Abstract
A new scheme to determine irrigation depths using a two-point of predicted cumulative transpiration over irrigation interval is presented. Rather than maximizing water use efficiency, this scheme aims to maximize net income. The volumetric water price is considered to give farmers an incentive to save irrigation water. A field experiment for soybeans was carried out in the Arid Land Research Center, Tottori University, Japan in 2019. The total irrigation amount yield and net income by the proposed scheme were compared to those by a tensiometer-operated automated irrigation. The scheme could save irrigation water by 16% with a yield increment of 20%; resulting in a 22% increase in net income compared to the automated irrigation. The model simulated the volumetric water content in the effective root zone of the plant in fair agreement. These results indicate the effectiveness of the proposed scheme that may replace an automated irrigation system even considering uncertainty in weather forecast to determine irrigation depth and secure investment costs.
Highlights
Irrigation is a vital practice for enhancing the global agricultural production under population growth and climatic change
We present a faster scheme to determine economically optimum irrigation depth assuming a trapezoidal relationship between irrigation depth and cumulative transpiration
Where Pc is the producer’s price of crop ($ kg−1 DM), ε is transpiration productivity of the crop (produced dry matter divided by cumulative transpiration), τi is cumulative transpiration between two irrigation events (1 mm = 10,000 kg ha−1 ), ki is the income correction factor, used to avoid underestimation of In due to smaller τi values in the initial growth stage compared to later growth stages; Pw is the price of water ($ kg−1 ), W is the irrigation depth (1 mm = 10,000 kg ha−1 ), and Cot is other costs ($ ha−1 )
Summary
Irrigation is a vital practice for enhancing the global agricultural production under population growth and climatic change. Water scarcity is getting serious as it threatens the future of world food production as more than 40% of the world’s population lives in areas experiencing high water stress [2]. Irrigation under such conditions will have to be managed most efficiently to achieve maximum productivity from limited water. In order to improve water productivity (WP), both irrigation amount and irrigation timing must be carefully determined considering weather, crop, and soil characteristics. This process is called irrigation scheduling (IS).
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