Modeling Approaches for Determining Dripline Depth and Irrigation Frequency of Subsurface Drip Irrigated Rice on Different Soil Textures

• Main Authors: Gerard Arbat, Sílvia Cufí, Miquel Duran-Ros, Jaume Pinsach, Jaume Puig-Bargués, Joan Pujol, Francisco Ramírez de Cartagena
• Format: Article
• Language: English
• Published: MDPI AG 2020-06-01
• Series: Water
• Subjects: microirrigation; <i>Oriza sativa</i> L.; Onice; water productivity; simulation; HYDRUS-2D
• Online Access: https://www.mdpi.com/2073-4441/12/6/1724

Water saving techniques such as drip irrigation are important for rice (<i>Oriza sativa</i> L.) production in some areas. Subsurface drip irrigation (SDI) is a promising alternative for intensive cropping since surface drip irrigation (DI) requires a higher degree of labor to allow the use of machinery. However, the semi-aquatic nature of rice plants and their shallow root system could pose some limitations. A major design issue when using SDI is to select the dripline depth to create appropriate root wetting patterns as well as to reduce water losses by deep drainage and evaporation. Soil texture can greatly affect soil water dynamics and, consequently, optimal dripline depth and irrigation frequency needs. Since water balance components as deep percolation are difficult to estimate under field conditions, soil water models as HYDRUS-2D can be used for this purpose. In the present study, we performed a field experiment using SDI for rice production with Onice variety. Simulations using HYDRUS-2D software successfully validated soil water distribution and, therefore, were used to predict soil water contents, deep drainage, and plant water extraction for two different dripline depths, three soil textures, and three irrigation frequencies. Results of the simulations show that dripline depth of 0.15 m combined with one or two daily irrigation events maximized water extraction and reduced percolation. Moreover, simulations with HYDRUS-2D could be useful to determine the most appropriate location of soil water probes to efficiently manage the SDI in rice.