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Cooperative identification for critical periods and critical source areas of nonpoint source pollution in a typical watershed in China

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Abstract

Critical periods (CPs) and critical source areas (CSAs) refer to the high-risk periods and areas of nonpoint source (NPS) pollution in a watershed, respectively, and they play a significant role in NPS pollution control. The upstream Daning River Basin is a typical watershed in the Three Gorges Reservoir area. In this study, a Hydrological Simulation Program-Fortran (HSPF) model was used to simulate phosphorus loss in the upstream Daning River Basin. Co-analysis of critical periods and critical source areas (CACC) is a quantitative collaborative analysis method for the identification of CSAs in CPs, and it was used to classify the periods and areas of NPS pollution as CPs, sub-CPs, non-CPs, CSAs, and non-CSAs. The CPs occurred in months 5–7 and accounted for 53.7% of the total phosphorus (TP) loads, and the sub-CPs occurred in months 1, 3, 4, and 8 and accounted for 29.2% of the TP loads. In CSAs, 49.4% of the TP loads occurred in 26.8% of the basin. Furthermore, we proposed the following multilevel priority control measure for NPS pollution in the upstream Daning River Basin: CSAs in CPs (with load-area rate of 1.4), CSAs in sub-CPs (0.7), CSAs in non-CPs (0.4), non-CSAs in CPs (0.3), non-CSAs in sub-CPs (0.2), and non-CSAs in non-CPs (0.1). CSAs in CPs accounted for 25.8% of the TP loads from 19.0% of the areas in only 3 months while 49.4% of the TP loads from similar areas over an entire year. These findings indicated that the CSAs in CPs located in farmland along the Daning, Dongxi, and Houxi Rivers should be prioritized for pollution management measures.

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References

  • Abari ME, Majnounian B, Malekian A, Jourgholami M (2017) Effects of forest harvesting on runoff and sediment characteristics in the Hyrcanian forests, northern Iran. Eur J For Res 136:375–386

    Article  Google Scholar 

  • Bicknell BR, Imhoff JC, Kittle JL (2001) Hydrological simulation program–FORTRAN (HSPF), User’s manual for version 12.0. EPA, Athens

    Google Scholar 

  • Borah D, Bera M (2013) Watershed-scale hydrologic and nonpoint-source pollution models: review of mathematical bases. Trans ASAE 46:1553–1566

    Article  Google Scholar 

  • Carpenter SR, Caraco NF, Correll DL, Howarth RW, Sharpley AN, Smith VH (1998) Nonpoint pollution of surface waters with phosphorus and nitrogen. Ecol Appl 8:559–568

    Article  Google Scholar 

  • Chen L, Shen ZY (2014) Method and application of watershed non-point source pollution priority control area identification. China Environmental Press, Beijing

    Google Scholar 

  • Cheng X, Chen L, Sun R, Jing Y (2018) An improved export coefficient model to estimate non-point source phosphorus pollution risks under complex precipitation and terrain conditions. Environ Sci Pollut Res 25:20946–20955

    Article  CAS  Google Scholar 

  • Davis RL, Zhang H, Schroder JL, Wang JJ, Payton ME, Zazulak A (2005) Soil characteristics and phosphorus level effect on phosphorus loss in runoff. J Environ Qual 34:1640–1650

    Article  CAS  Google Scholar 

  • Djodjic F, Borling K, Bergdtrom L (2004) Phosphorus leaching in relation to soil type and soil phosphorus content. J Environ Qual 33:678–684

    Article  CAS  Google Scholar 

  • Gburek W, Sharpley A (1998) Hydrologic controls on phosphorus loss from upland agricultural watersheds. J Environ Qual 27:267–277

    Article  CAS  Google Scholar 

  • Heathwaite AL, Dils RM (2000) Characterising phosphorus loss in surface and subsurface hydrological pathways. Sci Total Environ 251:523–538

    Article  Google Scholar 

  • Liu ZA, Yang J, Yang Z, Zou J (2012) Effects of rainfall and fertilizer types on nitrogen and phosphorus concentrations in surface runoff from subtropical tea fields in Zhejiang, China. Nutr Cycl Agroecosyst 93:297–307

    Article  CAS  Google Scholar 

  • Mao XY, Sun KJ, Wang DH, Liao ZW (2005) Controlled-release fertilizer(CRF): a green fertilizer for controlling non-point contamination in agriculture. J Environ Sci 17:181–184

    CAS  Google Scholar 

  • Nelson NO, Shober AL (2012) Evaluation of phosphorus indices after twenty years of science and development. J Environ Qual 41:1703–1710

    Article  CAS  Google Scholar 

  • Niraula R, Kalin L, Srivastava P, Anderson CJ (2013) Identifying critical source areas of nonpoint source pollution with SWAT and GWLF. Ecol Model 268:123–133

    Article  CAS  Google Scholar 

  • Pradhanang SM, Briggs RD (2014) Effects of critical source area on sediment yield and streamflow. Water Environ J 28:222–232

    Article  Google Scholar 

  • Renwick WH, Vanni MJ, Fisher TJ, Morris EL (2018) Stream nitrogen, phosphorus, and sediment concentrations show contrasting long-term trends associated with agricultural change. J Environ Qual 47:1513–1521

    Article  CAS  Google Scholar 

  • Ryberg KR (2017) Structural equation model of Total phosphorus loads in the Red River of the North Basin, USA and Canada. J Environ Qual 46:1072–1080

    Article  CAS  Google Scholar 

  • Sharpley AN, Weld JL, Beegle DB, Kleinman PJA, Gburek WJ, Moore PA, Mullins G (2003) Development of phosphorus indices for nutrient management planning strategies in the United States. J Soil Water Conserv 58:137–152

    Google Scholar 

  • Shen Z, Hong Q, Yu H, Liu R (2008) Parameter uncertainty analysis of the non-point source pollution in the Daning River watershed of the three gorges reservoir region, China. Sci Total Environ 405:195–205

    Article  CAS  Google Scholar 

  • Singh J, Knapp HV, Arnold JG, Demissie M (2005) Hydrological modeling of the Iroquois River watershed using HSPF and SWAT. J Am Water Resour Assoc 41:343–360

    Article  Google Scholar 

  • Volf CA, Ontkean GR, Bennett DR, Chanasyk DS, Miller JJ (2007) Phosphorus losses in simulated rainfall runoff from manured soils of Alberta. J Environ Qual 36:730–741

    Article  CAS  Google Scholar 

  • Wang F, Sun Z, Zheng S, Yu J, Liang X (2018a) An integrated approach to identify critical source areas of agricultural nonpoint-source pollution at the watershed scale. J Environ Qual 47:922–929

    Article  CAS  Google Scholar 

  • Wang M, Liu J, Liu Y, Li C, Xiao W (2018b) Analysis of nitrogen and phosphorus pollution loads from agricultural non-point sources in the three gorges reservoir of Hubei Province from 1991 to 2014. J Agro-Environ Sci 37:294–301

    Google Scholar 

  • Wang X, Hao F, Zhang X (2013) Optimization of best management practices for non-point source pollution in Danjiangkou Reservoir Basin. China Environ Sci 33:1335–1343

    Google Scholar 

  • Wang Y, Bian J, Wang S, Tang J, Ding F (2016) Evaluating SWAT snowmelt parameters and simulating spring snowmelt nonpoint source pollution in the source area of the Liao River. Pol J Environ Stud 25:2177–2185

    Article  CAS  Google Scholar 

  • Wei L, Wei A, Min Y, Jinfeng M (2016a) Runoff and sediment yield modeling and soil Erosion analysis in Daning River watershed in three gorges reservoir region based on SWAT model. J Soil Water Conserv 30:49–56

    Google Scholar 

  • Wei P, Ouyang W, Gao X, Hao F, Hao Z, Liu H (2017) Modified control strategies for critical source area of nitrogen (CSAN) in a typical freeze-thaw watershed. J Hydrol 551:518–531

    Article  CAS  Google Scholar 

  • Wei P, Ouyang W, Hao F, Gao X, Yu Y (2016b) Combined impacts of precipitation and temperature on diffuse phosphorus pollution loading and critical source area identification in a freeze-thaw area. Sci Total Environ 553:607–616

    Article  CAS  Google Scholar 

  • Wu L, Long T-Y, Cooper WJ (2011) Simulation of spatial and temporal distribution on dissolved non-point source nitrogen and phosphorus load in Jialing River watershed, China. Environ Earth Sci 65:1795–1806

    Article  Google Scholar 

  • Wu L, Long T, Li C (2010) The simulation research of dissolved nitrogen and phosphorus non-point source pollution in Xiao-Jiang watershed of three gorges reservoir area. Water Sci Technol 61:1601–1616

    Article  CAS  Google Scholar 

  • Xiang X, Zhong L, Wang L (2013) Review fo non-point source pollution models. J Shanghai Jiaotong Univ (Agric Sci) 31:53–60

    Google Scholar 

  • Xu F, Dong G, Wang Q, Liu L, Yu W, Men C, Liu R (2016) Impacts of DEM uncertainties on critical source areas identification for non-point source pollution control based on SWAT model. J Hydrol 540:355–367

    Article  CAS  Google Scholar 

  • Yang Y, Zhang M, Zheng L, Cheng D, Liu M, Geng Y, Chen J (2013) Controlled-release urea for rice production and its environmental implications. J Plant Nutr 36:781–794

    Article  CAS  Google Scholar 

  • Zhuang Y, Zhang L, Du Y, Yang W, Wang L, Cai X (2016) Identification of critical source areas for nonpoint source pollution in the Danjiangkou Reservoir Basin, China. Lake Reserv Manag 32:341–352

    Article  CAS  Google Scholar 

Download references

Funding

This study was supported by the Strategic Priority Research Program of the Chinese Academy of Sciences [grant number XDA23040403], the CRSRI Open Research Program of China [grant number CKWV2017531/KY], the Hubei Provincial Natural Science Foundation of China [grant numbers 2016CFA058], the Hubei Technological Innovation Special Fund of China [grant number 2018ACA148], and the Youth Innovation Promotion Association, CAS [grant number 2018370 and 2016304].

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Authors and Affiliations

  1. Hubei Provincial Engineering Research Center of Non-point Source Pollution Control, Institute of Geodesy and Geophysics, Chinese Academy of Sciences, Wuhan, 430077, People’s Republic of China

    Shuhe Ruan, Yanhua Zhuang, Liang Zhang & Weijia Wen

  2. School of Resource and Environmental Sciences, Wuhan University, Wuhan, 430079, People’s Republic of China

    Shuhe Ruan & Song Hong

  3. University of Chinese Academy of Sciences, Beijing, 100049, People’s Republic of China

    Shuhe Ruan & Weijia Wen

  4. College of Resources and Environment, Huazhong Agricultural University, Wuhan, 430070, People’s Republic of China

    Zhen Wang

  5. Changjiang River Scientific Research, Institute of Changjiang Water Resources Commission, Wuhan, 430010, People’s Republic of China

    Xianqiang Tang

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  1. Shuhe Ruan
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  2. Yanhua Zhuang
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  3. Song Hong
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  4. Liang Zhang
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  5. Zhen Wang
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  6. Xianqiang Tang
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Correspondence to Yanhua Zhuang or Song Hong.

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Ruan, S., Zhuang, Y., Hong, S. et al. Cooperative identification for critical periods and critical source areas of nonpoint source pollution in a typical watershed in China. Environ Sci Pollut Res 27, 10472–10483 (2020). https://doi.org/10.1007/s11356-020-07630-w

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  • DOI: https://doi.org/10.1007/s11356-020-07630-w

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