Estimating Groundwater Runoff Modulus Method Based on Remote Sensing in Mountainous Areas of Southeast Tibet
-
摘要: 如何科学评估野外场地条件下的地下水径流模数对于满足工程水文地质需求具有重要应用价值.结合现场调查、遥感解译和气象水文观测等技术手段,通过建立线性回归模型,开展了帕隆藏布流域场地条件下的地下水径流模数估算研究.结果表明:研究区具有典型的季节性积雪融雪规律.冬季积雪在夏季大量融化产流,作为地下水的一个额外补给源.去除融雪产流对径流模数影响后,研究区岩浆岩裂隙型、变质岩裂隙型、碎屑岩裂隙型、碳酸盐岩-碎屑岩裂隙溶隙型含水介质地下水径流模数分别在1.081~2.792 L/s·km2、1.833~3.225 L/s·km2、1.128~2.889 L/s·km2、3.455~3.879 L/s·km2之间.估算结果显示本文所建立的地下水径流估算模型可作为藏东南地区及类似条件区域地下水径流模数估算新方法,为雅鲁藏布江下游梯级开发等大型基础工程提供重要的水文地质参数支撑.Abstract: How to scientifically evaluate the groundwater runoff modulus under field conditions has important application value to meet the needs of engineering hydrogeology. In this paper, the study of groundwater runoff modulus under site conditions in the Parlung Zangbo watershed is carried out by establishing a linear regression model combined with technical means such as field survey, remote sensing interpretation and meteorological and hydrological observations. The results show that the study area has a typical seasonal snowmelt law. The snow accumulate in winter melt into runoff in summer, which serves as an additional source of groundwater recharge. After removing the influence of snowmelt runoff on the runoff modulus, the groundwater runoff modulus of magmatic aquifer, metamorphic aquifer, clastic aquifer and carbonate-clastic aquifer in the study area are respectively between 1.081-2.792 L/s·km2, 1.833-3.225 L/s·km2, 1.128-2.889 L/s·km2, 3.455-3.879 L/s·km2. The estimation results show that the groundwater runoff estimation model established in this paper can be used as a new method for estimating groundwater runoff modulus in southeastern Tibet and similar conditions, providing important hydrogeological parameter support for large-scale infrastructure projects in this area included the cascade development of the lower reaches of the Yarlung Zangbo River.
-
Key words:
- remote sense /
- linear regression /
- groundwater runoff modulus /
- southeast Tibet /
- hydrogeology
-
图 5 研究区小流域各地层面积占比$ {A}_{nm} $及径流模数$ {\overline{M}}_{gn} $
面积占比为小流域内各地层面积占小流域面积的比例,径流模数为小流域内平均地下水径流模数. 图例各地层代号为所有小流域涉及地层,其中E1ηγ、K1ηγ、J3ηδ、D1ηγ为岩浆岩;AnNqa、AnNqb、AnOI、AnP、w为变质岩;C2P1l、C1n、P3x、K1d、J2-3l、J2m为碎屑岩;P2l、D2-3s为碳酸盐岩-碎屑岩互层
Fig. 5. Stratums area proportion in subordinate watershed($ {A}_{nm} $) and groundwater runoff modulus($ {\overline{M}}_{gn} $)
表 1 来古冰川融雪产流模数
Table 1. Snowmelt runoff modulus in Laigu glacier
积雪面积(km2) 流量(L/s) 融雪产流模数(L/s·km2) 258.212 4 132.180 16.003 表 2 A、B、C分区平均地下水径流模数统计
Table 2. Average groundwater runoff modulus in A、B and C zone
流域分区 平均地下水径流模数$ {\overline{M}}_{g} $(L/s·km2) 均方差σ2 A 2.297 0.642 B 2.696 0.195 C 3.099 0.165 表 3 不同区域含水岩组径流模数回归结果
Table 3. Linear regression result of aquifer groundwater runoff modulus in different zone
地层 含水介质类型 $ {M}_{gm\mathrm{A}} $ $ {M}_{gm\mathrm{B}} $ $ {M}_{gm\mathrm{C}} $ E1ηγ 岩浆岩裂隙型 1.081 \ 2.561 K1ηγ 1.919 1.298 2.286 J3ηδ 1.536 2.459 \ D1ηγ \ 2.792 \ AnNqa 变质岩裂隙型 2.812 2.816 3.021 AnNqb \ 3.039 3.225 AnOI \ 1.835 2.127 AnP \ \ 1.833 w \ \ 2.764 C2P1l 碎屑岩裂隙型 1.646 1.997 1.816 C1n 2.872 2.889 2.492 P3x 2.810 \ \ K1d 1.128 \ \ J2-3l 1.792 \ \ J2m 2.392 \ \ P2l 碳酸盐岩-碎屑岩裂隙溶隙型 3.455 \ \ D2-3s 3.879 3.781 \ 残差均值$ \stackrel{-}{\varepsilon } $ 0.233 0.071 0.097 $ {R}^{2} $ 0.891 0.704 0.834 注:\表示分区内测流流域未涉及该含水岩组. -
[1] Burg, J.P., Davy, P., Nievergelt, P., et al., 1997. Exhumation During Crustal Folding in the Namche Barwa Syntaxis. Terra Nova, (2): 53-56. https://doi.org/10.1111/j.1365-3121.1997.tb00001.x [2] Burs, D., Bruckmann, J., Rüde, T.R., 2016. Developing a Structural and Conceptual Model of a Tectonically Limited Karst Aquifer: a Hydrogeological Study of the Hastenrather Graben near Aachen, Germany. Environ. Earth Sci., 1253: 1-21. https://doi.org/10.1007/s12665-016-6039-x [3] Dankers, R., De, J. SM., 2004. Monitoring Snow-Cover Dynamicsin Northern Fennoscandia with Spot Vegetation Images. International Journal of Remote Sensing, 25: 2933-2949. https://doi.org/10.1080/01431160310001618374 [4] Montgomery, D.C., 2012. Introduction to Linear Regression Analysis, Fifth Edition. John Wiley & Sons, New York. [5] Ding, L., Zhong, D.L., Yin, A., et al., 2001. Cenozoic Structural and Metamorphic Evolution of the Eastern Himalayan Syntaxis (Namche Barwa). Earth and Planetary Science Letters, 192: 423-438. https://doi.org/10.1016/S0012-821X(1)00463-0 [6] Gul, C., Kang, S.C., Ghauri, B., et al., 2017. Using Landsat Images to Monitor Changes in the Snow-Covered Area of Selected Glaciers in Northern Pakistan. Journal of Mountain Science, 14(10): 2013-2027. https://doi.org/10.1007/s11629-016-4097-x [7] Hall, D.K., Riggs, G.A., Salomonson, V.V., et al., 1995. Development of Methods for Mapping Global Snow Cover Using Moderate Resolution Imaging Spectroradiometer Data. Remote Sensing of Environment, 54 (2): 127-140. https://doi.org/10.1016/0034-4257(95)00137-P [8] Jodar, J., Cabrera, J.A., Martos-Rosillo, S., et al., 2017. Groundwater Discharge in High-Mountain Watersheds: A Valuable Resource for Downstream Semi-Arid Zones. The Case of the Berchules River in Sierra Nevada (Southern Spain). Sci. Total Environ. , 593: 760-772. https://doi.org/10.1016/j.scitotenv.2017.03.190 [9] Leng, J.F., Gao, X., Zhu, J.P., 2016. Application of Multiple Linear Regression Statistical Forecast Model. Statistics & Decision, (7): 82-85 (in Chinese with English abstract). [10] Li, X.S., Wang, L.S., 2016. Parameter Estimation of Multiple Linear Regression Model with Linear Constraints. Statistical Research, 33(11): 85-92(in Chinese with English abstract). [11] Liang, H., 1998. A Relative Analysis Between The Lithological Features and The Characteristics of Flood Discharge and Low Flow in Karst District: Case Study of The Rivers, Guizhou Province. Carsologica Sinica, 17(1): 67-73(in Chinese with English abstract). [12] Liu, J.T., Song, H.Q., Zhang X.N., et al., 2014. The Development and Discussion of Theoretical Research on Xin'anjiang Model. Journal of China Hydrology, 34(1): 1-6(in Chinese with English abstract). [13] Liu, X.L., Yang, S.T., Zhao, C.S., et al., 2015. Research and Application of SRM Model Driven by Multi-Source Remote Sensing in Data-Deficient Areas. Remote Sensing Technology and Application, 30(4): 645-652(in Chinese with English abstract). [14] Mario, R., Nadine, S., Markus, S., et al., 2013. Missing (In-Situ) Snow Cover Data Hampers Climate Change and Runoff Studies in The Greater Himalayas. Science of the Total Environment, 468: S60-S70. https://doi.org/10.1016/j.scitotenv.2013.09.056 [15] Meng, X.Y., Ji, X.N., Liu, Z.H., et al., 2014. Research on Improvement and Application of Snow Melting Module of SWAT Model. Journal of Natural Resources, 29(3): 528-539(in Chinese with English abstract). [16] Mogaji, K.A., Lim, H.S., Abdullah, K., et al., 2017. Modeling of Groundwater Recharge Using A Multiple Linear Regression (MLR) Recharge Model Developed From Geophysical Parameters: A Case of Groundwater Resources Management. Environmental Earth Sciences, 73(3): 1217-1230. https://doi.org/10.1007/s12665-014-3476-2 [17] Mo, X.X., Zhao, Z.D., Zhu, D.C., et al., 2009. Lithosphere of India-Asia Collision Zone in Southern Tibet: Petrological-Geochemical Constraints. Earth Science, 34(1): 17-27(in Chinese with English abstract). [18] Pan, G.T., Ren, F., Yin, F.G., et al., 2020. Key Zones of Oceanic Plate Geology and Sichuan-Tibet Railway Project. Earth Science, 45(7): 2293-2304(in Chinese with English abstract). [19] Tallaksen, L.M., 1995. A Review of Baseflow Recession Analysis. Journal of Hydrology, 165: 349-370. https://doi.org/10.1016/0022-1694(94)02540-R [20] Wang, X.N., Tang, F.T., Shao, C.R., 2018. The Current Movement Characters of Main Faults Surrounding the Namcha Barwa Syntaxis. Technology for Earthquake Disaster Prevention, 13(2): 267-275(in Chinese with English abstract). [21] Wang, Y., Qin, F., Li, D.T., 2005. Groundwater Runoff Modulus, Rock Permeability and Prediction of Water Quantities of Tunnel in West Route of South-to-North Water Transfer Project. Chinese Journal of Rock Mechanics and Engineering, 24(20): 3673-3678(in Chinese with English abstract). [22] Xu, L.L., Liu, J.L., Jin, C.J., et al., 2011. Baseflow Separation Methods in Hydrological Process Research: A Review. Chinese Journal of Applied Ecology (11): 3073-3080(in Chinese with English abstract). [23] Xu, Z.Q., Ji, S.C., Cai, Z.H., et al., 2012. Kinematics And Dynamics of The Namche Barwa Syntaxis, Eastern Himalaya: Constraints From Deformation, Fabrics And Geochronology. Gondwana Research, 21(1): 19-36. https://doi.org/10.1016/j.gr.2011.06.010 [24] Yang, Y.D., 1986. Regression Equation Applying in Groundwater Analysis. Hydrogeology & Engineering Geology, 1: 38-41(in Chinese). [25] Yang, Z.N., Hu, M.G., 1990. River Runoff Feature at East Tibet Plateau. Journal of Glaciology and Geocryology, 12(3): 219-226(in Chinese). [26] Zeng, Q.G., Wang, B.D., Xiluo, L.J., et al., 2020. Suture Zones in Tibetan and Tethys Evolution. Earth Science, 45(8): 2735-2763(in Chinese with English abstract). [27] Zhang, P.Q., Gao, M.X., Lei, Y.L., et al., 2009. Quantitative Geomorphic Features and Causes of the Great Bend Area of the Yarlung Zangbo River in Tibet. Earth Science, 34(4): 595-603(in Chinese with English abstract). [28] Zhao, L., Zhang, L., Cheng, L., et al., 2015. Groundwater Storage Trends in The Loess Plateau of China Estimated From Streamflow Records. Journal of Hydrology, 530: 281-290. https://doi.org/10.1016/j.jhydrol.2015.09.063 [29] 冷建飞, 高旭, 朱嘉平, 2016. 多元线性回归统计预测模型的应用. 统计与决策(7): 82-85. https://www.cnki.com.cn/Article/CJFDTOTAL-TJJC201607023.htm [30] 李小胜, 王申令, 2016. 带线性约束的多元线性回归模型参数估计. 统计研究, 33(11): 85-92. https://www.cnki.com.cn/Article/CJFDTOTAL-TJYJ201611012.htm [31] 刘金涛, 宋慧卿, 张行南, 等, 2014. 新安江模型理论研究的进展与探讨. 水文, 34(1): 1-6. https://www.cnki.com.cn/Article/CJFDTOTAL-SWZZ201401001.htm [32] 刘晓林, 杨胜天, 赵长森, 等, 2015. 多源遥感驱动的SRM模型在缺资料地区的研究及应用. 遥感技术与应用, 30(4): 645-652. https://www.cnki.com.cn/Article/CJFDTOTAL-YGJS201504006.htm [33] 孟现勇, 吉晓楠, 刘志辉, 等, 2014. SWAT模型融雪模块的改进与应用研究. 自然资源学报, 29(3): 528-539. https://www.cnki.com.cn/Article/CJFDTOTAL-ZRZX201403016.htm [34] 莫宣学, 赵志丹, 朱弟成, 等, 2009. 西藏南部印度-亚洲碰撞带岩石圈: 岩石学-地球化学约束. 地球科学, 34(1): 17-27. https://www.cnki.com.cn/Article/CJFDTOTAL-DQKX200901004.htm [35] 潘桂棠, 任飞, 尹福光, 等, 2020. 洋板块地质与川藏铁路工程地质关键区带. 地球科学, 45(7): 2293-2304. https://www.cnki.com.cn/Article/CJFDTOTAL-DQKX202007007.htm [36] 王晓楠, 唐方头, 邵翠茹, 2018. 南迦巴瓦构造结周边地区主要断裂现今运动特征. 震灾防御技术, 13(2): 267-275. https://www.cnki.com.cn/Article/CJFDTOTAL-ZZFY201802024.htm [37] 王媛, 秦峰, 李冬田, 2005. 南水北调西线工程区地下径流模数、岩体透水性及隧洞涌水量预测. 岩石力学与工程学报, 24(20): 3673-3678. https://www.cnki.com.cn/Article/CJFDTOTAL-YSLX200520010.htm [38] 徐磊磊, 刘敬林, 金昌杰, 等, 2011. 水文过程的基流分割方法研究进展. 应用生态学报, (11): 3073-3080. https://www.cnki.com.cn/Article/CJFDTOTAL-YYSB201111041.htm [39] 杨远东, 1986. 回归方程在地下水分析中的应用. 水文地质工程地质, 1: 38-41. https://www.cnki.com.cn/Article/CJFDTOTAL-SWDG198601012.htm [40] 杨针娘, 胡鸣高, 1990. 青藏高原东部河川径流特征. 冰川冻土, 12(3): 219-226. https://www.cnki.com.cn/Article/CJFDTOTAL-BCDT199003005.htm [41] 曾庆高, 王保弟, 西洛郎杰, 等, 2020. 西藏的缝合带与特提斯演化. 地球科学, 45(8): 2735-2763. https://www.cnki.com.cn/Article/CJFDTOTAL-DQKX202008001.htm [42] 张沛全, 高明星, 雷永良, 等, 2009. 西藏雅鲁藏布江大拐弯地区量化地貌特征及其成因. 地球科学, 34(4): 595-603. https://www.cnki.com.cn/Article/CJFDTOTAL-DQKX200904005.htm