Abstract
Water eutrophication caused by the extensive expansion of slope farming has caused the high attention of the Chinese government. We choose Lake Tianmu basin as the study area because it can represent vast majority of basins plagued by water eutrophication derived from slope tillage in southern China. The water ecosystem in the reservoir Daxi and Shahe within the basin has been seriously threatened by multiple pollution sources related to many intricate human activities especially agricultural production. For the first time, we identified the critical source areas (CSAs) within the basin based on nutrient load and nutrient load intensity (NLI), and on this basis, we further excavated the main causes of pollution and proposed pertinent remediation measures. The results based on the calibrated Soil and Water Assessment Tool model indicated that the TN load of each reservoir remarkably exceeded their respective water environmental capacity from 2014 to 2018. Accordingly, six main tributaries with great nutrient contributions and their corresponding sub-basins were then identified. Overall, tea and rice plantations appear to be the major nutrient contributors to reservoir Daxi. And the main nutrient sources for reservoir Shahe are tea plantations, orchards, farmland, forestland, and point sources. Regarding the CSAs identified only by nutrient load, agronomic measures such as reducing fertilizer amount, biochar application, straw incorporation, and plastic mulch coverage can be employed to improve soil water retention and curb soil erosion. Regarding the CSAs identified by nutrient load intensity (NLI), the CSAs with narrow areas should be turned directly into forestland. For the CSAs with large areas, engineering measures such as constructing ecological riparian zone, filtration, and sedimentation tank can be employed to prevent pollutants from entering downstream reaches. Overall, the present results can provide the decision-making support for the safe and efficient management of watershed land use in southern China.
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References
Arnold JG, Moriasi DN, Gassman PW, Abbaspour KC, Jha MK (2012) SWAT: model use, calibration, and validation. Trans ASABE 55:1549–1559. https://doi.org/10.13031/2013.42256
Brown TC, Froemke P (2012) Nationwide assessment of nonpoint source threats to water quality. BioScience 62:136–146. https://doi.org/10.1525/bio.2012.62.2.7
Cao L, Liang Y, Wang Y, Lu H (2015) Runoff and soil loss from Pinus massoniana forest in southern China after simulated rainfall. Catena 129:1–8. https://doi.org/10.1016/j.catena.2015.02.009
Chen L, Dai Y, Zhi X, Xie H, Shen Z (2018) Quantifying nonpoint source emissions and their water quality responses in a complex catchment: a case study of a typical urban-rural mixed catchment. J Hydrol 559:110–121. https://doi.org/10.1016/j.jhydrol.2018.02.034
Chen L, Chen S, Li S, Shen Z (2019) Temporal and spatial scaling effects of parameter sensitivity in relation to non-point source pollution simulation. J Hydrol 571:36–49. https://doi.org/10.1016/j.jhydrol.2019.01.045
El-Naggar A et al (2019) Biochar application to low fertility soils: a review of current status, and future prospects. Geoderma 337:536–554. https://doi.org/10.1016/j.geoderma.2018.09.034
Gujre N, Soni A, Rangan L, Tsang DCW, Mitra S (2020) Sustainable improvement of soil health utilizing biochar and arbuscular mycorrhizal fungi: a review. Environ Pollut. https://doi.org/10.1016/j.envpol.2020.115549
Gurung DP, Githinji LJM, Ankumah RO (2013) Assessing the nitrogen and phosphorus loading in the Alabama (USA) River basin using PLOAD model. Air, Soil and Water Research 6:ASWR.S10548. https://doi.org/10.4137/aswr.S10548
Han L-x, HOU F, SUN J (2011) Method for calculating non-point source pollution distribution in plain river. Water Sci Eng 4:83–91. https://doi.org/10.3882/j.issn.1674-2370.2011.01.008
He R, Yang X, Gassman PW, Wang G, Yu C (2019) Spatiotemporal characterization of nutrient pollution source compositions in the Xiaohong River Basin, China. Ecol Indic 107:105676–105688. https://doi.org/10.1016/j.ecolind.2019.105676
He J, Wu X, Zhang Y, Zheng B, Meng D, Zhou H, Lu L, Deng W, Shao Z, Qin Y (2020a) Management of water quality targets based on river-lake water quality response relationships for lake basins - a case study of Dianchi Lake. Environ Res 186:109479. https://doi.org/10.1016/j.envres.2020.109479
He Y, Wang P, Sheng H, Wang D, Huang M, Cao C (2020b) Sustainability of riparian zones for non-point source pollution control in Chongming Island: status, challenges, and perspectives. J Clean Prod:244. https://doi.org/10.1016/j.jclepro.2019.118804
Jiang M, Chen H, Chen Q, Wu H (2014) Study of landscape patterns of variation and optimization based on non-point source pollution control in an estuary. Mar Pollut Bull 87:88–97. https://doi.org/10.1016/j.marpolbul.2014.08.008
Kirchner WB, Dillon PJ (1975) An empirical method of estimating the retention of phosphorus in lakes. Water Resour Res 11:182–183
Lee C-S, Wen C-G (1996) River assimilative capacity analysis via fuzzy linear programming. Fuzzy Sets Syst 79:191–201
Li YJ, Chen ZL, Lou HJ, Deng HG, Wang C (2014) Denitrification controls in urban riparian soils: implications for reducing urban nonpoint source nitrogen pollution. Environ Sci Pollut Res 21:10174–10185. https://doi.org/10.1007/s11356-014-2944-2
Liu R, Zhang P, Wang X, Chen Y, Shen Z (2013) Assessment of effects of best management practices on agricultural non-point source pollution in Xiangxi River watershed. Agric Water Manag 117:9–18. https://doi.org/10.1016/j.agwat.2012.10.018
Liu R, Xu F, Zhang P, Yu W, Men C (2016) Identifying non-point source critical source areas based on multi-factors at a basin scale with SWAT. J Hydrol 533:379–388. https://doi.org/10.1016/j.jhydrol.2015.12.024
Lowe M-A, McGrath G, Leopold M (2021) The impact of soil water repellency and slope upon runoff and erosion. Soil Tillage Res:205. https://doi.org/10.1016/j.still.2020.104756
Luo C, Li Z, Liu H, Li H, Wan R, Pan J, Chen X (2020) Differences in the responses of flow and nutrient load to isolated and coupled future climate and land use changes. J Environ Manag 256:109918. https://doi.org/10.1016/j.jenvman.2019.109918
Ma Y, Hao S, Zhao H, Fang J, Zhao J, Li X (2018) Pollutant transport analysis and source apportionment of the entire non-point source pollution process in separate sewer systems. Chemosphere 211:557–565. https://doi.org/10.1016/j.chemosphere.2018.07.184
Makarewicz CJ (2009) Nonpoint source reduction to the nearshore zone via watershed management practices: Nutrient fluxes, fate, transport and biotic responses — background and objectives. J Great Lakes Res 35:3–9. https://doi.org/10.1016/j.jglr.2008.08.002
McKergow LA, Matheson FE, Quinn JM (2016) Riparian management: a restoration tool for New Zealand streams. Ecol Manag Restor 17:218–227. https://doi.org/10.1111/emr.12232
Niraula R, Kalin L, Wang R, Srivastava P (2011) Determining nutrient and sediment critical source areas with SWAT: effect of lumped calibration. American Society of Agricultural and Biological Engineers 55:137–147. https://doi.org/10.13031/2013.41262
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. https://doi.org/10.1016/j.ecolmodel.2013.08.007
Nobre RLG, Caliman A, Cabral CR, Araújo FC, Guérin J, Dantas FCC, Quesado LB, Venticinque EM, Guariento RD, Amado AM, Kelly P, Vanni MJ, Carneiro LS (2020) Precipitation, landscape properties and land use interactively affect water quality of tropical freshwaters. Sci Total Environ 716:137044. https://doi.org/10.1016/j.scitotenv.2020.137044
Ongley ED, Xiaolan Z, Tao Y (2010) Current status of agricultural and rural non-point source pollution assessment in China. Environ Pollut 158:1159–1168. https://doi.org/10.1016/j.envpol.2009.10.047
Parajuli PB, Nelson NO, Frees LD, Mankin KR (2009) Comparison of AnnAGNPS and SWAT model simulation results in USDA-CEAP agricultural watersheds in south-central Kansas. Hydrol Process 23:748–763. https://doi.org/10.1002/hyp.7174
Shan N, Ruan X-H, Xu J, Pan Z-R (2014) Estimating the optimal width of buffer strip for nonpoint source pollution control in the Three Gorges Reservoir Area. China Ecological Modelling 276:51–63. https://doi.org/10.1016/j.ecolmodel.2013.12.019
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 Science of the Total Environment 405:195–205. https://doi.org/10.1016/j.scitotenv.2008.06.009
Shen Z, Liao Q, Hong Q, Gong Y (2012) An overview of research on agricultural non-point source pollution modelling in China. Sep Purif Technol 84:104–111. https://doi.org/10.1016/j.seppur.2011.01.018
Shen Z, Qiu J, Hong Q, Chen L (2014) Simulation of spatial and temporal distributions of non-point source pollution load in the Three Gorges Reservoir Region. Sci Total Environ 493:138–146. https://doi.org/10.1016/j.scitotenv.2014.05.109
Shrestha A, Kelty CA, Sivaganesan M, Shanks OC, Dorevitch S (2020) Fecal pollution source characterization at non-point source impacted beaches under dry and wet weather conditions. Water Res 182:116014. https://doi.org/10.1016/j.watres.2020.116014
Siedt M, Schaffer A, Smith KEC, Nabel M, Ross-Nickoll M, van Dongen JT (2020) Comparing straw, compost, and biochar regarding their suitability as agricultural soil amendments to affect soil structure, nutrient leaching, microbial communities, and the fate of pesticides. Sci Total Environ 751:141607. https://doi.org/10.1016/j.scitotenv.2020.141607
Singh AP, Ghosh SK, Sharma P (2006) Water quality management of a stretch of river Yamuna: an interactive fuzzy multi-objective approach. Water Resour Manag 21:515–532. https://doi.org/10.1007/s11269-006-9028-0
Srinivas R, Singh AP (2017) Impact assessment of industrial wastewater discharge in a river basin using interval-valued fuzzy group decision-making and spatial approach Environment. Dev Sustain 20:2373–2397. https://doi.org/10.1007/s10668-017-9994-9
Srinivas R, Singh AP, Dhadse K, Garg C (2020) An evidence based integrated watershed modelling system to assess the impact of non-point source pollution in the riverine ecosystem. J Clean Prod 246:118963. https://doi.org/10.1016/j.jclepro.2019.118963
Sun S, Zhang J, Cai C, Cai Z, Li X, Wang R (2020) Coupling of non-point source pollution and soil characteristics covered by Phyllostachys edulis stands in hilly water source area. J Environ Manag 268:110657. https://doi.org/10.1016/j.jenvman.2020.110657
Thompson J, Cassidy R, Doody DG, Flynn R (2013) Predicting critical source areas of sediment in headwater catchments Agriculture. Ecosyst Environ 179:41–52. https://doi.org/10.1016/j.agee.2013.07.010
Tibebe D, Kassa Y, Melaku A, Lakew S (2019) Investigation of spatio-temporal variations of selected water quality parameters and trophic status of Lake Tana for sustainable management. Ethiopia Microchemical J 148:374–384. https://doi.org/10.1016/j.microc.2019.04.085
Tu T et al (2020) Coupling hydroclimate-hydraulic-sedimentation models to estimate flood inundation and sediment transport during extreme flood events under a changing climate. Sci Total Environ 740:140117. https://doi.org/10.1016/j.scitotenv.2020.140117
Uniyal B, Jha MK, Verma AK, Anebagilu PK (2020) Identification of critical areas and evaluation of best management practices using SWAT for sustainable watershed management. Sci Total Environ 744:140737. https://doi.org/10.1016/j.scitotenv.2020.140737
Vollenweider RA (1976) Advances in defining critical loading levels for phosphorus in lake eutrophication. Mem 1st Ital Idrobiol 33:53–83
Wang X et al (2013) Simulating sediment loading into the major reservoirs in Trinity River Basin. J Soil Water Conserv 68:372–383. https://doi.org/10.2489/jswc.68.5.372
Wang Q, Liu R, Men C, Guo L (2018) Application of genetic algorithm to land use optimization for non-point source pollution control based on CLUE-S and SWAT. J Hydrol 560:86–96. https://doi.org/10.1016/j.jhydrol.2018.03.022
Wang J, Zhang Z, Johnson B (2019) Low flows and downstream decline in phytoplankton contribute to impaired water quality in the lower. Minnesota River Water Res 161:262–273. https://doi.org/10.1016/j.watres.2019.05.090
Wang W, Chen L, Shen Z (2020) Dynamic export coefficient model for evaluating the effects of environmental changes on non-point source pollution. Sci Total Environ 747:141164. https://doi.org/10.1016/j.scitotenv.2020.141164
Winchell MF, Folle S, Meals D, Moore J, Srinivasan R, Howe EA (2015) Using SWAT for sub-field identification of phosphorus critical source areas in a saturation excess runoff region. Hydrol Sci J 60:1–19. https://doi.org/10.1080/02626667.2014.980262
Wu J, Lu J (2019) Landscape patterns regulate non-point source nutrient pollution in an agricultural watershed. Sci Total Environ 669:377–388. https://doi.org/10.1016/j.scitotenv.2019.03.014
Wu Y, Huang W, Zhou F, Fu J, Wang S, Cui X, Wang Q, Bo Y, Yang S, Wang N, Gu X, Chen J, Zhu J (2020) Raindrop-induced ejection at soil-water interface contributes substantially to nutrient runoff losses from rice paddies. Agric Ecosyst Environ:304. https://doi.org/10.1016/j.agee.2020.107135
Xueman Y, Wenxi L, Yongkai A, Weihong D (2020) Assessment of parameter uncertainty for non-point source pollution mechanism modeling: a Bayesian-based approach. Environ Pollut:263. https://doi.org/10.1016/j.envpol.2020.114570
Yan P, Shen C, Fan L, Li X, Zhang L, Zhang L, Han W (2018) Tea planting affects soil acidification and nitrogen and phosphorus distribution in soil Agriculture. Ecosyst Environ 254:20–25. https://doi.org/10.1016/j.agee.2017.11.015
Yi X, Lin C, Ong EJL, Wang M, Zhou Z (2019) Occurrence and distribution of trace levels of antibiotics in surface waters and soils driven by non-point source pollution and anthropogenic pressure. Chemosphere 216:213–223. https://doi.org/10.1016/j.chemosphere.2018.10.087
Yu Y, Tao H, Yao H, Zhao C (2018) Assessment of the effect of plastic mulching on soil respiration in the arid agricultural region of China under future climate scenarios. Agric For Meteorol 256-257:1–9. https://doi.org/10.1016/j.agrformet.2018.02.025
Zhang QL, Chen YX, Jilani G, Shamsi IH, Yu QG (2010) Model AVSWAT apropos of simulating non-point source pollution in Taihu lake basin. J Hazard Mater 174:824–830. https://doi.org/10.1016/j.jhazmat.2009.09.127
Zhang Y, Yin Y, Feng L, Zhu G, Shi Z, Liu X, Zhang Y (2011) Characterizing chromophoric dissolved organic matter in Lake Tianmuhu and its catchment basin using excitation-emission matrix fluorescence and parallel factor analysis. Water Res 45:5110–5122. https://doi.org/10.1016/j.watres.2011.07.014
Zhang T, Yang Y, Ni J, Xie D (2019a) Adoption behavior of cleaner production techniques to control agricultural non-point source pollution: a case study in the Three Gorges Reservoir Area. J Clean Prod 223:897–906. https://doi.org/10.1016/j.jclepro.2019.03.194
Zhang X et al (2019b) Plastic film mulching stimulates soil wet-dry alternation and stomatal behavior to improve maize yield and resource use efficiency in a semi-arid region. Field Crop Res 233:101–113. https://doi.org/10.1016/j.fcr.2019.01.002
Zhang T, Yang Y, Ni J, Xie D (2020a) Construction of an integrated technology system for control agricultural non-point source pollution in the Three Gorges Reservoir Areas Agriculture. Ecosyst Environ:295. https://doi.org/10.1016/j.agee.2020.106919
Zhang W, Li H, Pueppke SG, Diao Y, Nie X, Geng J, Chen D, Pang J (2020b) Nutrient loss is sensitive to land cover changes and slope gradients of agricultural hillsides: evidence from four contrasting pond systems in a hilly catchment. Agric Water Manag:237. https://doi.org/10.1016/j.agwat.2020.106165
Zhong S, Chen F, Xie D, Shao J, Yong Y, Zhang S, Zhang Q, Wei C, Yang Q, Ni J (2020) A three-dimensional and multi-source integrated technology system for controlling rural non-point source pollution in the Three Gorges Reservoir Area, China. J Clean Prod:272. https://doi.org/10.1016/j.jclepro.2020.122579
Zhu W, Chen WM, Zhang WS (2019) Investigation and evaluation of pollution sources in Lake Tianmu Basin. Report of the People’s Government of Tianmuhu Town, Liyang City
Zou L, Liu Y, Wang Y, Hu X (2020) Assessment and analysis of agricultural non-point source pollution loads in China: 1978-2017. J Environ Manag 263:110400. https://doi.org/10.1016/j.jenvman.2020.11
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The datasets used and analyzed during the current study are available from the corresponding author on reasonable request.
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The National Natural Science Foundation of China (No. 41671388) and the Natural Science Foundation of Jiangsu Province (No. BK20190711) provided the financial supports for the study.
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All authors contributed to the study conception and design. Material preparation and data collection were performed by ZQL, SL, DL, and JZ. The data analysis and first draft of the manuscript were written by DC. All authors read and approved the final manuscript.
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Highlights
• A typical slope tillage watershed plagued by water eutrophication in southern China was studied.
• TN loads of the reservoirs remarkably exceed their water environmental capacity.
• Critical source areas of TN/TP are identified and assessed using the SWAT model.
• Nutrient contributions to water from different land use are quantitatively assessed.
• Specific restoration strategies tailored to water quality target are proposed.
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Chang, D., Lai, Z., Li, S. et al. Critical source areas’ identification for non-point source pollution related to nitrogen and phosphorus in an agricultural watershed based on SWAT model. Environ Sci Pollut Res 28, 47162–47181 (2021). https://doi.org/10.1007/s11356-021-13973-9
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DOI: https://doi.org/10.1007/s11356-021-13973-9