Publication:
Enhancing reservoir operations with charged system search (CSS) algorithm: Accounting for sediment accumulation and multiple scenarios

Simple item page
dc.citedby2
dc.contributor.authorAlmubaidin M.A.A.en_US
dc.contributor.authorAhmed A.N.en_US
dc.contributor.authorMalek M.A.en_US
dc.contributor.authorMahmoud M.A.en_US
dc.contributor.authorSherif M.en_US
dc.contributor.authorEl-Shafie A.en_US
dc.contributor.authorid57476845900en_US
dc.contributor.authorid57214837520en_US
dc.contributor.authorid55636320055en_US
dc.contributor.authorid55247787300en_US
dc.contributor.authorid7005414714en_US
dc.contributor.authorid16068189400en_US
dc.date.accessioned2025-03-03T07:44:00Z
dc.date.available2025-03-03T07:44:00Z
dc.date.issued2024
dc.description.abstractOptimizing reservoir operation is a complex problem with non-linearities, numerous decision variables, and challenging constraints to simulate and solve. Researchers have tested various metaheuristics algorithms (MHAs) to reduce water deficit in reservoirs and presented them to decision-makers for adoption. Optimization methods vary depending on objectives, reservoir type, and algorithms used. The paper utilizes the CSS algorithm to study the impact of various scenarios on the optimal operation of the Mujib reservoir in Jordan to reduce water deficits using historical date between 2004 and 2019. The study explores different scenarios, including sediment impact, water demand management, and increasing the storage volume for the reservoir, to identify the optimal operation of the reservoir. The study compares the results of these scenarios with the current operation of the reservoir. Risk analysis (volumetric reliability, shortage index (SI), resilience, vulnerability) and error indexes (correlation coefficient R2, the root mean square error (RMSE), and the mean absolute error (MAE)) were used to compare results between scenarios, in addition to the annual water deficit values from the CSS algorithm for each scenario. The simulation of monthly sediment values in the Mujib reservoir showed that sediment accumulation accounts for 14.6% of the reservoir's volume at the end of 2019. Removing sediments retained by the dam can reduce water deficit by 19.42% when using the CSS algorithm. Additionally, reducing agricultural water demand by 11% and removing sediment reduced water deficit by 42.40%. The study also examined the impact of increasing the storage capacity of the reservoir by 10%, 20%, and 30%, revealing a decrease in water deficit by 35.44% when sediment removal was included in the analysis. The study examined the scenario of increasing the storage capacity of the Mujib reservoir by 30%, reducing water demand by 11%, and removing sediment. This scenario resulted in a 53.59% decrease in water deficit, providing decision-makers with viable solutions to address the water deficit problem in the reservoir. ? 2024 The Authorsen_US
dc.description.natureFinalen_US
dc.identifier.ArtNo108698
dc.identifier.doi10.1016/j.agwat.2024.108698
dc.identifier.scopus2-s2.0-85184080440
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85184080440&doi=10.1016%2fj.agwat.2024.108698&partnerID=40&md5=291282c24c0dea68dc142da852a7bd59
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/36699
dc.identifier.volume293
dc.publisherElsevier B.V.en_US
dc.relation.ispartofAll Open Access; Green Open Access; Hybrid Gold Open Access
dc.sourceScopus
dc.sourcetitleAgricultural Water Management
dc.subjectJordan
dc.subjectErrors
dc.subjectMean square error
dc.subjectOptimization
dc.subjectReliability analysis
dc.subjectReservoir management
dc.subjectRisk analysis
dc.subjectRisk assessment
dc.subjectRisk perception
dc.subjectSediments
dc.subjectWater resources
dc.subjectCharged system search
dc.subjectCharged system search algorithms
dc.subjectCharged system searches
dc.subjectReservoir operation
dc.subjectReservoir operation optimizations
dc.subjectSediment accumulation
dc.subjectSediment simulation
dc.subjectWater deficit in reservoir
dc.subjectWater deficits
dc.subjectWater resources management
dc.subjectalgorithm
dc.subjecterror analysis
dc.subjectgeoaccumulation
dc.subjectheuristics
dc.subjectoptimization
dc.subjectsedimentation
dc.subjectwater demand
dc.subjectwater management
dc.subjectwater stress
dc.subjectReservoirs (water)
dc.titleEnhancing reservoir operations with charged system search (CSS) algorithm: Accounting for sediment accumulation and multiple scenariosen_US
dc.typeArticleen_US
dspace.entity.typePublication
Files
Collections
SCOPUS