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Original Articles

Assimilation of satellite data into agrohydrological models to improve crop yield forecasts

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Pages 2523-2545 | Received 04 Oct 2007, Accepted 04 Mar 2008, Published online: 11 Jun 2009
 

Abstract

This paper addresses the question of whether data assimilation of remotely sensed leaf area index and/or relative evapotranspiration estimates can be used to forecast total wheat production as an indicator of agricultural drought. A series of low to moderate resolution MODIS satellite data of the Borkhar district, Isfahan (Iran) was converted into both leaf area index and relative evapotranspiration using a land surface energy algorithm for the year 2005. An agrohydrological model was then implemented in a distributed manner using spatial information of soil types, land use, groundwater and irrigation on a raster basis with a grid size of 250 m, i.e. moderate resolution. A constant gain Kalman filter data assimilation algorithm was used for each data series to correct the internal variables of the distributed model whenever remotely sensed data were available. Predictions for 1 month in advance using simulations with assimilation at a regional scale were very promising with respect to the statistical data (bias = ±10%). However, longer‐term predictions, i.e. 2 months in advance, resulted in a higher bias between the simulated and statistical data. The introduced methodology can be used as a reliable tool for assessing the impacts of droughts in semi‐arid regions.

Acknowledgements

This research in Borkhar district (Isfahan), Iran, was financed by the Iranian Ministry of Science, Research and Technology and was supported by the Agricultural Planning and Economic Research Institute in Iran, Iranian Soil and Water Research Institute in Esfahan. The authors would like to thank Prof. A. Alizadeh (Professor of the Irrigation Group at Ferdowsi University of Mashad, Iran), Dr A. Sharifi (Associate Professor at the Department of Urban–Regional Planning and Geo‐Information Management, International Institute for Geo‐Information Science and Earth Observation, ITC, The Netherlands) and M. Feizi and M. Fathi (Researchers at the Soil and Water Research Institute in Esfahan, Iran) for their help during the early phases of this research.

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