No abstract

Measurement of plant and soil indices as well as their combinations are generally used for irrigation scheduling and water stress management of crops and horticulture. Rapid and accurate determination of irrigation time is one of the most important issues of sustainable water management in order to prevent plant water stress. The objectives of this study are to develop baselines and provide irrigation scheduling relationships during different stages of black gram growth, determine the critical limits of plant and soil indices, and also determine the relationships between plant physiology and soil indices. This study was conducted in a randomized complete block design at the four irrigation levels 50 (I1), 75 (I2), 100 (I3 or non-stress treatment) and 125 (I4) percent of crop’s water requirement with three replications in Urmia region in Iran in order to irrigation scheduling of black gram using indices such as canopy temperature (Tc), crop water stress index (CWSI), relative water content (RWC), leaf water potential (LWP), soil water (SW) and penetration resistance (Q) of soil under one-row drip irrigation. The plant irrigation scheduling was performed by using the experimental crop water stress index (CWSI) method. The upper and lower baseline equations as well as CWSI were calculated for the three treatments of I1, I2 and I3 during the plant growth period. Using the extracted baselines, the mean CWSI values for the three treatments of I1, I2 and I3 were calculated to be 0.37, 0.23 and 0.15, respectively, during the growth season. Finally, using CWSI, the necessary equations were provided to determine the irrigation schedule for the four growing stages of black gram, i.e. floral induction-flowering, pod formation, seed and pod filling and physiological maturity, as (Tc − Ta)c = 1.9498 − 0.1579(AVPD), (Tc − Ta)c = 4.4395 − 0.1585(AVPD), (Tc − Ta)c = 2.4676 − 0.0578(AVPD) and (Tc − Ta)c = 5.7532 − 0.1462(AVPD), respectively. In this study, soil and crop indices, which were measured simultaneously at maximum stress time, were used as a complementary index to remove CWSI constraints. It should be noted that in Urmia, the critical difference between the canopy temperature and air temperature (Tc − Ta), soil penetration resistance (Q), soil water (SW) and relative water content (RWC) for the whole growth period of black gram were − 0.036 °C, 10.43 MPa and 0.14 cm3 cm−3 and 0.76, respectively. Ideal point error (IPE) was also used to estimate RWC, (Tc − Ta) and LWP as well as to select the best regression model. According to the results, black gram would reduce its RWC less through reducing its transpiration and water management. Therefore, it can be used as a low-water-consuming crop. Furthermore, in light of available facilities, the farmer can use the regression equations between the obtained soil and plant indices and the critical boundaries for the irrigation scheduling of the field.

In order to evaluate the ability of the crop water stress index to estimate grain yield and water productivity of maize and black gram in the climatic conditions of Urmia (Iran), research was conducted under the conditions of single-row drip irrigation. This study was conducted in a randomized complete block design with four irrigation levels including 50 (I 1), 75 (I 2), 100 (I 3) and 125 (I 4) percent of the water requirements of the plants with three replications. The mean crop water stress index values for the I 1 , I 2 and I 3 treatments were 0.53, 0.44, and 0.28, respectively during the growth period of maize, and 0.37, 0.23, and 0.15 for black gram, respectively. In the present study, the correlation between the crop water stress index and the grain yield and also the water productivity of maize and black gram was high. According to the results, the highest grain yield for maize and black gram was obtained at crop water stress index values of 0.28 and 0.15, respectively. Therefore, these values are recommended for the irrigation scheduling of the plants. It should be noted that the maximum water productivity index for maize and black gram was obtained at crop water stress index values of 0.44 (I 2) and 0.37 (I 1), respectively, which are the values recommended for irrigation scheduling under restricted access to water. K e y w o r d s: canopy temperature, crop yield, CWSI, phenolic and flavonoid compounds, water stress

Subsurface drip irrigation systems, compared to other irrigation systems (basin and furrow), enhance the delivery of water and nutrients directly into the root zone. The purposes of this study were to determine wetting front advancement in a subsurface drip irrigation and to compare the results with the HYDRUS 2D model simulation. In this study, the irrigation using T-Tape was carried out on a sandy-loam soil by two emitters at different irrigation times. The Wet moisture meter device was used to determine the soil water content. Evaluation of the simulated and measured soil water content was performed by using the adjusted determination coefficient (R 2), relative error (RE), and the normalized root mean square error (NRMSE). Based on the results, the NRMSE of soil water content prediction for the emitters at the depths of 20 and 40 cm was calculated to be in the range of 10 to 19 and 10 to 13 percent, respectively. Also, RE for the emitters at depths of 20 and 40 cm was in the range of-16 to-5 and 8 to 11 percent, respectively. The average R 2 for the emitters at depths of 20 and 40 cm was calculated to be 0.87 and 0.98, respectively. Also, five scenarios (F1, F2, T1, T2 and S1) were evaluated to assess the amount of water stored in the soil profile and water mass balance. The results indicated that the model could be used to predict the soil water content subsurface drip irrigation.

In this study, the performance of SWAP and FAO Aquacrop agro-hydrological models to predict water flow and salt transport in soil profile was evaluated under water and salt stresses during growing season of winter wheat.Field experiments were conducted with three levels of saline irrigation water including: S1, S2 and S3 corresponding to 1.4, 4.5 and 9.6 dSm -1 and four levels of irrigation depth including: I1, I2, I3 and I4 corresponding to 50, 75, 100 and 125 percent of crop water requirement with three replications for [2005][2006] period in Birjand region in Iran. The SWAP and Aquacrop models predicted the soil water content with an appropriate precision. The average normalized root mean square error (NRMSE) of calibration in soil water content prediction by SWAP and Aquacrop models, were calculated 4.81 and 18.91 %, respectively, and for validation, were calculated 7.34 and 19.6 %, respectively. The average normalized root mean square error (NRMSE) of calibration in ECe prediction by SWAP and Aquacrop models, were calculated 8.87 and 37.34 %, respectively, and for validation, were calculated 13.6 and 36.93 %, respectively. Results indicated that the Aquacrop model predicted ECe with more error compared with SWAP model.