عنوان مقاله [English]
نویسندگان [English]چکیده [English]
About 80% of agricultural lands are irrigated with surface irrigation practices. In order to achieve proper irrigation management and taking into account the exact amount of infiltration, high efficiency irrigation has been considered. One of the physical characteristics of the soil that play an important role in the management and design of irrigation systems is infiltration. However, infiltration is of one of the most difficult and time consuming of soil physical parameters. Surface irrigation, especially furrow irrigation, is one of the most commonly used methods for irrigating crops around the word due to the low cost, low energy requirements and improved aeration of the root zone. The efficiency of surface irrigation is a function of the field design, infiltration characteristics of the soil and the irrigation management practices. However, the complexity of the interactions makes it difficult for irrigators to identify optimal design or management practices. The infiltration characteristic of the soil is one of the dominant factors in determining the performance of surface irrigation applications, and both spatial and temporal variations in the infiltration characteristic are a major physical constraint for achieving higher irrigation application efficiencies. There are some potential ways to reduce the amount of data required to determine the specific infiltration characteristic and characterize the general infiltration equation, using process of scaling. This approach formulates the relevant equation with the smallest possible number of variables and generalizes an infiltration equation for a broad range of applications. A real time control method can overcome these spatial and temporal variations. Also, a significant improvement in performance is achievable with real time optimization of individual irrigation events. The scaling process proposed for reducing the amount of data required to predict the infiltration characteristics for each furrow and each irrigation event and even for a whole field, with the purpose of real time irrigation management and control.
The aim of this study is to determine infiltration in furrow irrigation using real-time method of water in the furrows (with advance information) and the scaling factor. For determining infiltration variability in furrow irrigation, 3 different of soil textures was selected including: heavy texture (Isfahan Site with silty clay soil), Loam Texture (Karaj Site) and Sandy soil (Kerman Site). The infiltration rate of water in furrow irrigation, using scaling factor (dynamic) was estimated and applied for determining infiltration of advance data in the half of the furrow length. Finding a generalized solution for two dimensional infiltrations in furrow irrigation by scaling is a very useful way of reducing field data measurements required for prediction of the infiltration from irrigation advance. The proposed method was evaluated using data from 3 fields having different irrigation characteristics and for which extensive advance data were available.
Scaling factor is convenient and easy way for determining infiltration in furrow irrigation with advance data for proper irrigation management. The results showed, the average absolute error values (comparison scaling factor and measurement method) were 0.00556, 0.00215 and 0.00449), respectively in light texture (sandy loam), medium (loamy) and heavy (silty clay. Also root mean square error in all different soil types had low values and the agreement index of soil textures showed high values. The agreement index of sandy loam, loam and silty clay were 095, 0.96 and 0.94, respectively. High correlation (R2=0.90) and the proximity of the measured and obtained values of scaling factor with 1:1 line, indicating that the scaling factor is proper method for determining infiltration in furrow irrigation in different soil textures. Also, the strong correlations between the scaled and actual infiltrations clearly demonstrate the suitability of the scaling process for predicting the infiltration characteristics, while using only the minimum of field data. The statistical analyzed mentioned the scaling gives acceptable reproduction of the infiltration curves for the most furrows. The scaling will be successful (for the purpose of inclusion in a real time control system) if the mean and variability of the cumulative infiltration over the fields with different soil textures and/or over time is predicted successfully, i.e. if the statistical properties are predicted successfully. This implies that the irrigation performance for that field will also be predicted successfully, the confirmation of which is the subject of this paper. Consequently, this method could give good estimates of irrigation performance for the three fields so the proposed method could be suitable for use in real time control on different soil textures.