Literature DB >> 33400117

The impact of land use and socio-economic factors on ammonia nitrogen pollution in Weihe River watershed, China.

Zhilei Bi1, Yan Zhang2, Peng Shi3, Xin Zhang1, Zexuan Shan1, Lijiang Ren1.   

Abstract

Rapid socio-economic development has led to a significant deterioration in the water environment, which has limited sustainable regional development. The soil and water assessment tool (SWAT) and statistical regression method were used to model the ammonia nitrogen (NH4+-N) pollution and explore the impacts of land use and socio-economic factors on NH4+-N pollution within the Weihe River watershed in China from 2015 to 2018. The result of SWAT model revealed that the NH4+-N concentrations were usually relatively high under low runoff conditions and relatively low under high runoff conditions. The average NH4+-N concentration in the upper reaches was 0.77 mg/L, whereas it was 0.87 mg/L in the middle and lower reaches of the watershed. Serious NH4+-N pollution mainly occurred in 2015 and 2016, and the V (2.0 mg/L) and V+ (>2.0 mg/L) water quality classes were associated with approximately 6.67% and 28.94% of the total watershed area, respectively. The multiple linear regression indicated that the building land and secondary industry were the significant controlling factors (P < 0.01). According to the scenario analysis, modelled scenarios for interception measures reduced the NH4+-N load to a greater degree than scenarios for source control measures. To improve the surface water quality in the Weihe River, it is recommended to adjust industrial structure, increase sewage treatment, and strengthen the rural management of the watershed.

Entities:  

Keywords:  Land use; Multiple linear regression; NH4 +-N; SWAT model; Social economy; Weihe River

Mesh:

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Year:  2021        PMID: 33400117     DOI: 10.1007/s11356-020-11960-0

Source DB:  PubMed          Journal:  Environ Sci Pollut Res Int        ISSN: 0944-1344            Impact factor:   4.223


  2 in total

1.  Water quality change and pollution source accounting of Licun River under long-term governance.

Authors:  Minghui Zhang; Lin Wang; Chunxia Mu; Xuda Huang
Journal:  Sci Rep       Date:  2022-02-17       Impact factor: 4.379

2.  Exploring the Driving Factors of Remote Sensing Ecological Index Changes from the Perspective of Geospatial Differentiation: A Case Study of the Weihe River Basin, China.

Authors:  Kaili Zhang; Rongrong Feng; Zhicheng Zhang; Chun Deng; Hongjuan Zhang; Kang Liu
Journal:  Int J Environ Res Public Health       Date:  2022-09-01       Impact factor: 4.614

  2 in total

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