Operational Precise Irrigation for Cotton Cultivation through the Coupling of Meteorological and Crop Growth Models

• Published in: Water resources management Vol. 31; no. 1; pp. 563 - 580
• Main Authors: Tsakmakis, I., Kokkos, N., Pisinaras, V., Papaevangelou, V., Hatzigiannakis, E., Arampatzis, G., Gikas, G.D., Linker, R., Zoras, S., Evagelopoulos, V., Tsihrintzis, V.A., Battilani, A., Sylaios, G.
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 2017; Springer Nature B.V
• Subjects: Agricultural production; Atmospheric models; Atmospheric Sciences; Canopies; Civil Engineering; Cotton; Crop growth; Crop yield; Crops; Cultivation; Drip irrigation; Earth and Environmental Science; Earth Sciences; Engineering; Environment; Environmental engineering; Evapotranspiration; Farmers; Geotechnical Engineering & Applied Earth Sciences; Gossypium hirsutum; Growth models; Hydrogeology; Hydrology/Water Resources; Irrigation; Irrigation scheduling; Irrigation systems; Laboratories; Mathematical models; Moisture content; Precipitation; Productivity; Remote sensing; Scheduling; Soil moisture; Soil water; Sprinkler systems; Studies; Traditional farming; Water; Water balance; Water content; Water demand; Water management; Water resources management; MED, Greece; Meteorological model; Irrigation scheduling; Precise irrigation; TAPM; AquaCrop; Crop growth model
• ISSN: 0920-4741; 1573-1650
• DOI: 10.1007/s11269-016-1548-7

In this paper, we tested the operational capacity of an interoperable model coupling system for the irrigation scheduling (IMCIS) at an experimental cotton ( Gossypium hirsutum L. ) field in Northern Greece. IMCIS comprises a meteorological model (TAPM), downscaled at field level, and a water-driven cultivation tool (AquaCrop), to optimize irrigation and enhance crop growth and yield. Both models were evaluated through on-site observations of meteorological variables, soil moisture levels and canopy cover progress. Based on irrigation management (deficit, precise and farmer’s practice) and method (drip and sprinkler), the field was divided into six sub-plots. Prognostic meteorological model results exhibited satisfactory agreement in most parameters affecting ET o , simulating adequately the soil water balance. Precipitation events were fairly predicted, although rainfall depths needed further adjustment. Soil water content levels computed by the crop growth model followed the trend of soil humidity measurements, while the canopy cover patterns and the seed cotton yield were well predicted, especially at the drip irrigated plots. Overall, the system exhibited robustness and good predicting ability for crop water needs, based on local evapotranspiration forecasts and crop phenological stages. The comparison of yield and irrigation levels at all sub-plots revealed that drip irrigation under IMCIS guidance could achieve the same yield levels as traditional farmer’s practice, utilizing approximately 32% less water, thus raising water productivity up to 0.96 kg/m 3 .