Regional GNSS-Derived SPCI: Verification and Improvement in Yunnan, China

From the aspect of global drought monitoring, improving the regional drought monitoring method is becoming increasingly important for the sustainable development of regional agriculture and the economy. The standardized precipitation conversion index (SPCI) calculated by the Global Navigation Satellite System (GNSS) observation is a new means for drought monitoring that has the advantages of simple calculation and real-time monitoring. However, only SPCI with a 12-month scale has been verified on a global scale, while its capability and applicability for monitoring drought at a short time scale in regional areas have never been investigated. Therefore, this study aims to evaluate the performance of SPCI at other time scales in Yunnan, China, and propose an improved method for SPCI. The data of six GNSS stations were selected to calculate SPCI; the standardized precipitation evapotranspiration index (SPEI) and composite meteorological drought index (CI) are introduced to evaluate the SPCI at a short time scale in Yunnan Province. In addition, a modified CI (MCI) was proposed to calibrate the SPCI because of its large bias in Yunnan. Experimental results show that (1) SPCI exhibits better agreement with CI in Yunnan Province when compared to SPEI; (2) the capability of SPCI for drought monitoring is superior to that of SPEI in Yunnan; and (3) the improved SPCI is more suitable for drought monitoring in Yunnan, with a relative bias of 5.43% when compared to the MCI. These results provide a new means for regional drought monitoring in Yunnan, which is significant for dealing with drought disasters and formulating related disaster prevention and mitigation policies.

[1]  Jie He,et al.  The first high-resolution meteorological forcing dataset for land process studies over China , 2020, Scientific Data.

[2]  Feng Zhang,et al.  Spatiotemporal drought variability on the Mongolian Plateau from 1980-2014 based on the SPEI-PM, intensity analysis and Hurst exponent. , 2017, The Science of the total environment.

[3]  Zhaosheng Nie,et al.  Research on variety characteristics of mainland China troposphere based on CMONOC , 2018, Geodesy and Geodynamics.

[4]  W. Qian,et al.  Ranking regional drought events in China for 1960–2009 , 2011 .

[5]  J. Rodgers,et al.  Thirteen ways to look at the correlation coefficient , 1988 .

[6]  D. Wilhite,et al.  Drought and Water Crises: Integrating Science, Management, and Policy , 2017 .

[7]  Xing Ma,et al.  A Comparative Study of Potential Evapotranspiration Estimation by Eight Methods with FAO Penman–Monteith Method in Southwestern China , 2017 .

[8]  Chansheng He,et al.  A modified water demand estimation method for drought identification over arid and semiarid regions , 2016 .

[9]  Qiang Huang,et al.  Linkages between hydrological drought, climate indices and human activities: a case study in the Columbia River basin , 2016 .

[10]  X. Duan,et al.  The spatiotemporal patterns of rainfall erosivity in Yunnan Province, southwest China: An analysis of empirical orthogonal functions , 2016 .

[11]  Kai Zhang,et al.  Spatial–temporal variations of spring drought based on spring-composite index values for the Songnen Plain, Northeast China , 2014, Theoretical and Applied Climatology.

[12]  K. Fraedrich,et al.  Precipitable water vapor and its relationship with the Standardized Precipitation Index: ground-based GPS measurements and reanalysis data , 2016, Theoretical and Applied Climatology.

[13]  Shengzhi Huang,et al.  The propagation from meteorological to hydrological drought and its potential influence factors , 2017 .

[14]  Yibin Yao,et al.  Improved Drought Monitoring Index Using GNSS-Derived Precipitable Water Vapor over the Loess Plateau Area , 2019, Sensors.

[15]  Wanqiang Yao,et al.  A novel method of retrieving potential ET in China , 2021, Journal of Hydrology.

[16]  Nico Sneeuw,et al.  Annual variations of monsoon and drought detected by GPS: A case study in Yunnan, China , 2017, Scientific Reports.

[17]  Bob E. Schutz,et al.  Monitoring precipitable water vapor in real-time using global navigation satellite systems , 2013, Journal of Geodesy.

[18]  Luis S. Pereira,et al.  Climate trends and behaviour of drought indices based on precipitation and evapotranspiration in Portugal , 2012 .

[19]  B. Ghahraman,et al.  Integrated meteorological and hydrological drought model: A management tool for proactive water resources planning of semi-arid regions , 2017 .

[20]  Xiangyu Xu,et al.  Copula based drought frequency analysis considering the spatio-temporal variability in Southwest China , 2015 .

[21]  Ningbo Cui,et al.  Improvement of Makkink model for reference evapotranspiration estimation using temperature data in Northwest China , 2018, Journal of Hydrology.

[22]  J. Vogt,et al.  Development of a Combined Drought Indicator to detect agricultural drought in Europe , 2012 .

[23]  Jia Guo,et al.  Construction of a drought monitoring model using deep learning based on multi-source remote sensing data , 2019, Int. J. Appl. Earth Obs. Geoinformation.

[24]  Mohammad Abouali,et al.  Development and evaluation of a comprehensive drought index. , 2017, Journal of environmental management.

[25]  Abdüsselam Altunkaynak,et al.  Investigation Anthropogenic Impacts and Climate Factors on Drying up of Urmia Lake using Water Budget and Drought Analysis , 2017, Water Resources Management.

[26]  Tiejian Li,et al.  Evaluation of the gridded CRU TS precipitation dataset with the point raingauge records over the Three-River Headwaters Region , 2017 .

[27]  Qiang Huang,et al.  Reference evapotranspiration forecasting based on local meteorological and global climate information screened by partial mutual information , 2018, Journal of Hydrology.

[28]  Li Li,et al.  The correlation between GNSS-derived precipitable water vapor and sea surface temperature and its responses to El Niño–Southern Oscillation , 2018, Remote Sensing of Environment.

[29]  Wenjin Yu,et al.  Analysis on spatial and temporal characteristics drought of Yunnan Province , 2013 .

[30]  Xiao Pu,et al.  Multi-models for SPI drought forecasting in the north of Haihe River Basin, China , 2017, Stochastic Environmental Research and Risk Assessment.

[31]  Yang Hong,et al.  Drought and flood monitoring for a large karst plateau in Southwest China using extended GRACE data , 2014 .

[32]  Mohamed Khaled Salahou,et al.  Analysis and Application of Drought Characteristics Based on Theory of Runs and Copulas in Yunnan, Southwest China , 2020, International journal of environmental research and public health.

[33]  Xing Wan-ru.  Dynamic changes of composite drought indiex in Liaoning Province in recent 50 years , 2009 .

[34]  Jane Qiu,et al.  China drought highlights future climate threats , 2010, Nature.

[35]  Yi Li,et al.  Recent changes in extreme precipitation and drought over the Songhua River Basin, China, during 1960-2013 , 2015 .

[36]  Hao Zhang,et al.  Impacts of Drought on Vegetation Assessed by Vegetation Indices and Meteorological Factors in Afghanistan , 2020, Remote. Sens..

[37]  Jaroslaw BOSY.  GNSS meteorology , 2011 .