Monitoring of Irrigation Schemes by Remote Sensing: Phenology versus Retrieval of Biophysical Variables

Nadia Akdim,Elijah Cheruiyot,Silvia Alfieri,Massimo Menenti,Abdeloihab Choukri,Adnane Habib,Kamal Labbassi

doi:10.3390/rs6065815

Abstract

The appraisal of crop water requirements (CWR) is crucial for the management of water resources, especially in arid and semi-arid regions where irrigation represents the largest consumer of water, such as the Doukkala area, western Morocco. Simple and (semi) empirical approaches have been applied to estimate CWR: the first one is called Kc-NDVI method, based on the correlation between the Normalized Difference Vegetation Index (NDVI) and the crop coefficient (Kc); the second one is the analytical approach based on the direct application of the Penman-Monteith equation with reflectance-based estimates of canopy biophysical variables, such as surface albedo (r), leaf area index (LAI) and crop height (hc). A time series of high spatial resolution RapidEye (REIS), SPOT4 (HRVIR1) and Landsat 8 (OLI) images acquired during the 2012/2013 agricultural season has been used to assess the spatial and temporal variability of crop evapotranspiration ETc and biophysical variables. The validation using the dual crop coefficient approach (Kcb) showed that the satellite-based estimates of daily ETc were in good agreement with ground-based ETc, i.e., R2 = 0.75 and RMSE = 0.79 versus R2 = 0.73 and RMSE = 0.89 for the Kc-NDVI, respective of the analytical approach. The assessment of irrigation performance in terms of adequacy between water requirements and allocations showed that CWR were much larger than allocated surface water for the entire area, with this difference being small at the beginning of the growing season. Even smaller differences were observed between surface water allocations and Irrigation Water Requirements (IWR) throughout the irrigation season. Finally, surface water allocations were rather close to Net Irrigation Water Requirements (NIWR).

Highlights

The interest for the assessment of irrigation performance using satellite data developed in the late1980s due to growing consensus on the difficulty of collecting the required ground data continuously, reliably and in a consistent way across all major irrigation schemes worldwide [1,2,3,4]
We have demonstrated the potential of using satellite remote sensing as a practical tool for crop water requirements (CWR) estimation for improved understanding of water use in major irrigation schemes such as the Doukkala
The study confirmed that crop water requirement (CWR) can be estimated with satisfactory accuracy using a generic algorithm, which does not require prior classification of crops

Summary

Introduction

The interest for the assessment of irrigation performance using satellite data developed in the late1980s due to growing consensus on the difficulty of collecting the required ground data continuously, reliably and in a consistent way across all major irrigation schemes worldwide [1,2,3,4]. The interest for the assessment of irrigation performance using satellite data developed in the late. On a higher level of abstraction, irrigation performance may be evaluated for different objectives such as equity, adequacy, or effectiveness [30,31,32]. We focus on the evaluation of adequacy by relating water allocation to water requirement. The most common and practical approach used for estimating crop water requirements (CWR) is the FAO-56 method (the Food and agricultural Organization of United States (FAO) Irrigation and Drainage Paper No 56) [33], based on the combination of reference evapotranspiration ET0 and crop coefficients (Kc) to determine crop evapotranspiration (ETc) under unrestricted water availability

Methods

Results

Conclusion