Abstract
The surface energy balance algorithm for land (SEBAL) has been demonstrated to provide accurate estimates of crop evapotranspiration (ET) and yield at different spatial scales even under highly heterogeneous conditions. However, validation of the SEBAL using in-field direct and indirect measurements of plant water status is a necessary step before deploying the algorithm as an irrigation scheduling tool. To this end, a study was conducted in a maize field located near the Venice Lagoon area in Italy. The experimental area was irrigated using a 274 m long variable rate irrigation (VRI) system with 25-m sections. Three irrigation management zones (IMZs; high, medium and low irrigation requirement zones) were defined combining soil texture and normalized difference vegetation index (NDVI) data. Soil moisture sensors were installed in the different IMZs and used to schedule irrigation. In addition, SEBAL-based actual evapotranspiration (ETr) and biomass estimates were calculated throughout the season. VRI management allowed crop water demand to be matched, saving up to 42 mm (−16%) of water when compared to uniform irrigation rates. The high irrigation amounts applied during the growing season to avoid water stress resulted in no significant differences among the IMZs. SEBAL-based biomass estimates agreed with in-season measurements at 72, 105 and 112 days after planting (DAP; r2 = 0.87). Seasonal ET matched the spatial variability observed in the measured yield map at harvest. Moreover, the SEBAL-derived yield map largely agreed with the measured yield map with relative errors of 0.3% among the IMZs and of 1% (0.21 t ha-1) for the whole field. While the FAO method-based stress coefficient (Ks) never dropped below the optimum condition (Ks = 1) for all the IMZs and the uniform zone, SEBAL Ks was sensitive to changes in water status and remained below 1 during most of the growing season. Using SEBAL to capture the daily spatial variation in crop water needs and growth would enable the definition of transient, dynamic IMZs. This allows farmers to apply proper irrigation amounts increasing water use efficiency.
Highlights
Agriculture is a major and inefficient consumer of fresh water and the competition with other sectors for water is likely to increase exponentially in the decades [1]
Soil texture and normalized difference vegetation index (NDVI) data were integrated in order to delineate the irrigation management zones (IMZs) using the aforementioned Management Zone Analyst software
The optimal number of management zones was selected based on the fuzziness performance index (FPI) and the normalized classification entropy (NCE) indices as shown in Figure 3 [29]
Summary
Agriculture is a major and inefficient consumer of fresh water and the competition with other sectors for water is likely to increase exponentially in the decades [1]. For this reason, a more reasonable and efficient use of water in agriculture is a crucial aspect in order to meet the food needs of the rapidly increasing world population [2,3]. Variable rate irrigation (VRI) has been demonstrated to provide better water use efficiency (WUE) while increasing crop yields [4,5,6]. ETc from agricultural areas is calculated by multiplying the reference evapotranspiration (ET0; [12]) by a constant crop coefficient without considering the possible ETc spatial variations in water or nutrient-limited zones ([13])
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