J. Jiang - School of Environmental Science and Engineering, Southern University of Science and Technology, ۵۱۸۰۵۵, China
T. Ri - School of Environment, Harbin Institute of Technology, Harbin, ۱۵۰۰۹۰, China| Department of Earth and Environmental Science, Kim II Sung University, Pyongyang, ۹۹۹۰۹۳, DPR of Korea
T. Pang - School of Environmental Science and Engineering, Southern University of Science and Technology, ۵۱۸۰۵۵, China| School of Environment, Harbin Institute of Technology, Harbin, ۱۵۰۰۹۰, China
Y. Wang - Shenyang Urban Planning Design and Research Institute, Shenyang, ۱۱۰۱۷۹, China

Precisely management of water quality in urban rivers is of significant and water environmental capacity provide a useful tool. This study presented a water quality analysis simulation program model-based approach for dynamical load reduction in Ashi River, highly contaminated tributaries of Songhua River, China. The actual and surplus dynamic environmental capacity of CODCr and NH3-N, as the two controlling endpoints, were computed based on segment-end-control method for monthly or seasonal management. The dynamic pollution control scheme and monthly to annual control strategies were produced based on calculated results. Results show that CODCr and NH3-N need to be cut down to approximately 462.47t/a and 5.2t/a at Zhujia-Acheng down reach and 282.42 t/a and 9.25t/a Acheng down-Chenggaozi town reach, respectively under 90% hydrological design reliability to keep the water quality at class-IV. The CODCr and NH3-N of three ditches should be strictly controlled throughout the year. Some interesting temporal-spatial characteristics of surplus environmental capacity were also found in the study. This study provides local governments with technical measurements and policy recommendations for highly contaminated water body treatment. In the future, the river water quality management in the winter season should take into particular consideration.

Ashi River, Chemical oxygen demand, Ammonia nitrogen, Water environmental capacity, Water quality analysis simulation program (WASP)