JWSS - Journal of Water and Soil Science

Infiltration is the most important characteristic in the design and management of any surface irrigation system. Since the hydraulic of flow in meandering furrows is different from the standard furrows, the accuracy of infiltration function parameter estimation methods should be examined for the optimal design and management of meandering furrow irrigation. The main objective of this study was to compare Elliot and Walker’s two-point and two-time methods for estimating the empirical infiltration function parameters of meandering furrow irrigation using four sets of field data. The estimated infiltration functions, as obtained by the two methods, were validated by performing the unsteady flow simulations and using the Slow-change/slow-flow (SC/SF) model. The results showed that Elliot and Walker prediction of the advance trajectories (with a mean RMSE of 0.68 minutes) was comparable to the two-time method (with an average RMSE of 0.66 min). The Nash–Sutcliffe efficiency coefficient for the simulated outflow hydrograph by the two-time and two-point methods was 0.89 and 0.50, respectively, indicating the excellent predictive power of the two-times method. In addition, the two-time method predicted the total volume of infiltration with the less relative error (-1.5%), in comparison to the two-point method (-47.2%). Therefore, the use of post-advance data (such as a two-time method) for infiltration function parameters estimation improves the flow simulation in the meandering furrows.

Evaluation of groundwater hydro chemical characteristics is necessary for planning and water resources management in terms of quality. In the present study, a self-organizing map (SOM) clustering technique was used to recognize the homogeneous clusters of hydro chemical parameters in water resources (including well, spring and qanat) of Kerman province; then, the quality classification of groundwater samples was investigated for drinking and irrigation uses by employing SOM clusters. Patterns of water quality parameters were visualized by SOM planes, and similar patterns were observed for those parameters that were correlated with each other, indicating a same source. Based on the SOM results, the 729-groundwater samples in the study area were grouped into 4 clusters, such that the clusters 1, 2, 3, and 4 contained 73%, 6.2%, 6.7%, and 14.1% of groundwater samples, respectively. The increase order of electrical conductivity parameter in the clusters was as 1, 4, 3 and 2. The results of water quality index based on the entropy weighting (EWQI) showed that all of the samples with excellent and good quality (36.3% of samples) for drinking belonged to the cluster 1. According to the Wilcox diagram, 435-groundwater samples (81.7%) in the cluster 1 had the permitted quality for irrigation activities, and the other 285-groundwater samples were placed in all four clusters, indicating the unsuitable quality for irrigation. The Piper diagram also revealed that the dominant hydro chemical faces of cluster 1 were Na-Cl, Mixed Ca-Mg-Cl and Ca-HCO₃, whereas the clusters 2, 3, and 4 had the Na-Cl face. This study, therefore, shows that the SOM approach can be successfully used to classify and characterize the groundwater in terms of hydrochemistry and water quality for drinking and irrigation purposes on a provincial scale.

In the present study, the spatial and temporal changes of climate variables such as pan evaporation (Ep), temperature (T), relative humidity (RH), sunshine duration (SD), wind speed (W) and precipitation (P), as well as their relationship with altitude, were investigated. For this purpose, 68 meteorological stations with 30 years of data (1987-2016) throughout Iran on both seasonal and annual time scales were selected. Trend analysis of climate variables showed that over the past 30 years, most areas of Iran have become warmer and drier although all trends have not been significant. Investigation of the relationship between the trend slope of climate variables and altitude illustrated that there was no significant relationship between them during the study period on the annual time scale (p>0.1). However, in winter, the rate of increase in T (minimum, maximum and mean temperatures) and SD (p<0.1), as well as the rate of decrease in P (p<0.01), was significantly enhanced by increasing the altitude. The increase in mean and maximum T (p<0.1) and SD rates (p<0.001) in summer were significantly lower in the highlands than in the lowlands. In autumn, the trend slopes of minimum and mean T (p<0.05) were negatively correlated with altitude; in addition, the rates of increase in P and RH (p<0.05) in the highlands demonstrated a sharper increase. It seems, therefore, that most changes in climate variables have occurred in both autumn and winter. The results also showed that in winter, the highest rates of increase in Ts were related to the altitude of 1500-2000 m; however, the highest decrease in P belonged to the altitude of 2000-2500 m. In autumn, the highest rates of decrease in minimum and mean Ts had occurred in the altitude of 2000-2500 m; as well, he highest rate of increase in P was observed in the altitudes of both 0-500 m and 2000-2500 m.