A New Water Environmental Load and Allocation Modeling Framework at the Medium–Large Basin Scale

Abstract

Waste load allocation (WLA), as a well-known total pollutant control strategy, is designed to distribute pollution responsibilities among polluters to alleviate environmental problems, but the current policy is unfair and limited to single scale or single pollution types. In this paper, a new, alternative, multi-scale, and multi-pollution WLA modeling framework was developed, with a goal of producing optimal and fair allocation quotas at multiple scales. The new WLA modeling framework integrates multi-constrained environmental Gini coefficients (EGCs) and Delphi-analytic hierarchy process (Delphi-AHP) optimization models to achieve the stated goal. The new WLA modeling framework was applied in a case study in the Xian-jiang watershed in Zhejiang Province, China, in order to test its validity and usefulness. The results, in comparison with existing practices by the local governments, suggest that the simulated pollutant load quota at the watershed scale is much fairer than the existing policies and even has some environmental economic benefits at the pollutant source scale. As the new WLA is a process-based modeling framework, it should be possible to adopt this approach in other similar geographic areas.

Leverage Points Used in a Systems Approach of River and River Basin Restoration

“…The research demonstrates that proposed rules to allocate 10 to 25% of flows to the environment will not achieve ecological health targets without considering the coupling between flow timing (i.e., delays) and flow to achieve naturalization of the flow regime that supports key ecological processes [8]. Liu et al [9] examined how power to add, change, evolve, or self-organize system structure (leverage point #4) could lead to changes in the rules (leverage point #5) that are fairer and achieve water quality targets. The research used a multi-scale and multi-pollutant waste-load allocation model to explore changes in pollution quotas across 1350 areas within the Xian-jiang river basin of China, finding an allocation that reduced inequality (based on Gini coefficients) yet was more economical and met pollutant thresholds for chemical oxygen demand, ammonia nitrogen, and total phosphorus [9].…”

“…Liu et al [9] examined how power to add, change, evolve, or self-organize system structure (leverage point #4) could lead to changes in the rules (leverage point #5) that are fairer and achieve water quality targets. The research used a multi-scale and multi-pollutant waste-load allocation model to explore changes in pollution quotas across 1350 areas within the Xian-jiang river basin of China, finding an allocation that reduced inequality (based on Gini coefficients) yet was more economical and met pollutant thresholds for chemical oxygen demand, ammonia nitrogen, and total phosphorus [9].…”

A new fuzzy approach and bankruptcy theory in risk estimation in Waste Load Allocation

“…Waste Load allocation (WLA) is a well-known strategy for controlling water quality. It is calculated by distributing responsibility for pollutant discharge effects based on wastewater treatment level (Saadatpour & Afshar 2007;Ghosh & Mujumdar 2010;liu et al 2019). However, there is always uncertainty in simulating such systems, due to the intrinsic and deepseated uncertainty of water quality model prediction (Haan 1989).…”