Estimation of Groundwater Recharge Based on the Corrected Remote Sensing Data: A Case Study of the Taigemiao Mining Area in Ordos Basin

doi:10.19657/j.geoscience.1000-8527.2023.046

Abstract

Abstract:

The groundwater recharge acts as a decisive factor affecting the groundwater resources in the Yellow River Basin. Accurate calculation of the net groundwater recharge is of great importance for the rational development and utilization of regional groundwater resources and for regional hydrological cycle. At the point scale, equipment such as lysimeter can be used to directly monitor groundwater recharge, however, it is difficult to use this method to obtain the groundwater recharge at the regional scale. This calls for a simple method to quantify groundwater recharge at the regional scale. In this study, we proposed a new method to calibrate remote sensing data and estimate the multi-year groundwater recharge at the regional scale. We applied this proposed new method to the Taigemiao mining area in Xinjie, Ordos Basin, located in the middle reaches of the Yellow River. Based on the screened multi-source precipitation data and the corrected evaporation remote sensing data, we calculated the accurate mean annual net groundwater recharge in the mining area. The Hydras-1D numerical simulation based on measured data further verifies the effectiveness of the proposed evaluation method. The result indicates that the precipitation data from TPDC is more accurate in term of reflecting the spatial distribution of precipitation in the study area. The MOD16 remote sensing data underestimated the actual evapotranspiration in the mining area, which is 1.41 times of the MOD16 data. The mean annual net groundwater recharge ranges from -65.70 mm to 73.93 mm and the net groundwater recharge of more than 80% of the area ranges from -30 mm to 30 mm. The groundwater recharge estimated by the new method is consistent with the numerically simulated results based on the measured data, indicating that the method can be used in the prediction in areas where there is lack of surface runoff or detailed observation data of surface runoff.

Key words: groundwater recharge, MOD16, remote sensing, hydrus-1D, Taigemiao mining area

CLC Number:

WANG Xudong, HAN Pengfei, ZHANG Suo, ZHU Xiaoqian, XING Zhenguo, WANG Lujun, WAN Li. Estimation of Groundwater Recharge Based on the Corrected Remote Sensing Data: A Case Study of the Taigemiao Mining Area in Ordos Basin[J]. Geoscience, 2024, 38(02): 409-418.

Figures/Tables 9

Fig.1 Map showing the location (a) and topographic characteristics (b) of the study area

Table 1 Meteorological dataset information in the Taigemiao mining area

变量	数据名称	分辨率	网址链接
降水量	中国地面气象站逐日降水量观测资料	逐日	https://data/cma.cn
	中国1 km分辨率逐月降水量数据集	逐月; 1 km	http://data.tpdc.ac.cn
	中国气象要素年度空间插值数据集	逐年; 1 km	https://www.resdc.cn/DOI/DOI.aspx?DOIID=96
蒸散量	MYD16A3GFv061	逐年; 500 m	https://doi.org/10.5067/MODIS/MYD16A3 GF.061

Table 2 Summarized data required for the correction of mean annual MOD16 evapotranspiration

分项	数值	分项	数值
总面积A_b (km²)	3671.27	径流深Q_m(mm)	0
陆地面积A_l(km²)	3632.62	水面蒸发量E₀(mm)	1200.00
水体面积A_w(km²)	38.65	实际蒸散量ET_a(mm)	338.19
MOD16蒸散量ET_m(mm)	241.94	校正系数γ_m(-)	1.41
降水量P_m(mm)	338.19	-	-

Fig.2 Interannual change characteristics in precipitation of the six meteorological stations of Otog Qi (a), Uxin Qi (b), Dongsheng (c), Yulin (d), Shenmu (e) and Hequ (f)

Fig.3 Spatial distribution (a)(b), and statistical histogram (c)(d) of the mean annual precipitation from TPDC and RESDC data sets in the Taigemiao mining area

Fig.4 Spatial distribution (a) and statistical histogram (b) of mean annual evapotranspiration from the MOD16 datasets in the Taigemiao mining area

Fig.5 Map of watershed division in the study area

Fig.6 Spatial distribution (a) and statistical histogram (b) of mean annual net groundwater recharge in the Taigemiao mining area

Fig.7 Comparison between measured and simulated soil water content of T1 and T2 profiles in the Taigemiao mining area

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