Share Email Print

Proceedings Paper

Estimation of irrigation water requirements at irrigation district level using MODIS evapotranspiration product
Author(s): Giuseppe Peschechera; Nicola Lamaddalena; Umberto Fratino
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

An accurate Soil Water Balance (SWB) assessment is a crucial tool to guarantee efficient and sustainable management of water resources in agriculture, especially in the context of limited water availability. However, developing an SWB over large areas (i.e. irrigation district, river basin) requires a large number of input data obtained from expensive and timeconsuming field measurements. Remote sensing (RS) thus represents a valid source to retrieve the necessary biophysical vegetation’s parameters useful for estimating the SWB’s components. The main scope of this study is to set an operational large-scale SWB model, derived from an adaptation of FAO-56 model, and test its capacity to estimate the seasonal Irrigation Water Requirements (IWR) using as input a combination of in-situ agrometeorological measurements and MODIS derived evapotranspiration and vegetation’s parameters products. The SWB was assessed over the “Sinistra Ofanto” irrigation scheme (Italy), characterized by a semi-arid climate and an extremely fragmented and heterogeneous landscape with the presence of the most significant Mediterranean crops. The comparison of the estimated IWR with the water volumes provides by the Irrigation Consortium for the considerate two crop season (2015 and 2016) allows a first assessment about the SWB’s performance. Though the moderate spatial resolution of MODIS products (500 meters), the comparison demonstrates as the prosed SWB procedure has a good capability to estimate the IWR volumes at irrigation district scale in a simple and cost-effective way. Moreover, the SWB proposed exploits only free of charge products and thus can be easily applied in other contexts characterized by similar agroclimatic conditions and limited field data.

Paper Details

Date Published: 27 June 2019
PDF: 10 pages
Proc. SPIE 11174, Seventh International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2019), 111740H (27 June 2019); doi: 10.1117/12.2533475
Show Author Affiliations
Giuseppe Peschechera, Politecnico di Bari (Italy)
Nicola Lamaddalena, CIHEAM-Mediterranean Agronomic Institute of Bari (Italy)
Umberto Fratino, Politecnico di Bari (Italy)

Published in SPIE Proceedings Vol. 11174:
Seventh International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2019)
Kyriacos Themistocleous; Giorgos Papadavid; Silas Michaelides; Vincent Ambrosia; Diofantos G. Hadjimitsis, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?