JWSS - Journal of Water and Soil Science

The purpose of this study was to model biomass with soil parameters in Hir-Neur rangelands of Ardabil Province. Initially, considering the vegetation types and different classes of environmental factors, at the maximum vegetative growth stage, using one square meter plot, biomass was estimated by clipping and weighing method. For each transect, a soil sample was taken and transferred to the soil laboratory and the various parameters were measured by conventional methods. The relationship between soil factors and the rangeland biomass was analyzed and simulated using linear multiple regression. Among the measured soil factors, the Silt, EC, Ca, K_soluble, OC, POC, pH, Mg, TNV, clay, P, and volumetric moisture had the highest effect and percentage of biomass forecast (p<0.01). The accuracy of the simulated maps was analyzed using RMSE criteria and for grasses, forbs, shrubs, and total biomass were equal to 0.81, 0.65, 0.34, and 0.46, respectively. The results of this study, not only point out the importance of soil factors on the biomass but also as a baseline data for managing rangelands, supply-demand, and carbon balance can be used in the current section.

The FAO Penman-Monteith is a baseline method to estimate reference evapotranspiration. In many cases, it is difficult to access all data, so replacing simpler models with ‎lower input data and appropriate accuracy is necessary. ‎ The purpose of this study is to investigate the capability of the experimental ‎models, gene expression programming, stepwise regression, and Bayesian network in estimating ‎reference evapotranspiration.‎ In this research, daily information of the Boroujerd synoptic station in the period of 1996 -2017 was used as model inputs. ‎Based on the correlation between input and output parameters, six input patterns were ‎determined for modeling. The results showed that the Kimberly-Penman model has the ‎best performance among the experimental models.‎ Gene expression programming with fourth pattern ‎‎and Default Model Operators (R² = 0.98 and RMSE = 0.9), Bayesian Network with sixth pattern (R²=0.91 and RMSE = 1.01), and stepwise regression with sixth pattern have the most accurate patterns at R² = 0.91 and RMSE = 0.9 in the ‎training stage.‎ Comparison of the performance of the three models showed that the gene expression ‎programming model was superior to the other two models with the Average Absolute Relative Error (AARE) of 0.12 and the Mean Ratio (MR) of 0.94.‎ The results showed that gene expression programming had an acceptable ability to estimate ‎reference evapotranspiration under the weather conditions of Boroujerd and could be introduced as a ‎suitable model.‎

In this study, spatial-temporal variation of dust deposition rate in the western and eastern half of Tehran and its climatic parameters affecting were studied. At 34 points in the city, dust samples were collected by glass traps from the roof, for twelve months, and the climatic data were obtained and analyzed from relevant organizations. The highest deposition rate is in the western half of the city and its total amount has varied from 54.52 to 121.21 g/m²/y. In both halves of the city, summer has the highest dust deposition rate and its central areas have the highest amount. There were significant positive correlations between dust deposition rate with temperature and medium wind speed, and there were significant negative correlations between dust deposition rate with rainfall and relative humidity in all months, which justifies the high dust deposition rate in the dry seasons of the year. The results of stepwise regression showed that rainfall was the most important factor affecting the dust deposition rate in both halves of the city. The city of Tehran has a special geographical location the presence of mountains like a barrier has prevented dust from leaving the city and the air inlet corridor of Tehran has faced problems due to the expansion of building construction and high-rise building. Other factors affecting the rate of dust deposition in this city, in addition to the distance from the main source of dust production, atmospheric parameters can be mentioned the existence of barren lands around the city, vegetation cover, construction operations, and traffic.

Delineation of gully erosion susceptible areas by using statistical models, as well as optimum usage of existing data and information with the least time and cost and more precision, is important. The main objective of this study is to determine the areas accuracy to gully erosion and susceptibility mapping by using data mining of the bivariate Dempster-Shafer, linear multivariate statistical methods and their integration in Semirom watershed, southern Isfahan province. First, the geographical location of a total of 156 randomly gullies were mapped using preliminary reports, satellite imagery interpretation and field survey. In the next step, 14 conditioning parameters of the gullies in the study area were selected including the topographic, geomorphometric, environmental, and hydrologic parameters using the regional environmental characteristics and the multicollinearity test for modeling. Then, the Dempster-Shafer statistical, linear regression, and ensembled methods were developed using 70% of the identified gullies and 14 effective parameters as dependent and independent variables, respectively. The remaining 30% of the gully distribution dataset were used for validation. The results of the multivariate regression model showed that land use, slope and distance to drainage network parameters have the most significant relation to gully occurrence. The gully erosion susceptibility maps were prepared by individual and ensemble methods and they were divided to 5 classes of very low to very high rate. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve was used to validate gully erosion susceptibly maps. The verification results showed that the AUC of ensemble method (0.948) is higher than Dempster-Shafer (0.924) and Multivariate regression (0.864) methods. Also, the the seed core area index (SCAI) value of the ensembled model from very low to very high susceptible classes have a decreasing trend that indicating a proper separation of susceptible classes by this model.

Soil classification in a standard system is usually defined based on information obtained from properties and their variations in different map units. The aim of this study was to compare soil genesis and morphological characteristics in different landforms with WRB and Soil Taxonomy (ST) Systems. From nine studied profiles, six profiles were selected as representative profiles and dug in Colluvial fans, Piedmont plain, and Alluvial plain physiographic units, respectively. Then, the soils were classified according to the pattern of the two systems. Also, variation analysis of variance (ANOVA) and comparing means were used to quantify interested soil properties. The results of soil physio-chemical properties at different landform positions were significant based on analysis of variance of the effect of physiographic units and soil depth at the level of 1 %. Soil classification results based on WRB indicated that WRB were recognized four reference soil groups (RSG) included Regosols, Cambisols, Calcisols, and Gleysols at the first level of WRB classification in comparison of ST with recognizing two order Entisols and Inceptisols could separate more soils. The soils were located on the alluvial plain with a high groundwater level in the WRB due to the creation of restrictive conditions for root development in contrast to the ST called “Aquepts” in the suborder level but in a WRB is classified as the “Gleysols” RSG. On the other hand, ST, unlike WRB, used the Shallow criteria at the family level to describe the shallowness of soils and the limitations of root development. Generally, the efficiency of each system varies despite the differences in their structure and depending on the purpose of using them.

Land use changes identifying to assess and monitor sensitive areas for sustainable planning and land management is essential. Remote sensing and the use of GIS technology as some of the most common methods in the world in monitoring land changes, especially, in the study of large areas. In this study, the trend of spatial land use changes in the area of Karun 3 dam was investigated. in the before and after the construction periods and dam intake using remote sensing and GIS over 27 years. In this study, the satellite imagery of Landsat 5 TM sensors from 1991 and 2008 and Landsat 8 OLI sensors in 2018 were analyzed and processed. Using object-oriented classification with land use maps for the three periods 1991, 2008, and 2018 with the overall accuracy of the Kappa index of 0.93 and 0.89 percent for 1991, 0.94, and 0.88 percent in 2008 and 0.93, respectively, and 0.86% in 2018 was prepared. The results showed that the water use of the region with an area of 37.68 square kilometers is increasing and agricultural lands and residential areas with an area of 1349.04 and 226.56, respectively, forest lands with an area of 1041.49 remained as the dominant cover of the region and rangelands by going through a decreasing trend of increase in both periods after forest use, with an area of 878.87, they had the largest area. According to the obtained results, it can be said that the construction of the Karun 3 dam has caused the flooding of agricultural lands and their conversion to another use, as a result of which the villagers were forced to migrate due to losing their jobs and abandoned residential areas become other uses.

Increasing crop production per unit volume of water consumption requires recognizing the most dependent variable in drip irrigation to the volume of water consumption and also identifying the most important variables independent of water productivity in surface and subsurface drip irrigation for optimal use of available water resources. The present research was carried out in Behbahan Agricultural Research Station during four cropping seasons (2013-2017) on a Kabkab date variety. Experimental treatments include the amount of water in the subsurface drip irrigation method based on two levels of 75% and 100% water requirement and in surface drip irrigation based on 100% water demand. Data were analyzed using a randomized complete block design with three replications. The results of the analysis of variance of the mean of different irrigation treatments in quantitative traits showed that the effect of irrigation was significant at the level of 1% in terms of cluster weight index, fruit weight, and fruit flesh to kernel weight ratio. The results of regression analysis of variance showed that in the dependent variable of cluster weight, the consumption water volume explained 19.1% (R2 = 0.191) of the fluctuations of the dependent variable (cluster weight). Among all the studied variables, the volume of water consumption explained the most significant changes in date cluster drying. Fruit moisture with t (2.096) and equivalent beta coefficient (0.046) had a significant positive effect on water productivity at the level of 5%. The results of the Pearson correlation coefficient showed that the effect of yield on changes in water productivity was much greater than the volume of water consumed so the yield caused significant changes in water productivity. While the effect of water consumption on water productivity was not significant.

The optimal strategy selection is an influential factor to enhance the efficiency of land reclamation projects. On the other hand, the process of desertification of the land during environmental degradation is the consequence of the interaction between various factors that make it challenging to select appropriate solutions. Therefore, this study aimed to provide systematic optimization strategies in the form of a group decision-making model in the Yazd-Khezrabad plain. The important strategies were identified using the Delphi model. Then, the alternative initial ranking was formed by Cook and Seiford method framework using the vote taken from the decision makers on strategies. Finally, by estimating the linear distance of each option and including the matrix of the intervals, the last priority of the strategies was obtained from solving the assignment problem. The results indicated that the strategies of "prevent land use inappropriate change" (A18) and "the regeneration of vegetation cover" (A23) with Value=1 and Reduced Cost=0, were identified as the most important combating-desertification strategies in the region, respectively. The results of this study help desert managers to utilize limited facilities and capital dedicated to controlling the desertification process efficiently and effectively.

This study was conducted to investigate the effects of climate change on temperature and precipitation changes in important synoptic weather stations in Yazd province (including Yazd, Bafgh, Marvast, and Robat-e-Poshtebadam). Accordingly, a combination of the outputs of the latest AOGCM models presented in the IPCC sixth assessment report (CMIP6) were used to increase the accuracy of temperature and precipitation forecasts. A weighting method was used based on the Kling-Gupta combined index (KGE) to combine these models. After weighting the models, the monthly temperature and precipitation changes were calculated based on SSP126, SSP245, and SSP585 emission scenarios. Then, daily temperature and precipitation time series were extracted for different weather stations using the LARS-WG downscaling model. The results showed that in all the weather stations, CanESM5 and BCC-CSM2-MR models have the best ability to simulate the temperature and precipitation of the historical period, respectively. Results also showed that in all emission scenarios, the annual temperature will increase and the annual precipitation will decrease. The annual temperature of this region will increase between 0.2 to 0.6 °C, and the annual precipitation will decrease between 2.9 and 13.7% in different weather stations. Also, the maximum temperature increase and precipitation decrease in this region, will occur in spring and autumn, respectively.

In the last decade, the use of gabion structures in hydraulic engineering for stabilizing the structure due to its high density and weight has become widespread. Also, the material's roughness and porosity cause it to be used in energy dissipation and drainage projects. This study evaluates the relative energy dissipation of gabion structures downstream of the ogee spillway in the conditions of a submerged hydraulic jump. The evaluated parameters in this study were Froude number, gabion height, gabion thickness, and material diameter. The experiments were performed with three average diameters of 1.5, 2.2, and 3 cm for rock material, three gabion heights of 10 and 20 cm, and Max. The end sill heights were 10, 20, and 30 cm. The operated discharges were regulated from 20 to 40 l/s. The results showed that by decreasing the average diameter of gabion aggregates, the amount of relative energy dissipation increases in all tested models, so that in gabion with a 1.5 cm average diameter of aggregates, the amount of energy dissipation increased by 3.6% in comparison with using the diameter of 3cm for the average diameter of the material. Increasing the height of the gabion to the extent that the flow is entirely inward can have up to 33% more relative energy dissipation than the gabion with a height of 10 cm. Also, by increasing the diameter of the gabion from 10 cm to 30 cm, relative energy dissipation increases up to 15%.

The existence of silty sand in the infrastructure under concrete constructions, hydraulic structures, and irrigation systems has always caused challenges. Improving this kind of soil is always a challenging approach to increase compressive strength and shear stress. There is a conception that adding some extra material such as concrete can increase the stability of this soil against contributed forces. The present study investigated the effects of curing time (3, 7, 14, 21, and 28 days) and different percentages of various additives (3%, 5%, and 7%) on the strength of the silty sand soils. A series of laboratory tests were carried out to measure the Uniaxial Compressive Strength (UCS) and California Bearing Ratio (CBR) by evaluating the effect of additives on the strength parameters of silty sand soil. In total, 299 experimental tests have been conducted in the soil mechanics laboratory of SRBIAU. Results indicated that adding additives such as concrete to silty sand soil improved significantly the compressive strength and shear strength. The comparisons among the experimental test illustrate that due to increasing the curing time, the aforementioned parameters were increased significantly; however, Confix and Bentonite aggregates did not have a marginal effect on the compressive strength and shear strength. Also, after the 21^st day of the curing time, the rate of increment of the UCS and CBR reached slightly and then attained a constant value. Also, after this duration, the curing time is an independent factor in the variation of the UCS and CBR tests. Furthermore, the addition of 5% Pozzolana cement and 7% Portland cement with 28 days of curing had the highest CBR number and UCS resistance of 176.26 and 17.58 kg/cm², respectively. Also, the sketch of the different failure patterns was shown during the curing time. Finally, by increasing the curing time, the behavior of specimens from semi-brittle to brittle made them harder.

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.

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.