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GRACE satellite monitoring and driving factors analysis of groundwater storage under high-intensity coal mining conditions: a case study of Ordos, northern Shaanxi and Shanxi, China

Observation par le satellite GRACE et analyse des facteurs déterminants du stockage des eaux souterraines dans les conditions d’une exploitation intensive du charbon: une étude de cas à Ordos, Nord-Ouest du Shaanxi et du Shanxi, Chine

Monitoreo del satélite GRACE y análisis de factores impulsores del almacenamiento de agua subterránea bajo condiciones de la minería del carbón: un estudio de caso de Ordos, Shaanxi del Norte y Shanxi, China

高强度煤炭开采条件下地下水储量GRACE卫星监测及驱动因素分析——以中国鄂尔多斯、陕北及山西地区为例

Monitoramento pelo satélite GRACE e análise de fatores determinantes do armazenamento de águas subterrâneas sob condições de mineração de carvão de alta intensidade: um estudo de caso em Ordos, Shaanxi Setentrional e Shanxi, China

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Abstract

Coal mining in northwestern China is an important industry. For the traditional monitoring of water resources in coal-rich regions, a single monitoring well or remote-sensing image is often used to obtain the groundwater level or water body area. The process is restricted by the spatial distribution of monitoring wells and the quality of remote sensing images. The regions of Ordos, Northern Shaanxi (including Yan’an and Yulin cities), herein collectively referred to as OYY, and Shanxi (SX) were studied. Here, groundwater storage anomalies (GWSA) were derived using the gravity recovery and climate experiment (GRACE) satellite data and WaterGAP global hydrology model, and the change trend of groundwater storage (GWS) was explored. Using time series analysis and grey slope relational analysis, the potential driving factors of regional GWSA were derived and considered independent variables. In combination with GWSA, the quantitative relationship between the variables was established by partial least squares regression. Results showed that: (1) the decreasing rate of GWS in OYY and SX reached –0.65 and –1.16 cm/year, respectively, from 2003 to 2014; (2) the main driving factors leading to the reduction of GWS included coal-mining water consumption for OYY and water consumption by coal mining and agricultural irrigation for SX, and the weights of water consumption by coal mining and agricultural irrigation for SX were both 50%. Therefore, GRACE satellite data show good application in groundwater monitoring of coal-mining concentrated areas, providing an important basis for the formulation of water resource management measures.

Résumé

L’exploitation de charbon dans le Nord Ouest de la Chine est une industrie importante. Pour la surveillance habituelle des ressources en eau dans les régions riches en charbon, un simple puits de contrôle ou une image satellitaire est couramment utilisé pour connaître le niveau des eaux souterraines ou la superficie des étendues d’eau. Ce procédé est contraint par la disitribution spatiale des puits de contrôle et la qualité des images satellitaires. Les régions d’Ordos, dans le Nord Ouest du Shaanxi (où se situent les villes de Yan’an et de Yulin), désignées globalement ci-après par OYY et le Shanxi (SX) ont été étudiés. Ici, les anomalies du stockage des eaux souterraines (ASES) ont été calculées à l’aide des données du satellite Gravity Recovery and Climate Experiment (GRACE) et le modèle d’hydrologie à grande échelle Water-GAP, et la tendance du changement affectant le stockage des eaux souterraines (SES) a été examinée. En utilisant les analyses de séries temporelles et l’analyse relationnelle de la pente du domaine gris en fonction de la connaissance de l’information (aucune information: noir; information exacte: blanc), les facteurs déterminants potentiels des ASES régionales ont été calculés et considérés comme des variables indépendantes. En la combinant avec les ASES, la relation quantitative entre variables a été établie par la régression partielle des moindres carrés. Les résultats ont montré que: (1) le taux de décroissance du SES dans OYY et au SX a atteint –0.65 et −1.16 cm/an respectivement, entre 2003 et 2014; (2) les principaux facteurs déterminants qui conduisent à une réduction du SES comprenaient la consommation d’eau par l’exploitation du charbon pour OYY et la consommation d’eau par l’exploitation du charbon et l’irrigation agricole au SX, et les poids de la consommation de l’eau par l’exploitation du charbon et l’irrigation agricole au SX totalisant 50%. Ainsi, les données du satellite GRACE constituent une bonne appplication pour l’exploration de la variation du SES dans les zones d’exploitation intensive du charbon, fournissant une base importante pour la formulation des mesures de gestion de la ressource en eau.

Resumen

La minería de carbón en el noroeste de China es una industria importante. Para el monitoreo tradicional de los recursos hídricos en las regiones ricas en carbón, a menudo se utiliza un solo pozo de monitoreo o una imagen de teledetección para obtener el nivel de agua subterránea o el área de la masa de agua. El proceso está restringido por la distribución espacial de los pozos de monitoreo y la calidad de las imágenes de teledetección. Se estudiaron las regiones de Ordos, Shaanxi del Norte (incluyendo las ciudades de Yan’an y Yulin), aquí referidas colectivamente como OYY, y Shanxi (SX). En este caso, las anomalías en el almacenamiento de aguas subterráneas (GWSA) se obtuvieron utilizando los datos de los satélites Gravity Recovery and Climate Experiment (GRACE) y el modelo de hidrología global WaterGAP, y se exploró la tendencia al cambio en el almacenamiento de aguas subterráneas (GWS). Utilizando el análisis de series de tiempo y el análisis relacional, se derivaron los factores impulsores potenciales de la GWSA regional y se consideraron variables independientes. En combinación con GWSA, la relación cuantitativa entre las variables se estableció por regresión parcial de los mínimos cuadrados. Los resultados mostraron que: (1) la tasa decreciente de GWS en OYY y SX alcanzó −0.65 y −1.16 cm/año, respectivamente, entre 2003 y 2014; (2) los principales factores que llevaron a la reducción del GWS incluyeron el consumo de agua para la minería del carbón para OYY y el consumo de agua para la minería del carbón y el riego agrícola para SX, y las ponderaciones de este último caso que fueron del 50%. Por lo tanto, los datos del satélite GRACE muestran una buena aplicación en la exploración de los cambios del GWS en las áreas concentradas de la minería del carbón, proporcionando una base importante para la formulación de medidas de gestión de los recursos hídricos.

摘要

煤炭开采是中国西北地区重要的工业。采煤富集区传统的水资源监测常采用单个监测井点或遥感影像来获取地下水位或水体面积,其易受监测井点的空间分布和遥感影像质量的制约。本文以鄂尔多斯与陕北地区(包括延安和榆林地区)(简称为OYY)、山西地区(简称为SX)作为研究区,采用重力恢复与气候试验卫星(Gravity Recovery and Climate Experiment, GRACE)与全球概念分布式水文模型(WaterGAP global hydrology model, WGHM)提取地下水储量异常(Groundwater Storage Anomalies, GWSA) ,并探究其变化趋势。根据时间序列分析及灰色斜率关联度分析方法,获得影响区域GWSA的潜在驱动因素,作为自变量。结合GWSA,应用偏最小二乘回归方法,可建立变量之间的定量关系。结果显示:(1)2003~2014年, OYY地区与SX地区地下水储量分别以–0.65 cm/year、–1.16 cm/year的速度减少。(2)OYY地区地下水储量减少的主要驱动因素为采煤耗水量, SX地区地下水储量减少的主要驱动因素为采煤耗水量与农业灌溉耗水量,且SX地区两个主要驱动因素的权重分别占比50%。因此, GRACE重力卫星在采煤集中区地下水监测具有较好的应用前景,且为水资源管理机制的形成提供重要基础。

Resumo

A mineração de carvão é uma indústria de grande importância no noroeste da China. Costuma-se usar um único poço de monitoramento ou uma única imagem de sensoriamento remoto para obter o nível das águas subterrâneas ou a área do corpo d’água no monitoramento de recursos hídricos em regiões ricas em carvão. Esse processo é restrito pela distribuição espacial dos poços de monitoramento e pela qualidade das imagens de sensoriamento remoto. As regiões de Ordos, Shaanxi Setentrional (incluindo as cidades de Yan’an e Yulin), aqui referidas coletivamente como OYY e Shanxi (SX) foram estudadas. Aqui, as anomalias de armazenamento de águas subterrâneas (AAAS) foram obtidas usando dados do satélite de recuperação da gravidade e experimento climático (GRACE) e o modelo de hidrologia global WaterGAP, e a tendência de mudança do armazenamento de águas subterrâneas (AAS) foi explorada. Usando a análise de séries temporais e o método de análise relacional grey, os potenciais fatores determinantes da AAAS regional foram obtidos e considerados como variáveis independentes. Em combinação com a AAAS, a relação quantitativa entre as variáveis foi estabelecida por regressão parcial via mínimos quadrados. Os resultados mostraram que: (1) a taxa decrescente de AAS em OYY e SX atingiu −0.65 e −1.16 cm/ano, respectivamente, de 2003 a 2014; (2) os principais fatores que levaram à redução de AAS incluíram mineração de carvão, o consumo de água para o OYY e o consumo de água pela mineração de carvão e irrigação agrícola para o SX, enquanto os pesos do consumo de água pela mineração de carvão e irrigação agrícola para o SX foram ambos 50%. Portanto, os dados de satélite GRACE mostram boa aplicabilidade na avaliação de mudanças no AAS em áreas concentradas de mineração de carvão, fornecendo uma base importante para a formulação de medidas para gerenciamento de recursos hídricos.

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References

  • Cao SX, Chen J, Chen L, Gao WS (2007) Impact of grain for green project to nature and Society in North Shaanxi of China. Sci Agric Sin 40(5):972–979

    Google Scholar 

  • Chen X, Jiang J, Li H (2018) Drought and flood monitoring of the Liao River basin in Northeast China using extended GRACE data. Remote Sens 10(8):1168

    Article  Google Scholar 

  • Deng JL (1990) Tutorial on grey system theory. Huazhong University of Science and Technology Press, Wuhan, China

  • Döll P, Fiedler K (2008) Global-scale modeling of groundwater recharge. Hydrol Earth Syst Sci 12(3):863–885

    Article  Google Scholar 

  • Döll P, Kaspar F, Lehner B (2003) A global hydrological model for deriving water availability indicators: model tuning and validation. J Hydrol 270(1–2):105–134

    Article  Google Scholar 

  • Döll P, Müller Schmied H, Schuh C, Portmann FT, Eicker A (2014) Global-scale assessment of groundwater depletion and related groundwater abstractions: combining hydrological modeling with information from well observations and GRACE satellites. Water Resour Res 50(7):5698–5720

    Article  Google Scholar 

  • Du Z, Ge L, Ng AH-M, Li X (2017) Satellite-based estimates of ground subsidence in Ordos Basin, China. J Appl Geod 11(1):9–20

    Google Scholar 

  • Ergon R (2014) Principal component regression (PCR) and partial least squares regression (PLSR)// Mathematical and Statistical Methods in Food Science and Technology. Wiley, Chichester, UK

  • Fan XS, Gao JX, Tian MR, Zhang W (2015) Resources depletion & ecological damage cost accounting and analysis related to the coal mining in Inner Mongolia. J Arid Land Resour Environ 29(9):39–44

    Google Scholar 

  • Feng W, Zhong M, Lemoine JM, Biancale R, Hsu HT, Xia J (2013) Evaluation of groundwater depletion in North China using the gravity recovery and climate experiment (GRACE) data and ground-based measurements. Water Resour Res 49(4):2110–2118

    Article  Google Scholar 

  • Feng W, Wang CQ, Mu DP, Zhong M, Zhong YL, Xu HZ (2017) Groundwater storage variations in the North China plain from GRACE with spatial constraints. Chin J Geophys 60(5):1630–1642

    Google Scholar 

  • Güntner A, Stuck J, Werth S, Doell P, Verzano K, Merz B (2007) A global analysis of temporal and spatial variations in continental water storage. Water Resour Res 43(5):687–696

    Article  Google Scholar 

  • He WQ, Yan WJ, He GQ, Yang ZB, Tan Y, Li G, Lin L (2016) Study on the wavelength selection based on VIP analysis in noninvasive measurement of blood components. Spectrosc Spect Anal 36(4):1080–1084

    Google Scholar 

  • Huang ZY, Pat JFY, Pan Y, Jiao JJ, Gong HL, Li XJ, Andreas G, Zhu YQ, Zhang C, Zheng LQ (2019) Detection of large-scale groundwater storage variability over the karstic regions in Southwest China. J Hydrol 569:409–422

    Article  Google Scholar 

  • Jia LL, Wang HS, Xiang LW (2017) Measuring terrestrial water storage change using GRACE, GPS and absolute gravity data in Scandinavia. Acta Geodaet Cartograph Sin 46(2):170–178

    Google Scholar 

  • Li B, Chen Y, Xun S (2012) Why does the temperature rise faster in the arid region of northwest China. J Geophys Res Atmos 117(D16)

  • Li N, Yan CZ, Xie JL (2015) Remote sensing monitoring recent rapid increase of coal mining activity of an important energy base in northern China: a case study of Mu Us Sandy land. Resour Conserv Recycl 94:129–135

    Article  Google Scholar 

  • Liu H (2017) Research on effect evaluation of resource-based city and its influencing factors in Shanxi Province. East China Normal University, Shanghai, Putuo, China

  • Liu SF, Xie NM, Forrest J (2011) Novel models of grey relational analysis based on visual angle of similarity and nearness. Grey Syst Theory Appl 1(1):8–18

    Article  Google Scholar 

  • Liu Y (2013) Vegetation and soil moisture monitoring by remote sensing in Shendong mining area. China University of Mining and Technology, Beijing

  • National Meteorological Information Centre (2003–2014) China Meteorological Data Network. http://data.cma.cn/. Accessed December 2019

  • Ning SZ (2013) Coal resources and tectonic division of Ordos Basin. Adv Mater Res 734-737:316–319

    Article  Google Scholar 

  • Olabode OF (2019) Potential groundwater recharge sites mapping in a typical basement terrain: a GIS methodology approach. J Geovisual Spatial Anal 3(1):5

    Article  Google Scholar 

  • Qiao X, Li G, Li M, Zhou J, Du J, Du C, Sun Z (2011) Influence of coal mining on regional karst groundwater system: a case study in West Mountain area of Taiyuan City, northern China. Environ Earth Sci 64(6):1525–1535

    Article  Google Scholar 

  • Save H, Bettadpur S, Tapley BD (2016) High-resolution CSR GRACE RL05 mascons. J Geophys Res Solid Earth 121:7547–7569

    Article  Google Scholar 

  • Scanlon BR, Zhang Z, Save H, Wiese DN, Chen J (2016) Global evaluation of new GRACE mascon products for hydrologic applications. Water Resour Res 52(12):9412–9429

  • Schmidt R, Petrovic S, Güntner A, Barthelmes F, Wünsch J, Kusche J (2008) Periodic components of water storage changes from GRACE and global hydrology models. J Geophys Res Solid Earth 113(B8)

  • Shi Y, Shen Y, Kang E, Kang E, Li D, Ding Y, Zhang G, Hu R (2007) Recent and future climate change in Northwest China. Clim Chang 80(3–4):379–393

    Article  Google Scholar 

  • Statistics Bureau of Inner Mongolia Autonomous Region (2003–2014) Statistical Communique of National Economic and Social Development of Inner Mongolia Autonomous Region, 2003–2014. Statistics Bureau of Inner Mongolia Autonomous Region, Hohhot, Inner Mongolia Autonomous Region

  • Statistics Bureau of Shanxi Province (2003–2014) Statistical Yearbook of Shanxi Province, 2003–2014. Statistics Bureau of Shanxi Province, Taiyuan, China

  • Tao S, Fang JY, Zhao X, Zhao SQ, Shen HH, Hu HF, Tang ZY, Wang ZH, Guo QH (2015) Rapid loss of lakes on the Mongolian Plateau. Proc Natl Acad Sci USA 112(7):2281

    Article  Google Scholar 

  • Tiwari VM, Wahr J, Swenson S (2009) Dwindling groundwater resources in northern India, from satellite gravity observations. Geophys Res Lett 36(18):184–201

    Article  Google Scholar 

  • Tong CF (2011) Study on research of comprehensive water saving technology and prediction water requirement in ERDOS. Inner Mongolia Agriculture University, Hohhot, Inner Mongolia Autonomous Region

  • Wold S (1995) PLS for multivariate linear modeling. In: QSAR: chemometric methods in molecular design. Verlag Chemie, Weinheim, Germany, pp 195–218

  • Woodworth MD (2012) Frontier boomtown urbanism in Ordos, Inner Mongolia Autonomous Region. Cross-Currents 1(1):74–101

    Article  Google Scholar 

  • Wu XJ, Li HE (2013) Water resources and its availability in northern Shaanxi Province. Bull Soil Water Conserv 33(2):296–300

    Google Scholar 

  • Xie X, Xu CJ, Wen YM, Li W (2018) Monitoring groundwater storage changes in the loess plateau using GRACE satellite gravity data, hydrological models and coal mining data. Remote Sens 10(4):605

    Article  Google Scholar 

  • Xu GQ (2008) The forecast model of mine water discharge’s research about coal mining area in Shanxi Province. Taiyuan University of Technology, Taiyuan, China

  • Xu W, Ma CW, Duan ZP (2017) External cost estimation and internalization of coal Mining in Shanxi from the perspective of supply chain. J Shandong Uni Sci Technol 19(4):65–75

    Google Scholar 

  • Yellow River Conservancy Commission of the Ministry of Water Resources (2003–2014) Website. http://www.yrcc.gov.cn/zwzc/gzgb/. Accessed December 2019

  • Zeng QM (2010) Study on the damage mechanism of coal mining on groundwater resources and its protection countermeasures: taking Huafeng coalmine as an example. Shandong University of Science and Technology, Shandong, China

  • Zeng T, Ju CY, Cai TJ, Liu WB, Yao YF (2010) Selection of parameters for estimating canopy closure density using variable importance of projection criterion. J Beijing For Univ 32(6):37–41

    Google Scholar 

  • Zhang BY (2013) Study on hydrological effect caused by coal mining and rational utilization of mine water. Northwest A&F University, Yangling, China

  • Zhang MS, Dong Y, Du RJ, Gu XF (2010) The strategy and influence of coal mining on the groundwater resources at the energy and chemical base in the north of Shaanxi. Earth Sci Frontiers 17(6):235–246

    Google Scholar 

  • Zhang Q, Zhao YD, Zhang CJ, Li YH, Sun GW, Gao QZ (2008) Issues about hydrological cycle and water resource in arid region of Northwest China. Arid Meteorol 26(2):1–8

  • Zhao CH (2015) Research on disturbing mechanism of groundwater environment system and its evaluation technique in Shaanxi-Inner Mongolia intensive coal mining region. Graduate School of China Coal Research Institute

  • Zhuang Y (2015) Study on the water and land resources carrying capacity in Yan’an. Chang’an University, Xi’an, China

  • Zipper C, Balfour W, Roth R, Randolph J (1997) Domestic water supply impacts by underground coal mining in Virginia, U.S.A. Environ Geol 29(1–2):84–93

    Article  Google Scholar 

Download references

Acknowledgements

We are grateful for the CSR GRACE RL05 Mascon Solutions provided by the Center for Space Research (CSR).

Funding

This work was supported by the National Natural Science Foundation of China through Grant 41571412, 41601569.

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Correspondence to Jinbao Jiang.

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Chen, X., Jiang, J., Lei, T. et al. GRACE satellite monitoring and driving factors analysis of groundwater storage under high-intensity coal mining conditions: a case study of Ordos, northern Shaanxi and Shanxi, China. Hydrogeol J 28, 673–686 (2020). https://doi.org/10.1007/s10040-019-02101-0

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