Spatio-temporal variability of drought and effect of large scale climate in the source region of Yellow River

Abstract The effects of drought, a devastating natural disaster, have expanded due to intense global warming. Therefore, studying the spatio-temporal evolution and formation mechanism of drought is urgent and important. In this paper, the standardized precipitation evapotranspiration index (SPEI) of the source region of Yellow River was calculated for the years 1961–2015, and the heuristic segmentation and Modified Mann-Kendall methods were used to study the change points and trends of precipitation, temperature, and SPEI. The empirical orthogonal function was used to study the major modes of the SPEI, and cross wavelet analysis was used to demonstrate the relationship between SPEI and large-scale climate factors. The results initially demonstrated no change point and an insignificant positive trend in precipitation. Temperature revealed a significant increasing trend, and a change point was detected in 1997. SPEI indicated a change point in 1993, and a significant increasing trend was observed thereafter. These findings reveal that drought in the study area is highly related to the El Niño-Southern Oscillation. The North Atlantic and Arctic oscillations caused similar impacts on drought. By comparison, changes in SPEI were slightly related to the Pacific decadal oscillation. These results provide useful information for evaluating drought changes in the study area, early warning of drought, and water resource management.

[1]  C. Torrence,et al.  A Practical Guide to Wavelet Analysis. , 1998 .

[2]  Lonnie H. Hudgins,et al.  Wavelet transforms and atmopsheric turbulence. , 1993, Physical review letters.

[3]  Meixue Yang,et al.  Permafrost degradation and its environmental effects on the Tibetan Plateau: A review of recent research , 2010 .

[4]  Jian-xia Chang,et al.  Copula-based drought risk assessment combined with an integrated index in the Wei River Basin, China , 2016 .

[5]  F. Martin Ralph,et al.  Influence of ENSO on Flood Frequency along the California Coast , 2004 .

[6]  Wei Guo,et al.  SNPP/VIIRS vegetation health to assess 500 California drought , 2017 .

[7]  Shengzhi Huang,et al.  The asymmetric impact of global warming on US drought types and distributions in a large ensemble of 97 hydro-climatic simulations , 2017, Scientific Reports.

[8]  Yimin Wang,et al.  Efficiency Evaluation of Hydropower Station Operation: A Case Study of Longyangxia Station in the Yellow River, China , 2017 .

[9]  Yutong Chen,et al.  Copulas-Based Drought Evolution Characteristics and Risk Evaluation in a Typical Arid and Semi-Arid Region , 2015, Water Resources Management.

[10]  D. Verdon‐Kidd,et al.  Climatic drivers of Victorian streamflow: Is ENSO the dominant influence? , 2009 .

[11]  J. Hurrell,et al.  DECADAL VARIATIONS IN CLIMATE ASSOCIATED WITH THE NORTH ATLANTIC OSCILLATION , 1997 .

[12]  Aslak Grinsted,et al.  Nonlinear Processes in Geophysics Application of the Cross Wavelet Transform and Wavelet Coherence to Geophysical Time Series , 2022 .

[13]  V. Singh,et al.  Drought characterization from a multivariate perspective: A review , 2015 .

[14]  V. Gorini,et al.  Hydrological signals in height and gravity in northeastern Italy inferred from principal components analysis , 2010 .

[15]  Douglas Maraun,et al.  Nonlinear Processes in Geophysics , 2000 .

[16]  Prabir Kumar Das,et al.  Monitoring of seasonal dryness/wetness conditions using shortwave angle slope index for early season agricultural drought assessment , 2014 .

[17]  T. McKee,et al.  THE RELATIONSHIP OF DROUGHT FREQUENCY AND DURATION TO TIME SCALES , 1993 .

[18]  J. Lenters,et al.  Potential extents for ENSO-driven hydrologic drought forecasts in the United States , 2010 .

[19]  S. Mitra,et al.  Baseflow response to climate variability induced droughts in the Apalachicola-Chattahoochee-Flint River Basin, U.S.A. , 2015 .

[20]  Vijay P. Singh,et al.  A general framework for multivariate multi-index drought prediction based on Multivariate Ensemble Streamflow Prediction (MESP) , 2016 .

[21]  Eric F. Wood,et al.  Detection of Intensification in Global- and Continental-Scale Hydrological Cycles: Temporal Scale of Evaluation , 2003 .

[22]  Edward R. Cook,et al.  The changing relationship between ENSO variability and moisture balance in the continental United States , 1998 .

[23]  Karl Pearson F.R.S..  LIII. On lines and planes of closest fit to systems of points in space , 1901 .

[24]  Dawen Yang,et al.  Spatio-temporal variation of drought in China during 1961–2012: A climatic perspective , 2015 .

[25]  H. Tabari,et al.  Hydrological drought in the west of Iran and possible association with large‐scale atmospheric circulation patterns , 2014 .

[26]  J. Hurrell.  Decadal Trends in the North Atlantic Oscillation: Regional Temperatures and Precipitation , 1995, Science.

[27]  J. Dracup,et al.  Drought monitoring , 1991 .

[28]  Wei Guo,et al.  Modelling and prediction of crop losses from NOAA polar-orbiting operational satellites , 2016 .

[29]  Jan Adamowski,et al.  Determining the amplitude and timing of streamflow discontinuities: A cross wavelet analysis approach , 2014 .

[30]  Chi-Farn Chen,et al.  Drought monitoring in cultivated areas of Central America using multi-temporal MODIS data , 2017 .

[31]  Richard R. Heim,et al.  Are droughts becoming more frequent or severe in China based on the Standardized Precipitation Evapotranspiration Index: 1951–2010? , 2011 .

[32]  Jiuping Xu,et al.  Risk analysis and evaluation of agricultural drought disaster in the major grain-producing areas, China , 2016 .

[33]  Upmanu Lall,et al.  Flood frequencies and durations and their response to El Niño Southern Oscillation: Global analysis , 2016 .

[34]  Huafang Lv,et al.  Spatial variability of the trends in climatic variables across China during 1961–2010 , 2015, Theoretical and Applied Climatology.

[35]  Khaled H. Hamed,et al.  A modified Mann-Kendall trend test for autocorrelated data , 1998 .

[36]  Jianping Huang,et al.  Bivariate wavelet analysis of Asia monsoon and ENSO , 1996 .

[37]  Chong-Yu Xu,et al.  Possible influence of ENSO on annual maximum streamflow of the Yangtze River, China , 2007 .

[38]  Dawen Yang,et al.  Impacts of climate warming on the frozen ground and eco-hydrology in the Yellow River source region, China. , 2017, The Science of the total environment.

[39]  N. Christidis,et al.  Modeling the Recent Evolution of Global Drought and Projections for the Twenty-First Century with the Hadley Centre Climate Model , 2006 .

[40]  R. P. Ohir.  Agro-Ecological Regions of India , 1994 .

[41]  J. Wallace,et al.  A Pacific Interdecadal Climate Oscillation with Impacts on Salmon Production , 1997 .

[42]  T. Stocker,et al.  Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation. A Special Report of Working Groups I and II of IPCC Intergovernmental Panel on Climate Change , 2012 .

[43]  A. Limsakul,et al.  Long-term trends and variability of total and extreme precipitation in Thailand , 2016 .

[44]  Guodong Cheng,et al.  Changes in frozen ground in the Source Area of the Yellow River on the Qinghai–Tibet Plateau, China, and their eco-environmental impacts , 2009 .

[45]  Jian-xia Chang,et al.  Assessing the impact of climate variability and human activities on streamflow variation , 2015 .

[46]  W. Alley.  The Palmer Drought Severity Index: Limitations and Assumptions , 1984 .

[47]  Space-time Trends in U.S. Meteorological Droughts , 2015, 1512.08526.

[48]  B. Soden,et al.  Atmospheric Warming and the Amplification of Precipitation Extremes , 2008, Science.

[49]  N. Wanders,et al.  Human and climate impacts on the 21st century hydrological drought , 2015 .

[50]  Qiang Huang,et al.  Drought structure based on a nonparametric multivariate standardized drought index across the Yellow River basin, China , 2015 .

[51]  S. Franks,et al.  Multidecadal variability of rainfall and streamflow: Eastern Australia , 2004 .

[52]  V. Singh,et al.  Toward a categorical drought prediction system based on U.S. Drought Monitor (USDM) and climate forecast , 2017 .

[53]  Wei Guo,et al.  2006–2015 mega-drought in the western USA and its monitoring from space data , 2015 .

[54]  Sergio M. Vicente-Serrano,et al.  A multi-scalar drought index sensitive to global warming: The Standardized Precipitation Evapotranspiration Index - SPEI , 2009 .

[55]  N. I. Dvinskikh.  Expansion of ionospheric characteristics fields in empirical orthogonal functions , 1988 .

[56]  R. Maity,et al.  Drought prediction using a wavelet based approach to model the temporal consequences of different types of droughts , 2016 .

[57]  S. Vicente‐Serrano,et al.  A Multiscalar Drought Index Sensitive to Global Warming: The Standardized Precipitation Evapotranspiration Index , 2009 .

[58]  B. Zaitchik,et al.  Trend and periodicity of drought over Ethiopia , 2017 .

[59]  H. Stanley,et al.  Scale invariance in the nonstationarity of human heart rate. , 2000, Physical review letters.

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

[61]  U. Sommer,et al.  Global warming benefits the small in aquatic ecosystems , 2009, Proceedings of the National Academy of Sciences.

[62]  Khaled H. Hamed.  Trend detection in hydrologic data: The Mann–Kendall trend test under the scaling hypothesis , 2008 .

[63]  Dawen Yang,et al.  Climatic factors influencing changing pan evaporation across China from 1961 to 2001 , 2012 .

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

[65]  Vijay P. Singh,et al.  Influence of ENSO on precipitation in the East River basin, south China , 2013 .

[66]  P. Sen.  Estimates of the Regression Coefficient Based on Kendall's Tau , 1968 .

[67]  J. Adamowski,et al.  Assessing agricultural drought at a regional scale using LULC classification, SPI, and vegetation indices: case study in a rainfed agro-ecosystem in Central Mexico , 2016 .

[68]  Qiang Huang,et al.  A nonparametric multivariate standardized drought index for characterizing socioeconomic drought: A case study in the Heihe River Basin , 2016 .

[69]  Robert F. Cahalan,et al.  Sampling Errors in the Estimation of Empirical Orthogonal Functions , 1982 .

[70]  J. Hao.  Characteristics of Water Vapor Transport and Atmospheric Circulation for Precipitation over the Source Regions of the Yellow and Yangtze Rivers , 2006 .

[71]  Wayne C. Palmer,et al.  Keeping Track of Crop Moisture Conditions, Nationwide: The New Crop Moisture Index , 1968 .

[72]  Edward R. Cook,et al.  Asian Monsoon Failure and Megadrought During the Last Millennium , 2010, Science.

[73]  P. K. Mishra,et al.  Evaluation of drought using SPEI drought class transitions and log-linear models for different agro-ecological regions of India , 2017 .

[74]  B. Chao,et al.  Terrestrial water storage anomalies of Yangtze River Basin droughts observed by GRACE and connections with ENSO , 2015 .