مجله مهندسی و مدیریت آبخیز
سال دوازدهم شماره 3 (پاییز 1399)

The aim of this study is to predict and verify the number of days of dust phenomenon selected stations in Khuzestan Province using Box-Jencks model. Study in eight selected stations of the province to compare the Box-Jenkins model and predict the effect of dust has been done. Using the Minitab 17 software Box-Jykyz time series model, number of days of dust monthly was checked and best models were fitted, the accuracy of the model using normal distribution of residuals, assuming constant variance, charts left over time, Mvntv Perth test was confirmed. Finally, Arc-GIS10.4 software was used for output mapping. Results showed that the best monthly pattern for Ramhormoz, Aghajari, Behbahan, Abadan, Dezful, Omidiyeh, Ahwaz and Masjed Soleiman are ARIMA (2,0,1)(1,1,1), ARIMA (2,1,1)(1,1,1), ARIMA (3,0,1)(2,1,1), ARIMA (1,0,1)(2,1,1), ARIMA (2,0,1)(2,1,1), ARIMA (3,1,1)(1,1,1), ARIMA (3,0,1)(1,1, 1) and ARIMA (4,0,3) (1,1,1), respectively. These models have a good accurately for predicting dust and the numbers of dusty days for 2018 to 2027. Also, results showed that Agajari, Abadan and Masjed Soleiman are more exposure with dust phenomena in Khuzestan Province that needs for further attention to city officials and planners in facing with this phenomena.

The global water scarcity crisis is affecting water management in various sectors, including water and agriculture. Aquatic basins and their surrounding areas have been encountered with serious challenges such as drying up of lakes and rivers, negative aquifer balance, changes in surrounding land use, increased cultivation of irrigated and horticultural lands, and changes in the pattern of cultivation from low-crop to high-water crops in recent years. Satellite imagery due to its wide spatial coverage, high resolution, low cost, rich time archive of satellite imagery and ease of use methods is a useful and efficient tool to help manage water and soil resources. In this study, four classes of soil, water and wet, urban and agricultural areas were selected. Then, two random forest classification methods and support vector machines are used to classify images. Classification methods were evaluated by calculating two indices of accuracy and Kappa coefficient using test data. The random forest classification in the four years, 2012, 2014, 2016 and 2018 and classification of support vector machines in two years, 2008 and 2010 have the most accuracy. Therefore, the random forest algorithm has worked well in separating the classes, especially in water basin, and can be used as a reliable method in this area.

Using erosion plots is a way to research on soil erosion and conservation that with different dimensions, which are constructed in the natural arenas or in laboratories. Mistakes and false conclusions are common task that should be avoided when sampling runoff and sediment from the tanks of these plots. A few researches have been done on the ways of sampling from these tanks and reducing the errors. In this study, the accuracy of sampling was investigated by placing a bucket in the tank and using bottle sampling. For this purpose, two 220 liter tanks were used. In the first tank located at the upper level, concentrations of sediment were prepared for five, 10 and 20 grL-1 and the mixture of runoff and sediment was transferred to the second tank. Coarse particles were trapped by a bucket of twenty liters placed underneath the importer tube in the second tank. The contents of the bucket were weighed in the laboratory after drying. Also, sampling of the second tank contents was carried out after mixing the solution and using one-liter bottles in three replications per each concentration. Sampling was also done without placing the bucket as a witness. The significance of the effect of concentrations on the error value was defined by analysis of variance through a random block design scheme. Results demonstrated that there was a significant difference between the concentrations obtained in the experiment with bucket and without bucket at a level of one percent. Without using bucket, the amount of errors were 63.13, 78.40 and 73.97 percent for 5, 10 and 20 gr.L-1 concentrations, respectively and with using bucket they were 15.90, 15.07 and 4.83 percent. The mean errors in all concentrations were 71.83 and 11.93 percent without and with using buckets, respectively.

On average, 70 percent of the precipitation that reach Earth's surface, returns to the atmosphere through evapotranspiration, and this rate reaches 90 percent in arid areas. Meanwhile, watershed measures directly related to water, soil and plant, and ultimately to evapotranspiration on the natural resources region (ecochydrology). In this study, in order to study the effect of biological activities of watersheds (enhancement and increase of vegetation) on the process of soil moisture and evapotranspiration changes, paired watersheds of Taleghan, Alborz Province were selected. In order to calculate evapotranspiration by soil moisture balance method, soil moisture monitoring points were selected using field and laboratory studies in three main areas (northwest, eastern and southeast) and three replications and at three depths of 0-20, 40-20 and 40 -60 cm during plant growth period in 2017. Data were analyzed by ANOVA method, and Duncan test. The results showed that the actual evapotranspiration in the treated watershed and control watersheds were not statistically significant and, respectively, they showed 181 mm and 159 mm in a period of growth. In other words, the actual evapotranspiration value in the treated watershed was 14% higher than the control one during the growth period. Also, the results showed that evapotranspiration under different aspect slopes had a significant difference. The total actual evapotranspiration in the northwestern slopes were 229 and 226 mm, in east slopes were 207 and 171 and in the southeastern slopes were 109 and 80 mm in the treated and control watersheds, respectively.

Alterations in river morphological quality are derived from quantification of human pressures as well as river morphological alteration. Taleghan River is an important source of water for the irrigation of Agri cultural lands in Qazvin Plain. For some economic considerations of Taleghan dam reservoir on the river as well as geology, some reaches of the river have undergone alterations. It seems important to morphological quality assessment in order to planning issues. Our study’s aim is to contribute to the morphological quality evaluation based on a revisited Morphological Quality Index (rMQI) protocol. The rMQI scoring system allows for the quantification of changes when compared to reference conditions. The rMQI corresponds to less than 30%, reflecting a good morphological quality; the rMQI corresponds to more than 30%, reflecting an extremely poor morphological quality. In this context, the paper presents all of the Taleghan River reaches suffer from an extremely poor morphological quality. Causes of degradation are meandering as well as numerous anthropogenic pressures in the upstream part of the basin. In order to revive Taleghan River as well as improve its water quality, preserving and remediating native vegetation, prevention and remediation of land use degradation in upstream's basin as well as river bank erosion control measures can use hard and soft strategies engineering are recommended.

Nowadays spectroscopy is used for estimating soil properties. The main objective of this research was to estimate some soil properties of Susceptible Areas of Dust Production using visible and near infrared. Therefore 142 soil sample of Susceptible Areas of Dust Production were Collected and analyzed. Equivalent calcium carbonate, gypsum, organic carbon and nitrogen of soil sample were measured and linear regression models of PCR and PLSR were used to estimate these properties .Three methods of reflection of the main spectra and pre-process methods of first derivative and second derivative were compared in two regression models of PCR and PLSR. The results showed that the PLSR method is more accurate than the PCR model for estimating soil properties. The PLSR model in the pre-processing second derivative with noise reduction, showed the highest accuracy for equivalent calcium carbonate, organic carbon and total nitrogen with the coefficient of determination as 0.95, 0.92 and 0.81, respectively. For gypsum, the highest accuracy in the first derivative with the coefficient of determination was 0.87. The results of this research revealed the use of spectroscopy in estimating soil properties of dust production-prone areas in Khuzestan province have an appropriate accuracy; and due to the extent of these areas and the speed of operation and cheapness of this method, it can be used to predict the amount of soil properties in these areas.

Different models have been designed to simulate incoming floods into urban areas from rural areas, one of the models is the EPASWMM. Mashhad urban watershed with 8 inde-pendent subbasins and area of 2,472 hectares, located in south of Mashhad city . Study area is the residential area of Mashhad Paydari township (Area= 95.6 ha) that located below the M2, M3 and M4 subbasins. Due to high peak flood events in M2, M3 and M4 subbasins, the capacity of urban transmission channels in the Paydari township is’nt suf-ficient and after every rain, a lot of runoff enters the residential areas. The purpose of this research is evaluate the efficiency of EPASWMM model in simulating runoff. The study area was divided into 12 hydrological units (OUT1 to OUT12) and after determine of input parameters of the model, the runoff gathering network in the form of nodes-channels was introduced into the model. Four rainfall events were used to evaluate and calibrate the model with (NS), (RMSE) and (R2) coefficients. In the calibration section of the model, the value of the (NS) coefficient for discharge in the first and third events was 0.94 and 0.92 respectively and for runoff height, 0.9 and 0.86, respectively and indicates simulation accuracy of EPASWMM model in both parameters. The results of the model evaluation section for the second and fourth events shows that the NS and R2 coefficients for three parameters of discharge, height and runoff were from 0.78 to 0.9 and 0.73 to 0.89 and indicates a large correlation between observational and simulated data. Flood reduction scenarios in hydrological units have been investigated according to the simulation results.

Dust phenomenon is one of the important climatic and environmental hazards in arid and semi-arid regions of the world. The aim of this study is to determine the mineralogical and physicochemical properties of some soil samples in Iraq and dust particles in Ilam province in order to find out the origin of dust. Dust samples were collected from Ilam, Mehran and Dehloran cities. In addition, some surface soil samples were collected from different parts of Iraq as the source of dust. Physico-chemical and mineralogical analysis of dust and soil samples was fulfilled. The results revealed that the highest percentage of particles forming Iraqi dust and dust in Ilam province are sand and silt and clay was the least. Electrical conductivity in all samples was more than 4 dS/m in both samples meaning as saline classes and pH of the samples was similar in dust of Ilam and Iraqi soils, and showed the neutral to alkaline range. The lime content of all samples was more than 25%. Different regions had low organic carbon percentage, the highest rate was in the Iraqi margin (1.18%), and the lowest was in Najaf (0.16%). The SAR of most Iraqi soils was more than 13 and showed severe alkalinity in dust particles, SAR is also relatively high. Mineralogical results showed that dominant minerals in Iraqi soils and dust of Ilam province are calcite, gypsum, quartz and palygorskite. The results of XRD studies in clay samples of Iraqi soil and Ilam province dust indicated the presence of minerals such as kaolinite, chlorite, ilite and smectite. Overally, the results of physical, chemical, and mineralogical analysis indicated that desert regions in Iraq are the sources of dust production in Ilam, and that dust storms can lead to salinity and alkalinity of the surface soil in Ilam province.

Long meteorological drought can lead to the onset of hydrological drought. In this research, the lag time between the two types of drought was investigated for determining the hydrologic drought onset after realizing the climatological drought. This is a matter to provide managers with enough time for decision making before the occurrence of water shortage in the watershed. The SWAT water balance model was used to determine and predict the lag time between the two types of drought for Foomanat (Anzali wetland) watershed in Gilan province Due to the ability to simulate the long-term flow of representative rivers in the basin. The OAT method was employed for the sensitivity analysis of the water balance model. Among the parameters used in SWAT, three parameters including curve number, available water, and the evaporation compensation factor in the soil were recognized as the most effective parameters for the results of the model. Calibration and validation of SWAT were performed using SCH model. The calculated Nash-Sutcliff and correlation coefficient in estimating runoff as well as determining and predicting the lag time between the two types of drought by SWAT were acceptable. The Nash coefficient was obtained as 0.68 and 0.8 for calibration, and 0.65 and 0.79 for validation periods, respectively. Using the calibrated model, one can predict the water balance situation and the lag time between the onset of meteorological drought and the emerging hydrological drought in the watershed for any interested meteorological drought scenarios. Based on the results, the chance of having a one -month lag time, is more than 70 percent, while the chance of a 2-month lag time in the Foomanat watershed Anzali wetland) is more than 23 percent.

Drought management is an essential task to exploit water resources. In this study, the monthly rainfall of 35 synoptic stations in Qazvin province during 30-year were considered for drought monitoring. In this study two drought monitoring indices including modified standard Precipitation index (MSPI) and Standardized Precipitation Index (SPI) are accomplished and compared to the reports of four indices in the study area. The obtained results showed that the MSPI is more accurate than the SPI and other indices. Having the drought conditions in the stations, zoning of drought were calculated by Interpolation methods such as IDW, Kriging, GPI, and RBF.The obtained results demonstrated that IDW method with first power is the best method in terms of average error. Moreover, zoning of the precipitation is conducted using Kriging interpolation then the MSPI value for each cell is computed for monthly precipitation. The results show that if the precipitation interpolation is conducted firstly, the drought index is calculated more accurately than the method that drought index calculated in the stations. In order to assess the drought condition more accurately, the vegetation condition index (VCI) is computed using monthly NDVI product of MODIS. The correlation between VCI and MSPI was calculated that the results illustrated that MSPI confirms the results obtained by VCI. As a result, VCI can be used to monitor drought in the watersheds which suffer from sufficient ground stations.

Abstract In dry and semi-arid areas, water is the most factor of limiter in agriculture. In these areas, due to the lack of surface flows, major pressures enter on groundwater. Groundwater resources in the studied area (Dashte-Abbas plain) also suffered a severe drop in surface water due to unplanned use. In this study, we compared four different models of evolutionary neural network, a multi-layered perceptron neural network with Genetic Algorithm (ANN-GA), a multilayered perceptron neural network with particle swarm optimization (ANN-PSO), a multilevel perceptron neural network with Imperialism competitive algorithm (ANN-ICA) and multi-layered perceptron neural network with ant colony optimization (ANN-ACOR) for estimating groundwater level according to groundwater inflow, effective penetration of rainfall, effective penetration of surface flow and flood, effective penetration of return water Agriculture, underground outflow, withdrawal from aquifer for agriculture, evaporation from groundwater level and past groundwater data Were used. groundwater level comparisons are the combination of inputs has been prepared using Auto-correlation analysis, partial Auto-correlation and cross-correlation for each model. Optimal models are obtained by changing the control parameters. The best results are obtained from the input models (GWLt-1, GWLt-2, Qint, Qpt-1, Qrt-1, Qit-1, Qoutt-1, Qwt-1, and Qet-1). The accuracy of the mean squared error in the test phase for ANN-PSO, ANN-ICA, ANN-ACOR models was 1.2208, 0.9456 and 1.7720, respectively, and for the ANN-GA model, it was 0.8739. The mean relative error of ANN-GA model is 3.6% and its determined coefficient is 0.9388. According to the results, the ANN-GA model showed better performance than the other three models for estimating groundwater level.

The proper estimation of the amount of suspended sediment in rivers has an important role in erosion and sediment studies, hydrology and management of watersheds. The simulation of suspended sediment in hydrological systems that has a lot of complexity and at the same time our understanding of the components and processes within them is always uncertain led to the use of many intelligent models, including artificial neural networks (ANNs). However, the use of these smart models also faces challenges. Determining the proper structure of the network requires optimization of the parameters used (such as the optimal number of neurons and layers, weight and bias, and the type of activation functions), which their proper calibration, using test and error, leads to a lot of time spent in low efficiency. In this study, a multilayer perceptron (MLP) was used to simulate the daily sediment load of the Nirchai River at the site of the Nair hydrometric station in Ardebil province. In order to train the models, in addition to the error back propagation (BP) algorithm, Particle Swarm Optimization (PSO) algorithm was used to optimize the weight and bias of ANNs. The fuzzy clustering method was also used to increase the power of generalization of the models. The results showed that training of ANN models with PSO algorithm with decreasing estimation error (decreasing the PBIAS of estimation and root mean square error up to 0.3% and 10.4 tons per day respectively) is more effective than ANN models that use only error BP techniques. Due to insufficient recorded sediment data in most hydrometric stations of the country on the one hand and the need to train ANNs with sufficient data on the other hand, the use of evolutionary algorithms (e.g. PSO algorithm) can be a good solution for improving the efficiency of intelligent models.

Simulation of the rainfall-runoff process is the most important step in water engineering and water resource management studies. Exploitation of surface water and underground water resources, river management and flood warning requires prediction of river and runoff discharges of the watershed. In this study, Extended Kalman Filter-based Neural Network (EKFNN) method was used for rainfall-runoff modelling. Then, the results were compared with the Gene Expression Planning method, which showed good performance in rainfall-runoff modelling in most recent studies. The data used in this study is related to daily runoff and rainfall of the rain gauge and hydrometric stations of Malayer plain which includes Peyhan, Marvil and Namyleh stations, during the period of 2001 to 2013. The results indicated that the EKFNN model was superior to GEP model in daily river flow modelling in Malayer plain. In addition, the speed of implementation of the Gene Expression Planning model was greater and was able to present results in a short time. Finally, EKFNN model was selected as the superior model for Malayer plain.

At present, there are a variety of reliable and practical methods for measuring soil moisture from point to world scale. Recently, remarkable progress in remote sensing techniques has allowed the scientific community to accurate and repeatedly map soil moisture anywhere in the world. The above points out the need for this research. In this research, this is the hypothesis, Do MERRA-LAND remote sensing data have an acceptable accuracy in determining the soil moisture content of the baft watershed? To answer this question, After downloading the data and reading them, Pearson correlation method was used to validate the data between monthly average remote sensing data and monthly average precipitation of baft synoptic and Kiskan Rainfall stations measurement in 2009-2013. The results showed 99% confidence in the Kiskan station and 95% confidently at the baft station There is a high correlation between monthly average soil moisture content downloaded with average monthly rainfall, Then, to compare the mean of MERRA-LAND data from the Goddard earth science(GES DISC) As predicted data at the specified date and time and the percentage moisture content obtained from 14 sampling points from the soil surface and the root zone area in the baft basin, the same time and date was used as in-situ data. Mean comparison of T-pair method was performed in SPSS software for each sample. The results showed that due to the higher T calculated from the table T with a degree of freedom 13 compared to the moisture content of the surface area and the root area there is no significant difference with surface download data and root area with 99% confidence. And can be recommended to the executive department Instead of spending a lot of time and cost Use the percentage moisture content provided by this site to predict and monitoring agricultural drought.

Accurate estimation of a watershed response to rainfall events plays an important role in its soil and water resources management as well as civil works design within watersheds and over or around its downstream rivers. Nowadays, due to improvement in our knowledge and understanding from watershed systems and enhancement in hardware and software technology as well as facilitation in learning and application of these technologies, researchers prefer to design and apply their required models themselves according to their aims and availability of data. The aim of this research is to develop a spatio- temporally distributed model within PCRaster GIS and programming environment to achieve a better representation of watershed processes at a small scale agricultural micro-watershed. In this study, based on the available local data, an event based rainfall – runoff hydrological simulation model was developed within PCRaster GIS and programming software and its performance was evaluated using observed data from a 27.6 ha agricultural micro-watershed discharging to the Shahrak – Behzisti residential area in the Gorgan city. This is a tightly coupled GIS model. During the research period, only two rainfall events leading to runoff generation occurred on 2/11/2014 and 16/9/2015 which were, respectively, used for calibration and validation of the model. Statistical comparison of the simulated and observed hydrographs of the rainfall - runoff events on 2/11/2014 and 16/9/2015 showed the correlation coefficients of of 0.69 and 0.65 and Nash-Sutcliffe criteria of 0.5 and 0.51, respectively. The results indicate that the developed model has a good performance at simulating rainfall-runoff processes during events.

Now a day, carbon sequestration is an important issue due to its serious role on global warming. The aim of this research was to evaluate mechanical measure of check dams on vegetation cover and soil carbon storage in watersheds of Kermanshah Province, Iran. These check dams were constructed in the drainage systems to reduce surface runoff velocity and optimize channel slope. Small sedimentary dams are made by gabions and dry structures. The soil and vegetation characteristics of the areas under mechanical operation and its control (severe grazing and grazing management) by field survey in selected sites of Gilan Ghab, Kangavar and Sarfirozabad. The plant biomass including canopy cover and plant root as well as plant litter were samplled along transect path using the quadrat plot. 36 soil sampls were collected from 0-20 cm of soil depths and were air dried and sieved through two milimeter mesh and analyzed in the soil laboratory. Soil organic carbon was measured by the Walkley and Black method and statistical analysis was carried out using SPSS software (version 19). Results showed that both mechanical (check dams) contributed to store 49.28 tonha-1 of carbon which was significantly lower than biological measures. It was concluded that vegetation cover has the most effects on carbon sequestration of the rangelands compared to mechanical methods.

Evaluation of mining methods and the volume of the bed and flood plain sand and gravel mining show that many problems will be created due to geometry and naturally changing of rivers, increasing of the flood power and environmental and ecological dangers. Hence, applying correct management on river sand and gravel mining can create many positive effects. In this research, the effect of locating of the consequent river bed material mining pits on their sedimentation is investigated in order mining management via an experimental study. Results indicated that, there is no perceptible effect on the infilling and migration velocity of the upstream pit by increasing the distance between the pits up to 16 times the flow depth. Also, mining near the wall of the channel (20% width of the channel) leads to decrease infilling volume up to 25% and decreases migration velocity of the upper edge of the upstream pit up to 37%. By increasing of the distance between the pits, infilling of downstream pit is decreased, but it depends on the distance between the downstream pit and the wall. When the distance between the pits doubles, migration velocity of the downstream pit decreases up to 70%. If the mining is located at the center of the channel and the pits are in close proximity, it creates more suitable condition due to the infilling and migration for upstream and downstream pits.

Water quality, as its quantity, is one of the most important determinant factors for its application in various uses. Physical and chemical properties of water play an important role in categorizing and evaluating water quality. With the aim of detecting the water chemical quality of Gupal river in the south of the country and studying its annual changes during the years 1982 to 2011, its physical and chemical parameters were studied. Since the presentation of the results of water quality analysis in the graphical form simplifies and makes faster understanding of complexity of surface water systems, graphical methods such as Wilcox, Schuler, Piper and Collins diagrams were also used. The results of variation and trends analysis of water quality parameters showed that in spite of the decreasing in the trend of acidity and flow rates, other chemical parameters of water had an increase in their trend and their terms was in order of 5, 10, 20 and 30, respectively. Increasing in the trend of variation in the water quality parameters and dissolved salts indicates a decrease in water quality and an increase in dissolved salts. The Wilcox diagram showed that the water lied in the class of C4S3and was inappropriate for irrigation and agricultural uses, and Schuler’s diagram showed the water quality is not acceptable and in terms of industrial water consumption the river was precipitate and the Piper diagram showed that the dominant ions in this river are sodium and sulfate, and water has type and facies of sulfate sodic.

Flooding is one of the most important environmental hazards that can cause severe damage to life and financial damage. In many cases land use changes cause flooding. In this study in Gonbad Chi warershed to assess the impact of proposed and the built watershed mechanical operations (check dams) on flood mapping, firstly the fuzzy logic and AHP were used to prepare base map based on combination of layers i.e. slope, land use, Permeability and flow accumulation. In next step by determining the location of check dams and separation of the operation according to dam height and determine the extent of the effect of the check dams using elevation contour lines, the mapping of impact of watershed management operations was prepared. In the end with composition of base mapping with impact of check dams, a new map that called flood mapping is created. Although the results have a positive impact 9% and less than it on reducing the risks of flood but these results in built check dams is very low than proposed check dams but in total the impact of built and proposed dams is low that it’s result is from low number and distribution of check dams.

Physicochemical properties and the forms of erosion of marl formations as well studied in this experiment within Zanjanrud watershed basin. At first, the distribution and erosion landscape maps for different marl formation were prepared and then by overlying different maps the final map of working units were produced. Soil samples from selected points within each working unit were collected and after laboratory measurements statistical analyses were applied. The results suggested that surface and sheet erosion were more dominated than other forms of erosion. While gypsum content was concentrated at surface, some elements such as Ca, Mg, and dissolved Na subsided in lower layers. Marl units account for 20% of the total area of the basin, which consists of two types of Marl Pliocene (Plm) (99.75%) and the upper Red marl (Mur) (0.25%). In this basin, there are four superficial erosional facies, surface,rill, badland and gully erosin, with the rill erosion facies having the highest and most expanse of 61%. Toward the deeper layers in marl soils level of salinity, pH and clay percentage increases as the result of leaching of salts and fine material by runoff and transferring them from surface to depth. There is statistical significant difference in the amount of EC, clay, limestone, and gypsum among various forms of erosion, so that the highest and lowest level of EC were found respectively in deep gully and upper layers of surface erosions. Highest content of gypsum was found in badland erosion while the lowest of that was found in surface erosion. Therefore, changes of chemical properties are mostly found in surface and badland erosions. Finally, prevention of these two types of erosion must be prioritized because they can be precursors to other forms of erosion in this type of marl soil.