Drought and flood monitoring for a large karst plateau in Southwest China using extended GRACE data

Droughts and floods alternately occur over a large karst plateau (Yun–Gui Plateau) in Southwest China. Hereweshow that both the frequency and severity of droughts and floods over the plateau are intensified during therecent decade from three-decade total water storage anomalies (TWSA) generated by Gravity Recovery andClimate Experiment (GRACE) satellite data and artificial neural network (ANN) models. The developed ANNmodels performed well in hindcasting TWSA for the plateau and its three sub-regions (i.e., the upper MekongRiver, Pearl River, and Wujiang River basins), showing coefficients of determination (R2) of 0.91, 0.83, 0.76,and 0.57, respectively. The intensified climate extremes are indicative of large changes in the hydrologicalcycle and brought great challenges in water resource management there. TheTWSA of the plateau remained fairlystable during the 1980s, and featured an increasing trend at a rate of 5.9±0.5mm/a in the 1990s interspersedextreme flooding in 1991 and during the second half of the 1990s. Since 2000, the TWSA fluctuated drastically,featuring severe spring droughts from2003 to 2006, the most extreme spring drought on record in 2010, and severeflooding in 2008. TheTWSA of the upperMekong has decreased by ~100mm(~15km3) comparedwith thatat the end of the 1990s. In addition to hindcastingTWSA, the developed approach could be effective in generatingfuture TWSA and potentially bridge the gap between the current GRACE satellites and the GRACE Follow-OnMission expected to launch in 2017.

[1]  Anny Cazenave,et al.  Interannual variability in water storage over 2003–2008 in the Amazon Basin from GRACE space gravimetry, in situ river level and precipitation data , 2010 .

[2]  B. Scanlon,et al.  GRACE satellite monitoring of large depletion in water storage in response to the 2011 drought in Texas , 2013 .

[3]  A. Sahoo,et al.  Multisource estimation of long-term terrestrial water budget for major global river basins , 2012 .

[4]  J. Randerson,et al.  Forecasting terrestrial water storage changes in the Amazon Basin using Atlantic and Pacific sea surface temperatures , 2013 .

[5]  Problems of Flood and Drought in a Typical Peak Cluster Depression Karst Area (SW China) , 2010 .

[6]  Michael J. A. Berry,et al.  Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management , 2004 .

[7]  Jeffrey P. Walker,et al.  THE GLOBAL LAND DATA ASSIMILATION SYSTEM , 2004 .

[8]  Guillaume Ramillien,et al.  Basin‐scale, integrated observations of the early 21st century multiyear drought in southeast Australia , 2009 .

[9]  Alexander Y. Sun,et al.  Predicting groundwater level changes using GRACE data , 2013 .

[10]  S. Swenson,et al.  Post‐processing removal of correlated errors in GRACE data , 2006 .

[11]  Lily House-Peters,et al.  Urban water demand modeling: Review of concepts, methods, and organizing principles , 2011 .

[12]  J. Famiglietti,et al.  Global terrestrial water storage capacity and flood potential using GRACE , 2009 .

[13]  S. Yirdaw,et al.  GRACE satellite observations of terrestrial moisture changes for drought characterization in the Canadian Prairie , 2008 .

[14]  Anny Cazenave,et al.  Past terrestrial water storage (1980–2008) in the Amazon Basin reconstructed from GRACE and in situ river gauging data , 2010 .

[15]  K. Trenberth,et al.  A Global Dataset of Palmer Drought Severity Index for 1870–2002: Relationship with Soil Moisture and Effects of Surface Warming , 2004 .

[16]  Jason S. Polk,et al.  Evolution of major environmental geological problems in karst areas of Southwestern China , 2013, Environmental Earth Sciences.

[17]  Alexander Y. Sun,et al.  Inferring aquifer storage parameters using satellite and in situ measurements: Estimation under uncertainty , 2010 .

[18]  B. Scanlon,et al.  Uncertainty in evapotranspiration from land surface modeling, remote sensing, and GRACE satellites , 2014 .

[19]  D. Lettenmaier,et al.  A simple hydrologically based model of land surface water and energy fluxes for general circulation models , 1994 .

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

[21]  F. Landerer,et al.  Accuracy of scaled GRACE terrestrial water storage estimates , 2012 .

[22]  M. Watkins,et al.  GRACE Measurements of Mass Variability in the Earth System , 2004, Science.

[23]  Di Long,et al.  Statistical analysis of the relationship between spring soil moisture and summer precipitation in East China , 2014 .

[24]  S. Running,et al.  A continuous satellite‐derived global record of land surface evapotranspiration from 1983 to 2006 , 2010 .

[25]  Y. Hong,et al.  The TRMM Multisatellite Precipitation Analysis (TMPA): Quasi-Global, Multiyear, Combined-Sensor Precipitation Estimates at Fine Scales , 2007 .

[26]  Byron D. Tapley,et al.  The 2009 exceptional Amazon flood and interannual terrestrial water storage change observed by GRACE , 2010 .

[27]  Gordon S. Linoff,et al.  Data mining techniques for marketing, sales and customer relationship , 2004 .

[28]  Maosheng Zhao,et al.  Improvements to a MODIS global terrestrial evapotranspiration algorithm , 2011 .

[29]  Simon Haykin,et al.  Neural Networks and Learning Machines , 2010 .

[30]  Yinhao Lu,et al.  Changes of daily climate extremes in northwestern China during 1961–2008 , 2011, 2011 International Conference on Remote Sensing, Environment and Transportation Engineering.

[31]  Matthew Rodell,et al.  Groundwater depletion in the Middle East from GRACE with implications for transboundary water management in the Tigris-Euphrates-Western Iran region , 2013, Water resources research.

[32]  Jianchu Xu,et al.  Mekong Hydropower Development , 2011, Science.

[33]  B. Scanlon,et al.  GRACE Hydrological estimates for small basins: Evaluating processing approaches on the High Plains Aquifer, USA , 2010 .

[34]  S. Swenson,et al.  Satellites measure recent rates of groundwater depletion in California's Central Valley , 2011 .

[35]  Radford M. Neal.  Pattern Recognition and Machine Learning , 2007, Technometrics.

[36]  P. Younger.  Water in the balance , 2013 .

[37]  Kuolin Hsu,et al.  Artificial Neural Network Modeling of the Rainfall‐Runoff Process , 1995 .