Abstract
A scheme for determining irrigation depth us-ing a numerical model of crop response to irrigation and quantitative weather forecast was presented. To optimize each irrigation depth, a concept of virtual income, which is proportional to an increment in transpiration amount dur-ing an irrigation interval, is introduced. A field experiment was carried out to evaluate effectiveness of the presented scheme in terms of net income considering the price of water. Potato was grown in summer season of 2015 us-ing a drip irrigation system in Arid Land Research Cen-ter, Tottori, Japan. Two treatments were conducted: auto-mated irrigation and proposed scheme with two replicates for each. Results indicated that predicted water content agreed well with observation although some underestima-tion of water content due to overestimation of transpiration was observed. Proposed scheme could save water by 27 %, while yield was increased by 15 %, resulting in higher net income as compared to automated irrigation. Based on these results together with previous works, we can con-clude that proposed scheme can at least realize similar net income to automated irrigation systems without high ini-tial investment.
