Developing a Reliability-Based Waste Load Allocation Strategy for River-Reservoir Systems

2018 ◽  
Vol 144 (9) ◽  
pp. 04018052 ◽  
Author(s):  
Abbas Afshar ◽  
Fariborz Masoumi ◽  
Samuel Sandoval Solis
1989 ◽  
Vol 21 (8-9) ◽  
pp. 1057-1064 ◽  
Author(s):  
Vijay Joshi ◽  
Prasad Modak

Waste load allocation for rivers has been a topic of growing interest. Dynamic programming based algorithms are particularly attractive in this context and are widely reported in the literature. Codes developed for dynamic programming are however complex, require substantial computer resources and importantly do not allow interactions of the user. Further, there is always resistance to utilizing mathematical programming based algorithms for practical applications. There has been therefore always a gap between theory and practice in systems analysis in water quality management. This paper presents various heuristic algorithms to bridge this gap with supporting comparisons with dynamic programming based algorithms. These heuristics make a good use of the insight gained in the system's behaviour through experience, a process akin to the one adopted by field personnel and therefore can readily be understood by a user familiar with the system. Also they allow user preferences in decision making via on-line interaction. Experience has shown that these heuristics are indeed well founded and compare very favourably with the sophisticated dynamic programming algorithms. Two examples have been included which demonstrate such a success of the heuristic algorithms.


Water ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 340
Author(s):  
Wenjuan Ouyang ◽  
Zhe Li ◽  
Jixiang Yang ◽  
Lunhui Lu ◽  
Jinsong Guo

The resting stages of phytoplankton are usually regarded as the seed bank and source of harmful algal blooms because of the recruitment of phytoplankton from sediment to the water column under suitable environmental conditions. Information about resting stages of phytoplankton is abundant in shallow lakes and littoral sea; yet, studies on river–reservoir systems are rare. The river–reservoir continuum shows a unique structuring of longitudinal gradients of hydrological and hydrodynamic conditions. We hypothesized that the seed bank and algal blooms in reservoirs are influenced by the hydrodynamic conditions of each reservoir. We used Illumina Miseq sequencing to examine the spatio-temporal variation in the phytoplankton community in the sediment as reservoir drawdown and in surface water during algal blooms in Pengxi River, a tributary of China’s Three Gorges Reservoir. The results show that the cyanobacteria community in sediment is significantly influenced by temperature, total carbon, maximum flow velocity, and total phosphorous, the eukaryotic phytoplankton community in sediment is significantly influenced by total phosphorous, temperature, total carbon, maximum flow velocity, and total nitrogen. Additionally, the dominant species in sediment is significantly different from that in surface water during algal blooms. Our results suggest that the dominant species in surface water during algal blooms is more influenced by the environmental factors and hydrodynamic conditions in the water column than the seeds in the sediment. These findings are fundamental for further research on the influence of hydrodynamic conditions on algal blooms in artificially regulated river-reservoir systems.


Water ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 2618
Author(s):  
Jae Heon Cho ◽  
Jong Ho Lee

In traditional waste load allocation (WLA) decision making, water quality-related constraints must be satisfied. Fuzzy models, however, can be useful for policy makers to make the most reasonable decisions in an ambiguous environment, considering various surrounding environments. We developed a fuzzy WLA model that optimizes the satisfaction level by using fuzzy membership functions and minimizes the water quality management cost for policy decision makers considering given environmental and socioeconomic conditions. The fuzzy optimization problem was formulated using a max–min operator. The fuzzy WLA model was applied to the Yeongsan River basin, which is located in the southwestern part of the Korean Peninsula and Korean TMDLs were applied. The results of the fuzzy model show that the pollutant load reduction should be increased in the Gwangju 1 and Gwangju 2 wastewater treatment plants (WWTPs) and in subcatchments with high pollutant load. In particular, it is necessary to perform advanced wastewater treatment to decrease the load of 932 kg ultimate biochemical oxygen demand (BODu)/day in the large-capacity Gwangju 1 WWTP and reduce the BODu emission concentration from 4.3 to 2.7 mg/L during the low-flow season. The satisfaction level of the fuzzy model is a relatively high at 0.81.


2020 ◽  
Vol 22 (4) ◽  
pp. 815-841 ◽  
Author(s):  
Behnam Andik ◽  
Mohammad Hossein Niksokhan

Abstract This article aims to present a new methodology for waste load allocation (WLA) in a riverine system considering the uncertainty and achieve the lowest amount of inequity index, cost, and fuzzy risk of standard violation. To find a surface of undominated solutions, a new modified PAWN method, initially designed for sensitivity analysis, was developed and coupled with a simulation-optimization process using multi-objective particle swarm optimization (MOPSO) algorithm, to consider the uncertainty of all affecting variables and parameters by using their probability distribution. The proposed methodology applied to Sefidrood River in the northern part of Iran. Graph model for conflict resolution (GMCR) as a subset of game theory was implemented to attain a compromise on WLA among the stakeholders of a river system's quality in Iran: Department of Environment, Municipal Waste Water, and Private Sector. Some undominated solutions were used in GMCR model and modeling the conflict among decision makers reveals that their preferences and the status quo do not lead to a solely stable equilibrium; thus the intervention of a ruler as arbitrator leads them to reach a compromise on a scenario that has a median FRVS and cost. Sensitivity analysis was done using the PAWN method to assess the sensitivity of three intended objectives to all variables and parameters.


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