TY - JOUR
T1 - Water and waste load allocation in rivers with emphasis on agricultural return flows
T2 - Application of fractional factorial analysis
AU - Tavakoli, Ali
AU - Kerachian, Reza
AU - Nikoo, Mohammad Reza
AU - Soltani, Maryam
AU - Estalaki, Siamak Malakpour
N1 - Funding Information:
Acknowledgments The authors would like to acknowledge the financial support of the University of Tehran for this research under grant number 8102060/1/05.
PY - 2014/9
Y1 - 2014/9
N2 - In this paper, a new methodology is developed to handle parameter and input uncertainties in water and waste load allocation (WWLA) in rivers by using factorial interval optimization and the Soil, Water, Atmosphere, and Plant (SWAP) simulation model. A fractional factorial analysis is utilized to provide detailed effects of uncertain parameters and their interaction on the optimization model outputs. The number of required optimizations in a fractional factorial analysis can be much less than a complete sensitivity analysis. The most important uncertain inputs and parameters can be also selected using a fractional factorial analysis. The uncertainty of the selected inputs and parameters should be incorporated real time water and waste load allocation. The proposed methodology utilizes the SWAP simulation model to estimate the quantity and quality of each agricultural return flow based on the allocated water quantity and quality. In order to control the pollution loads of agricultural dischargers, it is assumed that a part of their return flows can be diverted to evaporation ponds. Results of applying the methodology to the Dez River system in the southwestern part of Iran show its effectiveness and applicability for simultaneous water and waste load allocation in rivers. It is shown that in our case study, the number of required optimizations in the fractional factorial analysis can be reduced from 64 to 16. Analysis of the interactive effects of uncertainties indicates that in a low flow condition, the upstream water quality would have a significant effect on the total benefit of the system.
AB - In this paper, a new methodology is developed to handle parameter and input uncertainties in water and waste load allocation (WWLA) in rivers by using factorial interval optimization and the Soil, Water, Atmosphere, and Plant (SWAP) simulation model. A fractional factorial analysis is utilized to provide detailed effects of uncertain parameters and their interaction on the optimization model outputs. The number of required optimizations in a fractional factorial analysis can be much less than a complete sensitivity analysis. The most important uncertain inputs and parameters can be also selected using a fractional factorial analysis. The uncertainty of the selected inputs and parameters should be incorporated real time water and waste load allocation. The proposed methodology utilizes the SWAP simulation model to estimate the quantity and quality of each agricultural return flow based on the allocated water quantity and quality. In order to control the pollution loads of agricultural dischargers, it is assumed that a part of their return flows can be diverted to evaporation ponds. Results of applying the methodology to the Dez River system in the southwestern part of Iran show its effectiveness and applicability for simultaneous water and waste load allocation in rivers. It is shown that in our case study, the number of required optimizations in the fractional factorial analysis can be reduced from 64 to 16. Analysis of the interactive effects of uncertainties indicates that in a low flow condition, the upstream water quality would have a significant effect on the total benefit of the system.
KW - Factorial analysis
KW - SWAP
KW - The Dez River
KW - Uncertainty analysis
KW - Water and waste load allocation
KW - Water quality
UR - http://www.scopus.com/inward/record.url?scp=84905991192&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84905991192&partnerID=8YFLogxK
U2 - 10.1007/s10661-014-3830-6
DO - 10.1007/s10661-014-3830-6
M3 - Article
C2 - 24880723
AN - SCOPUS:84905991192
SN - 0167-6369
VL - 186
SP - 5935
EP - 5949
JO - Environmental Monitoring and Assessment
JF - Environmental Monitoring and Assessment
IS - 9
ER -