Runoff simulation of modified SWAT model in karst watershed: A case study of Yangjichong sub-watershed
-
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。
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.
-
-
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 
下载: 导出CSV
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 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
下载: 导出CSV
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%
下载: 导出CSV
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
-
[1] 熊康宁, 池永宽. 中国南方喀斯特生态系统面临的问题及对策[J]. 生态经济, 2015, 31(1):23-30. doi: 10.3969/j.issn.1671-4407.2015.01.006
XIONG Kangning, CHI Yongkuan. The problems in Southern China karst ecosystem in southern of China and its countermeasures[J]. Ecological Economy, 2015, 31(1): 23-30. doi: 10.3969/j.issn.1671-4407.2015.01.006
[2] 卢卫中. 岩溶流域水文模型初步研究[J]. 水文, 1995(2):29-33.
[3] 杨杨, 赵良杰, 潘晓东, 夏日元, 曹建文. 西南岩溶山区地下水资源评价方法对比研究:以寨底地下河流域为例[J]. 中国岩溶, 2022, 41(1):111-123. doi: 10.11932/karst20220106
YANG Yang, ZHAO Liangjie, PAN Xiaodong, XIA Riyuan, CAO Jianwen. Comparative study on evaluation methods of groundwater resources in karst area of Southwest China: Taking Zhaidi underground river basin as an example[J]. Carsologica Sinica, 2022, 41(1): 111-123. doi: 10.11932/karst20220106
[4] Pang S, Wang X, Melching C S, Feger K H. Development and testing of a modified SWAT model based on slope condition and precipitation intensity[J]. Journal of Hydrology, 2020, 588: 125098. doi: 10.1016/j.jhydrol.2020.125098
[5] Arnold J G, Srinivasan R, Muttiah R S, Williams J R. Large area hydrologic modeling and assessment part I: Model development[J]. JAWRA Journal of the American Water Resources Association, 1998, 34(1): 73-89. doi: 10.1111/j.1752-1688.1998.tb05961.x
[6] 杨明德, 谭明, 梁虹. 喀斯特流域水文地貌系统[M]. 北京:地质出版社, 1998.
[7] 刘文冲, 赵良杰, 崔亚莉, 曹建文, 王莹, 李美玲. 基于SWAT-MODFLOW地表–地下水耦合模型的结构与应用研究[J]. 中国岩溶, 2023, 42(6):1131-1139.
LIU Wenchong, ZHAO Liangjie, CUI Yali, CAO Jianwen, WANG Ying, LI Meiling. Structure and application of SWAT-MODFLOW coupling model for surface-groundwater[J]. Carsologica Sinica, 2023, 42(6): 1131-1139.
[8] 张金存, 芮孝芳. 分布式水文模型构建理论与方法述评[J]. 水科学进展, 2007(2):286-292.
ZHANG Jincun, RUI Xiaofang. Discussion of theory and methods for building a distributed hydrologic model[J]. Advances in Water Science, 2007(2): 286-292.
[9] 张程鹏, 张凤娥, 耿新新, 冀俊杰, 陈永康. 岩溶地下河在SWAT中的概化方法:以毕节倒天河流域为例[J]. 中国岩溶, 2020, 39(5):665-672.
ZHANG Chengpeng, ZHANG Feng'e, GENG Xinxin, JI Junjie, CHEN Yongkang. Generalization method of karst underground river in SWAT: An example of the Daotian riverwatershed in Bijie, Guizhou[J]. Carsologica Sinica, 2020, 39(5): 665-672.
[10] 赖格英, 易姝琨, 刘维, 盛盈盈, 彭小娟, 熊家庆, 潘思怡, 吴青. 基于修正SWAT模型的岩溶地区非点源污染模拟初探:以横港河流域为例[J]. 湖泊科学, 2018, 30(6):1560-1575.
LAI Geying, YI Shukun, LIU Wei, SHENG Yingying, PENG Xiaojuan, XIONG Jiaqing, PAN Siyi. WU Qing. Non-point source pollution simulation in karst region based on modified SWAT Model: A case study in Henggang river basin[J]. Journal of Lake Sciences, 2018, 30(6): 1560-1575.
[11] 梁桂星, 覃小群, 崔亚莉, 陈爽, 黄奇波. 分布式水文模型在岩溶地区的改进与应用研究[J]. 水文地质工程地质, 2020, 47(2):60-67.
LIANG Guixing, QIN Xiaoqun, CUI Yali, CHEN Shuang, HUANG Qibo. Improvement and application of a distributed hydrological model in karst regions[J]. Hydrogeology and Engineering Geology, 2020, 47(2): 60-67.
[12] Nguyen V T, Dietrich J, Uniyal B. Modeling interbasin groundwater flow in karst areas: Model development, application, and calibration strategy[J]. Environmental Modelling & Software, 2020, 124: 104606.
[13] 马芊红, 张科利. 西南喀斯特地区土壤侵蚀研究进展与展望[J]. 地球科学进展, 2018, 33(11):1130-1141. doi: 10.11867/j.issn.1001-8166.2018.11.1130.
MA Qianhong, ZHANG Keli. Progresses and prospects of the research on soil erosion in karst area of Southwest China[J]. Advances in Earth Science, 2018, 33(11): 1130-1141. doi: 10.11867/j.issn.1001-8166.2018.11.1130.
[14] 张家俊, 龚壁卫, 胡波, 周小文, 王军. 干湿循环作用下膨胀土裂隙演化规律试验研究[J]. 岩土力学, 2011, 32(9):2729-2734. doi: 10.3969/j.issn.1000-7598.2011.09.028
ZHANG Jiajun, GONG Biwei, HU Bo, ZHOU Xiaowen, WANG Jun. Study of evolution law of fissures of expansive clay under wetting and drying cycles[J]. Rock and Soil Mechanics, 2011, 32(9): 2729-2734. doi: 10.3969/j.issn.1000-7598.2011.09.028
[15] 罗舒玉, 邓羽松, 陈洪松, 王金悦, 廖达兰. 干湿交替条件下喀斯特峰丛洼地土壤裂隙发育规律[J]. 应用生态学报, 2023, 34(2):387-395.
LUO Shuyu, DENG Yusong, CHEN Hongsong, WANG Jinyue, LlAO Dalan. Development law of soil cracks in karst peak-cluster depressions under dry and wet alternations[J]. Chinese Journal of Applied Ecology, 2023, 34(2): 387-395
[16] Novák V, Simunek J Jirka, Van Genuchten M. Infiltration of water into soil with cracks[J]. Journal of Irrigation and Drainage Engineering, 2000, 126: 41-47. doi: 10.1061/(ASCE)0733-9437(2000)126:1(41)
[17] Tuong T P, Cabangon R J, Wopereis M C S. Quantifying flow processes during land soaking of cracked rice soils[J]. Soil Science Society of America Journal, 1996, 60(3): 872-879. doi: 10.2136/sssaj1996.03615995006000030028x
[18] 王晓朋, 乔飞, 雷坤, 任广军, 王小龙. SWAT模型在我国的研究和应用进展[J]. 中国农村水利水电, 2015(5):109-113.
WANG Xiaopeng, QIAO Fei, LEI Kun, REN Guangjun, WANG Xiaolong. Research on and application of SWAT model in China[J]. China Rural Water and Hydropower, 2015(5): 109-113.
[19] 谢晖, 邱嘉丽, 董建玮, 高田田, 赖锡军. 流域水文模型在面源污染模拟与管控中的应用研究进展[J]. 生态学报, 2022, 42(15):6076-6091.
XIE Hui, QIU Jiali, DONG Jianwei, GAO Tiantian, LAI Xijun. Research of the HSPF model on nonpoint source pollution modeling and management: Progresses and perspectives[J]. Journal of Ecology, 2022, 42(15): 6076-6091.
[20] 景珂星, 毛欢, 宋进喜, 黄鹏, 吴琼, 庞国伟. 岔巴沟流域汛期径流模拟及地表产流特征分析[J]. 水土保持研究, 2023, 30(1):62-69.
JING Kexing, MAO Huan, SONG Jinxi, HUANG Peng, WU Qiong, PANG Guowei. Simulation of runoff in flood season and analysis of surface runoff characteristics in Chabagou watershed[J]. Research of Soil and Water Conservation, 2023, 30(1): 62-69.
[21] 贵州省土壤普查办公室. 贵州土种志[M]. 贵阳:贵州科技出版社, 1994.
[22] Zhang J M, Luo Y, Zhou Z, Chong L, Victor C, Zhang Y F. Effects of preferential flow induced by desiccation cracks on slope stability[J]. Engineering Geology, 2021, 288: 106164. doi: 10.1016/j.enggeo.2021.106164
[23] 张中彬, 彭新华. 土壤裂隙及其优先流研究进展[J]. 土壤学报, 2015, 52(3):477-488.
ZHANG Zhongbin, PENG Xinhua. A review of researches on soil cracks and their impacts on preferential flow[J]. Acta Pedologica Sinica, 2015, 52(3): 477-488.
[24] 陈洪松, 杨静, 傅伟, 何菲, 王克林. 桂西北喀斯特峰丛不同土地利用方式坡面产流产沙特征[J]. 农业工程学报, 2012, 28(16):121-126. doi: 10.3969/j.issn.1002-6819.2012.16.019
CHEN Hongsong, YANG Jing, FU Wei, HE Fei, WANG Kelin. Characteristics of slope runoff and sediment yield on karst hill-slope with different land-use types in northwest Guangxi[J]. Transactions of the Chinese Society of Agricultural Engineering, 2012, 28(16): 121-126. doi: 10.3969/j.issn.1002-6819.2012.16.019
[25] Salmani H, Javadi S, Eini M R, Golmohammadi G. Compilation simulation of surface water and groundwater resources using the SWAT-MODFLOW model for a karstic basin in Iran[J]. Hydrogeology Journal, 2023, 31(3): 571-587.
[26] Reza Eini M, Javadi S, Delavar M, Gassman P W, Jarihani B. Development of alternative SWAT-based models for simulating water budget components and streamflow for a karstic-influenced watershed[J]. Catena, 2020, 195: 104801. doi: 10.1016/j.catena.2020.104801
[27] Santhi C, Arnold J G, Williams J R, Hauck L M, Dugas W A. Application of a watershed model to evaluate management effects on point and nonpoint source pollution[J]. Transactions of the ASAE, 2001, 44(6): 1559.
[28] 桑灿, 李兆华, 冯学高, 张劲. 白莲河流域总磷关键源区识别与最佳管理措施(BMPs)研究[J]. 长江流域资源与环境, 2024, 33(2):374-386.
SANG Can, LI Zhaohua, FENG Xuegao, ZHANG Jin. Identification of phosphorus emission critical source areas and evaluation of best management practices in Bailian river basin based on SWAT model[J]. Resources and Environment in the Yangtze Basin, 2024, 33(2): 374-386.
[29] 袁江, 李瑞, 舒栋才, 黄凯, 盘礼东, 张琳卿. 基于SWAT模型的喀斯特流域产流特征对石漠化治理措施的响应[J]. 水土保持学报, 2021, 35(6):151-160.
YUAN Jiang, LI Rui, SHU Dongcai, HUANG Kai, PAN Lidong, ZHANG Linqing. Response of runoff characteristics of karst watershed to rocky desertification control measures based on SWAT model[J]. Journal of Soil and Water Conservation, 2021, 35(6): 151-160.
[30] Moriasi D N, Arnold J G, Van Liew M W, Bingner R D, Harmel R D, Veith T L. Model evaluation guidelines for systematic quantification of accuracy in watershed simulations[J]. Transactions of the ASABE, 2007, 50(3): 885-900.
[31] 董力轩, 常顺利, 张毓涛. SWAT模型在天山林区林冠截留过程中的改进应用[J]. 生态学报, 2022, 42(18):7630-7640.
DONG Lixuan, CHANG Shunli, ZHANG Yutao. Improvement and application of SWAT model in canopy interception in Tianshan forest area[J]. Acta Ecologica Sinica, 2022, 42(18): 7630-7640.
[32] 许昆. 降水量与地下水补给量的关系分析[J]. 地下水, 2004(4):272-274.
XU Kun. Analysis on relationship between the precipitation & groundwater replenishment[J]. Ground Water, 2004(4): 272-274.
[33] 李占斌, 朱冰冰, 李鹏. 土壤侵蚀与水土保持研究进展[J]. 土壤学报, 2008(5):802-809.
LI Zhanbin, ZHU Bingbing, LI Peng. Advancement in study on soil erosion and soil and water conservation[J]. Acta Pedologica Sinica, 2008(5): 802-809.
[34] 霍思远, 靳孟贵. 不同降水及灌溉条件下的地下水入渗补给规律[J]. 水文地质工程地质, 2015, 42(5):6-13, 21.
HUO Siyuan, JIN Menggui. Effects of precipitation and irrigation on vertical groundwater recharge[J]. Hydrogeology & Engineering Geology, 2015, 42(5): 6-13, 21.
[35] 闫钇全, 刘琦, 邓大鹏, 王涵. 表层岩溶裂隙带土壤地表流失/地下漏失室内模拟实验[J]. 中国岩溶, 2022, 41(2):240-248.
YAN Yiquan, LIU Qi, DENG Dapeng, WANG Han. Laboratory simulation study on soil surface loss and underground leakage in the epikarst fissure zone[J]. Carsologica Sinica, 2022, 41(2): 240-248.
[36] Jafari T, Kiem A S, Javadi S, Nakamura T, Nishida K. Fully integrated numerical simulation of surface water-groundwater interactions using SWAT-MODFLOW with an improved calibration tool[J]. Journal of Hydrology: Regional Studies, 2021, 35: 100822. doi: 10.1016/j.ejrh.2021.100822
[37] 李航, 郑丽萍, 甘永德, 王尚涛, 吴玉帅, 李润杰, 郭立. 膨胀性土壤干缩裂隙对入渗产流影响[J]. 中国农村水利水电, 2023(10):114-120. doi: 10.12396/znsd.222193
LI Hang, ZHENG Liping, GAN Yongde, WANG Shangtao, WU Yushuai, LI Runjie, GUO Li. Influence of swelling soil shrinkage cracks on rainfall infiltration tests[J]. China Rural Water and Hydropower, 2023(10): 114-120. doi: 10.12396/znsd.222193
-
图(7)
表(4)
计量
- 文章访问数: 1043
- PDF下载数: 266
- 施引文献: 0