نشریه هیدروژیومورفولوژی
پیاپی 14 (بهار 1397)

Introduction
Investigation of river terraces is one of the main issues in the field of river geomorphology. River terraces, as a medium of alluvial landforms and heritage of stratigraphy, are widely investigated by geomorphologists to understand the tectonic and climatic time. The formation of alluvial terraces is primarily the result of tectonic rise alongside the cycling cycles. The edges of a river that is hard and resistant to geology are wall-bound or steep sloping, similar to water-breakers, and limit the number of the steppes to the alluvial terraces; but on the sides with a looser lithology, alluvial terraces are formed with a slight slope. Go up or down to the basin or the sea level changes are accompanied by a change in the slope along the river, creating tectonics alluvial terraces. Ghezel Owzan River, as one of Iran''s longest river systems, has well responded to lithological and tectonic factors. The Ghezel Ozan Basin is located in the northwest of Iran, and in latitude of 34° 53'' 21" to 37 ° to 56'' 2" north and longitude is 46 ° 27'' 43" to 49 ° 19'' 43 "east. The origin of the Ghezel Ozan River is from the heights of Chehel Cheshmeh Kordestan and with a length of more than 550 km, after crossing Zanjan, East Azarbaijan and Ardebil provinces, along with several streams along its path, intersects in the Guilan province with the river Shahroud and enters the reservoir of the Sefidrood Dam.
Accordingly, river terraces are lithologically divided into marl, crystallized and conglomerate periods with the help of geological (1/100000) and topographic (1/50000) maps and using computer software such as Arc, GIS, Global Mapper, and Excel. River path is also lithologically and tectonically divided into eight periods and profiles of each period are drawn. In order for the collection of information, we have translated several English articles and examined various internal sources related to the subject matter of the research. With the help of geological maps and field observations of the region, we investigated the effect of tectonics and lithology on topography (symmetric-asymmetric) on alluvial terraces. Using the Global Mapper, the cross-sectional profile was mapped along the river''s perpendiculars and analyzed.
Results show that from among the major lithologies of Ghezel Owzan terraces (marl, crystallized, and conglomerate), marl terraces are more asymmetric and crystallized terraces are more symmetric in areas without tectonic movements. Symmetrical terraces are formed in areas without tectonic movements or in areas with the same tectonic movements on both sides with resistant lithology. Asymmetrical terraces are also formed in areas where tectonic movements are not the same on both sides or in areas where there are marls in-between geological layers. Marl lithology, which is the dominant lithology of the basin, has the greatest impact on the asymmetry of terraces on this river. Tectonic has been active in A, C, E, F & H periods and inactive during B, D & G periods.
Discussion and Conclusion On the bed of the Ghezel Ozan River and major parts of Dyvandra to the Miyaneh, Qareaghaj and the greater part of the province of Tarom, it is overcome with Marl Lithology (Hashtchin to Khalkhal, upper and lower part of Hashtrood and Turkmen Chay, southern provinces of Miyaneh and Zanjan, middle section of Sojas). The conglomerate sediments are the dominant lithology of Qazlazan from Soltaniyeh to Nikpay and the upper of most major branches. The irregular dispersion of lithology and faults in different parts of the Ghezel Ozan River makes it impossible to sequentially divide the alluvial terraces. In resistant lithology, alluvial terraces of symmetrical are formed and in the marl lithology, the slope of the arches of the arches provided the possibility of a deep cut and, with deep erosion and common landslides in the transverse surfaces, low-calorie alluvial terraces is created with low altitude difference. Another factor in the asymmetric of the alluvial terrace is the lithology of the basalt and limestone of the Ghezel Ozan River terrace that act as a barrier and by reducing the river slope and reducing the erosion of the water, the river is forced to move horizontally before the strait, the degradation of the compressive levels has led to asymmetry of the terraces and denser plains.

In a natural ecosystem, changing the environmental conditions of that ecosystem influences hydrological responses such as flooding and the extent of erosion and sedimentation of the area. One of the models used to investigate the effect of land use change and climate change on SWAT runoff, the SWAT model is a hydrological simulator and a continuous and semi-distributive time-space model with a physical base. Understanding the relationship between land use change and its causative factors and its secondary effects on hydrologic regimes provides essential information for land use planning and sustainable management of natural resources. Investigating the amount and trend of the changes and its effect on hydrological processes in the basin is a way to predict the state of future changes and provide more effective plans for sustainable development of water resources in the basin. The construction of the Garin Dam in the Garin Basin and the risk of filling the sediment reservoir with sediment and reducing its useful life due to seasonal floods and the effect of basin land use and climate change on the reason for choosing this area for this research. The purpose of this study was to study the land use and climate change in the studied watershed and determine the effect of these changes on the runoff rate of this watershed in order to better manage it. Study of Area Garin dam dam is located in the province of Hamedan and is located in the mountain range of Zagros mountains. This area includes the catchment area of Sarab Gamasiab River to the Garin Reservoir Dam and its area is up to the 22,000-square-meter Garin Garin Dam, the Garinland basin is mainly mountainous and its range of elevation ranges from 1833.9 to 3429.2229 meters above sea level.
Materials and Methods SWAT model input data include climatic and hydrological data (daily precipitation, maximum and minimum temperature, relative humidity, wind speed, dew point and solar radiation), which is ten years in the study of statistics related to the synoptic stations Skinheads Became Topographic maps, digital elevation model (DEM), soil and land use are also needed as model inputs. A digital elevation model (DEM) was extracted using a topography map of 1: 250,000 Garin River basin. Calibration and validation of the SWAT model in SWAT CUP software. The study used calibration data from 2002 to 2007 and 2008 to 2010 for validating the model. In order to determine the degree of sensitivity of flow parameters in the model SWAT using SUFI2 software SWAT CUP sensitivity analysis for 24 parameters election, the results of the sensitivity analysis on the Elimination of parameters that has the less sensitive they are, the calibration process decision It is accepted. According to the P-value and T-Stat criteria, the sensitivity of the parameters is determined. Land use maps of 1986, 2000, and 2014 were prepared in the previous stages, and the Markov chain and the CA Markov filter were used to map the land use in 2042. In this research, the outputs of the Hadcm3 model were used to predict Garin's future climate. In this research, the SDSM statistical method was used to fine-scale the output of the general atmospheric circulation models. The SWAT model was used in the range of calibrated parameters to simulate runoff from climate change in Garin basin under two scenarios A2 and B2. After micro-sampling, the SWAT model was converted and the model was analyzed for the scenarios. Then, the results of model implementation with different scenarios and the results of model implementation with the current climate conditions were compared

Discussion and Results:

Regarding the results of statistical indices, NS index is equal to 0.95, P factor and R factor were respectively 0.47 and 0.03 respectively, and the coefficient of determination (R2) for simulated and simulated floodguns was 60 / 0. Accordingly, the results were confirmed in the calibration phase. The validation phase was conducted to verify the correctness of the selection of parameters during the calibration period for the period 2008-2010. Given that the Nashatcliff coefficient for Garin's catchment area at calibration and validation stage was equal to 0.95 and 0.66, respectively, the results were satisfactory and the SWAT model was able to simulate surface runoff in Garin River Basin. In general, due to increased forest use due to increased permeability and water drainage to the surface and deep water aquifers and increased evapotranspiration, the amount of runoff has decreased. Regarding the results of temperature, rainfall and runoff of the next period, it can be seen that in the months when rainfall is reduced and the temperature increased, the amount of runoff in the coming period also decreases. The main reasons for this discrepancy can be attributed to the difference in the intensity of land use change as well as the extent of the altered land area, which, given the mountainous nature of the area in the Garinland basin, can be compared to other areas with flat lands with agricultural uses. It is concluded that the effect of climate change in the Garin dam basin is greater than the change in land use due to its mountainous nature.

The results of the study of the effect of land use change on runoff in the Garin basin indicate that the amount of runoff is decreasing daily and monthly in this catchment area. Also, the results of the study on the effect of climate change on runoff in the Garinwestern basin indicate that the amount of runoff is daily and monthly in this catchment area. Considering that in both scenarios A2 and B2 the monthly average temperature, especially in the first and last months of the year, has an increasing trend and rainfall has decreased in the spring and winter, this decrease can be attributed to the increase in temperature which Following this, evaporation also increases and decreases in rainfall in this catchment area. Regarding the results, it can be seen that the average monthly runoff in months when rainfall decreased in January, February, February, April, May and December, and in the months when rainfall increased As of June, July, August and September, the amount of runoff will increase compared to the current period. It is also observed that the effect of land use change on the reduction of runoff in the upcoming period is lower compared to the change effect under A2 and B2 scenarios and will affect the climate change of the runoff more flatly and the reduction of runoff is more affected by climate change. According to the information obtained from these predictions, it is possible to properly manage the watershed and adopt appropriate management measures in accordance with the conditions of this watershed and to prevent unauthorized land use changes and reduce the damage caused by The phenomenon of climate change.

Urmia Lake is located in the North West of Iran and its area between 4750 to 6100 square kilometers at an altitude of 1250 meters above sea level. This lake is a permanent lake in Iran. In fact, Urmia Lake is one of the lowest parts of the catchment area North West of Iran. The total surface area of Urmia Lake is 51,876 km square, which is 3.15% of the total area of Iran and 7% of all the water’s surface in the country. The depth varies between 6 and 16 meters, the length of the lake is 50 km and its width varies between 128 km to 140 km. In the catchment area of the lake, there is the main river with annual input about 2 billion cubic meters. Annual rainfall in the catchment area is variable between 200 and 300 mm. Air temperature the area around the lake in winter to 20°C and 40°C in summer increases. Urmia Lake is important in terms of economically, transport, exploitation of the mineral wealth of biodiversity, mitigating climate, and tourism. This unique Lake addition to the previous is habitat for kind of native artemia its name is urumiana artemia that this artemia is unique to this lake. Also, Urmia Lake is the world's second largest habitat for Artemia. According to the research, the main elements in the Urmia Lake include Cl-, Na , Ca2, Mg2, HCo3-, K, Li, So42- and F.
In this study, newly launched Landsat series (Landsat-8) was used for monitoring Urmia Lake salinity and retrieving the salinity map. By incorporating the Landsat-8 datasets, this study determined the salinity changes and created a model to estimate the salinity in Urmia Lake with processing Landsat-8 satellite images as a result; we can obtain salinity map regularly without ground operations. We can also monitor the health of the habitat in terms of salinity and examine the impact of increasing salinity on the plants, animals, and ecosystems of the region. This study applied remote sensing techniques to develop a salinity prediction model for Urmia Lake. In this study, we use Landsat-8 satellite images radiances of Urmia Lake and some salinity indices and in-situ data so we have 17 features to make water surface salinity model with support vector regression (SVR) with all features. After that, we use two algorithms; GA and SFS for selecting suitable features and make models with those features.
Results with all features model show RMSE=24.55 and R2=41% and result with GA feature selection model shows RMSE=21.97 and R2=54% and results with SFS feature selection model shows RMSE=21.93 and R2=53%.
Discussion and Satellite images show that from 1995 to 2003, the lake water surface dropped and proportionate to the dropping water salinity increased to 220 to 300 grams per liter. Also although Artemia is resistant to salt, appropriate salinity is below 100 grams per liter. When water salt is more than 100 grams per liter contents of his tiny body lost and die. Now because of reduction in salinity, the lake has arrived at about 300 grams per liter. Dissolved salt in water has a direct effect on the electrical conductivity of water. In this regard, incorporating high spatial resolution satellite like Landsat-8 images is inevitable. Also, the proposed modeling methods show these changes in multi-data and in widespread Urmia Lake very well

Introdution
Alluvial floodplains, and in particular those associated with the world's largest rivers, have a complex relief that is produced by recurring erosional, and depositional events.The magnitude, heterogeneity, spatial distribution, and connectivity of this relief controls river floodwater routing and storage, sediment dispersal, and biogeochemical cyclingChannel Lateral movement and course changes are main causes for floodplain extend ,bank erosion and soil loss due to cut bank .Aras river that located in NW of Iran(from 45°E to 48°E), have many curvatures on course and due to this reason Aras is made high rate movement yearly .Aras is a boarder river and for this reason is very important that direction is determined .
In this article for determining the rate of lateral movement is used landsats 5,2 (Mss) landsat5™landsat 7(ETM) and landsats(OLI) with 30 and 15 resoulation in 1985 to 2015 epoch. In this study is used Rm, R and MI for rate and degree movement and rate of river course curvature .
In order to determining of power flow against instability of mater in this article is used MI
idex: MI=S√Q/D50
And for determining of rate of displacement of channel, is used of Rm index: Rm=(A/L)/Y
Discusses
Investigation on the curvature radial Aras channel show that average rate of radial is 509.62 m. In other site this rate is 515.71 m. The study also show that changes in Aras river course is vary .When wide is high ,channel migration is excess .In recent time this changes is high ,but rate of migration in Iran site and other site is decrease to compare of past time .The average of channel migration to Iran site is 27,21m in 2010 and other site rate is 28,32 m.
Sum all area that located at other site due to displacement are 1410255 m3 (1985-2015).Area in site of Iran is 2230869 m3 (1985-2015).That is to say ,difference is 820614 m3.This has meaning that our land and soil is placed other site due to channel movement .Yearly average displacement of channel Aras river is 475 m at Iran site and 353 m at other site .So ,displacement at two site is vary .Over the past three decades, the fluvial dynamics of meander bends, including processes related to outer bank erosion, have been the focus of numerous scientific investigations. Despite this effort,a comprehensive understanding of the hydraulic processes of outer bank erosion—especially the role of flow turbulence—remains elusive.Because natural river flows are fully turbulent, the erosive stresses acting on the banks of meandering rivers should be related to turbulent stresses. Current models of outer bank erosion, however, rely on simple parameterization of the flow via excess velocity, excess shear stress at the bank toe, or excess flow depth .
Aras River is very dynamic .This river make curvature in its curse and cut bank .When river make meander in flow curse ,cut power of flow is increase .This high power is energy for bank cut and movement .Soil lost is other result for cut bank .This story is happened in northern border of Iran .

The variations of amount, intensity and type of precipitation variable are transformed through spatial and temporal dimensions. Flooding precipitation as a dangerous natural hazard is caused of such variations. The annual heavy precipitations are triggered many hazardous floods over the most of catchments in northern Iran. Hence, investigation of the generation and evolution mechanism of synoptic circulation patterns triggering of flooding and heavy precipitations could play a key role during risk management and mitigation measures of such natural hazards.
In this study, we aimed to investigate and analysis of synoptic condition of perceptible systems in Babol-Rud catchment. Two main questions were as below: how do the annual heavy precipitations follow the occurrences cycles? and how do the synoptic factors impact on annual heavy precipitations in Babol-Rud catchment?
Data In this paper, both type of ground level and remotely sensed data were used. Diurnal data were gathered from eleven rain gauge stations in addition of a hydrometric station named as Quran-Talar. Number of days with heavy precipitation were considered by confidence level of P=95%. Atmospheric variations were collected as sea level pressure and geo-potential heights in 500 hPa with spatial resolution of 2.5*2.5 arch degrees. Water discharge of Quran-Talar hydrometric station was selected as monitoring indicator of the study area.
Spectral analysis is a proper procedure to extract of cycles in time series. Its merit is related to low-volume statistical operations based on Fourier transform. In order to extract the heavy precipitation and number of days with heavy precipitation, the percentile indices and the thresholds of US climate variability and predictability program (CLIVAR) were used. In this regard, equal to 435 days from 7305 total days in time series were selected as days with heavy precipitation in the study area. Based on clustering analysis, all temporal sequences were classified as three precipitation clusters.
In this study, variations of annual heavy precipitation and water discharge data were investigated using synoptic and statistic techniques. Trends and occurrences cycles were investigated during temporal time series. Results revealed the significant annual and biennial curvilinear cycles in confidence level of P=95%.
Northern wards of Iran have been recorded as the prone of heavy precipitation and flooding events. The main aim of the present study was to investigate and analysis of synoptic condition of perceptible systems in Babol-Rud catchment. For this purpose, the heavy precipitation and number of days with heavy precipitation were extracted within time series. Thereafter, the synoptic conditions of perceptible systems were analyzed through sea level and height of 500 hPa. By assigning three clusters for heavy precipitation patterns in the study area, results revealed that the generation of short waves inside the main Rossby troughs is an important factor of heavy precipitation in Caspian coastal regions including the study area.

Tabarakabad catchment is a sub-catchment of the Gharaghom in the northeastern the Quchan city and in the Razavi Khorasan Province between the 37 º 02´41" until 37 º21´ 8" latitudes and 58 º 24´ 05" until 59 º 03´ 55" longitudes, 145 km away from west of Mashhad, which is located in Kopet Dagh geological zone. The formations have forms in the Tabarak Abad sub-catchment from late Jurassic period up to early Cretaceous period. Further, young sediment deposits in this basin are associated with Quaternary period. The purpose of this study was to evaluate the effects of morphometric indexes on textural parameters related to the size of the sediments in the catchment.
Two sub-basin catchment the Yadak and Zirabe the Tabarakabad catchment create a choice and some morphometric quantitative indexes like hypsometric integral (H), ratio of valley floor width to valley height (VF), drainage basin asymmetry (AF), index Gradient along the river (SL), transverse topographic symmetry index (T) and the index of mountain front sinuosity (Smf), the shape of the basin (BS) calculated using topographic maps and digital elevation model (DEM) and business information in the field study with the help of ArcGIS and the index (Iat) was classified.
In order to study textural parameters related to the size of the main channel sediments 12 sediment samples (6 samples from the main channel the Yadak basin and of the main channel the Zirabe 6 samples) were taken. The sampling anywhere to help Hoes geological volume of a cylinder with a diameter of 20 and a depth of 25 cm deep were taken in this connection to the example of the local texture deposition was intact removal, as well as in The exact location of the samples were recorded by GPS. Dried samples were then transferred to the laboratory and seed dry sieve methods were classified.
According to this Based on the study, the morphotectonic indexes include curves and hypsometry integral (H) of the Yadak 0.39 and class 1 in the Zirabe 0.7 class 3. The index Gradient along the river (SL) is an average value of 305.99 gradient meter in the Yadak and class 1 and 283.35 gradient meter in the Zirabe and class 1, the index of mountain front sinuosity (Smf) has been calculated as the Yadak 0.59 and class 1, and 0.86 in the Zirabe and class 2, the ratio of valley floor width to valley height (VF) index is the Yadak 0.23 and class 1 and the Zirabe 0.47 and class2, the drainage basin asymmetry (AF) is the Yadak 0.54 and class 2 and The Zirabe 0.59 and class 2, the shape of the basin (Bs) is in the Yadak 9.2 and class 1 and the Zirabe 0.47 and class 2, classification of the indexes based on Iat index suggested Class I for the Yadak and class 3 for the Zirabe sub-catchment, which represents the active sub-catchment Yadak of tectonic.
The sediments size it shows that in the Yadak sub-catchment sediment median size is -3.3, mean -2.5, sorting 2.5, skewed -0.05 and kurtosis 1.1. The Zirabe sub-catchment has sediment median size is -1.6, mean -1.2, sorting 2.1, skewed 0.47 and kurtosis 0.87. According to the obtained values for each sub-catchment can be stated that average size of sediments in the Yadak sub-catchment is coarser of the Zirabe sub catchment. Which reflects the high energy sub-catchment of the Yadak relative to the sub-catchment is Zirabe. The skewed shows according to of gravelly the average size of deposits in the sub-catchment Yadak of asymmetric curves have been fine gravel. While in the sub-catchment Zirabe sand deposits have created asymmetry, which reflects the average size of sediment in the subcatchment Yadak is coarser of the sub-catchment sub-catchment in times of low energy flow. The kourtosis sediments in the Yadak sub- catchment far more than the Zirabeh sub-catchment that represents Zirabe Changes less to flow is in the Yadak sub-catchment.
The results show that the Yadak sub-Catchment that was more active in class based on the morphometric indexes related to textural parameters is much higher. Finally it can be concluded in the catchment that have same effective elements in sediment texture, textured sedimentary catchment that are more active morphometry create their coarser.

Drainage density is an important hydrogeomorphologic indicator in determining activity quality of processes of overland run-off, flood intensity, soil erosion and sedimentation load in the basin. Drainage density was defined as the ratio of the total length of streams in a watershed over its contributing area. It describes the degree of drainage network development and was recognized by many authors to be significantly effective on the formation of flood flows. Drainage density is higher in arid areas with sparse vegetation cover. The higher the drainage density, the lower the infiltration and the faster the movement of the surface flow. The structure of watershed topography depends to a large extent on the interaction between slope and channel processes. The applicability of these relatively simple summaries, however, needs to be examined carefully. It is still uncertain how the development of drainage systems with time affects the relation of drainage density with lithology, slope, aspect and elevation. The Behrestagh watershed is a sub-basin of Haraz River basin where in varied geological and topographic conditions and the many overland flow cause soil erosion and destruction of pastures and gardens of the area. This study examines the relationship of drainage density with Geology and topography factors for Behrestagh watershed.
The Behrestagh watershed lies between the latitudes of 35° 56΄ N to 35° 59΄ N and longitudes of 52° 16΄ E to 52° 22΄ E. The main stream in the area is Haraz River. Topographic elevations in the study area vary between 1172 to 3548 m. Here, in order to examine drainage density in the studied area, map of the watershed’s streams was prepared first using GIS and Digital Elevation Model (DEM) of that area. Then, effective Geology and topographical properties including lithology, elevation, slope and aspect was considered and classified in ArcGIS environment and finally were overlaid with the streams as a dependent variable. Accordingly, sum of streams length per unit of each factor was calculated and drainage density was obtained. Data were analyzed in SPSS 20. Moreover, collected data were described using descriptive statistics (tables, charts, abundance distribution, mean and standard deviation). Data analysis was performed using one-way ANOVA to obtain differences with other studied variables.
Discussion of In this study, data analysis was performed using one-way ANOVA to obtain differences with studied variables. Results of the statistical test indicated that the relationship of lithology and slope with drainage density in the considered area was significant at .95 and .99 level of confidence, respectively. The relationship of drainage density with elevation and aspect was not significant, as well. The results showed that the most drainage density of the area was observed in elevation lower than 1400 meters (average density of 8.24). Also, the cretaceous melaphyre formation (km) with average density of 8.79 and the slope class of 20 -30 percent showed an average density of 10.7 and the western aspect (domain direction) indicated an average of 5.57.
To determine the geology and topography factors influencing drainage density, data layers of lithology, slope, aspect and elevation were analyzed through overlaying the dispersion map of the watershed’s streams. The results showed that cretaceous melaphyre formation, elevation below 1400 meters, slope of 20-30 percent and the west aspect are sensitive to streams. Also, results indicated a significant relationship between lithology and slope with drainage density in the considered area and slope was found to be the most important topography factor affecting drainage density. Therefore can used from these variables to assess erosion intensity and its control.

The mass movement of materials on steep slopes under the influence of gravity and motivation factors such as earthquakes, floods and torrential rains called landslide. Landslide similar the other natural phenomena is an important natural disaster that occur every year in the mountainous and highland areas of our country. By risk assessment of landslide occurrence, the sensitive areas with a high potential risk can be identified. Also the effect of different environmental factors on the pattern of high-risk areas can be used in risk management, practically.
One of the basic measures for achieving methods for mass movements control and management is identifying the effective factors in occurrence of this phenomenon. Also, in countries involved in the landslide, there is an increasing tendency for risk and damage assessment of this phenomenon. Therefore, at the present study, using fractal geometry, the effects of land use, geology and geomorphology on the landslide patterns were evaluated in the Tooye-Darvar watershed, Semnan province. Because the fractal theory studies and recent reviews in the earth science indicate that some geological processes such as mineralization, sedimentation, deposition, volcano, morphology and etc have self-similar characteristics. First, using aerial photo interpretation, field surveying and recording the position of landslides using GPS, the landslide distribution map prepared. Then, information layers for each slope, aspect, elevation, geology, geomorphic units, soil erosion class, distance from fault, distance from road, distance from stream and land-use factors prepared.in the ArcGIS software environment using digital elevation model (DEM) of the region with a pixel accuracy of 20 meters. Also the landslides information layer prepared according to the field studies and rasterized. Then, different layers overlapped and table of combined properties for merged layer includes the information of each pixel, extracted and entered into the Excel environment. In Excel, the relative importance (or frequency ratio) calculated for each different class of information layers.
Statistical analysis
After collecting and recording data and creating the database, the SPSS v.23 used for data analysis. In the first stage, the normalization checked using Kolmogorov-Smirnov test at the 5% confidence level. Then, the effect and significance of each measured variable investigated in landslide occurrence.
Calculating the fractal dimension
The landslide areas available in each unit extracted as a polygon and the resulting image transmitted to the Fractalyse software and its fractal dimension calculated using box-counting method. Then, the fractal dimension of landslides placed in work units transferred to the SPSS environment and statistical comparison performed with the aim of investigating the geometric or morphologic differences of sliding zones in different land uses and geologic and geomorphic units. Then to compare the different landslide hazard classes, the density or compression ratio of landslide used in each hazard class. The density ratio calculated by dividing the landslide density in a particular hazard class to the average density of landslides based on the area density or the number of landslides.
landslide susceptibility zonation
In order to zonate the landslide susceptibilityusing bivariate statistical methods, the information value and the area density, each of the factors affecting landslide occurrence include slope and elevation maps, slope aspect, soil erosion class, geomorphic type, geological unit, land use, distance from the stream, distance from the road and distance from fault in GIS environment digitized and classified. Then, based on the two above mentioned methods, the weight of each factor and its related classes determined. The weighted maps of effective factors combined and using natural breaks method, the obtained maps classified in very low, low, moderate, high and very high hazard classes. In order to evaluate the implemented model in the region , 2/3 of landslide points and 2/3 of landslide areas used for modelling and the remaining 1/3 of each one used to evaluate the model.
The results of fractal dimensions study in 146 landslide areas using box counting method showed an average of 1.987. Study of the spatial features in landslide areas include landuse, slope aspect, soil erosion class, geological unit, geomorphic type, height and slope class, distance from road, distance from fault and distance from stream showed that only the effect of geomorphic types on geometric dimension of landslide areas is significant and this significance is caused by high difference (sig=0/000)between mountains and plateaus and upperterraces types. Finally, the density ratio for landslide areas and points in each class of spatial characteristics for landslide occurrence, calculated and the effects of these variables on landslide occurrence severity, presented and analyzed. Also, in the landslide susceptibility zonation about 1/2 of landslides located in the high and very high risk classes that indicates the high potential for landslide in this region.
The results showed that the surface erosion has no significant effect on occurrence of large landslides but it has affected the landslide points. Also, the presence of marl and lime in study area that is a geological unit susceptible to dissolution can be effective in landslide occurrence. Geomorphologically, the mountain and hill types have been effective, which could be due to the high slope of these types. In the case of landslides occurrence in the vicinity of roads, faults and streams, it can be concluded that the small landslides has been affected by road, but it has no significant effect on the occurrence of large landslides. But the existence of fault in the area and proximity to the fault led to the occurrence of extensive landslides. Finally, the presence of stream in the area has also been effective in occurrence of large landslides, but the landslide points, has not been affected by existence of stream in their buffers. Also, high potential for landslide in the study area represents the being endangered for regional installations, agricultural lands, engineering structures and buildings.

Drought is one of the phenomena of climate that occurs in all climatic conditions and in all parts of the planet. Drought prediction has an important role in designing and managing natural resources, water resource systems, and determining the plant's water requirement. For estimating drought, various approaches have been introduced in hydrology that artificial models are the most important ones. In this study for evaluating the accuracy of the models in estimating the 12-month standard rainfall index, monthly data from four weather stations in Boroujerd, Dorood, Selseleh and Dolphan in Lorestan province have been used. For modeling of drought in these stations utilized wavelet neural network and artificial neural network models and the results were compared to each other for the accuracy of the studied models. In a few studies, each of the models presented in the drought estimation has been studied. But the purpose of this research is simultaneous analysis of these models at four stations for estimating the standard rainfall index.
In this study, Boroujerd, Dorood, Selseleh and Dolphan that located in Lorestan province have been selected as the study area During the statistical period, the precipitation parameter was used at monthly time scale (1962-1372) for input and standard rainfall index as the output parameter of the models. For this purpose, at first 80% of the data (1372-1382) were selected for calibration of the models and 20% of the data (2012-2013) were used to validate the models. The wavelet neural network, which has a very good fit with the sinusoidal equations by separating the signal into high and low frequencies, can greatly increase the accuracy of the model and reduce noise. Artificial neural networks are inspired by the brain information processing system that ability to approximate patterns of a model has increased the scope of these networks. Correlation coefficient, root mean square error and mean absolute error value were used for evaluation and performance of the models.
The results showed that both models have good performance in estimating the standard rainfall index in the four stations studied. Also, according to the evaluation criteria, the wavelet neural network model was found to have the highest accuracy and low error rate compared to the artificial neural network model.
In total, the results showed that the use of wavelet neural network model can be effective in estimating the standard rainfall index. also It can be useful in facilitating the development and implementation of management strategies to prevent drought and is a step in making managerial decisions to improve water resources.

Man's undue interference, livestock overgrazing, soil texture disorganization, and change in the geometry of channels are the main factors which could destroy the hydrologic balance of the watershed in an ecosystem. The systematic imbalance in a watershed could destroy the earth crust and increase flooding. It could also result in the erosion and soil sedimentation behind the reservoir dams and the destruction of the agricultural lands, roads, and villages. In addition, it could reduce the production ability of productive sources. Soil erosion is one of the environmental problems that threatens natural resources, agriculture, and the environment. The objective of the present study was to evaluate the biological, managerial, and constructional watershed projects and their effects on reducing erosion, sedimentation, and parameters of land protective cover. This study was conducted between 2001-2010 in the Khorrambid urban watershed from the Sivand dam in Fars province.
A. Primary Collection The preliminary data for Khorambid urban watershed from Sivand dam was collected by the executive detailed reports (Natural Resources and Watershed Management Office of Fars Province, 2001).
B. Estimating the parameters of land cover layer, erosion, and sedimentation before implementing the watershed projects
Before implementing the watershed projects, the vegetation parameters, erosion, and sediment yields in the executive and detailed reports were used to evaluate the parameters.
C. Estimating the parameters of land cover layer, erosion, and sedimentation after implementing the watershed projects
In the first step, the vegetation classification mapping was prepared and the vegetation parameters were sampled in the paired plots. It must be mentioned that one of the most effective items in estimating the erosion and sedimentation is to know the land cover parameters. To determine the rates of erosion and sediment exited from the network, it was required to calculate the rate of erosion and sediment on the domain. It was also required to calculate the controlled sediments on the waterway or at the rear of structures. In the first step, the locations of all structures executed in the intended sub-basins were specified by GPS to determine the sediments trapped at the rear of the structures. Meanwhile, their types, structural materials, and location maps were prepared. In the second step, the waterway slope, overflow height, reservoir length, waterway width, reservoir volume, and sediment volume were respectively determined by preparing some special forms via clinometer and meter. In addition, to estimate the erosion and the sedimentation of the domain, the experimental model of MPSIAC, modified by ArcGIS10, was used. When the nine layers of the MPSIAC model were combined and overlapped, the homogeneous units map was prepared. Next, the scores of nine factors were estimated and calculated to extract the sedimentation degree of each homogeneous unit according to the following equation: Qs = /253 e0.036R (Equ.1)
When the sedimentation map was prepared, the erosion rate was calculated by the Sedimentation Delivery Rate (SDR) equation in the level of homogeneous unit. Regarding the factor of the basin area ( based on square mile), the following equation was used to determine the percentage of SDR.
Log SDR = 1.8768 – 0.14191 log(10A) (Equ.2)
To evaluate the differences between sedimentation changes in the sub-basins for the pre and post watershed operations, the normality test and Paired T-test in SPSS software were used.
The results indicated that the factors’ score of river erosion and surface erosion which were respectively 30.77 % and 30.51% had the most effects and the land cover factor, with 15.05%, had the least effect on reducing the sedimentations to 21.97%. Also, the area of sediment class of 75-100 was 1375 hectares, which was equivalent to 15.78% of the basin's area. Indeed, in terms of the spatial distribution, it was located in the basin outlet and changed to class 50-75. The sediment class of 50-75 was 7339 hectares, equivalent to 84.22% of the basin's area. It reduced to 28.09 % and changed to the lower class of 25-50. Since there was a significant change in the sedimentation of the sub-basins in 0.05 levels, the results of this study indicated that the watershed projects were efficient in reducing the sediments. To manage the water and soil resources, to raise the effectiveness of watershed operations in reducing erosion and sediments, and to raise the land cover layer in Khorrambid watershed, the combination of both biological and constructional programs and treatments undertaken in the basin should be applied.
With regard to the findings of this study, before the watershed operation, the sedimentation degrees in two classes of 75-100 and 50-75 were respectively 15.78% and 84.22%. According to the sedimentation class map, the sedimentation degree of 75-100 was located in the basin outlet. Since the structural watershed operation has been extended more than biological watershed operation, the sediment class with the area of 1375 hectares experienced lower sediment degree and changed to 50-75 class after the watershed operation. The sediment class of 50-75 was 7339 hectares before the watershed operation; however, by implementing biological programs, 2447 hectares of that class changed to the lower class of 25-50. Therefore, 15.78% of class 75-100 before the watershed operation reduced to 0% after the watershed operation. In addition, 84.22% of class 50-75 was reduced to 71.91%. Regarding the equation of SDR based on the area factor, the rate of SDR for the basin was 33.03%. Thus, the sediment rates for pre and post watershed operations were respectively calculated as 23755 and 14390 tons, which indicated 39.42 % drops in the total sediments. The results of this study showed that the watershed operation, which was a combination of protective, managerial, and biological programs, was implemented well in the measures of domain and waterway (structural) in the basin. Consequently, the sedimentation mean in Khorambid watershed decreased to 39.42%. The findings of this study are in line with the findings of researchers such as Roghani (2012), Salmanpour (2013), Azami Rad (2013), and Agharazi (2016).