JWSS - Journal of Water and Soil Science

Using a rough bed for spillway compare to common dissipation methods such as stilling basins, stepped spillways, ski jumps, and bed elements may be more efficient to boost energy dissipation. In this research, the impact of spillway continuous bed roughness on energy dissipation was investigated. For this purpose, a non-dimensional relationship was developed, and by calibrating the numerical model based on the present experimental study, energy dissipation over the spillway for three slopes of 15, 22.5, and 30 (degree) with six roughness sizes of 0.0, 0.005, 0.0072, 0.0111, 0.016, and 0.022 (m) and three discharges of 170, 110, and 90 (lit/s) was investigated. Based on the present results, using a rough bed spillway will increase energy dissipation. Also, the ratio of energy lost per meter length of rough bed spillway to that of smooth spillway increases by chute slope. The results showed that the highest amount of relative energy consumption in the presence of roughness was related to the slope of 22.5 degrees and 22.2 mm for roughness (85%), and the lowest relative energy consumption was observed in the control state (25%). As a result of the present study, a natural rough bed without concrete coating has befitted in terms of environmental aspects, construction cost, and energy loss.

The impact of different management options on the region and the existing conditions can be evaluated with minimal cost and time to select the most practical case using various tools including mathematical models. In this study, the SWAT hydrological model was performed from 2009 to 2019 using climatic, hydrological, and hydrometric data in the Malayer catchment, and the final model was validated by SWAT-CUP. To reduce the amount of uncertainty in the input parameters to the MODFLOW model, using the values of surface recharge from the implementation of the SWAT hydrological model, quantitative modeling of Malayer aquifer was performed more reliably in GMS software by using MODFLOW model. After modeling the study area in the 2009-2018 period and calibrating the model in the years from 2018 to 2019, the mean values of absolute error (MAE) were 0.35-0.65 m, and root means square error (RMSE) was 0.62-0.94 m, which seems acceptable considering computational and observational heads equal to 1650 m. Results of water level changes in observation wells located in the Malayer region indicate that the groundwater level in the aquifer has decreased by an average value of 9.7 m in the 10-year study period.

Drought is one of the most complex natural disasters due to its slow onset and long-term impact. Today, the use of remote sensing techniques and satellite imagery has been considered a useful tool for monitoring agricultural drought. The objective of the present study was to evaluate spatial and temporal monitoring of agricultural drought in the lake Urmia catchment area with the ETDI drought index which is calculated from Nova satellite images based on actual evapotranspiration from the SEBS algorithm and compared with the ground index SPI. For this purpose, 248 AVHRR sensor images and NOAA satellites during the statistical period of 1998-2000 and 17 meteorological stations with a statistical period of 30 years were used to calculate the indicators. To determine agricultural lands, six thousand points were marked for different uses and their actual evapotranspiration was calculated using the SEBS algorithm. The results showed that with the onset of the drought period in 1998, the ETDI index indicated 9.4% in weak drought conditions in May and 90.6% in normal conditions. Over time, in June of 1998, the situation was different with 95% in a weak drought situation and 5% in a normal situation for the city of Tabriz. In July, the entire catchment area experiences a slight drought. Then, in August, 84% of the basin is in normal condition and 16% in Tabriz and Urmia are declared weak drought. It was also founded that the ETDI drought index due to the combination of visible and infrared bands and its combination with terrestrial data has a physical meaning and has high certainty and predicts drought faster and more accurately.

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.

Individuals spend a lot of time indoors, thus they can generally be exposed to polycyclic aromatic hydrocarbons (PAHs) as a teratogen, mutagen, and carcinogen pollutants with the potential for environmental and also human health risks. Therefore, the current study was performed to analyze PAHs in household dust samples of the city of Khorramabad, Iran in 2019. A total of 50 indoor dust samples were collected from 10 sampling sites. After the extraction of analytes, the gas chromatography/mass spectrometry (GC–MS) method was used to determine PAHs in the studied samples. All statistical analyses were performed by SPSS software. The results showed that 16 priority PAHs were detected in the samples with the minimum, maximum, and mean values of 14.0, 23.3, and 19.2 µg/kg. Also, based on the results the mean contents of detected PAHs were lower than the maximum permissible concentration (MPC) established by MHWS and Iran DOE. In conclusion, due to exposure risks of PAHs, regular and periodic analysis of these pollutants in different environmental samples including soil, sediment, dust, particulate matter, air, water, and tissues of living organisms for environmental and human health maintenance is recommended.

Class A pan evaporation method as one of the most common methods for reference evapotranspiration (ET₀) estimation has been widely used in the world due to its simplicity, relatively low cost, and ability to estimate daily ET. In this study, the performance of 8 empirical methods consisting of Allen and Pruitt (1991), Cuenca (1989), Snyder (1992), modified Snyder, Pereira, et al. (1995), Orang (1998), Raghuwanshi and Wallender (1998), and FAO/56 were analyzed to estimate class A pan coefficient and ET₀ at Fasa synoptic station located in Fars province. The calculated pan evaporation coefficients from the above equations were compared with measured pan evaporation coefficients which were obtained from the ratio of evapotranspiration calculated by the FAO-Penman-Monteith method to the rate of evaporation from the pan. The results showed that all empirical methods did not predict pan coefficient values well (R² < 0.3 and NRMSE > 0.25). The comparison results between ET₀ from empirical methods and ET₀ obtained from FAO-Penman–Monteith indicated that the FAO/56 method had the best performance (R² = 0.72 and NRMSE = 0.3). To increase the accuracy of empirical pan coefficient equations, these equations were modified with eight years (2007-2015) of meteorological data from the Fasa synoptic station and validated using two years of independent data (2015-2017). The results showed that the accuracy of all empirical models was improved and the Cuenca equation with NRMSE = 0.16 and R²= 0.63 was selected as the best equation for pan coefficient estimation and ET₀ (R² =0.85; NRMSE =0.18) in Fasa region. The sensitivity analysis revealed that the estimated pan coefficient is more sensitive to wind speed, followed by relative humidity, fetch distance, the slope of the saturation vapor pressure curve, sunshine hours, and air pressure. According to statistical results and sensitivity analysis, an equation was expanded for the Fasa region and other areas with the same climate.

The land use change as well as changes in climatic parameters such as temperature increase affect many natural processes such as soil erosion and sediment production, floods, and degradation of physical and chemical properties of soil. Therefore, it is necessary to pay attention to different aspects of the effect of these changes in studies and macro decisions of the country. In the present study, the SWAT conceptual model was used to test and analyze the existing scenarios in the Marvast basin. After calibrating the model, the two scenarios were tested. The first scenario is in the field of agricultural management and conversion of gardens to agricultural lands and the second scenario is a 0.5-degree increase in temperature by assuming other conditions are constant. The calibration and validation results of the model with the Nash-Sutcliffe test showed 0.66 and 0.68 respectively, which indicate the acceptable performance of the model in the study area. Then, the results of using two scenarios of land use change and heating, especially in recent years showed the effect of 30 percent of the climate scenario on the increase of flooding in the basin. The scenario of changing the use of garden lands to agriculture in two cases of 20% and 50% change of use of 10% and 12% was added to the flooding of the basin. The results indicate that in similar areas of the study area which is located in a dry climate zone, a possible increase in temperature can have a significant effect on flooding in the basin. However, the indirect impact of the human factor in increasing greenhouse gases and flooding in the basin should not be ignored.

Reservoir dams have had problems despite all the benefits for humans. one of the most important issues is exposing a large amount of water in contact with the air causing a large amount of water to evaporate. Using chemical methods including heavy alcohols is one of the evaporation suppression methods. In this study, three emulsions of octadecanol, hexadecanol, and a combination of octadecanol, and hexadecanol along with Brij-35 and two physical methods of the canopy and floating balls were used to evaluate the performance of different emulsions. A one-way analysis of variance was applied to compare the mean of evaporation in different chemical and physical methods and a two-way analysis of variance was performed to investigate the main and interaction effects of different meteorological parameters on the value of evaporation. The mean comparison of the evaporation in different methods showed that the two physical methods of the canopy and floating balls had better performance than the chemical methods, and the octadecanol was more efficient than the two other chemical methods. The results of one-way ANOVA showed that among the chemical methods, the octadecanol had no significant difference with floating balls at a 99% probability level (P <0.01). Two-way ANOVA indicated that air temperature and relative humidity had the greatest effect on evaporation. Examination of the effect of different levels of meteorological parameters on the performance of evaporation reduction methods showed that at low temperatures, octadecanol had poor performance than the two physical methods but with increasing temperature, its performance improved. In addition, this monolayer had a suitable performance at low wind speeds compared to physical methods. By increasing wind speed, its performance is severely affected and its efficiency decreases. So, at temperatures above 37° C, an increase in wind speed from 3.5 m/s to above 8.7 m/s has increased evaporation by more than 50%. The effects of monolayers and other evaporation suppression methods on the quality characteristics of the water including dissolved oxygen are significant and should be investigated in future research.

Precipitation is one of the most significant climatic parameters; its distribution and values in different areas is the result of complex linear and nonlinear relationships between atmospheric elements-climatic processes and the spatial structure of the earth's surface environment. Classification of data and placing them in small and homogeneous zones can be effective in improving the understanding of these complex relationships and their results. In the present study, zoning and analyzing the distribution of rainfall in Iran concerning environmental factors was performed using the annual precipitation data of 3423 synoptic, climatological, and gauge stations in the country during the period from 1961 to 2015 and the altitude, slope, aspect, and station density data. After standardization and preparation of the data matrix, the optimal number of clusters was determined and the data set was entered into the neural-fuzzy network model (ANFIS-FCM). The results showed that the values of R²  and MAE  indices were 0.76 and 0.23, respectively which indicate the appropriate accuracy of the model. It was also found that in the four output zones of the model, environmental factors have a high impact on the spatial distribution of precipitation. In the first and third zones, the combination of high altitude and slope factors along with geographical proximity to precipitation systems has caused the average annual rainfall in these zones to be 318 and 181 mm, respectively. The mean annual rainfall has decreased to about 100 mm by the weakening of the role of environmental factors in the second and fourth clusters.