Evaluation of remotely sensed actual evapotranspiration products from COMS and MODIS at two different flux tower sites in Korea

Estimating the evapotranspiration (ET) is a requirement for water resource management and agricultural productions to understand the interaction between the land surface and the atmosphere. Most remote-sensing-based ET is estimated from polar orbiting satellites having low frequencies of observation. However, observing the continuous spatio-temporal variation of ET from a geostationary satellite to determine water management usage is essential. In this study, we utilized the revised remote-sensing-based Penman–Monteith (revised RS-PM) model to estimate ET in three different timescales (instantaneous, daily, and monthly). The data from a polar orbiting satellite, the Moderate Resolution Imaging Spectroradiometer (MODIS), and a geostationary satellite, the Communication, Ocean, and Meteorological Satellite (COMS), were collected from April to December 2011 to force the revised RS-PM model. The estimated ET from COMS and MODIS was compared with measured ET obtained from two different flux tower sites having different land surface characteristics in Korea, i.e. Sulma (SMC) with mixed forest and Cheongmi (CFC) with rice paddy as dominant vegetation. Compared with flux tower measurements, the estimated ET on instantaneous and daily timescales from both satellites was highly overestimated at SMC when compared with the flux tower ET (Bias of 41.19–145.10 W m−2 and RMSE of 69.61–188.78 W m−2), while estimated ET results were slightly better at the CFC site (Bias of –27.28–13.24 W m−2 and RMSE of 45.19–71.82 W m−2, respectively). These errors in results were primarily caused due to the overestimated leaf area index that was obtained from satellite products. Nevertheless, the satellite-based ET indicated reasonable agreement with flux tower ET. Monthly average ET from both satellites showed nearly similar patterns during the entire study periods, except for the summer season. The difference between COMS and MODIS estimations during the summer season was mainly propagated due to the difference in the number of acquired satellite images. This study showed that the higher frequency of COMS than MODIS observations makes it more ideal to continuously monitor ET as a geostationary satellite with high spatio-temporal coverage of a geostationary satellite.

[1]  Hiroshi Kawamura,et al.  Validation and Improvement of Satellite-Derived Surface Solar Radiation over the Northwestern Pacific Ocean , 2005 .

[2]  Martha C. Anderson,et al.  Validation of GOES-Based Insolation Estimates Using Data from the U.S. Climate Reference Network , 2005 .

[3]  A. Prata.  A new long‐wave formula for estimating downward clear‐sky radiation at the surface , 1996 .

[4]  Zhanqing Li,et al.  Estimation of evaporative fraction from a combination of day and night land surface temperatures and NDVI: A new method to determine the Priestley-Taylor parameter , 2006 .

[5]  F. Tian,et al.  A comparison of methods for determining field evapotranspiration: photosynthesis system, sap flow, and eddy covariance , 2013 .

[6]  W. Maes,et al.  Estimating evapotranspiration and drought stress with ground-based thermal remote sensing in agriculture: a review. , 2012, Journal of experimental botany.

[7]  Minha Choi,et al.  Dual-model approaches for evapotranspiration analyses over homo- and heterogeneous land surface conditions , 2014 .

[8]  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 .

[9]  C. Willmott,et al.  A refined index of model performance , 2012 .

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

[11]  S. Running,et al.  Regional evaporation estimates from flux tower and MODIS satellite data , 2007 .

[12]  M. Tasumi.  Progress in operational estimation of regional evapotranspiration using satellite imagery , 2003 .

[13]  Y. Ryu,et al.  Evaluation of land surface radiation balance derived from moderate resolution imaging spectroradiometer (MODIS) over complex terrain and heterogeneous landscape on clear sky days , 2008 .

[14]  S. Tanahashi.  Improved Estimates of Hourly Insolation from GMS S-VISSR Data , 2000 .

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

[16]  W. James Shuttleworth,et al.  Solar radiation and evapotranspiration in northern Mexico estimated from remotely sensed measurements of cloudiness , 2001 .

[17]  Estimating evaporation from a wet grassland , 2007 .

[18]  W. Ju,et al.  Changes of evapotranspiration and water yield in China's terrestrial ecosystems during the period from 2000 to 2010 , 2013 .

[19]  Minha Choi,et al.  Seasonal trends of satellite-based evapotranspiration algorithms over a complex ecosystem in East Asia , 2013 .

[20]  Hiroshi Kawamura,et al.  Estimation of insolation over the Pacific Ocean off the Sanriku coast , 1998 .

[21]  M. S. Moran,et al.  Basin-scale solar irradiance estimates in semiarid regions using GOES 7 , 1994 .

[22]  Jerald A. Brotzge,et al.  Examination of the Surface Energy Budget: A Comparison of Eddy Correlation and Bowen Ratio Measurement Systems , 2003 .

[23]  S. Kizu,et al.  A study on thermal response of ocean surface layer to solar radiation using satellite remote sensing , 1995 .

[24]  Harden,et al.  Sensitivity of boreal forest carbon balance to soil thaw , 1998, Science.

[25]  Li Sun,et al.  Evapotranspiration from a freshwater marsh in the Sanjiang Plain, Northeast China , 2008 .

[26]  Adriaan A. Van de Griend,et al.  Bare soil surface resistance to evaporation by vapor diffusion under semiarid conditions , 1994 .

[27]  Gautam Bisht,et al.  Estimation and comparison of evapotranspiration from MODIS and AVHRR sensors for clear sky days over the Southern Great Plains , 2006 .

[28]  William P. Kustas,et al.  Use of remote sensing for evapotranspiration monitoring over land surfaces , 1996 .

[29]  Yoola Hwang,et al.  Implementation and Validation of Earth Acquisition Algorithm for Communication, Ocean and Meteorological Satellite , 2011 .

[30]  Richard G. Allen,et al.  Satellite-Based Energy Balance for Mapping Evapotranspiration with Internalized Calibration (METRIC)—Model , 2007 .

[31]  Minha Choi,et al.  Spatio‐temporal distribution of actual evapotranspiration in the Indus Basin Irrigation System , 2015 .

[32]  Yoola Hwang,et al.  Design and implementation of the flight dynamics system for COMS satellite mission operations , 2011 .

[33]  C. Gautier,et al.  A Simple Physical Model to Estimate Incident Solar Radiation at the Surface from GOES Satellite Data , 1980 .

[34]  G. Jia,et al.  Regional estimates of evapotranspiration over Northern China using a remote-sensing-based triangle interpolation method , 2013, Advances in Atmospheric Sciences.

[35]  Xuan Zhu,et al.  Pan evaporation modelling and changing attribution analysis on the Tibetan Plateau (1970–2012) , 2015 .

[36]  William P. Kustas,et al.  Tower and Aircraft Eddy Covariance Measurements of Water Vapor, Energy, and Carbon Dioxide Fluxes during SMACEX , 2005 .

[37]  W. Bastiaanssen,et al.  A remote sensing surface energy balance algorithm for land (SEBAL). , 1998 .

[38]  Christopher J. Watts,et al.  Use of satellite data to estimate radiation and evaporation for northwest Mexico , 1999 .

[39]  Seung Oh Lee,et al.  Estimation of instantaneous and daily net radiation from MODIS data under clear sky conditions: a case study in East Asia , 2012, Irrigation Science.

[40]  Gautam Bisht,et al.  Estimation of net radiation from the MODIS data under all sky conditions: Southern Great Plains case study , 2010 .

[41]  J. Wallace,et al.  Soil evaporation from tiger-bush in south-west Niger , 1997 .

[42]  J. D. Merritt,et al.  Testing energy balance closure with GOES‐retrieved net radiation and in situ measured eddy correlation fluxes in BOREAS , 1999 .

[43]  Martha C. Anderson,et al.  Solar radiation, longwave radiation and emergent wetland evapotranspiration estimates from satellite data in Florida, USA / Estimations à partir de données satellitales du rayonnement solaire, du rayonnement de grande longueur d’onde et de l’évapotranspiration d’une zone humide de Floride (EUA) , 2004 .

[44]  Tae-Woong Kim,et al.  Evapotranspiration estimation using the Landsat-5 Thematic Mapper image over the Gyungan watershed in Korea , 2011 .

[45]  Jennifer M. Jacobs,et al.  Evapotranspiration from a wet prairie wetland under drought conditions: Paynes prairie preserve, Florida, USA , 2002, Wetlands.

[46]  W. Brutsaert.  On a derivable formula for long-wave radiation from clear skies , 1975 .

[47]  H. Komatsu,et al.  Forest categorization according to dry‐canopy evaporation rates in the growing season: comparison of the Priestley–Taylor coefficient values from various observation sites , 2005 .

[48]  Renaud Mathieu,et al.  Validation of Global Evapotranspiration Product (MOD16) using Flux Tower Data in the African Savanna, South Africa , 2014, Remote. Sens..

[49]  Yuei-An Liou,et al.  Evapotranspiration Estimation with Remote Sensing and Various Surface Energy Balance Algorithms—A Review , 2014 .

[50]  X. Lee,et al.  Overview of ChinaFLUX and evaluation of its eddy covariance measurement , 2006 .

[51]  Gautam Bisht,et al.  Estimation of the net radiation using MODIS (Moderate Resolution Imaging Spectroradiometer) data for clear sky days , 2005 .

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

[53]  Richard G. Allen,et al.  Comparison of Latent Heat Flux Using Aerodynamic Methods and Using the Penman-Monteith Method with Satellite-Based Surface Energy Balance , 2014, Remote. Sens..

[54]  W. Brutsaert.  Land‐surface water vapor and sensible heat flux: Spatial variability, homogeneity, and measurement scales , 1998 .

[55]  Yong-Heack Kang,et al.  Estimation of Global Horizontal Insolation over the Korean Peninsula Based on COMS MI Satellite Images , 2013 .

[56]  Z. Su.  The Surface Energy Balance System ( SEBS ) for estimation of turbulent heat fluxes , 2002 .

[57]  Anzhi Wang,et al.  Comparison of three models to estimate evapotranspiration for a temperate mixed forest , 2008 .

[58]  Yan Zhang,et al.  A general predictive model for estimating monthly ecosystem evapotranspiration , 2011 .

[59]  Luiz Eduardo Oliveira E. Cruz de Aragão,et al.  A MODIS-Based Energy Balance to Estimate Evapotranspiration for Clear-Sky Days in Brazilian Tropical Savannas , 2012, Remote. Sens..

[60]  R. Jeu,et al.  Global canopy interception from satellite observations , 2010 .

[61]  Martha C. Anderson,et al.  GOES surface insolation to estimate wetlands evapotranspiration , 2002 .

[62]  Terri S. Hogue,et al.  Evaluation of a MODIS-Based Potential Evapotranspiration Product at the Point Scale , 2008 .

[63]  Keunchang Jang,et al.  Evaluation of Shortwave Irradiance and Evapotranspiration Derived from Moderate Resolution Imaging Spectroradiometer (MODIS) , 2009 .

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

[65]  C. Hepburn,et al.  Contributors to the frequency of intense climate disasters in Asia-Pacific countries , 2014, Climatic Change.

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

[67]  William P. Kustas,et al.  An intercomparison of three remote sensing-based surface energy balance algorithms over a corn and soybean production region (Iowa, U.S.) during SMACEX , 2009 .

[68]  J. Ardö,et al.  A Surface Temperature Initiated Closure (STIC) for surface energy balance fluxes , 2014 .

[69]  Kyung-Soo Han,et al.  Improved estimation of surface solar insolation using a neural network and MTSAT-1R data , 2010, Comput. Geosci..

[70]  A. Melesse,et al.  Evaporation and Evapotranspiration Measurement , 2013 .

[71]  Ryuichi Hirata,et al.  Mapping evapotranspiration using MODIS and MM5 Four-Dimensional Data Assimilation , 2010 .

[72]  John S. Kimball,et al.  Monitoring daily evapotranspiration in Northeast Asia using MODIS and a regional Land Data Assimilation System , 2013 .

[73]  Nicolo E. DiGirolamo,et al.  A biophysical process-based estimate of global land surface evaporation using satellite and ancillary data. I. Model description and comparison with observations , 1998 .

[74]  B. Choudhury,et al.  A BIOPHYSICAL PROCESS-BASED ESTIMATE OF GLOBAL LAND SURFACE EVAPORATION USING SATELLITE AND ANCILLARY DATA , 2000 .

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

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