiba, El Faleh El Mati, Berrada Mohamed, El Aissaoui Kamal, Essahlaoui Ali, El Ouali Abdelhadi

Journal of Water and Land Development

|

2021

|

no. 50

187--194

EN

The purpose of this study is to develop mathematical models based on artificial intelligence: Models based on the support vectors regression (SVR) for drought forecast in the Ansegmir watershed (Upper Moulouya, Morocco). This study focuses on the prediction of the temporal aspect of the two drought indices (standardized precipitation index – SPI and standardized precipitation-evapotranspiration index – SPEI) using six hydro-climatic variables relating to the period 1979–2013. The model SVR3-SPI: RBF, ε = 0.004, C = 20 and γ = 1.7 for the index SPI, and the model SVR3-SPEI: RBF ε = 0.004, C = 40 and γ = 0.167 for the SPEI index are significantly better in comparison to other models SVR1, SVR2 and SVR4. The SVR model for the SPI index gave a correlation coefficient of R = 0.92, MSE = 0.17 and MAE = 0.329 for the learning phase and R = 0.90, MSE = 0.18 and MAE = 0.313 for the testing phase. As for the SPEI index, the overlay is slightly poorer only in the case of the SPI index between the observed values and the predicted ones by the SVR model. It shows a very small gap between the observed and predicted values. The correlation coefficients R = 0.88 for the learning, R = 0.86 for testing remain higher and corresponding to a quadratic error average MSE = 0.21 and MAE = 0.351 for the learning and MSE = 0.21 and MAE = 0.350 for the testing phase. The prediction of drought by SVR model remain useful and would be extremely important for drought risk management.