JWSS - Journal of Water and Soil Science

Soil salinization is a phenomenon that threatens agricultural lands and natural areas, leading to reduced productivity, declinations of soil resources and vegetation covers, and finally, the abandonment of these areas. This study has quantified the groundwater Capillary Rise (CR) and actual Evapotranspiration (ETa) and their relationship with the soil salinity of Azadegan plain, west of Khuzestan Province. The study area has an arid climate, characterized by shallow and saline water table and a high potential evaporation rate. For this purpose, field samplings were carried out in four consecutive seasons of the year to measure salinity, soil moisture, and texture, groundwater table, and salinity at 27 scattered representative points of the study area. The CR values were estimated in different seasons of the year using UPFLOW model. Moreover, four representative Landsat satellite images were acquired to map seasonal changes of ETa through the SEBAL algorithm. Then, the effects of ETa on CR and consequent soil salinity build up were quantified in a seasonal time scale. The results showed that the average daily ETa of Azadegan plain varied from 1.55 to 7.96 mm day^-1 in different seasons which caused a capillary rise of around 1.2 to 1.5 mm.day^-1. This has led to the upward movement of 12 to 18.8 ton ha^-1  month^-1 of salts from shallow groundwater to the soil surface, which has caused surface soil salinization. Also, there was a close relationship between ETa, CR, and soil salinity parameters, which can provide insight into modeling of spatial and temporal changes of soil salinity and provision of solutions to reduce the accumulation of solutes in the soils of the study area.

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.

Desertification is a phenomenon that has more destructive effects in arid, semi-arid, and semi-humid regions than in other regions. This paper tries to provide a map of the future of desertification in Tehran Province, for futurism in the face of land degradation and desertification. The IMDPA model was used to evaluate land degradation and desertification. To use this model and evaluate desertification, three criteria of groundwater including groundwater depletion, electrical conductivity, and sodium adsorption ratio indices, climate criterion including precipitation, aridity, and drought indices, and land use criteria were selected as key criteria effected on desertification according to regional conditions. Land use index map with IGBP standard and zoning map of other indicators were prepared by IDW method for 2011 and 2016. The maps of land use index and other indices were predicted using the CA-Markov model in TerrSet software, and using the RBF method in artificial neural network toolbox, respectively. Scoring based on the IMDPA model, the maps of indices and criteria maps were prepared for 2011, 2016, and 2021. Finally, the desertification intensity map was calculated by geometric averaging for all three criteria for all three time periods. The results showed that 59.78% and 40.22% of the area of Tehran Province were in the low and medium classes, respectively. However, in 2016, the area of the medium class has increased to a 44.8%, and it is predicted that this increase will continue until 2021 so that 47.65% of the area of Tehran Province will be in the medium class. In addition, in this year, about 1% of the area of Tehran Province will be allocated to the high class in the western regions, which did not exist in the previous two periods. In general, due to human activities, the intensity of desertification in the western and southern parts of the province is higher than in the eastern and northern regions.

The southern regions of Kerman Province have repeatedly encountered dust storms. Therefore, the objective of this study was to identify dust sources using effective parameters such as vegetation cover, land surface temperature, soil moisture, soil texture, and slope as well as to detect dust storms originating from these regions based on 31 MODIS images in 2016 and SRTM data. After normalizing parameters, the dust source map was prepared by fuzzy logic and assessed with an error matrix and available dust source map. Results showed that 30.5% of the study area was classified as a low source of dust, 39.55% as moderate, and 29.85% as severe-very severe. The overall accuracy of the produced map was about 70% and the producer and user accuracy of the severe-very severe class was more than 87%. The detection of dust storms originated from the identified dust sources also confirmed a crisis situation in the region. Due to the repeatability and continuity of obtained dust source map at pixel scale, it can be used to update available dust source maps and manage dust crisis in the region, properly.

The application of simulation-optimization models is a valuable tool for selecting the appropriate cropping pattern. The main objective of this research is to develop a two-objective simulation-optimization model to determine the pattern of cultivation and water allocation. The model performs the optimization with the multi-objective metamorphic algorithm (MOALO) after simulating different states of the cultivation pattern. The decision variables including land and water allocated to ten-day periods of plant growth were designed in a way that the minimum utilization of water resources and economic maximization were identified as target functions. The developed model was used to simulate and optimize the cultivation pattern with an area of ​​5500 hectares and water allocation of Semnan plain with renewable water at the rate of 60.8 million cubic meters. Harvesting scenarios of 80 (GW80) and 100 (GW100) percent of renewable groundwater and scenarios of change in existing cropping pattern of 30 (AC30) and 60 (AC60) percent were considered and each scenario was simulated with the MOALO algorithm. Optimization using the proposed model in four scenarios improved the water and economic objective functions compared to the initial simulation performance. The results showed that the four proposed scenarios were obtained by minimizing the water objective function and maximizing the economic objective function relative to the current situation (simulation). In general, the proposed model had a good performance despite its simplicity, which is a specialized tool to optimize the crop pattern with water allocation.

Iran is located in the dry belt of the earth and is predicted to face water stress in the next half-century. Currently, the area of sugarcane cultivation in Khuzestan is over 85,000 hectares and due to the high water needs of sugarcane and drought conditions, optimization of water consumption and irrigation management is necessary to continue production. Therefore, in this study, the values of soil moisture, canopy cover, biomass yield in five treatments and irrigation levels (start of irrigation at 40%, 50%, 60%, 70%, and 80% soil moisture discharge) during 2 planting dates in the crop year 2015-2016 on sugarcane cultivar CP69-1062 in Amirkabir sugarcane cultivation and industry located in the south of Khuzestan was simulated by AquaCrop model. The measured data on the first culture date (D1) and the second culture date (D2) were used to calibrate and validate the model.  The results of NRMSE statistics in canopy cover simulation in calibration and validation sets with values of 2.1 to 15.6% and 3.8 to 18.3%, respectively, and in biomass simulation with values of 6.2 to 15.2%, and 9.5 to 12.6%, respectively and coefficient of determination (R2), range 0.98 to 0.99 indicated that the high ability of the AquaCrop model in simulation canopy cover and biomass yield. whereas, the values of NRMSE of soil depth moisture in the calibration and validation sets ranged from 11.6 to 23.8, and 12.2 to 22.7, respectively, with a coefficient of determination (R2), 0.73 to 0.96 (calibration) 0.8 to 0.93 (validation) showed less accuracy of the model in the simulation. The best scenario is related to the third proposal that water consumption, water use efficiency, and yield are 1710 mm, 1.53, and 42.27 tons per hectare, respectively, which shows a reduction in water consumption of 360 mm.

The present study is investigated the earth dam stability during drawdown based on both numerical and experimental aspects. To validate the numerical model, a model was performed experimentally. Some soil mechanic tests were carried out through the hydraulic experiments to attain the usage factors of the numerical investigation. To investigate the effect of hydraulic conductivity on the rapid drop of water level and the use of hydraulic parameters of materials, seepage flow in the model was modeled by seep/w software. The input information to the software including hydraulic conductivity and water volume were measured by performing a constant load test and using a disc penetration meter, respectively. After validation of hydraulic conductivity with the experimental model, the results were compared with observed data. Comparison between numerical and laboratory discharge illustrated that the numerical model with laboratory model is well confirmed. In addition, saturated and unsaturated simulations demonstrated that the unsaturated model is highly consistent with the experimental model. It is assumed that due to the drawdown conditions, unsaturated models can achieve high accuracy for simulating the flow through a homogeneous earth dam.

Soil salinity and its development are the main problems that should be prevented by correct management methods. Recognition of saline districts and the preparation of salinity maps are the first steps in this way. Nowadays, the application of auxiliary data in digital soil mapping is increasing due to the current associated problems in the preparation of traditional maps. The objectives of this study were to map soil salinity by the Regression Kriging (RK) method,  to identify areas with high salinity, and to investigate the relationship between soil salinity and soil-forming factors in Khuzestan Province. For this purpose, 291 surface soil samples (0-10 cm) were randomly collected in April 2014. Auxiliary variables or soil-forming factors were included in the land parameters such as slope, watershed and wetness index, OLI and TIRS images of Landsat 8, and the category maps (soil, land use, and geological maps). Also, kriging approaches were used to compare the precision of different mapping methods. The results indicated that the Regression Kriging method has a higher precision compared with other methods so that the coefficient of determination, Mean Absolute Error (MAE), and Root Mean Square Error (RMSE) were estimated as 0.84, 0.41, and 6.21, respectively. The Decision Tree Regression method could also create a good relationship between soil salinity and auxiliary variables. The results showed that some auxiliary variables were more effective on the prediction of soil salinity including 2, 4, 5, and 7 bands of Landsat 8, Brightness Index, Wetness Index, Multiresolution index of Valley Bottom Flatness (MrVBF), Channel Network Base Level (CNBL), NDVI, SAVI and soil map. A Digital map of soil salinity was prepared by the obtained rules, and then it was assimilated with the map of error of variance to prepare the final soil salinity map. Accordingly, soil salinity was found to have an increasing trend from north to south in Khuzestan Province which indicates a salinity problem in the south of the Province. The main reasons for the high salinity in the south and southwestern parts of the area could be attributed to the high water table levels, differences in topography, capillary movement of salt to the soil surface, the difference in the type of land uses, and also groundwater quality and irrigation water which is altered by the frequent application of wastewaters and animal manures.

At present, the occurrence of dust storms is one of the most important environmental problems in Khuzestan Province, and the south and southeast regions of Ahwaz have been recognized as one of the interior dust sources and are the priority of corrective operations. Given that land use change is one of the desertification factors in the mentioned region, therefore, modeling its changes is necessary and provides useful information for planners to control and revive the degraded lands. The objective of this study was to evaluate the efficiency of the CA-Markov model in predicting land use changes in the dust source of south and southeast of Ahwaz based on two long-term and short-term approaches. In the long-term approach, land use maps of 1986 and 2002 years and in the short-term approach, land use maps of 2002 and 2007 years have been used to predict land use for the year 2016 and then the simulation results were validated. The results showed that the values ​​of allocation error, quantity error, and kappa coefficient for the long-term approach were 42.55%, 13.95%, and 0.08 respectively, and for the short-term approach were 12.56%, 10.42%, and 0.22 respectively, which indicates the weak ability of the CA-Markov model to evaluate the desertification trend in the dust Source of south and southeast Ahwaz. Use of uniform transition rule throughout the simulation period without considering the factors and processes affecting land use change, the non-same trend of land use change during study periods, changes due to human activities, drought, and long forecast period can be the reasons for the poor performance of the CA-Markov model to predict the desertification trend the dust Source of south and southeast Ahwaz.

This study was conducted to investigate the temporal variations of runoff and rill erosion in various soil textures under different slope gradients. So, a laboratory experiment was set up in three soil textures (loam, clay loam, and sandy clay loam) and four slope gradients (5, 10, 15, and 20%) using the completely randomized design with three replications. Runoff production and rill erosion were measured at a flume with 4 m×0.32 m in dimensions using a simulated water flow with 0.5 lit min^-1 in discharge during 30 min. Results indicated that runoff and rill erosion and their interaction were significantly affected by soil texture and slope gradient (P < 0.001). Significant relations were found between rill erosion and runoff both in three soils and four slope gradients, and the strongest relations were in loam (R²= 0.86) and 15% slope gradient (R²= 0.94). Runoff and rill erosion varied considerably in the soil textures and slope gradients during the experiment. A 10-min pick time was found for runoff and rill erosion. In contrast to runoff, rill erosion appeared an irregular and gradual increasing pattern during the experiment which was associated with the frequency of transportable soil particles. Clay loam had more sensitive particles due to a higher percentage of fine particles and weaker structure, and most of them were washed in early times, and finally, rill erosion was reached to a constant pattern. This study revealed that temporal variation patterns of runoff and rill erosion are influenced by soil type (texture and structure) and slope gradient.

Street dust is mainly affected by the pollution of polycyclic aromatic hydrocarbons (PAHs). PAHs are a group of organic pollutants consisting of two or more benzene rings and are mainly produced during incomplete combustion. PAHs have attracted widespread attention due to their high carcinogenic and mutagenic properties in humans. Therefore, the purpose of this study was to investigate the sources and extent of the impact of these compounds on human health and the environment. To achieve this goal, 30 dust samples were collected from the sidewalks of the main streets of Dezful and the concentration of PAHs was determined by gas chromatography-mass spectrometry (GC-MS). The total concentration of PAHs in street dust of Dezful varied from 562.85 to 51447.10 μg / kg. The ratio of carcinogenic compounds to total PAHs was in the range between 0.73 to 0.91. Low molecular weight and high molecular weight PAHs accounted for 12% and 88% of total PAHs, respectively. The most important sources of PAHs in Dezful are the combustion of fossil fuels and petroleum products and emissions from vehicles and traffic. Moreover, incremental lifetime cancer risk (ILCR) in pathways ingestion in children was higher than in adults, but the ILCR in pathways dermal contact and inhalation in adults was higher than in children. The total cancer risk (CR) for children (5.77×10^-3) was higher than adults (5.56×10^-3), which shows the high potential for CR in the study area.