期刊
JOURNAL OF WATER PROCESS ENGINEERING
卷 40, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.jwpe.2020.101848
关键词
Treated wastewater; Artificial recharge; Infiltration rate; Soil clogging; Artificial neural network modelling
资金
- University of Malaya Research Grant (UMRG), Malaysia [RP025A-18SUS]
Artificial recharge of treated wastewater has been widely used in arid areas to replenish groundwater, but can lead to surface clogging and reduced infiltration rate in infiltration basins. This study focuses on factors influencing soil clogging and highlights the need to establish an integrated ideation.
Artificial recharge (AR) of treated wastewater (TWW) has been widely applied in arid areas as a promising technique to replenish groundwater and control the depletion of aquifers. Consequently, surface clogging and reduction of infiltration rate (IR) in infiltration basin problems have appeared on the surface. Clogging generally arises as a result of various chemical, physical and biological processes through the infiltration of TWW. The primary concern in this study is based on the factors influencing the development of soil clogging, thus contributing to the reduction of IR. These factors were classified into major categories, namely, factors related to soil characteristics, factors related to TWW, operation process and hydraulic loading rates. Furthermore, this study presents a review of the traditional models used in evaluating the IR and a comparison between these traditional models and artificial neural networks using various statistical criteria. The uncertainty remains in the precise impact of the quality of water and soil parameters on the clogging of basins. Thus, arousing a need to establish an integrated ideation for the factors impacting the clogging of infiltration basins, and to develop an artificial neural network model that can simulate all conditions and yield accurate results to the field value.
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