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[Identification and Optimization Method of Rainfall-Runoff Pollution Risk Level].
Qi, Xiao-Tian; Zhang, Zhi-Ming; Zhao, Xin; Hu, Wen-Han; Liu, Di.
Afiliación
  • Qi XT; School of Environment and Energy Engineering, Beijing University of Civil Engineering and Architecture, Beijing 100044, China.
  • Zhang ZM; Beijing Climate Change Response Research and Education Center, Beijing University of Civil Engineering and Architecture, Beijing 100044, China.
  • Zhao X; School of Environment and Energy Engineering, Beijing University of Civil Engineering and Architecture, Beijing 100044, China.
  • Hu WH; Beijing Climate Change Response Research and Education Center, Beijing University of Civil Engineering and Architecture, Beijing 100044, China.
  • Liu D; School of Environment and Energy Engineering, Beijing University of Civil Engineering and Architecture, Beijing 100044, China.
Huan Jing Ke Xue ; 43(3): 1500-1511, 2022 Mar 08.
Article en Zh | MEDLINE | ID: mdl-35258214
ABSTRACT
Runoff pollution control is currently a difficult problem in urban water environment protection. The identification of runoff pollution risk into rivers is the key to improve the efficiency of pollution control. By combining landscape patterns and processes and using the landscape pattern index and minimum cumulative resistance model, a set of integrated methods for river rainfall-runoff pollution risk identification and optimization was proposed. The rainfall-runoff pollution pattern, process, and comprehensive risk index of the major river reaches in the study area were calculated. The risk paths of runoff pollution generated by cultivated land, urban construction land, and traffic industrial and mining land were identified as 256, 182, and 208, respectively. The results showed that① according to the pattern factors, a ten-level rainfall runoff pollution pattern risk index was identified, and more rivers in the central and southern regions had a relatively high pollution risk. ② The risk of runoff pollution caused by fragmentation and dominance factors was higher than that caused by aggregation factors, and the range was wider. The corresponding landscape pattern optimization methods were proposed for the three types of indicators. ③ For the pollution process, the identified ten levels of rainfall runoff pollution process risk index showed that the rivers with high risk index were mainly concentrated in the central urban area and gradually decreased to the periphery. ④ The range and intensity of rainfall and runoff pollution caused by different types of land use were as followsin terms of range, cultivated land>traffic industrial and mining land>urban construction land. Regarding intensity, traffic industrial and mining land>urban construction land>cultivated land. ⑤ The river pollution risk in the middle and southeast of the study area was significantly higher than that in the west and north of the study area. Among them, there were 13 level 1 risk reaches with a length of 209.65 km, accounting for 9.39% of the total length. There were 11 level 2 risk river sections with a length of 186.83 km, accounting for 8.37% of the total length. These river reaches should be the focus of urban rainfall runoff pollution control in the future.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Movimientos del Agua / Contaminantes Químicos del Agua Tipo de estudio: Diagnostic_studies / Etiology_studies / Prognostic_studies / Risk_factors_studies País/Región como asunto: Asia Idioma: Zh Revista: Huan Jing Ke Xue Año: 2022 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Movimientos del Agua / Contaminantes Químicos del Agua Tipo de estudio: Diagnostic_studies / Etiology_studies / Prognostic_studies / Risk_factors_studies País/Región como asunto: Asia Idioma: Zh Revista: Huan Jing Ke Xue Año: 2022 Tipo del documento: Article País de afiliación: China