UNC-Chapel Hill GEOG 801 - A Coupled Remote Sensing and Simplified Surface Energy Balance Approach

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Abstract1. Introduction2. Methods2.1. Study sites2.2. Data Set Characteristics2.3. Procedures/Analysis3. Results and Discussion3.1. Kabul 13.2. Other Study Areas4. Discussion5. ConclusionsReferencesSensors 2007, 7, 979-1000 sensors ISSN 1424-8220 © 2007 by MDPI www.mdpi.org/sensors Full Research Paper A Coupled Remote Sensing and Simplified Surface Energy Balance Approach to Estimate Actual Evapotranspiration from Irrigated Fields Gabriel B. Senay 1,*, Michael Budde 2, James P. Verdin 3 and Assefa M. Melesse 4 1 SAIC, contractor to U.S. Geological Survey (USGS) Center for Earth Resources Observation and Science (EROS)/Geographic Information Science Center of Excellence (GIScCE), South Dakota State University, Sioux Falls, SD, USA. Work performed under USGS contract 03CRCN0001. E-mail: [email protected]; Tel: (605) 594-2758 2 SAIC/U.S. Geological Survey EROS, Sioux Falls, SD, USA. E-mail: [email protected]; Tel: (605) 594-2619 3 U.S. Geological Survey EROS, Sioux Falls, SD, USA. E-mail: [email protected]; Tel: (605) 594-6018 4 Department of Environmental Studies, Florida International University, Miami, FL, USA. E-mail: [email protected]; Tel: (305) 348-6518 * Author to whom correspondence should be addressed. Received: 14 May 2007 / Accepted: 12 June 2007 / Published: 15 June 2007 Abstract: Accurate crop performance monitoring and production estimation are critical for timely assessment of the food balance of several countries in the world. Since 2001, the Famine Early Warning Systems Network (FEWS NET) has been monitoring crop performance and relative production using satellite-derived data and simulation models in Africa, Central America, and Afghanistan where ground-based monitoring is limited because of a scarcity of weather stations. The commonly used crop monitoring models are based on a crop water-balance algorithm with inputs from satellite-derived rainfall estimates. These models are useful to monitor rainfed agriculture, but they are ineffective for irrigated areas. This study focused on Afghanistan, where over 80 percent of agricultural production comes from irrigated lands. We developed and implemented a Simplified Surface Energy Balance (SSEB) model to monitor and assess the performance of irrigated agriculture in Afghanistan using a combination of 1-km thermal data and 250-m Normalized Difference Vegetation Index (NDVI) data, both from the ModerateSensors 2007, 7 980Resolution Imaging Spectroradiometer (MODIS) sensor. We estimated seasonal actual evapotranspiration (ETa) over a period of six years (2000-2005) for two major irrigated river basins in Afghanistan, the Kabul and the Helmand, by analyzing up to 19 cloud-free thermal and NDVI images from each year. These seasonal ETa estimates were used as relative indicators of year-to-year production magnitude differences. The temporal water-use pattern of the two irrigated basins was indicative of the cropping patterns specific to each region. Our results were comparable to field reports and to estimates based on watershed-wide crop water-balance model results. For example, both methods found that the 2003 seasonal ETa was the highest of all six years. The method also captured water management scenarios where a unique year-to-year variability was identified in addition to water-use differences between upstream and downstream basins. A major advantage of the energy-balance approach is that it can be used to quantify spatial extent of irrigated fields and their water-use dynamics without reference to source of water as opposed to a water-balance model which requires knowledge of both the magnitude and temporal distribution of rainfall and irrigation applied to fields. Keywords: evapotranspiration, energy balance, SSEB, reference ET, irrigation 1. Introduction As reconstruction efforts in Afghanistan continue, the need for an accounting of the country’s water balance is necessary to address current and future water use scenarios. One aspect of the water balance equation involves an assessment of the water demands by irrigated agricultural lands. Since large and widely dispersed populations depend on rainfed and irrigated agriculture and pastoralism, large-area monitoring and forecasting are important inputs to such assessments. The Famine Early Warning Systems Network (FEWS NET), an activity funded by the United States Agency for International Development (USAID), employs a crop water-balance model (based on the water demand and supply at a given location) to monitor the performance of rainfed agriculture and forecast relative production before the end of the crop growing season. Although a crop water-balance approach is effective for monitoring rainfed agriculture [1, 2], irrigated agriculture is best monitored by other methods since the supply (water used for irrigation) is usually generated from upstream areas, which are distant from the demand location. The surface energy balance method has been successfully applied by several researchers [3-6] to estimate crop water use in irrigated areas. Their approach requires solving the energy balance equation at the surface (Equation 1) where the actual evapotranspiration (ETa) is calculated as the residual of the difference between the net radiation to the surface and losses due to the sensible heat flux (energy used to heat the air) and ground heat flux (energy stored in the soil and vegetation). LE = Rn - G - H (1) LE = Latent heat flux (energy consumed by evapotranspiration) (W/m2)Sensors 2007, 7 981 Rn = Net radiation at the surface (W/m2) G = Ground heat flux (W/ m2) H = Sensible heat flux (W/ m2) The estimation of each of these terms from remotely sensed imagery requires high quality data sets. Allen et al. [3] described the several steps required to estimate actual ET using the surface energy-balance method that employs the hot and cold pixel approach of Bastiaanssen et al. [4]. In summary, for the net radiation term, data on incoming and outgoing radiation and the associated surface albedo and emissivity fractions for shortwave and long wave bands are required. The ground heat flux is estimated using surface temperature, albedo, and normalized difference vegetation index (NDVI). The sensible heat flux is estimated as a function of the temperature gradient above the surface, surface roughness, and wind speed. Although solving the full energy-balance approach has been shown to give good results


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UNC-Chapel Hill GEOG 801 - A Coupled Remote Sensing and Simplified Surface Energy Balance Approach

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