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Frontiers of Environmental Science & Engineering

ISSN 2095-2201

ISSN 2095-221X(Online)

CN 10-1013/X

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Front. Environ. Sci. Eng.    2014, Vol. 8 Issue (6) : 922-928    https://doi.org/10.1007/s11783-014-0720-7
RESEARCH ARTICLE
Modeling agricultural non-point source pollution in a high-precipitation coastal area of China
Zhiyi LI,Pengfei DU(),Haiwei HUANG,Yong Ge,Xu LI
State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
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Abstract

Non-point source (NPS) pollution simulation in the high-precipitation coastal areas of China is difficult because varying annual typhoon incidence leads to highly contrasting rainfall patterns in dry years and wet years. An IMPULSE (Integrated Model of Non-point Sources Pollution Processes) based NPS model of the Changtan Reservoir watershed, which is a typical high-precipitation coastal area in China, was established based on the analysis of point and NPS pollution data, a digital elevation model, and data on land-use, soil, meteorology, economy, and agricultural management practice. Pre-processed pre-rainfall soil moisture levels were introduced during the simulation to model the effects of typhoons on hydrology. Rainfall events were simulated sequentially through the year and the model was calibrated and verified using hydrological and water quality data. Accuracy of the simulated rainfall runoff and water quality in the Changtan watershed was found to be acceptable. The study showed that the NPS modeling system could be applied to the simulation and prediction of NPS loadings in the Changtan Reservoir watershed.
Keywords Changtan Reservoir watershed      non-point source pollution modeling      pre-rainfall soil moisture      model calibration     
Corresponding Author(s): Pengfei DU   
Online First Date: 12 June 2014    Issue Date: 17 November 2014
 Cite this article:   
Zhiyi LI,Pengfei DU,Haiwei HUANG, et al. Modeling agricultural non-point source pollution in a high-precipitation coastal area of China[J]. Front. Environ. Sci. Eng., 2014, 8(6): 922-928.
 URL:  
https://academic.hep.com.cn/fese/EN/10.1007/s11783-014-0720-7
https://academic.hep.com.cn/fese/EN/Y2014/V8/I6/922
Fig.1  Study area and model domain
location fertilizer per unit area/(kg·ha-1·year-1) total fertilizer/(t·year-1)
phosphate nitrogen phosphate nitrogen
Ningxi 146 198 283 553
Beiyang 143 199 246 396
Youtou 296 444 625 1.18 × 102
Shangzheng 149 218 216 447
Fushan 44.7 57 140 250
Shangyang 195 235 366 544
Pingtian 107 171 84.9 193
Tab.1  Fertilizer application of the townships
location livestock manure/104t livestock urine/104t TN/t TP/t COD/t
Ningxi 0.03 0.05 5.07 0.78 78.1
Beiyang 0.02 0.04 3.94 0.5 52.4
Youtou 0.04 0.01 4.02 1.46 72.9
Shangzheng 0.07 0.04 7.4 2.07 123
Fushan 0.26 0.52 53.4 7.43 735
Shangyang 0.01 0.03 3.15 0.4 41.9
Tab.2  Pollutant emissions from livestock breeding
year measured data simulation results
rainfall/mm runoff/mm runoff coefficient simulated runoff/mm RE
1998 1917.6 1351.0 0.70 1343.4 0.56%
1999 2179.5 1369.3 0.63 1580.2 15%
2000 1961.4 1399.1 0.71 1398.1 0.07%
2001 1967.6 1259.8 0.64 1345.3 6.8%
2002 1801.1 1236.9 0.69 1259.3 1.8%
2003 1294.4 574.3 0.44 585.1 1.9%
2004 1956.5 1300.4 0.66 1242.8 4.4%
2005 2336.1 2078.7 0.89 1907.1 8.3%
2006 1994.8 1414.1 0.71 1336.0 5.5%
2007 2341.6 1665.5 0.71 1730.3 3. 9%
2008 1650.9 1069.0 0.65 1074.5 0.51%
2009 1936.1 1222.2 0.63 1308.2 7.0%
Tab.3  Results of model validation
types of years seasons model settings
wet year wet season wet period
dry season wet period
normal year wet season wet period
dry season normal period
dry year wet season normal period
dry season dry period
Tab.4  Year types and model settings
Fig.2  Hydrological model simulation results
rainfall /mm COD TN TP
event load/kg EMC/ (mg·L-1) event load/kg EMC/ (mg·L-1) event load/kg EMC/ (mg·L-1)
1st rainfall event in Huangyan 35 measured data 21.3 4.44 2.25 0.469 0.115 0.024
simulation results 15.7 3.26 2.12 0.442 0.104 0.022
RE 26% 5.8% 9.8%
1st rainfall event in Rouji 30 measured data 16.1 6.19 1.61 0.619 0.073 0.028
simulation results 17.9 6.88 1.64 0.631 0.074 0.028
RE 11% 1.9% 1.1%
Tab.5  Results of model calibration
rainfall /mm COD TN TP
event load/kg EMC/ (mg·L-1) event load/kg EMC/ (mg·L-1) event load/kg EMC/ (mg·L-1)
2nd rainfall event in Huangyan 11 measured data 5.33 4.39 0.93 0.776 0.050 0.042
simulation results 6.11 5.10 1.45 1.21 0.079 0.065
RE 15% 56% 58%
2nd rainfall event in Rouji 15 measured data 10.5 9.56 0.81 0.734 0.045 0.041
simulation results 15.5 14.1 1.48 1.34 0.079 0.072
RE 47% 83% 76%
Tab.6  Results of model validation
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