Abstract
This study aims to evaluate a remote sensing-based approach to allow estimation of the temporal and spatial distribution of crop evapotranspiration (ET) and irrigation water requirements over irrigated areas in semi-arid regions. The method is based on the daily step FAO-56 Soil Water Balance model combined with a time series of basal crop coefficients and the fractional vegetation cover derived from high-resolution satellite Normalized Difference Vegetation Index (NDVI) imagery. The model was first calibrated and validated at plot scale using ET measured by eddy-covariance systems over wheat fields and olive orchards representing the main crops grown in the study area of the Haouz plain (central Morocco). The results showed that the model provided good estimates of ET for wheat and olive trees with a root mean square error (RMSE) of about 0.56 and 0.54 mm/day respectively. The model was then used to compare remotely sensed estimates of irrigation requirements (RS-IWR) and irrigation water supplied (WS) at plot scale over an irrigation district in the Haouz plain through three growing seasons. The comparison indicated a large spatio-temporal variability in irrigation water demands and supplies; the median values of WS and RS-IWR were 130 (175), 117 (175) and 118 (112) mm respectively in the 2002–2003, 2005–2006 and 2008–2009 seasons. This could be attributed to inadequate irrigation supply and/or to farmers’ socio-economic considerations and management practices. The findings demonstrate the potential for irrigation managers to use remote sensing-based models to monitor irrigation water usage for efficient and sustainable use of water resources.
Highlights
Licensee MDPI, Basel, Switzerland.Irrigated agriculture is the main water consumer worldwide, accounting for about70% of all available fresh water [1]
The model was based on the well-known FAO56 dual crop coefficient approach [18], and we provide in the following a brief description of the main calculations focusing on the modifications implemented in the SAMIR tool
We assumed null values for Kcb and fc with the Normalized Difference Vegetation Index (NDVI) of bare soils extracted from the images, and at full cover, the corresponding NDVI was the maximum value extracted from the images [23,34,64]
Summary
Licensee MDPI, Basel, Switzerland.Irrigated agriculture is the main water consumer worldwide, accounting for about70% of all available fresh water [1]. Increasing pressure on available water resources, in semi-arid regions, due to population growth, climate change and competition from other economic sectors will affect the availability of water for irrigated agriculture in the future. In this context, assessing irrigation performance through accurate estimation of crop water use and improving irrigation water management using innovative. Monitoring crop water use is a critical component of effective water resource management, which provides a means to improve “water use efficiency”, an indicator specified in the UN Sustainable Development Goals (SDG 6.4) that should substantially increase by 2030 [2]
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