نشریه هیدروژیومورفولوژی
پیاپی 24 (پاییز 1399)

There is a logical connection between a hydrological event in a watershed, such as flood flows with a geomorphologic structure. The purpose of this study was to calculate peak discharge and transfer and sedimentation status using two GIUH and WinTR-55 models in the Sangkhar watershed from Karkheh sub basins. First, the domain is divided into 8 sub-basins and four reachs, and then the parameters such as area, branch ratio, length ratio, flow velocity, floor width of the waterway, channel gradient, gender and length of the route, manning roughness, tilt of the sides and sections of the waterway, type Flows, 24-hour rainfall in each sub-domain and peak hydrograph peak values were calculated. The results showed that the GIUH model was calculated to be 52.5% higher than the WinTR-55 model. The results showed that in S1 and S2 subfields S6 and S8, due to their mountainousness and increasing slope and flow velocity, sediment transport capacity and erosion are active. In S3, S4, and S5 S7 subfalls, due to low slope and low flow rate, low transmission capacity and sedimentation occurred. Also, the values of RMSE and R2 calculated for both models showed that the WinTR-55 model has higher accuracy and better performance than the GIUH model in estimating peak peak flow.

This study has been carried out for the modeling of monthly runoff using Temez model and then the effects of the different land use change scenarios on runoff components have been assessed. The OLI-Landsat 8 satellite imageries were used using a support vector machine (SVM) classification method. The 10 management scenarios have been developed based on field characteristics, changes trend in the land use pattern, and the suitability criteria. The Temez monthly hydrological model was employed. A 10-year (2002 to 2012) daily precipitation, temperature and runoff data were aggregated to monthly time scales. The calibration and validation steps were performed based on observed data. For calibration of the model, the first 6 years data and for model validation 4 years data were used. The accuracy of the land use map was quite high. A Kappa coefficient of 0.95 and an overall accuracy of 0.975 was obtained. The accuracy of the modeled runoff was presented using R2 coefficient, which was 0.77 and 0.65, for calibration and validation stages, respectively. The results showed that land use reclamation scenarios of 3, 4 and 5 had a decreasing effect on the runoff by 3.4, 3.3, and 4.1 percent, respectively. Also, the land use scenarios of degradation condition, 9 and 10 scenarios, caused an increasing effect on the monthly runoff to 15.24 and 4.5 percent, respectively. The monthly hydrological Temez model showed relatively good performance in estimating monthly runoff values based on the data used.

Mass movements of the earth's surficial materials downward the slopes is called slope instability, which is affected by the earth gravity, while the rate of material mobility increases by the presence of water in the sediments. Each year, slope instabilities cause enormous economic damages to roads, railways, power transmission and communication lines, irrigation and watering canals, ore extraction, as well as oil and gas refining installations, infrastructures in cities, factories and industrial centers, dams, artificial and natural lakes, forests, pastures and natural resources, farms, residential areas and villages or threaten them. Nowadays, many instabilities are resulted by human intervention and manipulations. One of the effective human factors in instability occurrence is the construction of roads. Road construction, especially in mountainous areas, increases the probability of occurrence of various types of instabilities, as it changes the natural balance of the slopes and causes deformations in the land. Each year, lots of casualties and financial losses are imposed by the occurrence of various types of instabilities in the slopes overlooking the roads, which also cause the destruction of many natural resources in the country. However, the construction of roads, highways and freeways is necessary and unavoidable in today’s life. The Karaj-Chaloos road and the Tehran-North highway are two routes that connect the Iran’s capital Tehran with the southern shores of the Caspian Sea, but suffer frequent slope instabilities.

The purpose of this study was to investigate and compare the two models of artificial neural network and TOPSIS model in the risk of landslide in the downstream of Sanandaj dam. This was done using ARCGIS software, Python programming language, and artificial neural network models and TOPSIS. For this purpose, 9 input layers were used in landslide risk zoning. Landslide and non-slip points in the area were determined using satellite imagery. Internal weighting was used to determine the weight of the layers. In the neural network model, the data were trained using a multilayer perceptron network with the Adam learning algorithm. The network structure has 9 neurons in the input layer, 30 neurons in the middle layer and 1 neuron in the output layer. In the Topsis model, after declassifying the decision matrix, Shannon's entropy method was used to weigh the criteria and to determine the relative distance from the Euclidean distance. After preparing the models, the study area was analyzed with 970 Km2 with 9 input variables that were converted to raster data into 30x30 pixels. The results of the analysis were mapped with five floors of landslide risk for each model. After applying 5 methods of calculating the error rate to validate the models, it was found that the perceptron neural network model has less error and more adaptation and is better compatible with the geography of the region.

SWARA Multi-Criteria Decision Analysis model was used to weight the parameters. The Step-wise weight assessment ratio analysis (SWARA) model was developed by Keršuliene et al (2010). WASPAS multi-criteria decision-making model was used to prioritize sub-basins in terms of flood sensitivity. The Weighted Aggregated Sum Product Assessment (WASPAS) method is proposed by Zavadskas et al in 2012. The WASPAS method consists of two aggregated parts: 1- The Weighted Sum Model (WSM) and 2- The Weighted Product Model (WPM). According to a comparison between 22 parameters using the SWARA method, it was specified that Drainage texture, Texture ratio, and Drainage density (weighted as 0.273, 0.273 and 0.156) have the highest impacts on Flood occurrence in study area. On the contrary, Rho Coefficient, Constant of channel maintenance, Infiltration Number, and Length of overland flow show the lowest weight.Sub-basins prioritization results using WASPAS model showed that sub-basin 1 with 0.907778 coefficients, sub-basin 3 with a coefficient of 0.858988 and sub-basin 2 with a coefficient of 0.818645 have high sensitivity to flooding. The results also showed that sub-basins 4, 7, 11 and 15 in high class, sub-basins 8 and 9 in moderate class, sub-basins 5, 10, 12 and 14 in low class and sub-basins 6 and 13 in the very low class of In terms of flood sensitivity. The total area of sub-basins in the high and very high class of flood is 656.72 km2, which comprises 57.24% of the total Aland Chai basin.

One of the most important issues, facing the human society and environment, is water resources management. Regarding the drought, this issue turns to a serious challenge for decision makers, and affect the people more than other natural hazards. In Lurestan, considerable number of springs and rivers have been dried in recent years, which are ascribed to precipitation shortage. This study evaluates meteorological drought in Lurestan by applying Percent of Normal Index (PNI) through 1988–2017 time span. The PNI indicates that only low percent (6.6–30%) of the studied time span experienced drought which has been weak drought type. This signifies that the area has not suffered from severe drought during this period. Therefore, symptoms of severe drought, appeared as dried rivers and springs, could not be products of meteorological drought, solely. They could rooted in overexploitation of the groundwater has dropped the water table far beyond the reach of tree roots and springs outlets. Analysis of the return period of the drought also proves an extremely long time of reoccurrence of severe drought. Weak drought also has a very long return period (100–200 years). Therefore, meteorological drought could not be solely responsible for the droughts in Lurestan, and socio-economic drought and associated water management must be the main reason. Based on the reconstructed data for the years without data, reliability for the acquired results in Khoramabad, Aligudarz, and borujerd stations is 100%, for Azna, Dorud, and Noorabad is 56.7%, Poldokhtar 63.4%, and Kuhdasht and Alashtar is 66.7%.

In the drainage basins of arid and semi-arid areas where the ecosystem is not able to recover quickly, extreme care should be taken in land use. The hydrological effects of changes in land use are manifested in the form of changes in runoff depth, minimum flow, maximum flow, soil moisture, and evapotranspiration. Increasing runoff production in a particular area, in addition to increasing the potential for flooding, has other effects. Due to the type of soil and the topographic and climatic characteristics, the hydrogeomorphological changes caused by human encroachment on slopes and land use changes have been high in Ojan Chai area (from the sub-basins located on the eastern slopes of Sahand Mountain). Due to erosion in the slopes of Ojan Chay area, it seems that the changes in the amount of runoff are very large due to land use changes in the area. The study area is one of the rangelands of the country and unfortunately, cultivation is done in an unprincipled manner in the slopes that are not suitable for cultivation. In the coming days, the turbulence of the slopes will intensify and the amount of runoff will increase and the number of destructive floods will increase. Often, the soil of the slopes is severely eroded by runoff due to the extreme cultivation in the rangelands.

The aim of this study was to investigate the changes in land features and its role in the study of soil erosion in the Sharif Beiglou watershed. In this regard, first using Fragstats 4.2.1 software, 9 measures of land appearance including spot density (PD), largest spot index (LPI), total margin (TE), margin density (ED), spot shape index (LSI) Average spot size (AREA-MN), average distance of Euclidean nearest neighbor (ENN-MN), DIVISION index, fragmentation index (SPLIT) were calculated. Then, the intensity of soil erosion in the area was estimated using the Erosion Potential (EPM) model with acceptable performance based on previous studies. Then, the results of calculating the measures and the severity of soil erosion were entered into SPSS software and a significant relationship was determined. Then, the results of calculating the measures and the severity of soil erosion were entered into SPSS software and a significant relationship was determined. The results showed that in the study basin, agricultural use has high erosion, rangeland and garden uses have moderate erosion. At the level of landscape, for Sharif Beiglou watershed, the number of spots is 49, the spot density is 1.15, the largest spot index is 80.64, the total margin is 75508.008, the margin density is 17.75, the spot shape index is 4.56, the average spot size is 86.79 and landscape rupture was calculated to be 0.34 and fragmentation to be 1.52. At the class level, the amount of fragmentation in the water body is the highest.

The purpose of this study is to monitor the effects of exploration and melting service on vegetation in areas of Varzeqan city, including Andaryan. The heap leaching method is used to produce gold in these areas, it is more likely that the chemicals used in the melting services would spread in the environment or penetrate. Vegetation is one of the phenomena that is severely affected and reduced by environmental pollution, especially cyanide leakage and infiltration. Therefore, monitoring of vegetation trends may put an end to such concerns. Therefore, the study area is divided into three parts: Zone 1 (mined area), Zone 2 (pristine and untouched area), and Zone 3 (downstream of Zone 1). For this aim, Landsat 5 and 8 satellite data in the period 1984-2019 were used as time series and temperature and precipitation data of Varzeqan station in the period 1989-2017. Using Normalized Difference Vegetation Index (NDVI), vegetation density was driven as a pixel scale (a pixel = 900 m2), the non-parametric Mann-Kendall statistical test was applied to NDVI at 95 and 99% confidence levels. Then, the areas of a significant reduction were analyzed using a sequential Mann-Kendall test to investigate the starting point of a significant decrease in all three areas. The results show that chemicals materials have not been returned into the environment and the climate controls land cove changes in the study area.

In this study, by combining GIS and multi-criteria decision making systems (MCDM), areas with different degrees of flood risk for sustainable settlement of the population in each of the cities of Khorasan Razavi province have been identified. For this purpose, first 6 effective parameter data including maximum discharge with 2, 3, 5, 10, 25, 50, 100 and 200 year return periods obtained from HEC-HMS software output, drainage density, land use and Vegetation, CN, slope and permeability of the study area were prepared in GIS software environment. Then, using ANP method and pairwise comparison, the weight of each criterion and the weight of the classes of each layer in Super Decision software were calculated, respectively. Then, using GIS software analysis functions, the whole range was zoned for each of the specified criteria. It was prepared a lot until the flood. The results showed that the area of ​​cities that are exposed to very high floods and the results of flood risk zoning with a return period of 2 years in the whole province showed that more than 86% of areas with low and very low floods, 2 12% of the areas are moderate and 1.8% are high in terms of flooding. While the results of flood zone in the 200-year return period showed that 41.3% low flood, 31.4% moderate flood, 13.3% high flood and 14.1% very high flood in the whole province.