JWSS - Journal of Water and Soil Science

Population growth, urbanization, and land use change have increased disastrous floods. Iran is also among the countries at high risk of floods. The latest examples of flood damage are the devastating floods of the spring of 2019 with significant mortality and financial losses in more than ten provinces of the country. The purpose of this study is to prepare an urban flood risk map of District 4 City Shiraz. The vulnerability of the region was made using PROMETHEE Ⅱ and COPRAS multi-criteria decision-making models and urban flood hazard zones were prepared by partial least squares regression (PLSR) and ridge regression (RR) models and a risk map was obtained by multiplying the vulnerability and hazard in ArcGIS software. The highest percentage of the study area in the PROMETHEE Ⅱ and COPRAS models belongs to the moderate class of vulnerability. The evaluation of the vulnerability models using Boolean logic and RMSE and MAPE statistics, showed that the COPRAS model provided better results than the PROMETHEE model. The results of partial least square regression (PLSR) and ridge regression (RR) models in flood risk modeling were analyzed by the Taylor diagram, which showed the superiority of the ridge regression (RR) model and the accuracy of this model in preparing urban flood hazard maps. The risk map of the study area indicated that 34% of the area (973 ha) is in the range of high and very high flood risk.

The objective of the present study was to conduct field studies for direct measurement of canola under farmers' management in one crop season (2019-2020) in 27 farms in Behbahan, Khuzestan province. Water requirement was calculated based on the FAO Penman-Monteith model using the daily statistics of the Behbahan synoptic meteorological station. A T-test was used to statistically compare the results such as the depth of irrigation and applied water productivity in the field in different irrigation systems. Linear multivariate regression analysis was used to investigate the effects of the independent variable on the dependent parameter of water productivity. The volume of applied water in the fields ranged from 4085.5 to 7865.3 m³/ha. The results of comparing the average yield of two irrigation systems in the t-test showed that the two sprinkler and surface irrigation systems with yields of 2614 and 2330 kg/ha, respectively, were not significantly different. Applied water productivity in traditional and modern irrigation systems was calculated to be 0.386 and 0.486 kg/m³, respectively, which had significant differences. The results of the analysis of variance in the regression model showed that among the independent variables, yield with t-statistic (23.997) and equivalent beta coefficient (0.880) had the most significant positive effect at a 1% level on applied water productivity. After that, the volume of applied water (irrigation water + effective rainfall) with a t-statistic of (-11.702) and a beta coefficient of equivalent (-0.793) had the most negative and significant effect at the level of 1% on the applied water productivity. The results of the Pearson correlation coefficient showed that irrigation events had a positive and significant correlation at a 5% level with applied water and yield. These correlations were 0.455 and 0.380, respectively. By increasing irrigation events, the volume of applied water has practically decreased and has become as close as the plant needs, and has increased water productivity.