4.7 Article

An innovative remote sensing based reference evapotranspiration method to support irrigation water management under semi-arid conditions

Journal

AGRICULTURAL WATER MANAGEMENT
Volume 131, Issue -, Pages 135-145

Publisher

ELSEVIER
DOI: 10.1016/j.agwat.2013.09.017

Keywords

Reference evapotranspiration; Remote sensing; Meteosat Second Generation; Penman-Monteith FAO56; Irrigation water requirements; AquaCrop

Funding

  1. Regional Government of Andalusia [P10-EXC10-0036/AGR-6126, PP.AVA.AVA201301.10]
  2. National Institute for Agricultural and Food Research and Technology (INIA) [RTA2011-00015-00-00]
  3. EUMETSAT within the framework of the LSA SAF

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Reference evapotranspiration (ETo) is an essential component of irrigation water management clue to it being a basic input for estimating crop water requirements. Multiple approaches have been identified for ETo assessment but most of them are based on daily meteorological data provided by weather station networks that provide an accurate. meteorological characterization. A new alternative approach called MA + LSE based on the Makkink-Advection (MAK-Adv) equation in combination with remotely sensed solar radiation and a numerical weather forecast of near surface air temperature has provided good estimates of ETo under different weather conditions in a semi-arid region located in Southern Spain. without requiring local meteorological data. In order to evaluate the utility of the MA + LSE approach for irrigation water management, some well-known methods for ETo assessment and the MA + LSE approach were considered for the development of irrigation schedules in ten irrigation schemes located in a semi-arid region in Southern Spain. The impact of the approach considered for ETo assessment on irrigation scheduling and on simulated yield for a maize crop was determined. Thus, MA + LSE and Hargreaves methods generated similar irrigation schedules and estimated yield to those determined by using ETo from the Penman-Monteith (PM-FAO56) approach. Thus, average seasonal irrigation volume estimated by MA + LSE was underestimated by around 2.6%, causing a yield reduction of 2.2% compared with the irrigation scheduling based on PM-FAO56. These results confirm the applicability of the MA + LSE approach, especially in areas where meteorological data are missing or inaccurate, obtaining a similar performance for irrigation water management to that of other approaches with high data requirements such as PM-FAO56. (C) 2013 Elsevier B.V. All rights reserved.

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