Improvements in irrigation system modelling when using remotely sensed ET for calibration

J. D. van Opstal; C. M. U. Neale; S. Lecina

doi:10.1117/12.2067565

29 October 2014 Improvements in irrigation system modelling when using remotely sensed ET for calibration

J. D. van Opstal, C. M. U. Neale, S. Lecina

Proceedings Volume 9239, Remote Sensing for Agriculture, Ecosystems, and Hydrology XVI; 92390P (2014) https://doi.org/10.1117/12.2067565
Event: SPIE Remote Sensing, 2014, Amsterdam, Netherlands

Abstract

Irrigation system modelling is often used to aid decision-makers in the agricultural sector. It gives insight on the consequences of potential management and infrastructure changes. However, simulating an irrigation district requires a considerable amount of input data to properly represent the system, which is not easily acquired or available. During the simulation process, several assumptions have to be made and the calibration is usually performed only with flow measurements. The advancement of estimating evapotranspiration (ET) using remote sensing is a welcome asset for irrigation system modelling. Remotely-sensed ET can be used to improve the model accuracy in simulating the water balance and the crop production. This study makes use of the Ador-Simulation irrigation system model, which simulates water flows in irrigation districts in both the canal infrastructure and on-field. ET is estimated using an energy balance model, namely SEBAL, which has been proven to function well for agricultural areas. The seasonal ET by the Ador model and the ET from SEBAL are compared. These results determine sub-command areas, which perform well under current assumptions or, conversely, areas that need re-evaluation of assumptions and a re-run of the model. Using a combined approach of the Ador irrigation system model and remote sensing outputs from SEBAL, gives great insights during the modelling process and can accelerate the process. Additionally cost-savings and time-savings are apparent due to the decrease in input data required for simulating large-scale irrigation areas.

Citation Download Citation

J. D. van Opstal, C. M. U. Neale, and S. Lecina "Improvements in irrigation system modelling when using remotely sensed ET for calibration", Proc. SPIE 9239, Remote Sensing for Agriculture, Ecosystems, and Hydrology XVI, 92390P (29 October 2014); https://doi.org/10.1117/12.2067565

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KEYWORDS

Systems modeling

Data modeling

Remote sensing

Agriculture

Modeling

Calibration

Earth observing sensors

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