Ground water and surface water under stress

Presented at Ground water and surface water under stress: competition, interaction, solutions: a USCID water management conference on October 25-28, 2006 in Boise, Idaho.Includes bibliographical references.The METRIC evapotranspiration (ET) estimation model was applied using MODIS (Moderate Resolution Imaging Spectroradiometer) satellite images in New Mexico to evaluate the applicability of MODIS images to ET estimation and water resources management. With the coarse resolution of MODIS (approximately 1km thermal resolution), MODIS was not found to be suitable for field-scale applications. In project and regional scale applications, MODIS has potential to contribute to ET estimation and water resources management. MODIS based ET maps for New Mexico were compared with Landsat based results for 12 dates. Average ET calculations using MODIS and Landsat applications were similar, indicating that MODIS images can be useful as an ET estimation tool in project and regional scale applications

Influence of Landsat Revisit Frequency on Time-Integration of Evapotranspiration for Agricultural Water Management

The objective of this study was to explore the improvement in accuracy of estimates for evapotranspiration (ET) over complete growing seasons and monthly periods, when more frequent Landsat imagery is made available. Conversely, we explored the reduction in accuracy in ET estimates when frequency of Landsat imagery was reduced. The study was implemented by conducting a series of METRIC applications for two Landsat WRS path overlap areas, one in southern Idaho (paths 39 and 40) during 2000, and a second one in Nebraska (paths 29 and 30) during 2002, years when two fully functioning satellites, Landsat 5 and Landsat 7, were in orbit. The results indicated that high frequency imagery provided by two satellites covering a WRS path overlap was more able to capture the impacts of rapid crop development and harvest, and evaporation associated by wetting events. That data set simulated a nominal four-day revisit time. Three-simulated 16-day revisit data sets created using a single Landsat series for a single path were unable to produce monthly and growing season ET due to the lack of sufficient number of images to even begin the time-integration process. This emphasizes the need to maintain two Landsat satellites in orbit and the high value of four-day revisit times. Limiting the data set to one path and two satellites (eight-day revisit) underestimated growing season ET accordingly by about 8% on average. Error in monthly ET was relatively high when image availability was limited to that for an eight-day revisit. This is due to the importance of timing of images to identify key inflection points in the ETrF curves and to capture special events such as wetting events from irrigation and rain or from water stress or cuttings, as in the case of forage crops. Results suggest that a four-day revisit time as represented by the full-run (run 1) of our analysis provides robustness in the development of time-integrated ET estimates over months and growing seasons, and is a valuable backstop for mitigation of clouded images over extended periods

Operational Remote Sensing of ET and Challenges

Satellite imagery now provides a dependable basis for computational models that determine evapotranspiration (ET) by surface energy balance (EB). These models are now routinely applied as part of water and water resources management operations of state and federal agencies. They are also an integral component of research programs in land and climat

Sensitivity of evapotranspiration retrievals from the METRIC processing algorithm to improved radiometric resolution of Landsat 8 thermal data and to calibration bias in Landsat 7 and 8 surface temperature

We made an assessment on the use of 12-bit resolution of Landsat 8 (L8) on evapotranspiration (ET) retrievals via the METRIC process as compared to using 8-bit resolution imagery of previous Landsat missions. METRIC (Mapping Evapotranspiration at high Resolution using Internalized Calibration) is an ET retrieval system commonly used in water and water rights management where the surface energy balance process is coupled with an extreme- end point calibration process to remove most impacts of systematic bias in remotely sensed inputs. We degraded L8 thermal images by grouping sequential digital numbers to reduce the apparent numerical resolution and then recomputed ET using METRIC and compared to nondegraded ET products. The use of 8-bit thermal data did not substantially impair the accuracy of ET retrievals derived from METRIC, as compared to the use of 12-bit thermal data. The largest error introduced into ET was \u3c1%. We also compared ET retrieved from images processed during the L8 and Landsat 7 (L7) March 2013 underfly to assess differences in ET caused by differences in signal to noise ratio (SNR) and scaling of the two systems. We evaluated the impact of bias in land surface temperature (LST) retrievals on ET determination using the CIMEC calibration approach (Calibration using Inverse Modeling using Extreme Member Calibration) employed in METRIC by introducing globally systematic biases into LST retrievals from L7 and L8 and comparing to ET from non-biased retrievals. The impacts of the introduction of both additive and multiplicative biases into surface temperature on ET were small for the three regions of the US studied, and for both L7 and L8 satellite systems. An independent study showed that METRIC-produced ET compared to within 3% of measured ET for the California site. The study assessed the impact of the February 2014 recalibration of L8 thermal data that caused a 3 K downward shift in LST estimation and changed reflectance values by about 0.7%. We found that the use of the recalibrated LST and shortwave data sets in METRIC did not change the accuracy of ET retrievals due to the automatic compensation for systematic biases employed by METRIC

METRIC-GIS: An advanced energy balance model for computing crop evapotranspiration in a GIS environment

A novel ArcGIS toolbox that applies the Mapping Evapotranspiration with Internalized Calibration model was developed and tested in a semi-arid environment. The tool, named METRIC-GIS, facilitates the pre-processing operations and the automatic identification of potential calibration and pixels review. The energy balance components obtained from METRIC-GIS were contrasted with those from the original METRIC version (R2 = 1; RMSE = 0 W m–2 or mm day–1 for ETc) Additionally, an irrigated scheme located at southern Spain was considered for assessing Kc variability in the maize fields with METRIC-GIS. The identified spatial variability was mainly due to differences in irrigation regimes, crop management practices, and planting and harvesting dates. This information is critical for developing irrigation advisory strategies that contribute to the area sustainability. The developed tool facilitates data input introduction and reduces computational time by up to 50%, providing a more user-friendly alternative to other existing platforms that use METRIC

EEFlux: A Landsat-based Evapotranspiration mapping tool on the Google Earth Engine

“EEFlux” is an acronym for ‘Earth Engine Evapotranspiration Flux.’ EEFlux is based on the operational surface energy balance model “METRIC” (Mapping ET at high Resolution with Internalized Calibration), and is a Landsat-imagebased process. Landsat imagery supports the production of ET maps at resolutions of 30 m, which is the scale of many human-impacted and human-interest activities including agricultural fields, forest clearcuts and vegetation systems along streams. ET over extended time periods provides valuable information regarding impacts of water consumption on Earth resources and on humans. EEFlux uses North American Land Data Assimilation System hourly gridded weather data collection for energy balance calibration and time integration of ET. Reference ET is calculated using the ASCE (2005) Penman-Monteith and GridMET weather data sets. The Statsgo soil data base of the USDA provides soil type information. EEFlux will be freely available to the public and includes a web-based operating console. This work has been supported by Google, Inc. and is possible due to the free Landsat image access afforded by the USGS

Evapotranspiration Using a Satellite-Based Surface Energy Balance with Standardized Ground Control

This study evaluated the potential of using the Surface Energy Balance Algorithm for Land (SEBAL) as a means for estimating evapotranspiration (ET) for local and regional scales in Southern Idaho. The original SEBAL model was refined during this study to provide better estimation of ET in agricultural areas and to make more reliable estimates of ET from other surfaces as well, including mountainous terrain. The modified version of SEBAL used in this study, termed as SEBALID (lD stands for Idaho) includes standardization of the two SEBAL anchor pixels, the use of a water balance model to track top soil moisture, adaptation of components of SEBAL for better prediction of the surface energy balance in mountains and sloping terrain, and use of the ratio between actual ET and alfalfa reference evapotranspiration (ETr) as a means for obtaining the temporal integration of instantaneous ET to daily and seasonal values. Validation of the SEBALID model at a local scale was performed by comparing lysimeter ET measurements from the USDA-ARS facility at Kimberly, Idaho, with ET predictions by SEBAL using Landsat 5 TM imagery. Comparison of measured and predicted ET values was challenging due to the resolution of the Landsat thermal band (120m x 120 m) and the relatively small size of the lysimeter fields. In the cases where thermal information was adequate, SEBALID predictions were close to the measured values of ET in the lysimeters. Application of SEBALID at a regional scale was performed using Landsat 7 ETM+ and Landsat 5 TM imagery for the Eastern Snake Plain Aquifer (ESP A) region in Idaho during 2000. The results indicated that SEBALID performed well for predicting daily and seasonal ET for agricultural areas. Some unreasonable results were obtained for desert and basalt areas, due to uncertainties of the prediction of surface parameters. In mountains, even though validation of results was not possible, the values of ET obtained reflected the progress produced by the refinements made to the original SEBAL algorithm

Estimation of Actual Evapotranspiration along the Middle Rio Grande of New Mexico Using MODIS and Landsat Imagery with the METRIC Model

Estimation of actual evapotranspiration (ET) for the Middle Rio Grande valley in central New Mexico via the METRIC surface energy balance model using MODIS and Landsat imagery is described. MODIS images are a useful resource for estimating ET at large scales when high spatial resolution is not required. One advantage of MODIS satellites is that images having a view angle < ~15° are potentially available about every four to five days. The main challenge of applying METRIC using MODIS is the selection of the two calibration conditions due to the low spatial resolution of MODIS. A calibration procedure specific to MODIS is described that utilizes the higher vegetation index areas of the image along with a consistently low ET location to develop the estimation function for sensible heat flux. This paper compares ET images for the Rio Grande region as produced by both MODIS and by Landsat. Application of METRIC energy balance processes along the Middle Rio Grande using MODIS imagery indicates that one can successfully produce monthly and annual ET estimates that are similar in value to those obtained using Landsat imagery if a cross-calibration scheme is considered. However, spatial fidelity is degraded

Información Investigador: Trezza Peña, Ricardo

http://webdelprofesor.ula.ve/nucleotrujillo/rtrezza/Resumen Curricular Ing. Agrícola (NURR-ULA); Magíster Scientiae en Ing. de Riego y Drenaje (CIDIAT-ULA); Doctor (PhD) en Ingeniería Agrícola y Biológica (Utah State University, EE.UU, 2002); Consultor en Riego y Drenaje (International Irrigation Center, Utah State University, USA, 2001); Graduated Research Assistant (University of Idaho, USA, 2001-2003); Investigador Visitante (University of Idaho, EE.UU, 2004); Profesor Visitante (University of Idaho, EE.UU, 2005 #150; 2006).Doctorado7111II - 2007; I - 2005191 - 2007; 27 - 2005; 17 - 2003Teledetección (Sensores Remotos), Ingeniería de Riego y Drenaje, Meteorología Agrícola, Micrometeorología, Hidrología, Manejo de Recursos Hídricos.Febrero de 2008Ing. AgrícolaNúcleo Rafael Rangel (NURR)[email protected]

Evapotranspiration from a remote sensing model for water management in an irrigation system in Venezuela

Artículo Publicado en Interciencia, junio año/vol 31, Nº 6, 2006, pp. [email protected] monográfic