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

• Autorzy: Bounif Mohammed , Rahimi Abdelmejid , Boutafoust Rachid , El Mjiri Ikram

Identyfikatory

DOI

10.12911/22998993/156666

• Języki publikacji: EN

Abstrakty

EN

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.

Słowa kluczowe

EN

spatial remote sensing; Al Massira dam reservoir; spectral indices; Landsat; satellite image; Doukkala; irrigated perimeter

• Wydawca: Polskie Towarzystwo Inżynierii Ekologicznej ; Lublin University of Technology
• Czasopismo: Journal of Ecological Engineering
• Rocznik: 2023
• Tom: Vol. 24, nr 2
• Strony: 340--349
• Opis fizyczny: Bibliogr. 27 poz., rys., tab.

Twórcy

autor

Bounif Mohammed

• Faculty of Sciences, Chouaib Doukkali University, El Jadida, Morocco

• https://orcid.org/0000-0003-3967-2755

autor

Rahimi Abdelmejid

• Faculty of Sciences, Chouaib Doukkali University, El Jadida, Morocco

autor

Boutafoust Rachid

• Faculty of Sciences, Chouaib Doukkali University, El Jadida, Morocco

autor

El Mjiri Ikram

• Faculty of Sciences, Chouaib Doukkali University, El Jadida, Morocco

Bibliografia

• 1. Agence du Bassin Hydraulique de l’Oum Er-Rbia (ABHOER) 2012. Projet de Plan Directeur d’Aménagement Intégré des Ressources en Eau du Bassin de l’Oum Er-Rbia et des bassins côtiers atlantiques. Rapport de présentation.
• 2. Fisher A., Flood N., Danaher T. 2016. Comparing Landsat water index methods for automated water classification in eastern Australia, Remote Sens. Environ, 175–167.
• 3. Bounif M., Rahimi A., Bouassria A., El Mjiri I. 2021. Study of agricultural land use variability in Doukkala irrigated area between 1998 and 2020,” 2021 Third International Sustainability and Resilience Conference: Climate Change, 2021, 170–175. DOI: 10.1109/IEEECONF53624.2021.9667965
• 4. Roy D.P. et al. 2016. Characterization of Landsat-7 to Landsat-8 reflective wavelength and normalized difference vegetation index continuity. Remote Sens. Environ., 185, 57–70. DOI: 10.1016/j.rse.2015.12.024
• 5. Vermote E., Roger J.C., Franch B., Skakun S. 2018. LaSRC (Land Surface Reflectance Code): Overview, application and validation using MODIS, VIIRS, LANDSAT and Sentinel 2 data’s, in IGARSS 2018 – 2018 IEEE International Geoscience and Remote Sensing Symposium, 8173–8176. DOI: 10.1109/IGARSS.2018.8517622.
• 6. ECS: Water Resources of Nepal in the Context of Climate Change, 2011. http://www.wecs.gov.np/uploaded/water-recource-climate-change.pdf.
• 7. Feyisa G., Meilby H., Fensholt R., Proud S.R. 2014. Automated Water Extraction Index: a new technique for surface water mapping using Landsat imagery. Remote Sens. Environ., 140, 23–35.
• 8. Feyisa G.L., Meilby H., Fensholt R. 2014. Proud, S.R. Automated water extraction index: A new technique for surface water mapping using Landsat imagery. Remote Sens. Environ, 140, 23–35.
• 9. Feyisa G.I., Meilby H., Fensholt R., Proud S.R. 2014. Automated Water Extraction Index: A new technique for surface water mapping using Landsat imagery, Remote Sensing of Environment, 140, 23–35.
• 10. Alaoui L., Agoumi A., Moncef M., Mokhliss K. 2000. Étude du régime thermique de la retenue Al Massira (Maroc). Hydroécol. Appl., 12(1–2), 183–206.
• 11. Masocha M. et al. 2018. Surface waterbodies mapping in Zimbabwe using Landsat 8 OLI multispectral imagery: a comparison of multiple water indices. Phys. Chem. Earth, 63–67.
• 12. Ministère d’Equipement et de l’Eau, 2022. Site web officiel. http://81.192.10.228/patrimoine/barrages/situation-journaliere-des-principaux-grands-barrages.
• 13. MAPMDREF. 2019. Agriculture en chiffres en 2018.
• 14. McFeeters S.K. 1996. The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features. Int. J. Remote Sens., 17, 1425–1432.
• 15. ORMVAD, 2020. Rapports d’activités annuels et de gestion de l’ORMVA des Doukkala, El Jadida, Morocco, 2010 à 2020.
• 16. Arreola-Esquivel M., Delgadillo-Herrera M., Toxqui-Quitl C., PadillaVivanco A. 2019. Index-based methods for water body extraction in satellite data. Proc. SPIE 11137, Applications of Digital Image Processing XLII, 111372N, September 2019. DOI: 10.1117/12.2529756
• 17. Palmer S.C., Kutser T., Hunter P.D. 2015. Remote sensing of inland waters: challenges:
• 18. Progress and future directions. Remote Sens. Environ., 175, 1–8.
• 19. Frazier P.S., Page K.J. 2000. Photogrammetric Engineering & Remote Sensing, 66(12), 1461–1467.
• 20. Rokni K., Ahmad A., Selamat A., Hazini S. 2014. Extraction des caractéristiques de l’eau et détection des changements à l’aide de l’imagerie Landsat multitemporelle. Remote Sens, 6, 4173–4189.
• 21. Harbouze R., Pellissier J.-P., Rolland J.-P., Khechimi W. 2019. Rapport de synthèse sur l’agriculture au Maroc. [Rapport de recherche] CIHEAM-IAMM, 104.
• 22. Rouse J.W., Haas R.H., Shell J.A., Deering D.W. 1973. Monitoring Vegetation Systems in the Great Plains with ERTS. In Proceedings of the Third Earth Resources Technology Satellite-1 Symposium, Washington, DC, USA 1973, 309–317.
• 23. Tri Dev Acharya, Anoj Subedi, He Huang, and Dong Ha Lee, 2019: Application of water indices in surface water change detection using landsat imagery in Nepal. Sensors and Materials, 31(5), 1429–1447.
• 24. El Orfi T., El Ghachi M., Lebaut S. 2020. Contributions of remote sensing in the diachronic study of the spatial and temporal evolution of the Ahmed El Hansali dam water reservoir from 2002-03 to 2018-19. E3S Web of Conferences, EDP Sciences, 183, 02004.
• 25. Zhou, Y., et al. 2017. Open surface water mapping algorithms: a comparison of water related spectral indices and sensors. Water, 9(256), 1–16.
• 26. Xu H. 2006. Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery. Int. J. Remote Sens., 27, 3025–3033.
• 27. Zhu Z., Wang S., Woodcock, C.E. 2015. Improvement and expansion of the Fmask algorithm: Cloud, cloud shadow, and snow detection for Landsats 4–7, 8, and Sentinel 2 images. Remote Sens. Environ., 159, 269–277. DOI: 10.1016/j.rse.2014.12.014

Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).