A drought index derived from a combination of GNSS GRACE/GRACE-FO and meteorological data

doi:10.11947/j.AGCS.2023.20220484

Abstract

Abstract: Developing the combined drought index (CDI) integrating multi-source data is of important significance for accurate, objective and comprehensive drought monitoring and assessment. In this study, we built a novel CDI reflecting hydro-meteorological variables in Southwest China based on the principle component analysis. The proposed CDI integrates drought indices derived from Global Navigation Satellite System (GNSS) vertical displacements and time-variable gravity fields from Gravity Recovery and Climate Experiment (GRACE)/GRACE Follow-On (GRACE-FO) as well as the commonly used meteorological composite index (CI) in China. The results show that compared to the individual CI index and the drought indices based on GNSS, GRACE/GRACE-FO data, correlation coefficients between the proposed CDI and self-calibrating palmer drought severity index (scPDSI) improved significantly, with the maximum value of 0.84; the number of sites with improved correlations for the individual drought indices account for 100%, 93%, and 67%, respectively;the averaged correlation coefficients of all studied sites increased from 0.48, 0.34, 0.57 to 0.64, respectively. The results indicate the effectiveness of integrating drought information containing in multi-source data in the proposed CDI index, which could help to improve regional drought monitoring.

Key words: GNSS, GRACE/GRACE Follow-On, data fusion, drought index, principle component analysis

CLC Number:

P227

YAO Chaolong, CHEN Yongxin, LUO Zhicai, LI Qiong, YE Xuemiao, WEN Jinjie. A drought index derived from a combination of GNSS GRACE/GRACE-FO and meteorological data[J]. Acta Geodaetica et Cartographica Sinica, 2023, 52(11): 1883-1891.

References

[1] AGHAKOUCHAK A, FARAHMAND A, MELTON F S, et al. Remote sensing of drought:progress,challenges and opportunities[J].Reviews of Geophysics,2015,53(2):452-480.
[2] JIAO Wenzhe, WANG Lixin, MCCABE M F. Multi-sensor remote sensing for drought characterization:current status, opportunities and a roadmap for the future[J]. Remote Sensing of Environment, 2021, 256:112313.
[3] VAN LOON A F. Hydrological drought explained[J]. Wiley Interdisciplinary Reviews:Water, 2015, 2(4):359-392.
[4] 粟晓玲, 张更喜, 冯凯. 干旱指数研究进展与展望[J]. 水利与建筑工程学报, 2019, 17(5):9-18. SU Xiaoling, ZHANG Gengxi, FENG Kai. Progress and perspective of drought index[J]. Journal of Water Resources and Architectural Engineering, 2019, 17(5):9-18.
[5] 吴志勇, 程丹丹, 何海, 等. 综合干旱指数研究进展[J]. 水资源保护, 2021, 37(1):36-45. WU Zhiyong, CHENG Dandan, HE Hai, et al. Research progress of composite drought index[J]. Water Resources Protection, 2021, 37(1):36-45.
[6] ZARGAR A, SADIQ R, NASER B, et al. A review of drought indices[J]. Environmental Reviews, 2011, 19:333-349.
[7] 张强, 张良, 崔显成, 等. 干旱监测与评价技术的发展及其科学挑战[J]. 地球科学进展, 2011, 26(7):763-778. ZHANG Qiang, ZHANG Liang, CUI Xiancheng, et al. Progresses and challenges in drought assessment and monitoring[J]. Advances in Earth Science, 2011, 26(7):763-778.
[8] 江笑薇, 白建军, 刘宪峰. 基于多源信息的综合干旱监测研究进展与展望[J]. 地球科学进展, 2019, 34(3):275-287. JIANG Xiaowei, BAI Jianjun, LIU Xianfeng. Research progress and prospect of integrated drought monitoring based on multi-source information[J]. Advances in Earth Science, 2019, 34(3):275-287.
[9] YAO Yibin, YANG Yuanxi, SUN Heping, et al. Geodesy discipline:progress and perspective[J]. Journal of Geodesy and Geoinformation Science, 2021, 4(4):1-10.
[10] 成帅, 袁林果, 姜中山, 等. 应用GPS数据和Slepian基函数反演川云渝地区陆地水储量变化[J]. 地球物理学报, 2021, 64(4):1167-1180. CHENG Shuai, YUAN Linguo, JIANG Zhongshan, et al. Investigating terrestrial water storage change in Sichuan, Yunnan and Chongqing using Slepian basis functions[J]. Chinese Journal of Geophysics, 2021, 64(4):1167-1180.
[11] 何思源, 谷延超, 范东明, 等. 利用GPS垂直位移反演云南省陆地水储量变化[J]. 测绘学报, 2018, 47(3):332-340. DOI:10.11947/j.AGCS.2018.20170255. HE Siyuan, GU Yanchao, FAN Dongming, et al. Seasonal variation of terrestrial water storage in Yunnan Province inferred from GPS vertical observations[J]. Acta Geodaetica et Cartographica Sinica, 2018, 47(3):332-340. DOI:10.11947/j.AGCS.2018.20170255.
[12] JIANG Weiping, YUAN Peng, CHEN Hua, et al. Annual variations of monsoon and drought detected by GPS:a case study in Yunnan, China[J]. Scientific Reports, 2017, 7(1):5874.
[13] 姚朝龙, 罗志才, 胡月明, 等. 利用GPS垂向位移监测西南地区干旱事件[J]. 测绘学报, 2019, 48(5):547-554. DOI:10.11947/j.AGCS.2019.20180308. YAO Chaolong, LUO Zhicai, HU Yueming, et al. Detecting droughts in Southwest China from GPS vertical position displacements[J]. Acta Geodaetica et Cartographica Sinica, 2019, 48(5):547-554.DOI:10.11947/j.AGCS.2019.20180308.
[14] FERREIRA V G, MONTECINO H C, NDEHEDEHE C E, et al. Space-based observations of crustal deflections for drought characterization in Brazil[J]. Science of the Total Environment, 2018, 644:256-273.
[15] JIANG Zhongshan, HSU Y J, YUAN Linguo, et al. Hydrological drought characterization based on GNSS imaging of vertical crustal deformation across the contiguous United States[J]. Science of the Total Environment, 2022, 823:153663.
[16] 姚朝龙. 联合GRACE和水文气象数据研究自然与人为因素对区域水储量变化的影响[D]. 武汉:武汉大学, 2017. YAO Chaolong.Natural-and human-induced impacts on regional terrestrial water storage changes from GRACE and hydro-meteorological data[D]. Wuhan:Wuhan University, 2017.
[17] 冉艳红, 钟敏, 陈威, 等. 利用GRACE-FO重力卫星探测2019年长江中下游极端干旱[J]. 科学通报, 2021, 66(1):107-117. RAN Yanhong, ZHONG Min, CHEN Wei, et al. Monitoring the extreme drought in the middle and lower reaches of the Yangtze River in 2019 from GRACE-FO satellites[J]. Chinese Science Bulletin, 2021, 66(1):107-117.
[18] 瞿伟, 晋泽辉, 张勤, 等. GRACE与GRACE Follow-On重力卫星数据揭示出的黄河流域2002-2020年干旱特征[J]. 测绘学报, 2023, 52(5):714-724. DOI:10.11947/j.AGCS.2023.20210458. QU Wei, JIN Zehui, ZHANG Qin, et al. Drought characteristics of the Yellow River Basin from 2002 to 2020 revealed by GRACE and GRACE Follow-On data[J]. Acta Geodaetica et Cartographica Sinica, 2023, 52(5):714-724. DOI:10.11947/j.AGCS.2023.20210458.
[19] ZHAO M, GERUO A, VELICOGNA I, et al. A global gridded dataset of GRACE drought severity index for 2002-14:comparison with PDSI and SPEI and a case study of the Australia millennium drought[J].Journal of Hydrometeorology,2017, 18:2117-2129.
[20] ZHOU Hao,LUO Zhicai, TANGDAMRONGSUB N, et al. Characterizing drought and flood events over the Yangtze River Basin using the HUST-Grace2016 solution and ancillary data[J]. Remote Sensing, 2017, 9, 1100.
[21] 何秀凤, 高壮, 肖儒雅, 等. InSAR与北斗/GNSS综合方法监测地表形变研究现状与展望[J]. 测绘学报, 2022, 51(7):1338-1355. DOI:10.11947/j.AGCS.2022.20220148. HE Xiufeng, GAO Zhuang, XIAO Ruya, et al. Application and prospect of the integration of InSAR and BDS/GNSS for land surface deformation monitoring[J]. Acta Geodaetica et Cartographica Sinica, 2022, 51(7):1338-1355. DOI:10.11947/j.AGCS.2022.20220148.
[22] LI Bofeng, ZHANG Zhetao. Several kinematic data processing methods for time-correlated observations[J]. Journal of Geodesy and Geoinformation Science, 2019, 2(4):1-9.
[23] GU Yanchao, YUAN Linguo, FAN Dongming, et al. Seasonal crustal vertical deformation induced by environmental mass loading in mainland China derived from GPS, GRACE and surface loading models[J]. Advances in Space Research, 2017, 59(1):88-102.
[24] 姜卫平, 王锴华, 邓连生, 等. 热膨胀效应对GNSS基准站垂向位移非线性变化的影响[J]. 测绘学报, 2015, 44(5):473-480. DOI:10.11947/j.AGCS.2015.20140296. JIANG Weiping, WANG Kaihua, DENG Liansheng, et al. Impact on nonlinear vertical variation of GNSS reference stations caused by thermal expansion[J]. Acta Geodaetica et Cartographica Sinica, 2015, 44(5):473-480. DOI:10.11947/j.AGCS.2015.20140296.
[25] YAO Chaolong, SHUMC K, WANG Chuzhu, et al. Human migration-induced impacts on noise in GNSS position time series[J].All Earth,2022,34(1):1-7.
[26] 明锋. GPS坐标时间序列分析研究[J]. 测绘学报, 2019, 48(10):1340. DOI:10.11947/j.AGCS.2019.20190006. MING Feng. Research on the GPS coordinate time series analysis[J]. Acta Geodaetica et Cartographica Sinica, 2019, 48(10):1340. DOI:10.11947/j.AGCS.2019.20190006.
[27] 常文娟, 梁忠民, 马海波. 基于主成分分析的干旱综合指标构建及其应用[J]. 水文, 2017, 37(1):33-38, 82. CHANG Wenjuan, LIANG Zhongmin, MA Haibo. Construction of drought composite indicator based on principal component analysis and its application[J]. Journal of China Hydrology, 2017, 37(1):33-38, 82.
[28] PRAJAPATI V K, KHANNA M K, SINGH M, et al. PCA-based composite drought index for drought assessment in Marathwada region of Maharashtra state,India[J].Theoretical and Applied Climatology,2022,149:207-220.
[29] LIU Yi, ZHU Ye, REN Liliang, et al. On the mechanisms of two composite methods for construction of multivariate drought indices[J]. Science of the Total Environment, 2019, 647:981-991.
[30] RAJSEKHAR D, SINGH V P, MISHRA A K. Multivariate drought index:an information theory based approach for integrated drought assessment[J]. Journal of Hydrology, 2015, 526:164-182.