Field Evaluation of Irrigation Scheduling Strategies using a Mechanistic Crop Growth Model

Abstract

In a field experiment with white cabbage (Brassica oleracea L. var. capitata (L.) alef.) in Germany, three irrigation scheduling approaches were tested: (i) three sprinkler irrigation schedules based on soil water balance calculations using different development-dependent crop coefficients; (ii) automatic drip irrigation based on soil water tension thresholds; (iii) irrigation scheduling by real-time application of a partially calibrated mechanistic crop growth model. Multi-objective calibration was applied to derive a fully calibrated model as a diagnostic tool to identify the water loss terms of the individual irrigation strategies.The results of the experiment showed that: (i) high yields can be achieved with relatively low amounts of irrigation water (~100 mm), provided the optimal irrigation strategy and technique are applied; (ii) automated tension threshold-based drip irrigation outperformed soil water balance or crop growth model-based strategies; (iii) the soil water balance calculation approach relying on recommended K c factors led to an enormous overirrigation; (iv) the application of a partially calibrated crop growth model led to an underestimation of the crop water requirements in conjunction with an incorrect timing of irrigation events and therefore resulted in the lowest yields. The diagnostic model identified percolation, for the wet sprinkler irrigation treatments, and canopy evaporation, for the dry and model-based treatments, as major water loss sources; only minimal additional water was lost in the tension-controlled treatment. Copyright © 2016 John Wiley & Sons, Ltd. RESUMÉDans une expérience de terrain avec du chou blanc (Brassica oleracea convar capitata var. alba) en Allemagne, trois approches de calendriers d'irrigation ont été testées: (i) trois programmes d'irrigation par aspersion, fondés sur des calculs du bilan hydrique du sol basés sur des coefficients culturaux; (ii) une irrigation au goutte à goutte automatique basée sur des seuils de pression d'eau du sol; (iii) une irrigation par l'application en temps réel d'un modèle mécaniste de croissance des cultures partiellement calibré. Des calibrations multiples objectives ont été conduites pour dériver un modèle entièrement calibré, qui servira d'outil de diagnostic et d'identification des termes de perte d'eau résultant des stratégies individuelles d'irrigation.Les résultats de l'expérience ont montré que: (i) des rendements élevés peuvent être atteints avec des quantités relativement faibles d'eau d'irrigation (~100 mm), à condition que les calendriers optimaux et que les techniques adaptées soient appliquées; (ii) l'irrigation au goutte à goutte à seuil de tension automatique a surperformé les stratégies fondées bilan hydrique du ‹‹sol bas » sur le modèle de croissance des cultures; (iii) les méthodes basées sur le calcul de bilan hydrique du sol à partir des coefficients culturaux K c ont conduit à une énorme surirrigation; (iv) l'application d'un modèle de croissance des cultures partiellement calibrée a conduit à une ...

Assessment of Irrigation Scheduling Systems in Germany: Survey of the Users and Comparative Study

“…For this reason, irrigation scheduling systems should be compared more systematically based on field tests and benchmarking studies (Seidel et al, 2016). For this reason, irrigation scheduling systems should be compared more systematically based on field tests and benchmarking studies (Seidel et al, 2016).…”

“…Points indicate each system (S1-S6) and the mean values as indicated in the legend field assessment based on, for example, soil moisture measurements and crop yields, should be considered (Seidel et al, 2016). In this regard, a specific difference between the two test cases.…”

“…In this regard, a specific difference between the two test cases. Points indicate each system (S1-S6) and the mean values as indicated in the legend field assessment based on, for example, soil moisture measurements and crop yields, should be considered (Seidel et al, 2016).…”

“…These systems provide suggestions regarding irrigation depth and frequency in almost real time, based on integration of data and modelling approaches of different complexity (Jones, 2004;Greenwood et al, 2009;Seidel et al, 2016;Calera et al, 2017). These systems provide suggestions regarding irrigation depth and frequency in almost real time, based on integration of data and modelling approaches of different complexity (Jones, 2004;Greenwood et al, 2009;Seidel et al, 2016;Calera et al, 2017).…”

“…Irrigation scheduling systems are considered a valuable tool for supporting correct agricultural water management. These systems provide suggestions regarding irrigation depth and frequency in almost real time, based on integration of data and modelling approaches of different complexity (Jones, 2004;Greenwood et al, 2009;Seidel et al, 2016;Calera et al, 2017). Originally developed at universities and research centres, the systems have been adopted by several organizations and companies that now offer irrigation scheduling advice in many countries all around the world (Smith and Munoz, 2002).…”