Estimation of the terrestrial water budget over northern China by merging multiple datasets

Summary The terrestrial water budget over northern China, which plays an important role in water resource management, has experienced great changes during the past decades. However, its spatiotemporal variations in the past calculated from individual datasets remain quite uncertain. In this study, we improve the accuracy of evapotranspiration ( E ), precipitation ( P ) and runoff ( R ) estimates by merging remote sensing, reanalysis, data assimilation datasets and ground observations, and further analyze the spatiotemporal characterization of the terrestrial water budget at 0.25° over northern China during the period of 1984–2010. The results illustrate that using any of the individual datasets, there is significant uncertainty and an obvious seasonal cycle in the terrestrial water budget. Large differences exist among the different datasets, and the merged E , P and R outperform the individual datasets. The root mean square errors ( RMSE s) from cross-validation are 8.4–14.2 mm, 15.9–27.3 mm and 4.1–14.2 mm for the monthly merged E , P and R at the site scale of the different basins, respectively. The spatial patterns of the merged annual E and R are consistent with that of P due to the water limitations mainly controlled by P . The interannual variations in these hydrological variables indicate a slight increase in the variables from 1984 to 1998, with a large El Nino event, and a larger decline thereafter as a result of a large-scale drought. However, decadal trends in terrestrial water storage changes ( TWSC ) over all five basins inferred from the merged products tend to increase to some extent with climate warming over the studied time period. The Budyko curve reveals that an increase in vegetation coverage increases the evaporation ratio ( E / P ) to some extent, but climate change is the dominant driver for the variations in the hydrological variables in these regions.

[1]  Chi Yang,et al.  Probabilistic precipitation forecasting based on ensemble output using generalized additive models and Bayesian model averaging , 2012, Acta Meteorologica Sinica.

[2]  Fulu Tao,et al.  GRACE, GLDAS and measured groundwater data products show water storage loss in Western Jilin, China. , 2012, Water science and technology : a journal of the International Association on Water Pollution Research.

[3]  E. Dutton,et al.  Do Satellites Detect Trends in Surface Solar Radiation? , 2004, Science.

[4]  D. Baldocchi,et al.  Global estimates of the land–atmosphere water flux based on monthly AVHRR and ISLSCP-II data, validated at 16 FLUXNET sites , 2008 .

[5]  Sujay V. Kumar,et al.  Land information system: An interoperable framework for high resolution land surface modeling , 2006, Environ. Model. Softw..

[6]  Yuqing Wang,et al.  Observed trends in extreme precipitation events in China during 1961–2001 and the associated changes in large‐scale circulation , 2005 .

[7]  Eric F. Wood,et al.  Multi‐model, multi‐sensor estimates of global evapotranspiration: climatology, uncertainties and trends , 2011 .

[8]  Xianhong Xie,et al.  Data assimilation for distributed hydrological catchment modeling via ensemble Kalman filter , 2010 .

[9]  Qiming Qin,et al.  Monitoring Drought over the Conterminous United States Using MODIS and NCEP Reanalysis-2 Data , 2010 .

[10]  T. Foken The energy balance closure problem: an overview. , 2008, Ecological applications : a publication of the Ecological Society of America.

[11]  Qiming Qin,et al.  Evaluation of EDI derived from the exponential evapotranspiration model for monitoring China’s surface drought , 2011 .

[12]  Minghua Zhang,et al.  Impact of climate change on streamflow in the arid Shiyang River Basin of northwest China , 2012 .

[13]  D. Lettenmaier,et al.  Simulation of reservoir influences on annual and seasonal streamflow changes for the Lena, Yenisei, and Ob' rivers , 2007 .

[14]  J. Norman,et al.  Correcting eddy-covariance flux underestimates over a grassland , 2000 .

[15]  William B. Rossow,et al.  Monitoring Flood and Discharge Variations in the Large Siberian Rivers From a Multi-Satellite Technique , 2008 .

[16]  Zhihua Ren,et al.  Errors and correction of precipitation measurements in China , 2007 .

[17]  Dominique Carrer,et al.  Verification of the new ECMWF ERA-Interim reanalysis over France , 2010 .

[18]  E. Wood,et al.  Development of a 50-Year High-Resolution Global Dataset of Meteorological Forcings for Land Surface Modeling , 2006 .

[19]  M. Hulme,et al.  Precipitation measurements and trends in the twentieth century , 2001 .

[20]  Qiang Liu,et al.  Preliminary evaluation of the long-term GLASS albedo product , 2013 .

[21]  Shaomin Liu,et al.  A comparison of eddy-covariance and large aperture scintillometer measurements with respect to the energy balance closure problem , 2011 .

[22]  R. Reynolds,et al.  The NCEP/NCAR 40-Year Reanalysis Project , 1996, Renewable Energy.

[23]  Pedro Viterbo,et al.  Impact of the ECMWF reanalysis soil water on forecasts of the July 1993 Mississippi flood , 1999 .

[24]  K. Trenberth,et al.  Estimates of the Global Water Budget and Its Annual Cycle Using Observational and Model Data , 2007 .

[25]  A. Cazenave,et al.  Global runoff anomalies over 1993–2009 estimated from coupled Land–Ocean–Atmosphere water budgets and its relation with climate variability , 2012 .

[26]  Shixiong Cao,et al.  Why large-scale afforestation efforts in China have failed to solve the desertification problem. , 2008, Environmental science & technology.

[27]  R. Dickinson,et al.  Evidence for decadal variation in global terrestrial evapotranspiration between 1982 and 2002: 1. Model development , 2010 .

[28]  Gerald Stanhill,et al.  Evaporative climate changes at Bet Dagan, Israel, 1964–1998 , 2002 .

[29]  S. Liang,et al.  Bayesian multimodel estimation of global terrestrial latent heat flux from eddy covariance, meteorological, and satellite observations , 2014 .

[30]  GLOBAL LAND DATA ASSIMILATION SYSTEM (GLDAS) PRODUCTS FROM NASA HYDROLOGY DATA AND INFORMATION SERVICES CENTER (HDISC) , 2008 .

[31]  Pedro Viterbo,et al.  An Improved Land Surface Parameterization Scheme in the ECMWF Model and Its Validation. , 1995 .

[32]  S. Goetz,et al.  Satellite based analysis of northern ET trends and associated changes in the regional water balance from 1983 to 2005 , 2008 .

[33]  S. Seneviratne,et al.  Recent decline in the global land evapotranspiration trend due to limited moisture supply , 2010, Nature.

[34]  Margarida Belo-Pereira,et al.  Evaluation of global precipitation data sets over the Iberian Peninsula , 2011 .

[35]  S. Nigam,et al.  Warm Season Rainfall Variability over the U.S. Great Plains in Observations, NCEP and ERA-40 Reanalyses, and NCAR and NASA Atmospheric Model Simulations , 2005 .

[36]  S. Kanae,et al.  Impact of vegetation coverage on regional water balance in the nonhumid regions of China , 2009 .

[37]  Yaning Chen,et al.  Regional climate change and its effects on river runoff in the Tarim Basin, China , 2006 .

[38]  Eric F. Wood,et al.  Global estimates of evapotranspiration for climate studies using multi-sensor remote sensing data: Evaluation of three process-based approaches , 2011 .

[39]  Yuqing Wang,et al.  Correction to “Observed trends in extreme precipitation events in China during 1961–2001 and the associated changes in large‐scale circulation” , 2005 .

[40]  Bruno Merz,et al.  A global analysis of temporal and spatial variations in continental water storage , 2007 .

[41]  Edwin W. Pak,et al.  An extended AVHRR 8‐km NDVI dataset compatible with MODIS and SPOT vegetation NDVI data , 2005 .

[42]  J. Janowiak,et al.  CMORPH: A Method that Produces Global Precipitation Estimates from Passive Microwave and Infrared Data at High Spatial and Temporal Resolution , 2004 .

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

[44]  Jennifer C. Adam,et al.  Evaluation of surface water fluxes of the pan‐Arctic land region with a land surface model and ERA‐40 reanalysis , 2006 .

[45]  Thomas Foken,et al.  Response of hydrological cycle to recent climate changes in the Tibetan Plateau , 2011 .

[46]  S. Liang,et al.  MODIS-driven estimation of terrestrial latent heat flux in China based on a modified Priestley-Taylor algorithm , 2013 .

[47]  Bin Yong,et al.  Spatial and temporal characteristics of changes in precipitation during 1957–2007 in the Haihe River basin, China , 2011 .

[48]  George H. Hargreaves,et al.  Defining and Using Reference Evapotranspiration , 1994 .

[49]  T. D. Mitchell,et al.  An improved method of constructing a database of monthly climate observations and associated high‐resolution grids , 2005 .

[50]  H. Tian,et al.  Effects of multiple environment stresses on evapotranspiration and runoff over eastern China , 2012 .

[51]  Y. Hong,et al.  Precipitation Estimation from Remotely Sensed Imagery Using an Artificial Neural Network Cloud Classification System , 2004 .

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

[53]  Xiaotong Zhang,et al.  Review on Estimation of Land Surface Radiation and Energy Budgets From Ground Measurement, Remote Sensing and Model Simulations , 2010, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[54]  Aaron A. Berg,et al.  Filling gaps in evapotranspiration measurements for water budget studies: Evaluation of a Kalman filtering approach , 2006 .

[55]  Yihui Ding,et al.  Climate simulation and future projection of precipitation and the water vapor budget in the Haihe River basin , 2012, Acta Meteorologica Sinica.

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

[57]  R. Dickinson,et al.  A review of global terrestrial evapotranspiration: Observation, modeling, climatology, and climatic variability , 2011 .

[58]  A. Barrett,et al.  Northern High-Latitude Precipitation as Depicted by Atmospheric Reanalyses and Satellite Retrievals , 2005 .

[59]  Shaomin Liu,et al.  Validation of remotely sensed evapotranspiration over the Hai River Basin, China , 2012 .

[60]  M. B. Parlange,et al.  Hydrologic cycle explains the evaporation paradox , 1998, Nature.

[61]  Julien Lerat,et al.  Has land cover a significant impact on mean annual streamflow? An international assessment using 1508 catchments , 2008 .

[62]  J. Susskind,et al.  Global Precipitation at One-Degree Daily Resolution from Multisatellite Observations , 2001 .

[63]  M. Budyko,et al.  Climate and life , 1975 .

[64]  Michael G. Bosilovich,et al.  Evaluation of Global Precipitation in Reanalyses , 2008 .

[65]  J.-Y. Parlange,et al.  Increasing Evapotranspiration from the Conterminous United States , 2004 .

[66]  Shunlin Liang,et al.  Evidence for decadal variation in global terrestrial evapotranspiration between 1982 and 2002: 2. Results , 2010 .

[67]  Shaomin Liu,et al.  Measurements of evapotranspiration from eddy-covariance systems and large aperture scintillometers in the Hai River Basin, China , 2013 .

[68]  Alfred Stein,et al.  Validation of ETWatch using field measurements at diverse landscapes: A case study in Hai Basin of China , 2012 .

[69]  Shaohua Zhao,et al.  Satellite detection of increases in global land surface evapotranspiration during 1984–2007 , 2012, Int. J. Digit. Earth.

[70]  A. Betts,et al.  Evaluation of the ERA-40 Surface Water Budget and Surface Temperature for the Mackenzie River Basin , 2003 .

[71]  Maosheng Zhao,et al.  Development of a global evapotranspiration algorithm based on MODIS and global meteorology data , 2007 .

[72]  Nannan Zhang,et al.  Validation and Application of the Modified Satellite-Based Priestley-Taylor Algorithm for Mapping Terrestrial Evapotranspiration , 2014, Remote. Sens..

[73]  Xuebin Zhang,et al.  Trends in Total Precipitation and Frequency of Daily Precipitation Extremes over China , 2005 .

[74]  Chong-yu Xu,et al.  Precipitation extremes in a karst region: a case study in the Guizhou province, southwest China , 2010 .

[75]  Hanqin Tian,et al.  Effects of Land‐Use and Land‐Cover Change on Evapotranspiration and Water Yield in China During 1900‐2000 1 , 2008 .

[76]  Fei Wang,et al.  Changes in streamflow and sediment discharge and the response to human activities in the middle reaches of the Yellow River , 2010 .

[77]  Chong-Yu Xu,et al.  Trend of estimated actual evapotranspiration over China during 1960-2002 , 2007 .

[78]  G. Sun,et al.  Regional annual water yield from forest lands and its response to potential deforestation across the southeastern United States , 2005 .

[79]  Xiaotong Zhang,et al.  Estimation of clear‐sky land surface longwave radiation from MODIS data products by merging multiple models , 2012 .

[80]  Zhuguo Ma,et al.  Some evidence of drying trend over northern China from 1951 to 2004 , 2006 .

[81]  X. Mo,et al.  Assessing the effect of climate change on mean annual runoff in the Songhua River basin, China , 2012 .

[82]  S. Swenson,et al.  Methods for inferring regional surface‐mass anomalies from Gravity Recovery and Climate Experiment (GRACE) measurements of time‐variable gravity , 2002 .

[83]  Jindi Wang,et al.  Use of General Regression Neural Networks for Generating the GLASS Leaf Area Index Product From Time-Series MODIS Surface Reflectance , 2014, IEEE Transactions on Geoscience and Remote Sensing.

[84]  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 .

[85]  Yan Wang,et al.  Stepwise decreases of the Huanghe (Yellow River) sediment load (1950–2005): Impacts of climate change and human activities , 2007 .

[86]  A. Raftery,et al.  Using Bayesian Model Averaging to Calibrate Forecast Ensembles , 2005 .

[87]  Sun Xiaofang Spatial Change Trends of Temperature and Precipitation in China , 2011 .

[88]  S. Liang,et al.  Surface-sensible and latent heat fluxes over the Tibetan Plateau from ground measurements, reanalysis, and satellite data , 2013 .

[89]  Lu Zhang,et al.  Response of mean annual evapotranspiration to vegetation changes at catchment scale , 2001 .

[90]  E. Wood,et al.  Estimation of the Terrestrial Water Budget over Northern Eurasia through the Use of Multiple Data Sources , 2011 .

[91]  S. Schubert,et al.  MERRA: NASA’s Modern-Era Retrospective Analysis for Research and Applications , 2011 .

[92]  N. Verhoest,et al.  El Niño-La Niña cycle and recent trends in continental evaporation , 2014 .

[93]  Yali Luo,et al.  Regional atmospheric anomalies responsible for the 2009–2010 severe drought in China , 2011 .

[94]  A. Sahoo,et al.  Reconciling the global terrestrial water budget using satellite remote sensing , 2011 .

[95]  T. McVicar,et al.  Developing a decision support tool for China's re-vegetation program: Simulating regional impacts of afforestation on average annual streamflow in the Loess Plateau , 2007 .

[96]  Thomas J. Jackson,et al.  Effects of remote sensing pixel resolution on modeled energy flux variability of croplands in Iowa , 2004 .

[97]  Jiemin Wang,et al.  Intercomparison of surface energy flux measurement systems used during the HiWATER‐MUSOEXE , 2013 .