Scientia Agricultura Sinica ›› 2020, Vol. 53 ›› Issue (16): 3319-3332.doi: 10.3864/j.issn.0578-1752.2020.16.010

• SOIL & FERTILIZER·WATER-SAVING IRRIGATION·AGROECOLOGY & ENVIRONMENT • Previous Articles     Next Articles

Impact of Soil Data with Different Precision on Water Quality and Flow Simulation

LI Ying1,2(),LEI QiuLiang1(),QIN LiHuan1,ZHU AXing3,4,LI XiaoHong1,ZHAI LiMei1,WANG HongYuan1,WU ShuXia1,YAN TieZhu1,LI WenChao1,HU WanLi5,REN TianZhi6,LIU HongBin1   

  1. 1Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences/Key Laboratory of Nonpoint Source Pollution Control, Ministry of Agriculture and Rural Affairs, Beijing 100081, China
    2 Institute of Geographical Sciences and Natural Resources Research, Chinese of Academy of Sciences, Beijing 100101, China
    3Nanjing Normal University/Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
    4Department of Geography, University of Wisconsin-Madison, Madison, WI 53706, USA
    5Institute of Agricultural Resources & Environment, Yunnan Academy of Agricultural Sciences, Kunming 650205, China
    6Chinese Academy of Agricultural Sciences, Beijing 100081, China
  • Received:2019-09-23 Accepted:2019-12-08 Online:2020-08-16 Published:2020-08-27
  • Contact: QiuLiang LEI E-mail:liying9391@126.com;leiqiuliang@caas.cn

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Abstract:

【Background】 Watershed model is an important tool to study non-point source pollution, and the reliability of input data is an important factor to ensure the accuracy of the model estimation. Soil data, as one of the important input data of the watershed model, has a significant influence on the runoff process. The previous studies mainly focused on the water quantity and hydrological process, while the research on water quality needs more attention. Furthermore, the disagreements over appropriate resolution of the soil maps also existed in the previous studies. 【Objective】 The purpose of this study was to enrich the prior knowledge of modeling and to provide useful suggestion for data selection in watershed simulation. 【Method】 This paper employed the widely used SWAT (soil & water assessment tool) model as an example and simulated flow, sediment, TN (total nitrogen) and TP (total phosphorus) of Fengyu river basin by three types of soil data with different scales. The scales were used for soil data as follows: 1﹕50 000 (soil-1), 1﹕500 000 (soil-2) and 1﹕1 000 000 (soil-3). SWAT-CUP software was used to adjust parameters. Based on the above methods, the effects of soil data with different scales (1﹕50 000, 1﹕500 000 and 1﹕1 000 000) on HRU (hydrologic response unit) division, model parameters and water quality and quantity were studied. 【Result】 (1) Soil data with different scales had great influence on the result of the HRU division, and the sensitivity of the number of HRU division was related to the division threshold and soil map precision. (2) The calibration of model parameters could remarkably improve the simulation performance of the model. The simulation performance associated with simulated substance, and the highest precision soil map not had the best simulation performance. (3) The attributes of soil tended to be consistent with the increase of sub-watershed area. The variation of simulation results caused by different soils gradually tends to be steady with the increase of confluence area, and the calibration process could have a great effect when confluence area was small. 【Conclusion】 In summary, the precision of soil data should be selected according to the basin size and simulated substance, and the impact of spatial scale need to be considered.

Key words: soil data, uncertainty, SWAT model, water quality, flow, hydrologic response unit

Fig. 1

Location of Fengyu river watershed in Yunnan province, digital elevation model (DEM), land use and monitoring site"

Table 1

The resolution and source of spatial data"

数据类别 Data item 数据来源 Data source 比例尺 Scale 数据用途 Purpose
数字高程图
Digital elevation model		 国家基础地理信息中心
National geomatic center of China		 1﹕50000 坡度、河网的提取及流域的划分
Extracting slope, river network and watershed division
土地利用数据
Land use data		 大理州洱源县土地局（2003年）
Land Resources Bureau		 1﹕10000 获得流域内土地利用类型及比例
Land use information
水系图
Drainage map		 国家基础地理信息中心
National geomatic center of China		 1﹕250000 获得流域内水系分布情况
Distribution of river systems
土壤图（soil-1）
Soil map		 全国第二次土壤普查土壤图
The 2nd national soil survey		 1﹕50000 获得土壤类型及分布
Soil type and distribution
土壤图（soil-2）
Soil map		 全国第二次土壤普查土壤图
The 2nd national soil survey		 1﹕500000 获得土壤类型及分布
Soil type and distribution
土壤图（soil-3）
Soil map		 中国科学院南京土壤研究所
Institute of soil science, CAS		 1﹕1000000 获得土壤类型及分布
Soil type and distribution

Fig. 2

Soil maps of three scales and samples"

Table 2

Other input datasets and their sources"

数据类别 Data item 数据来源 Data source 数据用途 Purpose
气象数据
Weather data		 气象观测站
Weather station		 降水、气温、太阳辐射、风速等数据
Precipitation, temperature and so on
土壤属性数据
Soil properties data		 土种志,野外挖掘土壤剖面及采样实测
Annals of soil classification, soil profiles and samples		 获得土壤物理及化学属性数据
Soil physical and chemical properties
农田管理措施
Management information		 农户调查、统计资料
Survey and statistical data		 作物种植模式、施肥、灌溉和耕作情况
Field management data
农村生活污染及畜禽养殖
Living pollution and livestock farming		 农户调查、统计资料
Survey and statistical data		 农村污水、固废垃圾产生量及处理方式,畜禽养殖
规模及其粪便处理方式等
Waste water, solid waste and livestock data

Table 3

Hydrologic cycle parameters and their initial ranges"

参数
Parameter		 参数说明
Parameter description		 初始阈值
Initial threshold
R_CN2.mgt 水分条件Ⅱ时的初始SCS径流曲线数 Initial SCS runoff curve number for moisture condition II -1 0.5
V_ALPHA_BF.gw 基流α因子 Baseflow alpha factor 0 1
V_RCHRG_DP.gw 深层含水层的渗透系数 Deep aquifer percolation fraction 0 1
V_GW_REVAP.gw 地下水的revap系数 Groundwater “revap” coefficient 0.02 0.2
V_GW_DELAY.gw 地下水的时间延迟 Groundwater delay time 0 500
V_GWQMN.gw 发生回归流的浅层含水层的水位阈值
Threshold depth of water in the shallow aquifer required for return flow to occur		 0 5000
V_SHALLST.gw 浅层含水层的初始水深 Initial depth of water in the shallow aquifer 0 50000
V_DEEPST.gw 深层含水层的初始水深 Initial depth of water in the deep aquifer 0 50000
V_SLSUBBSN.hru 平均坡长 Average slope length 10 150
V_OV_N.hru 坡面漫流的曼宁系数n值 Manning’s “n” value for overland flow 0.01 30
V_ESCO.hru 土壤蒸发补偿因子 Soil evaporation compensation factor 0.01 1
V_LAT_TTIME.hru 侧向流的运动时间 Lateral flow travel time 0 180
V_EPCO.hru 植物吸收补偿因子 Plant uptake compensation factor 0 1
V_HRU_SLP.hru 平均比降 Average slope steepness 0 1
V_CH_N2.rte 主河道的曼宁系数n值 Manning’s “n” value for the main channel -0.01 0.3
V_FFCB.bsn 初始土壤蓄水量 Initial soil water storage 0 1
V_SURLAG.bsn 地表径流滞后系数 Surface runoff lag coefficient 0.05 24

Table 4

Nutrients parameters and their initial ranges"

参数
Parameter		 参数说明
Parameter description		 初始阈值
Initial threshold
V_BIOMIX.mgt 生物混合效率 Biological mixing efficiency 0 1
V_FRT_SURFACE.mgt 表层10 mm土壤中的施肥量占施肥总量的分数 Fraction of fertilizer applied to top 10 mm of soil 0 1
V_FILTERW.mgt 过滤带宽度 Width of edge-of-field filter strip 0 100
V_GWSOLP.gw 向子流域河流输入的地下水中可溶性磷浓度
Concentration of soluble phosphorus in groundwater contribution to streamflow from subbasin		 0 1000
V_ERORGN.hru 泥沙运移中有机氮的富集比 Organic N enrichment ratio for loading with sediment 0 5
V_ERORGP.hru 泥沙运移中有机磷的富集比 Phosphorus enrichment ratio for loading with sediment 0 5
V_CDN.bsn 反硝化指数速率系数 Denitrification exponential rate coefficient 0 3
V_SDNCO.bsn 发生反硝化作用的土壤含水量阈值 Denitrification threshold water content 0 1
V_RSDCO.bsn 残留物的分解系数 Residue decomposition coefficient 0.02 0.1
V_PPERCO.bsn 磷的渗流系数 Phosphorus percolation coefficient in soil layer 10 17.5
V_PHOSKD.bsn 磷的土壤分配系数 Phosphorus soil partitioning coefficient 100 200
V_NPERCO.bsn 硝酸盐的渗流系数 Nitrate percolation coefficient 0 1
V_BC1_BSN.bsn NH3生物氧化的速率常数 Rate constant for biological oxidation of NH3 0.1 1
V_BC2_BSN.bsn 从NO2到NO3的生物氧化速率常数 Rate constant for biological oxidation NO2 to NO3 0.1 1
V_BC3_BSN.bsn 从有机氮到氨基的水解速率常数 Rate constant for hydrolysis of organic nitrogen to ammonia 0.02 0.4
V_BC4_BSN.bsn 从有机磷到可溶性磷的腐化速率常数 Rate constant for decay of organic phosphorus to dissolved phosphorus 0.01 0.7

Table 5

Sediment parameters and their initial ranges"

参数
Parameter		 参数说明
Parameter description		 初始阈值
Initial threshold
R_USLE_C.plant.dat USLE方程中的C因子的最小值 Minimum value of USLE C factor -10 10
V_USLE_P.mgt USLE方程中的P因子 USLE equation support practice factor 0 1
V_LAT_SED.hru 侧向流与地下径流中的泥沙含量 Sediment concentration in lateral and groundwater flow 0 5000
V_ADJ_PKR.bsn 子流域（支流）泥沙演算的最大流速调节因子 Peak rate adjustment factor for sediment routing in the subbasin 0.5 2

Table 6

Channel processes parameters and their initial ranges"

参数
Parameter		 参数说明
Parameter description		 初始阈值
Initial threshold
V_SPCON.bsn 最大泥沙量的线性参数 Linear parameter for calculating the maximum amount of sediment 0.0001 0.01
V_SPEXP.bsn 最大泥沙量的指数参数 Exponent parameter for calculating sediment restrained in channel sediment routing 1 2
V_CH_K2.rte 主河道冲积物的有效渗透系数 Effective hydraulic conductivity in main channel alluvium -0.01 500
V_CH_COV1.rte 河道侵蚀因子 Channel erodibility factor -0.05 0.6
V_CH_COV2.rte 河道覆盖因子 Channel cover factor -0.001 1
V_ALPHA_BNK.rte 河岸调蓄的基流α因子 Baseflow alpha factor for bank storage 0 1

Fig. 3

Effects of threshold settings on HRU numbers based on the difference soil datasets"

Table 7

Model parameters from different soil data"

土壤数据
Soil data		 SCS径流曲线数CN2
 最大根系深度
SOL_ZMX
(mm)		 土层埋深
SOL_Z
(mm)		 湿容重
SOL_BD
(g·cm-3)		 有效含水量SOL_AWC
(mm·mm-1)		 饱和渗透系数SOL_K
(mm·h-1)		 土壤侵蚀K因子USLE_K
soil-1 72.93 722.73 211.24 1.19 0.16 21.61 0.27
soil-2 77.43 879.93 160.66 1.15 0.36 42.56 0.29
soil-3 66.23 526.07 201.79 1.27 0.18 21.18 0.24

Table 8

Performance of the models before and after calibration"

土壤数据
Soil data		 项目
Item		 校准后 After calibration 校准前 Before calibration
R2 NS R2 NS
soil-1 流量Flow 0.81 0.68 0.84 -5.29
泥沙 Sediment 0.44 0.43 0.49 0.31
总氮Total nitrogen 0.58 0.57 0.50 -605.73
总磷Total phosphorus 0.53 0.53 0.30 -5007.4
soil-2 流量Flow 0.86 0.79 0.77 -6.86
泥沙 Sediment 0.46 0.41 0.50 0.1
总氮Total nitrogen 0.71 0.59 0.53 -710.97
总磷Total phosphorus 0.75 0.75 0.31 -1539.57
soil-3 流量Flow 0.75 0.64 0.86 -5.27
泥沙 Sediment 0.43 0.38 0.45 0.28
总氮Total nitrogen 0.85 0.69 0.49 -1097.61
总磷Total phosphorus 0.63 0.62 0.29 -5717.73

Fig. 4

Simulation performance for the three types of soil data after model calibration"

Fig. 5

Subbasin map"

Fig. 6

Differences between soil parameters from different soil data across varying subbasin areas"

Fig. 7

Differences in simulation results based on different soil data across varying subbasin areas"

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