Use of Spatial Remote Sensing to Study the Temporal Evolution of the Water Retention of Al Massira Dam in Morocco

Abstract

In Morocco, irrigated agriculture is still very much linked to the climate and the water retention of dams. With climate change, this country is experiencing recurrent drought, which has led to deficits in water inflow from the rivers to the various dams. The Al Massira dam, the area of study, does not escape this trend. This dam is the only surface water source for the irrigated area of Doukkala. Therefore, special attention must be paid to monitoring this resource at this dam. Thus, the proposed study examined the possibilities offered by spatial remote sensing to improve the current information system. It aims to evaluate this dam's reservoir by exploiting the data generated by using satellite images. The Landsat satellite images were used to assess the area of this dam by adopting an approach combining spectral indices with thresholding. Then, the existing relationship between the area of the dam lake were examined, determined by spatial remote sensing and its water retention measured in situ. The results obtained revealed a strong correlation between the two parameters. Therefore, a study was conducted to find the best model for predicting the dam's impoundment based on its lake. The second-degree polynomial model showed a better performance. Given the results obtained, it is recommended to use geospatial methods in the current and prospective monitoring and steering system of water resources.

Long-term spatiotemporal surface water dynamics using Google Earth Engine in southeastern Morocco

“…For instance, severe drought occurred in 1999, with [7] reporting that the inflow water drastically decreased from 367 Mm 3 to 79 Mm 3 during the hydrological years 1997/1998 and 1998/1999, respectively. This finding aligns with [5]'s results, which also indicate a water decline in al Massira dam during 1999-2000 and 2014-2021. Nevertheless, between 1988 and 1998, the EME's dam surface water area varied between 37.12 and 47.04 km 2 .…”

“…Additionally, four spectral water indices, namely modified normalized difference water index (MNDWI), enhanced water index (EWI), new water index (NWI), and automated water extraction index (AWEI) were used. Further information about these indices can be found in [3][4][5]. Applying these spectral water indices approach improves image features while reducing the surrounding environmental condition's influence on water, thereby emphasizing water differentiation from other features.…”

“…For example, Bijeesh and Narasimhamurthy [4] divide them into four categories: methods based on single bands, methods based on spectral indices, methods based on machine learning, and methods based on spectral mixture analysis. To our best knowledge, there has been limited research dedicated to exploring the long-term surface water dynamics in Morocco [5], notably at El Mansour Eddahbi Dam. This study investigates GEE and Landsat images, employing four water indices (MNDWI, EWI, NWI, and AWEI) in conjunction with the random forestsupervised algorithm.…”

Effect of Hydraulic Structure on Mitigating Extreme Hydrological Conditions of a Small River in the Temperate Zone (Główna River, Central Europe)

“…It was determined that catchments with functioning dams show economic activity approximately 25 times higher than catchments with no infrastructure [43]. The magnitude of water retention in the Al Massira Reservoir (Morocco) is a factor determining the maintenance of agricultural activity and an important resource for the population of the region [44]. After the construction of irrigation channels in the Punjab state (Pakistan), the cultivation intensity and agricultural yields increased.…”