نشریه پژوهش های آبخیزداری
پیاپی 133 (زمستان 1400)

Dust storms, one of the environmental problems in Central Iran, annually damage natural and human ecosystems. The dust has irreversible effects on human societies, including respiratory diseases and declining public health. Therefore, performing research on this subject and identifying the origin of dust is of great importance. Simulation and numerical analysis of severe dust storms are one of the new methods of studying this phenomenon. For the numerical analysis of dust, data related to the storm of July 10, 2014, and the MACC-ECMWF model were used for simulation. The results of the MACC-ECMWF model were extracted based on the Aerosol Optical Depth indices and dust concentration. The time series of the changes in the value of the AOD indices and dust concentration in a one-hour period indicated that the values ​​of these two indices had an increasing trend and reached a maximum at 23:00. Also, spatial analysis of the Aerosol Optical Depth and dust concentrations showed that the Central Desert of Iran, extending from Semnan and East Isfahan Provinces to the Central Loot Desert in the east of the Province of Kerman, is the largest dust source in Central Iran.

Morphometric analyses play an important role in understanding the geo-hydrological conditions of basins such as identification of the and potential management of groundwater resources. A hydrological DEM was prepared to draw the drainage network in four sub-basins of Lake Urmia. Linear, surface, and topographic morphometric parameters were calculated to prioritize the potential of groundwater resources in the sub-basins. The mean values obtained from the rank of the parameters in each sub-basin were close and the sub-basins were prioritized as Nazluchai, Baranduzchai, Shaharchai, and Rouzehchai, respectively. Furthermore, the morphometric indices of TPI, TRI, VRM, surface curvature, and surface ratio were studied to prepare the spatial value map of the groundwater resources. Each map was prepared and classified with the same cell size in seven classes and the morphometric index map was combined with the same weights. The map of potential groundwater areas under the study area was obtained with values of 2.2 to 5.0. The highest value in the map of the spatial value of groundwater resources belonged to the pixels that had the lowest TPI, the lowest TRI, the highest VRM, the lowest surface curvature, and the highest surface ratio. The findings were confirmed by examining the location of springs and yielding wells in the study area.

Accelerated soil erosion and high sediment production are important issues in many parts of Iran. The identification of high erosion risk regions is necessary for the planning of soil and water conservation measures in order to reduce erosion damages. Empirical models are required for estimating soil erosion and sediment yield in the absence of gauged small watersheds. The Erosion Potential Method (EPM), originally developed in Croatia, is a popular erosion estimating model in Iran; however, its efficiency across the country has not been thoroughly assessed. Therefore, a calibration study was carried out by comparison between the model the estimated and measured sediment yields through sediment survey for 63 reservoirs at the outlet of small catchments in the Semnan, Markazi, Isfahan, Chaharmahal va Bakhtiari, West Azarbaijan, Lorestan, Fars, Golestan, and the Khorasan Razavi Provinces. All required maps and information of the study basins for estimating the EPM sediment yield were produced via field survey as well as data analysis. Comparison of the results showed that in most cases, the model estimates (0.19 to 9.71 tons per square kilometer per year) are lower than the measured sediment yields ​​at the reservoir inlets (0.44 to 459.64 tons per square kilometer per year). Thus, we calibrated the EPM by modifying its original tables and evaluated the results using the Nash‐Sutcliffe efficiency coefficient in two scenarios, a, all basins, and b, after dividing into three geographical zones, which significantly improved the estimates. The Nash ‐ Sutcliffe efficiency coefficient for scenario a was 0.66, and 0.68, 0.50 and 0.89 for the Central, Zagros, and Northeast zones, for scenario b respectively. Based on the results, it is strongly recommended to use the modified EPM instead of the original model.

The side effects of climate change have affected most aspects of human life; Therefore, the study of the various effects of climate change is more important than the identification of the climate change itself. Using the 40-year discharge (1978-2017) of the using Kamish River in the WEAP model. The reservoir of the Harsin Dam has been simulated the LINGO model, optimization was performed with the aim of minimizing the shortage of the downstream needs and the effects of climatic scenarios. By applying the RCP climate scenarios, the results indicated a decrease in the inflow of the Harsin Reservoir; however, the output of the two climate models HADGEM2-ao and FGOALS-G2 increased the maximum temperature by 5 and at least by 3 degrees Celsius in future periods. According to the RCP8.5 scenario, the volume of runoff predicted in the periods 2020-2059 and 2060-2099, is less than the runoff predicted under the RCP2.6 scenarios. Application of the runoff prediction by the precipitation-runoff model under the RCP2.6 and RCP8.5 scenarios in the WEAP model caused the reliability index of downstream demands to fall below 80%. The highest value of reliability index by applying the climate scenarios using the HADGEM2-ao model under the RCP2.6 scenario is related to the industry demand, which in the simulation mode is equal to 77.08%, while this index in the optimal model is 88.42%. The lowest value of the reliability index in the WEAP model was estimated at 32.19%; it attained 52.71% using the LINGO model.

Determination of the role of each lithological unit in sediment production is an important priority of watershed management. The geochemical method provides the means to determine the origin of sediments in the Gheshlagh Dam, Sanandaj. Various lithological units were studied as sources of sediment deposited behind sediment-retaining structures. A total of 33 samples of sediment and sediment sources were collected and examined in the laboratory after sieving through a 62-micron sieve and identifying by instrument an ICP Initially, 9 sources of potassium, calcium, phosphorus, carbon, magnesium, chromium, sodium, cobalt, and nitrogen were used to determine the optimal composition of the tracers. Using the 2-stage analysis of variance and detection function, 3 elements, namely: cobalt, chromium, and calcium were selected as suitable tracers and entered the equation stepwise to determine the sources of sediment. The results indicated that the andesite lithological units with interlayers of shale (An / Sh) and microfossilized limestone (Lim) with 56.91 and 30.54%, respectively, had the highest share in the sediment production in the study area.

Carbonates contaminate soil and water resources. The use of stabilizers is an effective method to improve soil characteristics. The single and interaction effects of two treatments consisting of sodium-silicate and sulfur at 0, 5, 10, and 15 g/m2 were studied on the lime-covered Soil stabilization and water erosion control in a factorial design, on the 9% slope standard plots uses a rainfall simulator with an intensity and duration of 1.4mm/min and 20 min, respectively. The results indicated that between the two the sodium-silicate and sulfur factors, only the main effect of sodium-silicate had a significant effect on the runoff volume, sediment weight, and concentration as well as the runoff coefficient variables; however, it had no significant effect on the total infiltration rate and the lime percentage variables. Moreover, the sulfur and sodium-silicate factors had significant interaction effects on the sediment weight (Sig.=0.011), sediment concentration (Sig.=0.019), and lime percentage (Sig.=0.000) variables. The interactive effect of the two studied treatments significantly reduced the lime in the soil samples. Therefore, the combination of the two treatments had the highest effect on lime stabilization. Moreover, sodium-silicate had an effective role in soil stabilization. Therefore, a single application of 7.5 g/m2 of sodium-silicate and with its combination with 5 g/m2 sulfur is recommended for erosion control and lime stabilization, respectively.

Flooding is one of the most dangerous and common natural disasters, which yearly causes many damages and causalities for communities and the environment. A comprehensive flooding assessment and management is essential to reduce the effects of flooding on people's lives and livelihoods. Due to an increase in flooding in recent years, locating and identifying flood-prone areas is very important to predict this environmental disaster as mis-identification of flood-prone areas in a watershed may have devastating effects. The main purpose of this study was to evaluate the performance of the Bayesian Logistic Regression (BLR) and the weight-of-evidence (WOE) models for preparing flooding susceptibility maps in the Talvar Watershed of Province of Kurdistan. The geographical location of 93 flood prone areas identified in the watershed was randomly divided into one group (70%) for calibration and another (30%) for validation. Both models consider ten effective factors in causing flooding, namely: slope, slope direction, curvature, digital elevation model, distance from stream, topographic wetness index (TWI), stream power index (SPI), rainfall amount, geology, and land use. According to the WOE model, about 35.8% of the area is placed in the medium to very high hazard class, and based on the Bayesian logistic regression model, about 45.08% of the area is placed in the medium to very high hazard class. The relative performance detection curve was used to validate the flooding potential maps. Even though both models offered sufficient accuracy, the higher accuracy was assigned to the BLR model (93.4%). Therefore, the BLR model has better performance than the WOE model in terms of the flooding risk potential.

The Karun River provides an important sedimentary environment for the Great Karun Watershed, which receives large amounts of oil, industrial and municipal sewage, and agricultural wastes. The dominant physico-chemical conditions, which are controlled by water discharge rate and the river morphology, determine the conditions for the absorption of toxic metal and levels of pollution for aquatic creatures and utilizers; in other words, the food chain. Therefore, the study range limited the urban area of Ahvaz between the Fifth Bridge and the Sayyed Khalaf Alley.  The research objectives were to determine the concentration of seven toxic metals, namely: Cu, Cr, Cd, Zn, Pb, Ni, and As, and their consequences on the levels of pollution. A deterministic strategy of sampling was chosen based on the identified and surveyed contamination points. In total, twenty-one superficial sediments (0-10 cm) samples were collected using an undisturbed core sampler. The analytical procedure was carried out using the ICP-MS equipment following the Geological Survey procedures. The research method was designed to compare the concentration of toxic metals to their standard levels (ISQGs, PEL, SEL) of sediment quality guidelines of freshwater sediments to find out the level of pollution risk, and the high-risk ranges along the river reach. In addition, the enrichment factor was calculated to determine the rate at which the concentration of toxic metal bias from their background levels. The coefficient of variation of the predominant concentration of elements indicates the contribution of human pollutants in increasing their concentration in sediments and the order of enrichment of elements is Zn> Cu> Ni> As> Cr = Pb> Cd respectively in the surface sediments. The Karun River superficial sediments, especially from the Kianpars Bridge to the Fifth Bridge, were in a harmful condition for Cr, while the concentration was higher than the PEL level (90 mg kg -1). The study concluded that the Ni concentration of the sediments along the studied range was higher than the ISQG, PEL, and SEL (50 mg kg-1) standard level. Thus, aquatic bodies and the users of the Karun River water in such a range are exposed to severe poisoning due to nickel pollution. This situation has occurred while the drained sewage along the districts of the Kianpars Bridge to the Black Bridge and the Naderi Bridge to the Eighth Bridge has played a critical role in releasing pollutants. Thus, preventive measures to control pollutants from the source and methods of neutralizing and removing pollutants from the Karun River sediments are firmly recommended.

Soil properties and land use affect the soil carbon content and reduce the adverse effects of climate change. This study aims to assess the effect of some physical properties of soil and land use on the amount of soil organic carbon content (SOC) and model development to estimate the amount of SOC. This investigation was carried out in 2020 in the areas of flood spreading in of Fasa (Kowsar station). Land uses included acacia (Acacia salicina Lindl.), eucalyptus (Eucalyptus camaldulensis Dehnh.), atriplex (Atriplex lentiformis (Torr.) Wats.) plantation, and natural rangeland, all of which are irrigated by flood spreading. By sampling in three replications of the soil of different land uses from the depth of 0-30 cm (15 composite samples), percentage of sand, silt, clay, silt+clay, percentage of soil saturation moisture (SP), bulk density (BD), particle density (PD), porosity percentage (PS), void ratio (VR) and SOC were determined. Obtained data were statistically analyzed in a complete randomized design and the means were compared with the Duncan test at P<0.05. The analysis of variance showed that the effect of land use (PT) on the percentage of sand, silt, silt + clay, SP, BD, PS, VR, and SOC has been significant at P<0.01, and the clay, at P<0.05. Comparison of the means of SOC in different land uses showed that the Eucalyptus forest, with 1.68%, has the highest value and the control with 0.14% organic carbon has the lowest value. There was no statistically significant difference between the SOC in Acacia forest, Atriplex, and rangeland. Stepwise regression analysis was used to present the model. Soil physical properties and land use were considered as independent variables and SOC was considered as a dependent variable. The results showed that the variable of silt explains 77.00% of the changes in organic carbon. Based on the principal component analysis (PCA) method, according to the specific values, considering the first two axes, about 91.70% of the changes can be explained. Considering the first axis, 69.71% and considering the second axis, 21.99% of the changes are justifiable. The PT, with 91.40%, sand with 84.30%, BD, 82.70%, showed a negative correlation with SOC. While the SP had 90.30%, percentage of clay+silt had 84.80%, PS, 80.70%, VR, 79.10%, silt, 78.50%, clay, 78.50%, had a positive correlation with SOC.

Soil infiltration is one of the key processes in the design of irrigation systems, water resources management, soil conservation, and erosion control in watershed management. As to the importance of the mentioned subject, infiltration changes and modeling were investigated on the surface soil of geological formations in this study. The double-ring infiltrometer was used to measure the infiltration rate in the surface soil of some geological formations on the Alashtar Watershed due to the flooding potential of the area. The performance of the modified Green-Ampt, Philip, Kostiakov, the US Soil Conservation Service (SCS), and the Horton models were evaluated in estimating the infiltration rate in the surface soils formed or deposited on those formations. The results indicated that the Asmari Formation (Oml) had a higher cumulative infiltration, average infiltration rate, terminal infiltration rate than other formations. This was followed by the Quaternary Formations (Q and Qt). The results indicated that the modified Green-Ampt model had an acceptable accuracy as compared to other models in estimating infiltration in the Pabdeh (EL), the Khami Group (Jk, Mz), the Gachsaran (M), the Aghajari (Muplaj, Mpaj), and the Bakhtyari (Plb) Formations with efficiency coefficients of 93.9, 94.4, 95.9, 97.6, 87.7, and 92.7%, respectively. The Kostiakov model was more suitable for the Q and Oml Formations, and the Horton model was the best for the Qt Formation (C.C= 0.925), which may be used to quantify the amount of infiltrated water and to estimate the runoff volume for the soils formed or deposited on those formations different on the mentioned geological formations.