Water Quality Trading with Equitable Total Maximum Daily Loads
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 33122
Water Quality Trading with Equitable Total Maximum Daily Loads

Authors: S. Jamshidi, E. Feizi Ashtiani, M. Ardestani

Abstract:

Waste Load Allocation (WLA) strategies usually intend to find economic policies for water resource management. Water quality trading (WQT) is an approach that uses discharge permit market to reduce total environmental protection costs. This primarily requires assigning discharge limits known as total maximum daily loads (TMDLs). These are determined by monitoring organizations with respect to the receiving water quality and remediation capabilities. The purpose of this study is to compare two approaches of TMDL assignment for WQT policy in small catchment area of Haraz River, in north of Iran. At first, TMDLs are assigned uniformly for the whole point sources to keep the concentrations of BOD and dissolved oxygen (DO) at the standard level at checkpoint (terminus point). This was simply simulated and controlled by Qual2kw software. In the second scenario, TMDLs are assigned using multi objective particle swarm optimization (MOPSO) method in which the environmental violation at river basin and total treatment costs are minimized simultaneously. In both scenarios, the equity index and the WLA based on trading discharge permits (TDP) are calculated. The comparative results showed that using economically optimized TMDLs (2nd scenario) has slightly more cost savings rather than uniform TMDL approach (1st scenario). The former annually costs about 1 M$ while the latter is 1.15 M$. WQT can decrease these annual costs to 0.9 and 1.1 M$, respectively. In other word, these approaches may save 35 and 45% economically in comparison with command and control policy. It means that using multi objective decision support systems (DSS) may find more economical WLA, however its outcome is not necessarily significant in comparison with uniform TMDLs. This may be due to the similar impact factors of dischargers in small catchments. Conversely, using uniform TMDLs for WQT brings more equity that makes stakeholders not feel that much envious of difference between TMDL and WQT allocation. In addition, for this case, determination of TMDLs uniformly would be much easier for monitoring. Consequently, uniform TMDL for TDP market is recommended as a sustainable approach. However, economical TMDLs can be used for larger watersheds.

Keywords: Waste load allocation (WLA), Water quality trading (WQT), Total maximum daily loads (TMDLs), Haraz River, Multi objective particle swarm optimization (MOPSO), Equity.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1107646

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2066

References:


[1] USEPA “Water quality trading assessment handbook”, 2004, 1-120.
[2] S. Jamshidi, MH. Niksokhan, M. Ardestani “Surface Water Quality Management Using Integrated Discharge Permit and Reclaimed Water Market” Water Science and Technology, 70(5), 2014, 917-924.
[3] D. Collentine, “Including non-point sources in a water quality trading permit program”, Water science and technology, 51(3-4), 2005, 47-53.
[4] R.A., Ranga Prabodanie, J.F. Raffensperger, M.W. Milke, “A pollution offset system for trading non-point source water pollution permits”, Environmental and Resource Economics, 45, 2010, 499-515.
[5] M.O. Ribaudo, J. Gottlieb, “Point-Nonpoint Trading – Can it Work?”, Journal of the American Water Resources Association (JAWRA), 47(1), 2011, 5-14.
[6] B. Boyd, R. Greenwood, “Water quality trading: Assessment methods and lessons”, Environmental Quality Management, 2005, 23-29.
[7] M.R., Nikoo, R., Kerachian, M.H. Niksokhan, “Equitable Waste Load Allocation in Rivers Using Fuzzy Bi-matrix Games”, Water Resources Management, 26(15), 2012, 4539-4552.
[8] M.H., Niksokhan, R. Kerachian, P. Amin, “A stochastic conflict resolution model for trading pollutant discharge permits in river systems”, Environmental Monitoring and assessment, 154, 2009, 219- 232.
[9] M. H., Niksokhan, R. Kerachian, M. Karamouz, “A game theoretic approach for trading discharge permits in rivers”, Water Science and Technology, 60(3), 2009, 793-804.
[10] N. P., Nguyen, J. S., Shortle, P. M. Reed, T. T. Nguyen, “Water quality trading with asymmetric information, uncertainty and transaction costs: a stochastic agent-based simulation”, Resource and Energy Economics, 35(1), 2013, 60-90.
[11] J. S. Kardos, C. C. Obropta, “Water quality model uncertainty analysis of a point-point source phosphorus trading program”, Journal of the American Water Resources Association (JAWRA), 47(6), 2011, 1317- 1337.
[12] G, Ghosh M, Ribaudo J, Shortle, “Baseline requirements can hinder trades in water quality trading programs: Evidence from the Conestoga watershed”. Journal of environmental management, 92, 2011, 2076- 2084.
[13] D. O’Grady, “Sociopolitical conditions for successful water quality trading in the south nation river watershed, Ontario, Canada”, Journal of the American Water Resources Association (JAWRA), 47(1), 2011, 39- 51.
[14] JW, Eheart, T, Ling Ng, “Role of effluent permit trading in total maximum daily load programs: Overview and uncertainty and reliability implications”. Journal of environmental engineering ASCE, 130(6), 2004, 615-621
[15] A., Pejman, G., Nabi Bidhendi, A., Karbassi, N. Mehrdadi, M. Esmaeili Bidhendi, “Evaluation of spatial and seasonal variations in surface water quality using multivariate statistical techniques”, International Journal of Environmental Science and Technology, 6(3), 2009, 467-476.
[16] E., Feizi Ashtiani, M. H. Niksokhan, M. Ardestani, “Multi-objective Waste Load Allocation in River System by MOPSO Algorithm”, International Journal of Environmental Research, in press.
[17] P. R., Kannel, S., Lee, Y.S., Lee, S. R. Kanel, G. J. Pelletier, “Application of automated Qualt2kw for water quality modelling and management in the Bagmati River, Nepal”, Ecological Modelling, 202, 2007, 503-517.
[18] A. M. Baltar, D. G. Fontane, “Use of multi-objective particle swarm optimization in water resource management”, Journal of water resource planning and management, 134(3), 2008, 257-265.
[19] A. Azadnia, B. Zahraie, “Optimization of nonlinear Muskingum method with variable parameters using multi-objective particle swarm optimization”, World environmental and Water Resources Congress, ASCE, 2010, 2278-2284
[20] Ashtiani, E. F., Niksokhan, M. H., & Jamshidi, S. (2015), “Equitable fund allocation, an economical approach for sustainable waste load allocation” Environmental monitoring and assessment, 187(8), 1-11.
[21] I., Rahimi, K. Qaderi, A.M. Abasiyan, “Optimal Reservoir Operation Using MOPSO with Time Variant Inertia and Acceleration Coefficients”, Universal Journal of Agricultural Research, 1(3), 2013, 74-80.
[22] D. H. Burn, J.S. Yulianti “Waste-load allocation using genetic algorithms”, Journal of Water Resource Planning and Management, 127(2), 2001, 121-129.