A New Temperature-Vegetation Triangle Algorithm with Variable Edges (TAVE) for Satellite-Based Actual Evapotranspiration Estimation
The estimation of spatially-variable actual evapotranspiration (AET) is a critical challenge to regional water resources management. We propose a new remote sensing method, the Triangle Algorithm with Variable Edges (TAVE), to generate daily AET estimates based on satellite-derived land surface temp...
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MDPI AG
2016-09-01
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| Series: | Remote Sensing |
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| Online Access: | http://www.mdpi.com/2072-4292/8/9/735 |
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| author | Hua Zhang Steven M. Gorelick Nicolas Avisse Amaury Tilmant Deepthi Rajsekhar Jim Yoon |
| author_facet | Hua Zhang Steven M. Gorelick Nicolas Avisse Amaury Tilmant Deepthi Rajsekhar Jim Yoon |
| author_sort | Hua Zhang |
| collection | DOAJ |
| description | The estimation of spatially-variable actual evapotranspiration (AET) is a critical challenge to regional water resources management. We propose a new remote sensing method, the Triangle Algorithm with Variable Edges (TAVE), to generate daily AET estimates based on satellite-derived land surface temperature and the vegetation index NDVI. The TAVE captures heterogeneity in AET across elevation zones and permits variability in determining local values of wet and dry end-member classes (known as edges). Compared to traditional triangle methods, TAVE introduces three unique features: (i) the discretization of the domain as overlapping elevation zones; (ii) a variable wet edge that is a function of elevation zone; and (iii) variable values of a combined-effect parameter (that accounts for aerodynamic and surface resistance, vapor pressure gradient, and soil moisture availability) along both wet and dry edges. With these features, TAVE effectively addresses the combined influence of terrain and water stress on semi-arid environment AET estimates. We demonstrate the effectiveness of this method in one of the driest countries in the world—Jordan, and compare it to a traditional triangle method (TA) and a global AET product (MOD16) over different land use types. In irrigated agricultural lands, TAVE matched the results of the single crop coefficient model (−3%), in contrast to substantial overestimation by TA (+234%) and underestimation by MOD16 (−50%). In forested (non-irrigated, water consuming) regions, TA and MOD16 produced AET average deviations 15.5 times and −3.5 times of those based on TAVE. As TAVE has a simple structure and low data requirements, it provides an efficient means to satisfy the increasing need for evapotranspiration estimation in data-scarce semi-arid regions. This study constitutes a much needed step towards the satellite-based quantification of agricultural water consumption in Jordan. |
| first_indexed | 2024-04-11T18:27:22Z |
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| language | English |
| last_indexed | 2024-04-11T18:27:22Z |
| publishDate | 2016-09-01 |
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| series | Remote Sensing |
| spelling | doaj.art-3a5e479d191441feaf55145bdf171c5a2022-12-22T04:09:35ZengMDPI AGRemote Sensing2072-42922016-09-018973510.3390/rs8090735rs8090735A New Temperature-Vegetation Triangle Algorithm with Variable Edges (TAVE) for Satellite-Based Actual Evapotranspiration EstimationHua Zhang0Steven M. Gorelick1Nicolas Avisse2Amaury Tilmant3Deepthi Rajsekhar4Jim Yoon5Department of Engineering, School of Engineering and Computing Sciences, Texas A&M University-Corpus Christi, Corpus Christi, TX 78412, USADepartment of Earth System Science, Stanford University, Stanford, CA 94305-2115, USADepartment of Civil Engineering and Water Engineering, Université Laval, Québec, QC G1V 0A6, CanadaDepartment of Civil Engineering and Water Engineering, Université Laval, Québec, QC G1V 0A6, CanadaDepartment of Earth System Science, Stanford University, Stanford, CA 94305-2115, USADepartment of Earth System Science, Stanford University, Stanford, CA 94305-2115, USAThe estimation of spatially-variable actual evapotranspiration (AET) is a critical challenge to regional water resources management. We propose a new remote sensing method, the Triangle Algorithm with Variable Edges (TAVE), to generate daily AET estimates based on satellite-derived land surface temperature and the vegetation index NDVI. The TAVE captures heterogeneity in AET across elevation zones and permits variability in determining local values of wet and dry end-member classes (known as edges). Compared to traditional triangle methods, TAVE introduces three unique features: (i) the discretization of the domain as overlapping elevation zones; (ii) a variable wet edge that is a function of elevation zone; and (iii) variable values of a combined-effect parameter (that accounts for aerodynamic and surface resistance, vapor pressure gradient, and soil moisture availability) along both wet and dry edges. With these features, TAVE effectively addresses the combined influence of terrain and water stress on semi-arid environment AET estimates. We demonstrate the effectiveness of this method in one of the driest countries in the world—Jordan, and compare it to a traditional triangle method (TA) and a global AET product (MOD16) over different land use types. In irrigated agricultural lands, TAVE matched the results of the single crop coefficient model (−3%), in contrast to substantial overestimation by TA (+234%) and underestimation by MOD16 (−50%). In forested (non-irrigated, water consuming) regions, TA and MOD16 produced AET average deviations 15.5 times and −3.5 times of those based on TAVE. As TAVE has a simple structure and low data requirements, it provides an efficient means to satisfy the increasing need for evapotranspiration estimation in data-scarce semi-arid regions. This study constitutes a much needed step towards the satellite-based quantification of agricultural water consumption in Jordan.http://www.mdpi.com/2072-4292/8/9/735evapotranspirationremote sensingtriangle methodwater stresswater resources |
| spellingShingle | Hua Zhang Steven M. Gorelick Nicolas Avisse Amaury Tilmant Deepthi Rajsekhar Jim Yoon A New Temperature-Vegetation Triangle Algorithm with Variable Edges (TAVE) for Satellite-Based Actual Evapotranspiration Estimation Remote Sensing evapotranspiration remote sensing triangle method water stress water resources |
| title | A New Temperature-Vegetation Triangle Algorithm with Variable Edges (TAVE) for Satellite-Based Actual Evapotranspiration Estimation |
| title_full | A New Temperature-Vegetation Triangle Algorithm with Variable Edges (TAVE) for Satellite-Based Actual Evapotranspiration Estimation |
| title_fullStr | A New Temperature-Vegetation Triangle Algorithm with Variable Edges (TAVE) for Satellite-Based Actual Evapotranspiration Estimation |
| title_full_unstemmed | A New Temperature-Vegetation Triangle Algorithm with Variable Edges (TAVE) for Satellite-Based Actual Evapotranspiration Estimation |
| title_short | A New Temperature-Vegetation Triangle Algorithm with Variable Edges (TAVE) for Satellite-Based Actual Evapotranspiration Estimation |
| title_sort | new temperature vegetation triangle algorithm with variable edges tave for satellite based actual evapotranspiration estimation |
| topic | evapotranspiration remote sensing triangle method water stress water resources |
| url | http://www.mdpi.com/2072-4292/8/9/735 |
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