نشریه هیدروژیومورفولوژی
پیاپی 26 (بهار 1400)

Suspended sediment load is one of the most important river elements that, in addition to its impact on water quality, has an effective role in managing water resources and structures on these resources. Therefore, estimating the suspended load can be a great help in increasing the productivity of water resources and improving the efficiency of aquifers. Determining the exact and proper parameters that have an effective factor in the sedimentation rate of the catchment area has an effective role in increasing the accuracy of data mining models. Physiographic parameters that indicate the physical properties of the watershed can be considered as a determining factor in the extent of sedimentation of the catchment area. There are several methods to estimate the suspended load of rivers. One of these methods is the use of data mining models that are very useful in solving hydrologic problems. Therefore, in this research, by combining data mining models and sediment load physiographic parameters of 30 watersheds in Lorestan province with a statistical period of 33 years, in order to study the effect of different physiographic indices on sediment estimation in the first step of flow flow as the only input of models and in step Next, various field physiographic indices were selected as inputs of different data mining models. In this study, five data mining models including artificial neural network, evolutionary support vector machine, decision tree, Gaussian process and regression were used. All models have been well received.

Earth's climate is one of the most important structural factors. Any anomalies in each of the components will cause irregularity and commotion in the whole system. The coefficient of variation of less precipitation is reagent stability and even time distribution. To examine the relationship between climatic factors and its effect on local lakes dewatering was used of the temperature and precipitation data of 50-year-old Asfazari database in cells 15 x 15 km. In addition to measurements of temperature and precipitation of central tendency, indexes used of dispersion indexes in statistical processes. Thresholds obtained show that the basin con ensures exit of the lake that to be the average temperature of less than 15.78, average annual rainfall more than 215 millimeters, snowy coefficient more than 13 percent, the coefficient of variation of precipitation less than 40 percent and the coefficient of variation of temperature more than 7.43. All basins inside Iran changed to a temperature not fit in the Quaternary. Status and evidence there are of lakes dewatering in the Quaternary do not match whit precipitation double and decline of temperature 6-12 degrees compared to the current conditions. So that line equilibrium of water and land could be the effects of the Quaternary terrace lacks by reducing 3, 9 and 12-degree temperatures and increased precipitation. Change the line equilibrium of water and, land cannot be interpreted with a temperature and precipitation changes alone and causality must search in changes of precipitation regime and geomorphology of the region.

Groundwater is recognized as one of the most important and reliable sources of water supply all around the world. However, population growth and reducing the volume of surface water reserves have led to the overexploitation of groundwater and groundwater resource depletion over the world. Therefore, exploration and exploitation of groundwater resources require a thorough understanding of geology, hydrogeology, and geomorphology in any area. With the advancement of remote sensing science and the use of satellite imagery in various fields, costs have been reduced and the time required to explore various sources including groundwater has been reduced. Nowadays, using fuzzy decision-making methods, it is no longer necessary to use only the financial equivalent of social and environmental criteria in choosing the best alternatives, but also to use different quantitative and qualitative criteria in prioritizing and selecting the best options and criteria in water resources management. In this study, eleven thematic layers, including lithology, precipitation, vegetation cover, density and distance from the fault, elevation, slope, temperature, land use and density, and distance from drainages to potential detection sources of groundwater used Silakhor plain.

Coastal areas are of special importance to humans due to their many uses. Changes in the coastline are inevitable despite human beings and their effects such as land-use changes, and therefore it is necessary to study the relationship between coastline changes and land-use changes. Babolrood coastline with a length of about 9 km in most of its area intersects with the city of Babolsar, which causes the impact of human activities on changes in the coastline in this area. The fluctuating behavior of the Caspian Sea and the rate of regression and advancement of the coastline in this area can be affected by human activities and changes in coastal land use. The data used in this study include the level of the Caspian Sea and Landsat images on TM and OLI sensors. The length of the 42-year study period from 1976 to 2018 has been determined, which is in line with the trend of changes in the level of the Caspian Sea. The analytical research method is a comparison between sea level data and information and shoreline changes and land use maps. The system (DSAS) in ArcGIS10.7 and ENVI5.3.1 has been used to calculate land-use changes. After calculating the shoreline changes and calculating the NSM, the shoreline change diagram was extracted and compared with the land-use changes. The results show that human activities above sea level have been effective in shoreline changes, the most important of which is the development of coastal structures and structures beyond the natural shoreline.

Snow and ice cover is a vital resource and is very sensitive to climate change. Accurate measurement of the spatial distribution of snow and ice at regular intervals is essential for water resources management. In this research, the snow cover of Sabalan Mountain is extracted using Landsat 5 satellite images for 2000 and Landsat 8 for 2020 using object-oriented classification and also using NDSI and NDSINW spectral indices. The results of the classification maps extracted from the object-oriented method showed that the area covered by snow for the years 2000 and 2020 is 2500 and 1954 square kilometers, respectively, with a kappa coefficient and an overall accuracy of 99%. And 0/99 for both years. Then the snow covered area was extracted using NDSI spectral indices and NDSINW index. Both of these indicators are able to extract the snow cover surface with appropriate relative accuracy in cold and winter regions. However, because the NDSI index does not distinguish between snow and water, it may produce different results in areas with waterlogging associated with snow extraction. The NDSINW index, on the other hand, is more accurate in eliminating waterborne backgrounds. In relation to the present study, the NDSI index has extracted 2610 and 2577 square kilometers of snow cover and the NDSINW index has extracted 2577 and 1937 square kilometers for 2000 and 2020, respectively. The area obtained from the NDSINW index has been extracted by the object-oriented classification is closer.

Streamflow forecasting is required in many activities associated with the planning and operation of water reservoir systems. In hydrology, short and long-term streamflow forecasting are essential to optimize hydrological systems, which can lead to the expansion or reduction of future projects. In this research, using wavelet-based de-noising data and wavelet transform, a temporal pre-processing approach was applied to the monthly runoff time series in Samian station at the outlet of Ardabil plain. In the second stage, the rainfall-runoff modeling was performed by Artificial Neuron Network (ANN) for three different combinations of data. The first and second combinations of input were used from Samian station data but the third combination was used from the upstream runoff data of Samian station (Gilandeh and Kozatopraghi stations). The results showed that the serves of both wavelet-based de-noising data and wavelet transform (WT) techniques could improve the performance of the ANN rainfall-runoff modeling of the Samian station up to 4% and 18.5% in the verification phase. The third combination of data demonstrated better accuracy in comparison to the other data set.

Iran is one of the arid and semi-arid regions of the world with an average annual rainfall of 240 mm. The country is such arid that the average annual rainfall is less than 130 mm (Jafari and Tavili, 2013:149) in 65% of its regions; therefore, it has been facing a water shortage for a long time. Thus, due to the limitation of surface and groundwater resources in the country, particularly arid and semi-arid regions, it is necessary to identify the factors affecting the quality of water resources for protection to reduce the vulnerability of these resources. Among the various factors that cause water quality degradation, the type and material of rocks or geology are crucial in changing groundwater quality (Jehbez, 1994: 1). Accordingly, in this research, the efficiency of the GWR model was measured to determine the sources of water pollution by selecting the Izdakhvat basin as a sample of inland Zagros basin that has good but saline water resources; these areas received the most impact from a particular formation.

Landslide as a process of change in the stress-strain state of a slope occurs under the influence of natural and human parameters leading mass separation and its movement to down slopes. However, the relationship between the sliding mass and the slope remains constant. Accordingly, the mechanism of formation and development of a landslide is a systematic sequence of changes in the stress-tension state of a slope influenced by natural and anthropogenic parameters. This event is destroying human settlements and infrastructures and causing financial losses and many deaths around the world annually. The rapid population growth in the last half-century, the expansion of settlements towards steep mountainous areas on the one hand, and the false human being intervention in the destruction and changes of slopes, on the other hand, increased the frequency of landslides and this has led to an increase in damages. Iran has favorable natural conditions for a wide range of landslides with mainly mountainous topography, high tectonic and seismic activity as well as diverse climatic and geological conditions. Therefore, landslide studies on understanding factors and parameters affecting it, and identifying high risk and vulnerable areas in the world as well as in Iran have received serious attention. This research mainly aims to investigate the parameters affecting the landslide in the Vahregan catchment which located in the Sanandaj-Sirjan construction zone. Where metamorphic rocks, marl and shale, as well as wide area of quaternary sediments, have provided very favorable conditions for landslide occurrence.

Multiple linear regression method was used to perform this research. Thus, the scatter map of the landslides of the region as dependent variable and twelve factors includes elevation, slope, slope direction, lithology, fault, precipitation, drainage network, road,
land use, vegetation, TWI and SPI as independent variables were considered. To prepare landslide distribution map of the study area, aerial photographs of 1994 with a scale of 1: 40,000 were used and interpreted. Accordingly, the landslides area and their location in Google Earth software were determined. Then, 138 landslides occurred in the Vahregan catchment were determined with field studies, with the help of available maps and information, and the use of GPS system. It was then mapped using GIS software. After converting all the factors to information layers in GIS, these layers were adapted to the scattering map of the landslides of the region and were calculated the percentage of region located within the landslide area for all factors.

The results showed that the most effective factors in Vahregan catchment landslides based on multivariate regression method are distance from road, lithology, precipitation, land use, slope direction, distance from drainages, distance from faults, SPI drought, elevation, slope and TWI, with coefficient of 0.851, respectively. Their coefficient of R is 0.851 which is acceptable. The results showed that although natural factors can alone cause landslides, human factors are currently the most important parameters in causing landslides in the study area. Accordingly, most new landslides occur in close proximity to roads. In other words, it can be said that the downstream cutting of slopes by human being has increased the frequency and magnitude of landslides. Therefore, results showed that the road with 0.411 standard coefficient was the most important factor in creating landslide so that much of the landslide has occurred within less than 3 km of roads. Then, the natural factors includes lithology and precipitation with a standard coefficient of 0.362 and 0.299 and land use with a standard coefficient of 0.286 played the most role. However, vegetation factor and the TWI index with a standard coefficient of 0.103 and 0.127, played the lowest role in the landslides of the Vahregan catchment.  According to the final landslide zoning map, more than 50% of the area has located in a high risk area.

The study area has great potential for landslides in terms of natural features such as lithology, precipitation, elevation, Permanent River, and slope. The landslide map with 382 landslides indicates this. However, in the last two to three decades, environmental changes such as drought and consequently changes in vegetation covers on the one hand, and false human intervention, including the construction of multiple roads and the geometrical change of slope, on the other hand, have increased the frequency and magnitude of landslides in the studied area. The results of the final mapping showed that more than 50% of the basin is in high and very high risk areas. Accordingly, special attention should be paid to the extent of landslide risk and its threat in all human activities, especially environmental planning and management.

In this study, the water quality of Khorramabad river was simulated using a one-dimensional QUAL2Kw model over a distance of 35 km from the river. For this purpose, important water quality parameters such as dissolved oxygen (DO), carbon biochemical oxygen demand (CBODf), chemical oxygen demand (COD), nitrate (NO3), electrical conductivity (EC) and acidity (pH) and temperature parameter in two months July and September 1397 were used for calibration and validation of the model, respectively. The results of evaluation indices showed that the NRMSE index in the calibration and validation stage of the model was obtained for the lowest value for pH and equal to 8.83 and 9.22 percent and for EC was calculated as 11.05 and 13.86 percent, respectively. The simulation of the DO parameter also had fluctuations along the river, while the statistical indices NRMSE, RMSE and MAE for this parameter in both calibration and validation stages were obtained to an acceptable level, so that the above indices in the calibration stage of the model 12.49, 0.917 and 0.72, respectively, and in the validation stage of the model, 24.65, 1.78, and 1.55, respectively, were calculated. Also, the model was able to simulate the temperature parameter with good accuracy in July (RMSE = 1.92 and MAE = 1.57) and September (RMSE = 2.77 and MAE = 2.5709). Finally, the results of this study showed the appropriate accuracy of the QUAL2Kw model in simulating the above parameters in the Khorramabad River.

Due to the growing need of human societies for groundwater resources, especially in arid and semi-arid regions such as Iran, the protection and prevention of pollution of these resources is considered essential. To this end, groundwater vulnerability assessment can play a vital role in the protection and exploitation of these resources. Hajiabad plain with an area of ​​about 158 ​​square kilometers is located 160 kilometers north of Bandar Abbas. Due to the importance of this plain in terms of agricultural and drinking water supply in the region and due to the declining groundwater level in the region, the withdrawal of water resources has been prohibited in recent years. In this study, the vulnerability assessment of Hajiabad plain aquifer was performed by DRASTIC and SINTACS models. Finally, the final vulnerability maps were calibrated with EC values. In order to study the hydrogeochemical properties of groundwater resources in the plain, 26 water samples were collected from designated points in different periods of the water year 1398. Water samples were analyzed in Hormozgan soil and water laboratory. Also, the results of water sample data analyzed by Hormozgan Regional Water Organization have been used. The vulnerability index of the Drastic model for the study area is a value between (128-94) and for SINTACS (115-156). It is located in the central and eastern part of the study area.The value of the correlation index between EC and DRASTIC and SINTACS vulnerability models is estimated to be 39 and 35, respectively.