Assessment of Water Use in Pan-Eurasian and African Continents by ETMonitor with Multi-Source Satellite Data

The Pan-Eurasian and African Continents are characterized by large ranges of climates varying from humid, semi-humid, semi-arid and arid regions, and great challenges exist in water allocation for different sectors that related to water resource and food security, which depends strongly on the water use information. Quantitative information on water use is also important to understand the effectiveness of water allocation and further to prevent from water stress resulted by drought in water-scarce regions. Explosive development of satellite remote sensing observations provide great chance to provide useful spatiotemporal information for quantifying the water use at regional to global scales. In this paper, a process-based model ETMonitor was used in combination with biophysical and hydrological parameters retrieved from earth observations to estimate the actual evapotranspiration, i.e. the agricultural and ecological water use. The total water use is also partitioned into beneficial part, e.g. plant transpiration, and non-beneficial part, e.g. soil evaporation and canopy rainfall interception, according to the water accounting framework. The estimated water use show good agreements with the ground observation, indicating the ability of ETMonitor for global and continental scale water use estimation. The spatial and temporal patterns of the water use in the Pan-Eurasian and African Continents were further analysed, while large spatial variation of water use was convinced. Current study also highlights the great capability of satellite observations in studying the regional water resource and continental water cycle.

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

[2]  C. Alewell,et al.  Importance of vegetation, topography and flow paths for water transit times of base flow in alpine headwater catchments , 2013 .

[3]  P. Döll,et al.  Groundwater use for irrigation - a global inventory , 2010 .

[4]  Zheng Duan,et al.  Earth Observation Based Assessment of the Water Production and Water Consumption of Nile Basin Agro-Ecosystems , 2014, Remote. Sens..

[5]  J. Townshend,et al.  A long-term Global LAnd Surface Satellite (GLASS) data-set for environmental studies , 2013 .

[6]  Chenghu Zhou,et al.  A Review of Current Methodologies for Regional Evapotranspiration Estimation from Remotely Sensed Data , 2009, Sensors.

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

[8]  Matthew F. McCabe,et al.  The WACMOS-ET project – Part 2: Evaluation of global terrestrial evaporation data sets , 2015 .

[9]  W. Wagner,et al.  A Method for Estimating Soil Moisture from ERS Scatterometer and Soil Data , 1999 .

[10]  Li Jia,et al.  Monitoring of Evapotranspiration in a Semi-Arid Inland River Basin by Combining Microwave and Optical Remote Sensing Observations , 2015, Remote. Sens..

[11]  T. Steenhuis,et al.  Groundwater recharge from irrigated cropland in the North China Plain: case study of Luancheng County, Hebei Province, 1949–2000 , 2004 .

[12]  Massimo Menenti,et al.  Comparison of MOD16 and LSA-SAF MSG evapotranspiration products over Europe for 2011 , 2015 .

[13]  Chaolei Zheng,et al.  Coupling SEBAL with a new radiation module and MODIS products for better estimation of evapotranspiration , 2016 .

[14]  Matthew F. McCabe,et al.  The WACMOS-ET project – Part 1: Tower-scale evaluation of four remote-sensing-based evapotranspiration algorithms , 2015 .

[15]  A. Holtslag,et al.  A remote sensing surface energy balance algorithm for land (SEBAL)-1. Formulation , 1998 .

[16]  L. S. Pereira,et al.  Crop evapotranspiration : guidelines for computing crop water requirements , 1998 .

[17]  J. Eitzinger,et al.  The ASCAT Soil Moisture Product: A Review of its Specifications, Validation Results, and Emerging Applications , 2013 .

[18]  Massimo Menenti,et al.  Estimation of sensible heat flux using the Surface Energy Balance System (SEBS) and ATSR measurements , 2003 .

[19]  Wim G.M. Bastiaanssen,et al.  Water Accounting Plus (WA+) - a water accounting procedure for complex river basins based on satellite measurements , 2012 .

[20]  T. Huntington Evidence for intensification of the global water cycle: Review and synthesis , 2006 .

[21]  José A. Sobrino,et al.  Satellite-derived land surface temperature: Current status and perspectives , 2013 .

[22]  S. Kanae,et al.  Global Hydrological Cycles and World Water Resources , 2006, Science.

[23]  Markus Reichstein,et al.  Benchmark products for land evapotranspiration: LandFlux-EVAL multi-data set synthesis , 2013 .

[24]  J. Norman,et al.  Source approach for estimating soil and vegetation energy fluxes in observations of directional radiometric surface temperature , 1995 .

[25]  Chaolei Zheng,et al.  Spatiotemporal variations of reference evapotranspiration in recent five decades in the arid land of Northwestern China , 2014 .

[26]  Yanjun Shen,et al.  Effects of irrigation on water balance, yield and WUE of winter wheat in the North China Plain , 2006 .

[27]  Peter Bauer-Gottwein,et al.  Evaluation of Remotely Sensed Precipitation and Its Performance for Streamflow Simulations in Basins of the Southeast Tibetan Plateau , 2015 .

[28]  Di Long,et al.  Estimation of daily average net radiation from MODIS data and DEM over the Baiyangdian watershed in North China for clear sky days , 2010 .

[29]  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 .

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

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