Novel Hybrid Machine Learning Algorithms for Lakes Evaporation and Power Production using Floating Semitransparent Polymer Solar Cells

Ismail Abd-Elaty (), N. L. Kushwaha () and Abhishek Patel ()
Additional contact information
Ismail Abd-Elaty: Zagazig University
N. L. Kushwaha: ICAR-Indian Agricultural Research Institute
Abhishek Patel: ICAR-Central Arid Zone Research Institute, Regional Research Station

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2023, vol. 37, issue 12, No 4, 4639-4661

Abstract: Abstract The present study predicts the future evaporation losses by applying novel hybrid Machine Learning Algorithms (MLA). Water resources management is achieved by covering the reservoir water surface with floating semitransparent polymer solar cells. The energy produced by these panels will be used in the irrigation activities. The study is applied for the mass water body of Nasser Lake, Egypt and Sudan. Five MLAs namely additive regression (AR), AR-random subspace (AR-RSS), AR-M5Pruned (AR-M5P), AR-reduced error pruning tree (AR-REPTree), and AR- support vector machine (AR-SVM) were developed and evaluated for predicting future evaporation losses in the years 2030, 2050, and 2070. The study concludes that the hybrid AR-M5P ML model was not only superior to the AR model alone but also outperformed other hybrid models such as AR-RSS and AR-REPTree. The expected total annual water saving are projected to reach 3.47 billion cubic meters (BCM), 3.68 and 3.90 BCM, while the total annual power production is observed to be 1389 × 109 Megawatt (MW), 1535 × 109 MW and 1795 × 109 MW in the years 2030, 2050 and 2070, respectively. These results were achieved by covering the shallow water depths from contour level 0 m to 10 m below the surface water level. Additionally, this study shows the ability of using MLAs in the estimation of reservoir evaporation and addressing the water shortages in high stress regions. Graphical Abstract

Keywords: Machine learning; Evaporation; Solar panels; Water saving and energy (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s11269-023-03565-2 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:waterr:v:37:y:2023:i:12:d:10.1007_s11269-023-03565-2

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11269

DOI: 10.1007/s11269-023-03565-2

Access Statistics for this article

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA) is currently edited by G. Tsakiris

More articles in Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA) from Springer, European Water Resources Association (EWRA)
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().