Determination of maize water requirement using remote sensing data and SEBAL algorithm

Mohammad Ismaeil Kamali, Rouzbeh Nazari

Research output: Contribution to journalArticlepeer-review

21 Scopus citations

Abstract

Efficient agricultural water demand management in arid and semi-arid regions is key in continuing crop production in a changing climate. As such, there's a need for further investigation on various crops to identify the optimum water requirements to avoid water wasting in regions that are already facing water shortage. The focus of this work is to determine water requirement maize farming Mazandaran Province in Northern Iran, located on the southern side of the Caspian Sea, using Landsat satellite data. In order to use SEBAL algorithm, the images were atmospheric calibrated. Evapotranspiration maps with RMSE values equals to 0.73, 1.38 and 0.74 mm/day were produced and compared to Reference Book (RB), National Water Document (NWD) and FAO56 values. Furthermore, by computing reference evapotranspiration, crop coefficient curve was evaluated. In order to prepare maize water requirement maps, ET0 in 58 weather stations throughout the province were computed and interpolated. By using the daily ET0 maps and resulted Kc values, maize water requirement maps for the cultivated area of the province were 345.16–383.99 mm. The maize water requirement in the observation station of Sari compared to RB and NWD values showed −%20 and +%41 differences and RMSE was 76 and 156 mm, respectively.

Original languageEnglish (US)
Pages (from-to)197-205
Number of pages9
JournalAgricultural Water Management
Volume209
DOIs
StatePublished - Oct 30 2018

All Science Journal Classification (ASJC) codes

  • Agronomy and Crop Science
  • Water Science and Technology
  • Soil Science
  • Earth-Surface Processes

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