TY - JOUR
T1 - Review on wastewater treatment ponds clogging under artificial recharge
T2 - Impacting factors and future modelling
AU - Abdalrahman, Ghada A.M.
AU - Lai, Sai Hin
AU - Snounu, Ismael
AU - Kumar, Pavitra
AU - Sefelnasr, Ahmed
AU - Sherif, Mohsen
AU - El-shafie, Ahmed
N1 - Funding Information:
This research was funded by University of Malaya Research Grant (UMRG) , Malaysia, grant number RP025A-18SUS .
Publisher Copyright:
© 2020 Elsevier Ltd
PY - 2021/4
Y1 - 2021/4
N2 - 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.
AB - 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.
KW - Artificial neural network modelling
KW - Artificial recharge
KW - Infiltration rate
KW - Soil clogging
KW - Treated wastewater
UR - http://www.scopus.com/inward/record.url?scp=85097759925&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85097759925&partnerID=8YFLogxK
U2 - 10.1016/j.jwpe.2020.101848
DO - 10.1016/j.jwpe.2020.101848
M3 - Review article
AN - SCOPUS:85097759925
SN - 2214-7144
VL - 40
JO - Journal of Water Process Engineering
JF - Journal of Water Process Engineering
M1 - 101848
ER -