修正SWAT模型在喀斯特小流域的径流模拟研究

杨丽; 杨广斌; 李亦秋; 李蔓

doi:10.11932/karst2024y011

修正SWAT模型在喀斯特小流域的径流模拟研究——以羊鸡冲小流域为例

doi: 10.11932/karst2024y011

杨丽^{1, 2,},
杨广斌^{1, 2, ,},
李亦秋¹,
李蔓^{1, 2}

1.
贵州师范大学地理与环境科学学院, 贵州贵阳 550025
2.
贵州省山地资源与环境遥感应用重点实验室, 贵州贵阳 550025

基金项目: 贵州省科技重大计划项目（黔科合重大专项 [2022]001）；贵州省科技支撑项目（黔科合支撑[2023]一般176）；贵州省基础研究（自然科学）项目(黔科合基础-ZK[2024]一般445)

详细信息

作者简介:
杨丽（2000－），女，硕士研究生，研究方向：3S技术与水土保持。E-mail：1125832457@qq.com

通讯作者:
杨广斌（1973－），男，教授，研究方向：地理信息系统与遥感。E-mail：ygbyln@163.com。

中图分类号: P333.1
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- 被引次数: 0
出版历程
- 收稿日期: 2023-11-10
- 录用日期: 2024-01-29
- 修回日期: 2024-01-26
- 网络出版日期: 2024-04-28
- 刊出日期: 2024-04-30

Runoff simulation of modified SWAT model in karst watershed: A case study of Yangjichong sub-watershed

YANG Li^{1, 2
,},
YANG Guangbin^{1, 2
, ,},
LI Yiqiu¹,
LI Man^{1, 2}

1.
School of Geography and Environmental Science, Guizhou Normal University, Guiyang, Guizhou 550025, China
2.
Key Laboratory of Remote Sensing Application for Mountain Resources and Environment in Guizhou Province, Guiyang, Guangxi 550025, China

摘要

摘要: 在贵州喀斯特地区，地表径流通过土壤裂隙、岩溶管道等途径流失，限制了地表径流的形成。文章以龙里羊鸡冲小流域为研究区，基于2013—2019年的实测数据，修正SWAT（Soil and Water Assessment Tool）模型的裂隙流模块，修改了裂缝入渗的表示方法，对修正前后的日径流模拟进行对比分析。结果表明：率定期内纳什系数由0.32提升到0.60，决定系数由提高0.37提升到0.58。在验证期内，纳什系数由0.52提高到0.55，决定系数由0.56提高到0.60，修正后的模型与原模型相比具有更好的适用性。修正后模型的径流时间序列与实测数据更吻合，能合理估算研究区的入渗水量，为喀斯特小流域的水资源管理提供参考依据。
- SWAT模型修正 /
- 喀斯特小流域 /
- 土壤裂隙模块 /
- 径流模拟
Abstract: In the karst area of Guizhou, many factors can limit the formation of surface runoff, such as developed karst structures, strong rainfall leakage, rapidly changing hydrological processes, low water storage capacities, and lost surface runoff through soil fissures, karst pipes and other pathways. Therefore, for the protection of the ecological environment and the control of soil erosion in this area, it is of great significance for us to investigate the variation of surface runoff in karst areas and the law of flow production. The model of Soil and Water Assessment Tool (SWAT) is a distributed hydrological model developed by the Agricultural Research Center, United States Department of Agriculture (USDA-ARS), and it is widely used in the simulation and prediction of watershed runoff, sediment, water quality and so on in different environments. However, due to the dissolution and erosion in karst areas, the development of water systems and hydrological dynamics show great differences from non-karst areas. In general, scholars' modification of the SWAT model mainly focuses on the modeling of karst features, but the SWAT model has seldom been used in the study of the effect of soil fissures on runoff under wet conditions. Guizhou is located in the subtropical monsoon climate zone, with concentrated precipitation, alternating wet and dry conditions. The soil in Guizhou is characterized by strong expansion and contraction. Consequently, the fissure flow is developed from soil fissures during rainfall. Even after rewetting, the soil fissures will not close, leading to significant water infiltration, which in turn will affect surface-produced flows. However, in the original SWAT model, volume of fissures (volcr) under wet conditions will close by default, and hence water cannot infiltrate. In order to make the conditions of SWAT model closer to the real situation in the karst watershed, the calculation of the fissure volume in the SWAT model was modified in this study to balance the wet and dry soil conditions to prevent fissure closure and to ensure that soil fissures can be formed in wet soils as well. The modification process is as follows: the crack flow module was firstly activated; then the maximum crack volume of the soil layer was calculated; finally, the crack volume on the simulation day was modified in crackvol.f. Taking Yangjichong sub-watershed in Longli county as the study area, this study modified the fissure flow module of the SWAT model and the representation of fissure infiltration, based on the measured data from 2013 to 2019. Subsequently, a comparative analysis of daily runoff simulation before and after the modification was carried out so as to make the results of surface runoff simulation closer to the actual situation of the humid karst region. The study results show as follows: (1) The Nash coefficient increased from 0.32 to 0.60 and the coefficient of determination from 0.37 to 0.58 in the period of determining rate. In the validation period, the Nash coefficient increased from 0.52 to 0.55 and the coefficient of determination from 0.56 to 0.60. These data indicate that the runoff time series of the modified model is more consistent with the measured data, which can show a better applicability of the modified model than the original one. (2) There are some differences in the parameter sensitivity of the model before and after the modification, and the parameters SOL_BD, SOL_CRK, and CANMX are important to affect the soil fissure volume. (3) The modified model improved the water infiltration capacity of the soil. The soil moisture content was positively correlated with infiltration, and the surface runoff was negatively correlated with infiltration. The average daily infiltration increased from 0.23 mm to 0.84 mm, an increase of 3.65 times; the average daily surface runoff decreased from 3.98 mm to 3.14 mm, with a significant increase in infiltration and a decrease in surface runoff. At the same time, the soil water content increased from 139.53 mm to 158.30 mm, an increase of 18.77 mm. (4) The modified model showed a significant increase in infiltration and obvious seasonal differences, which was basically similar to the variation of rainfall, that is, the larger the rainfall is, the more infiltration recharge becomes, and the more significant infiltration is. The results of the study provide reference for water resource management in the karst sub-watershed.
- modification of SWAT model /
- karst sub-watershed /
- soil fissure module /
- runoff simulation

HTML

图 1 研究区地理位置示意图

Figure 1. Geographical location of the study area

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图 2 SWAT模型修正流程

Figure 2. Modification process of SWAT model

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图 3 SWAT模型修正前后径流量模拟对比

Figure 3. Simulation comparison of runoff capacity before and after the modification of SWAT model

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图 4 2017年径流量模拟对比图

Figure 4. Comparison of runoff simulation in 2017

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图 5 SWAT模型修正前后径流模拟散点图

Figure 5. Scatter plot of runoff simulation before and after the modification of SWAT model

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图 6 模型修正前后的月均入渗量与地表径流的变化

Figure 6. Changes of average monthly infiltration and surface runoff before and after the modification of SWAT model

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图 7 SWAT模型修正前后月入渗量随降雨量的变化

Figure 7. Changes of monthly infiltration with rainfall before and after the modification of SWAT model

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表 1 数据详情及来源

Table 1. Data details and sources

数据类型	数据描述	数据来源
数字高程模型	DEM数据分辨率10 m×10 m	由1∶10 000地形图采集生成
土壤类型和属性数据	10 m×10 m	查阅自《贵州土种志》^[21]、中国土壤属性库
土地利用数据	10 m×10 m	高分辨率影像解译与实地调查验证获取
气象数据	2013—2019年逐日气象数据（降雨量、最高和最低温度、相对湿度、风速和日照时数）	国家气象科学数据中心（http://data.cma.cn）
水文数据（龙里羊鸡冲站）	2013—2019年逐日流量数据	龙里羊鸡冲监测站提供

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表 2 参数敏感性分析结果对比

Table 2. Comparison of parameter sensitivity

参数名称	参数含义	取值范围	修正SWAT			原始SWAT
参数名称	参数含义	取值范围	t-Stat	P-Value	排名	t-Stat	P-Value	排名
SOL_BD(..).sol	土壤表层湿容重	[−0.5，0.5]	9.14	0.00	1	0.89	0.38	7
SOL_CRK.sol	土壤剖面潜在或最大裂隙体积	[0，1]	2.61	0.01	2	1.24	0.23	3
CANMX.hru	最大根系深度	[0，100]	2.07	0.04	3	−0.90	0.38	6
CN2.mgt	SCS径流曲线数	[−0.5，0.5]	−1.44	0.15	4	0.30	0.77	16
GW_DELAY.gw	地下水滞后时间	[1，500]	1.40	0.16	5	−0.76	0.45	10
LAT_TTIME.hru	侧向流的运动时间	[0，180]	1.33	0.19	6	0.21	0.84	17
SLSUBBSN.hru	平均坡长	[10，150]	−0.98	0.33	7	0.01	0.99	21
HRU_SLP.hru	平均坡度	[0，0.6]	0.8	0.42	8	−4.02	0.00	1
CH_N2.rte	主河道曼宁系数值	[0，0.3]	0.05	0.96	9	1.37	0.18	2

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表 3 模型日径流模拟评价指标

Table 3. Evaluation index of daily runoff simulation of the model

	率定期			验证期
	NSE	R²	PBIAS	NSE	R²	PBIAS
原始 SWAT	0.32	0.37	22.5%	0.52	0.56	19.9%
修正 SWAT	0.60	0.58	21.0%	0.55	0.60	21.0%

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表 4 HRU在模型修正前后的入渗量和地表径流

Table 4. Infiltration and surface runoff of HRU before and after the modification of SWAT model

模型	入渗量/mm	土壤含水量/mm	地表径流/mm
SWAT	0.23	139.53	3.98
修正 SWAT	0.84	158.30	3.14

下载: 导出CSV

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