Ommolbanin Bazrafshan; Azimeh Chashmberahm; Arashk Holisaz
Abstract
Evaporation is one of the most important and effective factors in water resources planning and management in arid and semi-arid areas and examining it's changes in time scales and different years as one of the most important climatic parameters, has an important role in planning and water resource management ...
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Evaporation is one of the most important and effective factors in water resources planning and management in arid and semi-arid areas and examining it's changes in time scales and different years as one of the most important climatic parameters, has an important role in planning and water resource management in agriculture section and determining cultivation pattern and proper water resource management. One of the methods to assess and forecast changes in evaporation is time series models by the generic name of ARIMA models. Therefore, in order to determine the best model to predict pan evaporation, after considering the climate using improved Domarton climatic classification method, in each climatic sample, one evaporation station was selected and standardized pan evaporation index (SPEI) was calculated for each of the stochastic model for estimation the amount of future monthly time series SPEI in the period of 1954-1955 to 2009-2010 over the next 12 months. Results showed that the Auto Regressive Moving Average model (ARMA) and Auto Regressive (AR) had the best performance, in Hormozgan province, so that, in the hot and dry, hyper hot arid and hyper hot hyper arid climates, in the next month, had the highest standard coefficient of determination (R) of 0.83, 0.71, 0.7 and the lowest value RMSE of 0.59, 0.8, 0.88, respectively and the AR model was able to predict the next 11 months, well. The results showed that AR model has better performance compared to ARMA model in estimating monthly pan evaporation in hot and dry climates in coastal wilderness areas.
sohrab jamalpour bergai; hassan ahmadi; Aboalfazl Moeini; mohammad faraji
Abstract
Dust storms is one of the most important environmental hazards, especially in arid and semi-arid climates, which causes irreparable damages to the various dimensions of the environment. The aim of this study was to identify dust sources in south-east Ahwaz, using a remote sensing technique and fuzzy ...
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Dust storms is one of the most important environmental hazards, especially in arid and semi-arid climates, which causes irreparable damages to the various dimensions of the environment. The aim of this study was to identify dust sources in south-east Ahwaz, using a remote sensing technique and fuzzy logic. For this purpose, the satellite images of dust events of Ahwaz City were investigated and the wind characteristic of the study area were studied by plotting the storm rose of Ahvaz Synoptic Station. In the next step, the criteria were categorized into two categories: soil moisture, land surface temperature and vegetation constitute the main layers and land use, spatial data of soil, climate, slope and sedimentology were used as constraint layers. The main layers were extracted from Landsat OLI-TIRS satellite images. The Boolean method were used to standardize the constraint layers, and the fuzzy membership functions were used to standardize the main layers. Also, main layers weighting was done using fuzzy analytic hierarchy process. Finally, the dust sources map was obtained by overlapping the layer. To validate the results, 44 ground control point were selected from the study area that showed high accuracy (81.8%) for identified areas. Based on investigating of satellite image and storm rose of Ahvaz Synoptic Station, the south-east of Ahwaz was recognized as dust-generating source and 145162.01 ha of lands are dust generating sources from which 69343/01 ha (47.77%) belongs to destroyed rangelands and 335.99 ha (0.23%) belongs to Canebrake, contains the highest and lowest level of sources of dust production in the study area, respectively.
Samad Shadfar
Abstract
Gully erosion is a type of water erosion that causes significant sedimentation in watersheds and damages in agricultural lands, rangelands, and infrastructures. This study was conducted to determine the potential of gully erosion by artificial neural network. The Levenberg-Marquardt (LM) ...
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Gully erosion is a type of water erosion that causes significant sedimentation in watersheds and damages in agricultural lands, rangelands, and infrastructures. This study was conducted to determine the potential of gully erosion by artificial neural network. The Levenberg-Marquardt (LM) algorithm and Multi-Layer Perceptron were used employing soil, geology, land use, distance to fault, slope, aspect, distance from roads, distance from drainage, and elevation data as its variables. Results showed that the structure of 1-13-9 with sigmoid activation function in the hidden layer is more suitable for gully erosion potential assessment. Zonation of gully erosion revealed that the watershed area was divided into different classes of different extent, including 70.26% in very low, 1.71% in low, 2.45% in medium, 2.65% in high, and 22.93% in very high potential class. Furthermore, results indicated that slope less than 10%, 50 m distance from the stream, rangeland area, and lithological units of EM and M2 had the greatest impact on the occurrence of gully erosion.
Payam Ebrahimi; Jamileh Salimi Kochi; Mohsen Mohseni Saravi
Abstract
SWAT is a continuous, physically based and distributed hydrologic model which all several hydrological processes like discharge, sediment yield nitrogen are simulated for each one of it. The purpose of this study is to test the efficiency of the Soil and Water Assessment Test (SWAT) and its applicability ...
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SWAT is a continuous, physically based and distributed hydrologic model which all several hydrological processes like discharge, sediment yield nitrogen are simulated for each one of it. The purpose of this study is to test the efficiency of the Soil and Water Assessment Test (SWAT) and its applicability as a flow simulator, and using SWAT-Cup software and the SUFI2 algorithm as a means to calibrate and validate Neka Watershed in Mazandaran Province. Four indices were used to assess the goodness of calibration, viz., P-factor, R-factor, R2 and Nash-Sutcliffe (NS). Runoff data (1995-2004) of four hydrometery stations were used for calibration and (2005-2009) for validation of this watershed. The results of these values for flows at four stations for calibration process in Ablo, Pain zarandin, Karkhane siman and Sefid chah were 0.85, 0.78, 0.78, 0.89 for P-factor; 2.55, 2.03, 1.71, 2.43 for R-factor; 0.76, 0.62, 0.69, 0.71 for Nash-Sutcliffe and 0.71, 0.82, 0.76, 0.63 for R2. The results of validation were 0.87, 0.88, 0.72, 0.72 for P-factor; 3.61, 2.24, 3.56, 1.78 for R-factor; 0.74, 0.66, 0.58, 0.64 for Nash-Sutcliffe (NS) and 0.81, 0.68, 0.73, 0.61 for R2 respectively. In general, the results showed that SWAT could be a proper tool for simulating the flow rate values of the Neka Watershed.
Mojtaba Soleimani-sardo; Esmaeil Silakhori
Abstract
Today, land use change is considered as a challenge of environmental issues and known as an ecological problem. Land use changing is one of the most important parameters in planning over time. The purpose of this study is to detect land use changes in the Jiroft Basin in the years 1997, 2008, and 2018 ...
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Today, land use change is considered as a challenge of environmental issues and known as an ecological problem. Land use changing is one of the most important parameters in planning over time. The purpose of this study is to detect land use changes in the Jiroft Basin in the years 1997, 2008, and 2018 and it’s predicting in 2040. For this, Landsat images were collected and the preprocessing steps, including atmospheric and radiometric corrections, were done by ENVI software. A false-color combination, as well as an NDVI vegetation index map, were prepared for these years. Land use maps were prepared by supervised classification using maximum likelihood algorithm. The land use changes evaluated by Land Change Modeler (LCM) in these periods. Finally, land use map for 2040 was predicted by the Markov chain and IDRISI software. According to the Kappa index, the exported maps showed an acceptable accuracy (>0.76). Land use changes between 2008 and 2018 showed that the urban areas, agricultural lands, gardens, salty lands, and barren area were increased, but rangelands and forests were decreased. In the coming years, it is expected that with the current management method, the urban areas, agriculture and barren area will increase, while forest, gardens, and rangeland areas will decrease. To reduce the land use change effects, it is recommended to act according to sustainable development by notice to the ecological potential of the land.
Bahram Choubin; Karim Solaimani; Mahmoud Habibnejad Roshan; Arash Malekian
Abstract
Integrated watershed management and regeneralization of available information to ungauged basin needs to recognize homogeneous watersheds. The hydrologic similarity of watersheds is caused by the hydroclimate and physical behaviors. In present study, hydroclimate and physical indices were used for indicating ...
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Integrated watershed management and regeneralization of available information to ungauged basin needs to recognize homogeneous watersheds. The hydrologic similarity of watersheds is caused by the hydroclimate and physical behaviors. In present study, hydroclimate and physical indices were used for indicating the homogeneous sub-watersheds in Karkheh Watershed and then results were compared. Factor analysis to reduce in the dimension of variables was conducted, separately for climatic, hydrological and physical parameters. Finally, using Fuzzy c-means (FCM) and hierarchical clustering analysis (HCA) homogeneous sub- watersheds were indicated by hydro-climate and physical parameters. Factor analysis results showed that indices of CSDI (cold spell duration index), GSL (growing season length), RX5day (monthly maximum consecutive 5-day precipitation), TX90p (percentage of days when daily maximum temperature is greater than 90th percentile) and TMAXmean (mean of maximum temperature) of climate indices, and indices of percent of hydrologica group D and flood potential index of hydrologic indices were selected. Also indices of basin area, basin elongation, average length of drainage and total topography between the physical parameters were selected. Comparing the results of the FCM and HCA indicated that the optimal number of clusters is same, but the results of watershed classification are not same in each cluster of two ways. Classification by hydroclimate and physical indices highlights that 25 and 27 basins were classified similar, respectively in two methods of clustering. Clustering by hydroclimate parameters produced different results compared with physical parameters, so that the 17 and 19 sub-basins are in the same classes in the FCM and HCA, respectively. However, there is no preference to accept watershed classification by hydroclimate or physical parameters, thus a combination of hydroclimate and physical parameters were used for classification. Watershed classification by the combination of hydroclimate and physical parameters indicated that 33 sub-basins were classified similar in both FCM and HCA methods. Classification in Karkheh basins based on the combination of physical and hydroclimate parameters revealed that the northern areas are in group 3, central regions (from east to west) are in group 2 and southern areas are in group 1. Inherently, these basins are similar in each group and demand the same protection operations in view of watershed management.
Somaiye Moghimi; Yahya Parvizi; Mohammad Hossein Mahdian; Mohammad Hassan Masihabadi
Abstract
Soil organic carbon is one of the most important soil characteristics, and any changes in its content and composition, affects soil physical, chemical, and biological characteristics. Enhancing soil organic carbon improves soil structure, increases water and nutrients in soils, reduces soil erosion and ...
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Soil organic carbon is one of the most important soil characteristics, and any changes in its content and composition, affects soil physical, chemical, and biological characteristics. Enhancing soil organic carbon improves soil structure, increases water and nutrients in soils, reduces soil erosion and degradation and thus greater productivity of plants and water quality are expected in watersheds and ultimately soil and ecosystem reclamation happens. Climatic, topographic and managerial factors affect soil organic carbon content. In local scale, climatic factors have not high efficiency on soil organic carbon and topographic factors play more important role compared to climate on soil organic carbon variability. The objective of this study was to predict and evaluate the effects of topographic factors such as elevation, slope percent, aspect, hill shade, and curvature on the soil organic carbon content of a rangeland in Mereg watershed, Kermanshah, Iran. Stepwise Multi Linear Regression (MLR) and Artificial Neural Network (ANN) were employed to develop models to predict soil organic carbon. AMulti-Layer Perceptrons (MLP) ANN withback-propagationerror algorithm was applied to this research.Theresult showed that themulti linear regression and ANN models explained53and 77percent of the total variability of soil organiccarbon, respectively. The calculated RMSE and MBE were 0.40 and 0 for the MLR and 0.16 and 0.003 for MLP models. Results indicated that designated ANN model with 5-9-1 arrange was more feasible than multi linear regression for predicting soil organic carbon. Elevation with 0.79, hill shade with 0.64 and slope percent with 0.24, were identified as the important factors that explained the variability of soil organic carbon.
Farhad Misaghi; Parisa Asgari; Maryam Nouri
Abstract
IntroductionThe availability of water for agriculture is of great importance, and despite the water crisis that is becoming more severe every year, both quantitatively and qualitatively, this issue should be seriously considered. Water resources include surface and groundwater, which are qualitatively ...
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IntroductionThe availability of water for agriculture is of great importance, and despite the water crisis that is becoming more severe every year, both quantitatively and qualitatively, this issue should be seriously considered. Water resources include surface and groundwater, which are qualitatively more at risk, therefore, in order to preserve them, the sources of pollution must be known and appropriate solutions must be provided to prevent or eliminate these pollutions. Materials and methodsIn this research, phosphate transfer cycle in Zanjanrood Watershed has been simulated using SWAT model. For calibration and validation, SWAT-CUP software and measured values of average monthly current intensity at Sarcham hydrometric station between (1996-2013) were used and 26 sensitive parameters were selected for sensitivity analysis. There are three options for irrigation method, three options for fertilizer application and two combined options. In order to analyze the uncertainty of the indicators p-factor and r-factor and to analyze the quality of the model results, two indices of coefficient of determination (R2) and nash-sutcliffe coefficient (NS) have been used. Results and discussionIn the monthly runoff calibration stage, at the output of the field, the coefficients of r-factor, p-factor, R2, NS were 0.27, 0.11, 0.83 and 0.53, respectively, and in the validation stage were 0.60, 0.18, 0.73 and 0.53, respectively. The results showed that with increasing the level of pressurized irrigation, the amount of phosphate contamination at the outlet of the basin did not change significantly. Regarding the amount of fertilizer, the 50% reduction in the consumption of phosphate fertilizers has reduced the amount of phosphate entering the Zanjanrud River by 19.2%. On the other hand, a 50% increase in the use of fertilizers has increased the input phosphate by 17.7%. ConclusionThe results showed the proper performance of the SWAT model and its ability in the mentioned simulation. Also, by changing the surface irrigation method to subsurface and increasing the irrigation efficiency, there is no significant change in the average amount of phosphate output from the basin. On the other hand, by reducing the amount of fertilizer and preventing improper fertilization by farmers, pollution of surface and groundwater resources can be greatly prevented.
Seyed Ali Ayyoubzadeh; Mahdi Habibi; Mohammad Rostami; Mojtaba Sanei; Mohammad Faramarz
Abstract
Side weirs are widely used to divert water from rivers. In movable bed rivers, deposition of sediment particles along the side weir may cause some problems in diverting water. This research is done in a laboratory flume of 0.9 meter wide and 10 meter long with a longitudinal slope of 0.001. Three value ...
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Side weirs are widely used to divert water from rivers. In movable bed rivers, deposition of sediment particles along the side weir may cause some problems in diverting water. This research is done in a laboratory flume of 0.9 meter wide and 10 meter long with a longitudinal slope of 0.001. Three value of weir length i.e. 0.6, 0.4 and 0.2 with a single weir height of 0.08 meter were used in the experiments. The variations of water surface profiles along the side weir were measured for various upstream Froude Numbers. The obtained results from experiments on movable bed condition were compared with those from rigid bed condition and also with the results from analytical solution. The results showed that bed form made by flow regime in the vicinity of the side weir does effect on the water surface profile over the weir and thus changes the diverted flow discharge. Water surface and discharges over the side weir were found in good agreement with the results obtained from the analytical solution in compare with the results obtained from channel with movable bed. The computed relative error for flow discharge in channels with movable and rigid bed is 6.35% and 24.18% respectively. This amount for variations of water surface profiles along the side weir is 8.03% and 9.88% respectively.
Ghazaale Madadi; Saeed Hamzeh; Aliakbar Noroozi
Abstract
Most of drought assessment systems are largely based on rainfall data. Although the short period of data, poor quality of rainfall measurement network and low-dense distribution of stations reduce the ability of detecting drought spatial patterns. Therefore, it is obligatory to detect climate data sources, ...
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Most of drought assessment systems are largely based on rainfall data. Although the short period of data, poor quality of rainfall measurement network and low-dense distribution of stations reduce the ability of detecting drought spatial patterns. Therefore, it is obligatory to detect climate data sources, which would get rid of this problem, then to be used as an alternative option. Accordingly, in this study for monitoring drought in West Frontier Basin (including the Ilam, Kermanshah, Kurdistan and Lorestan provinces), using meteorological data (including 30 climatology and synoptic stations), to assess monthly data satellite TRMM (3B43). Drought indicators using SPI index for time scales of three, six, nine and 12 months in the period of 12 years (2000-2012) were calculated. After evaluating the accuracy and validating of monthly data from satellite images, estimation value of the drought on the determined time scales was done by use of TRMM dataset. The estimated value of the drought (SPI) across the study area using TRMM satellite images and maps of rainfall of ground-stations was calculated in MATLAB software after that for all the pixels continuously SPI value was calculated. The results indicate that, the SPI index from satellite images and ground stations are closely related. According to the statistics of weather and precipitation, year 2008 was introduced as the low rainfall year, besides the results of the study showed that the SPI value of the basin, in 2008 was lowest that determined it as the dry year.
Behnam Farid Gigloo; Ebrahim Omidvar
Abstract
Ephemeral Gully (EG) erosion is one of the most destructive types of water erosion, which contributes significantly to land degradation. EG erosion prediction is necessary to assess the magnitude of soil loss and to implement the appropriate conservation measures. The aim of current study was to ...
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Ephemeral Gully (EG) erosion is one of the most destructive types of water erosion, which contributes significantly to land degradation. EG erosion prediction is necessary to assess the magnitude of soil loss and to implement the appropriate conservation measures. The aim of current study was to evaluate the efficiency of EGEM model for EG erosion prediction in Ghoorichay Watershed, Ardabil Province, Iran. For this purpose, a number of 17 EG erosion was identified and monitored between the years 2014 to 2016. The morphological characteristics and erosion rate of EGs were measured and recorded after seven effective rainfall events. In order to calculate the EG erosion, EGEM model requires four major categories of input data, including identification information, watershed data, soil data, and rainfall data. The model has two major components: hydrology and erosion. The runoff induced by a rainfall event in each gully catchment was determined by the Natural Recourses Conservation service (NRCS) Curve Number (CN). The result of EGEM model performance evaluation showed that the eroded soil volume and cross-section were predicted with a determination coefficient of 0.96 and 0.89, respectively. Sensitivity analysis revealed that the curve number was the most sensitive parameter, so that, with a 10% increasing and decreasing in CN, the volume of soil loss varied 22.98 and -18.92%, respectively. It can be concluded that EGEM model was suitable for event-based EG erosion prediction in Ghoorichay Watershed and it can be recommended for studying and planning on EGs in similar watersheds.
Seyed Hamidreza Sadeghi; Aliakbar Davudirad; Amir Sadoddin; Shahla Paimozd
Abstract
Today, land degradation is inevitable due to growing population and corresponding demands, and also economic development, unscientific and illogical utilization of resources. Monitoring and identification of factors affecting is therefore essential for controlling and management of land degradation in ...
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Today, land degradation is inevitable due to growing population and corresponding demands, and also economic development, unscientific and illogical utilization of resources. Monitoring and identification of factors affecting is therefore essential for controlling and management of land degradation in an area. However, such important issues have been less considered by experts and managers. To this end, the present study aimed to analyze the trend and identifying the important affecting factors on land degradation in the Shazand Watershed, Iran, based on the Environmental Sensitive Area Index (ESAI) for significant changes due to a variety of uses, management and industrial development from 1986 to 2014. According to the ESAI maps in five year nodes of 1986, 1998, 2008 and 2014, some 16.56, 33.39, 42.32 and 49.52 percent of the study area were in critical condition of land degradation, respectively. Based on the results, the process of land degradation in the region was increasing and land degradation was considerable in the periods leading up to 1998 and 2014. The sensitivity analysis on factors influencing land degradation in the study area also revealed that the role of vegetation, anthropogenic and managerial factors on ESAI changes were more than other factors and therefore could moderate or intensify the land degradation.
Hamzeh Noor; Ali Dastranj; Saeed Sadeghi
Abstract
Flood control projects, artificial recharge of ground water aquifers, and optimizing the efficiency of water and soil resources are the most important benefits that have been achieved as a result of the construction of flood spreading stations in the country. The aim of this research is assessment ...
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Flood control projects, artificial recharge of ground water aquifers, and optimizing the efficiency of water and soil resources are the most important benefits that have been achieved as a result of the construction of flood spreading stations in the country. The aim of this research is assessment and determination of effectiveness of Jajarm flood spreading project. For this purpose was the economic evaluation of flood spreading project using Net Present Value (NPV) and Benefit/Cost/ ratio studies in Jajarm Station. The social impacts of the Jajarm flood plan were also assessed through a popular questionnaire. Results showed that NPV was 262258 million Rials with discount rate according to the Central Bank. This shows that the Jajarm flood project is economically justified on the basis of economic evaluation and that investment is economical. The evaluation of the impacts of the floodplain project from the view point of the users of the project margin, also indicates that the people of the region are relatively satisfied with the project. Particularly people's satisfaction with the role of the flood spreading project in reducing flood damage to residential, land and communication areas in the region is significant.
Seyed Hamidreza Sadeghi; Mohsen Zabihi
Abstract
Rainfall erosivity factor is the first noticeable point in soil erosion issues that plays very important role in detachment of soil particle from the origin bed. Hence, investigation of rainfall erosivity factor trend is necessary in decision-making and planning in order to manage soil and water resources. ...
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Rainfall erosivity factor is the first noticeable point in soil erosion issues that plays very important role in detachment of soil particle from the origin bed. Hence, investigation of rainfall erosivity factor trend is necessary in decision-making and planning in order to manage soil and water resources. However, studies on various aspects of erosivity like trend and in interaction with precipitation and SPI index have not been attended well. The present study therefore aimed to investigate the rainfall erosivity factor trend based on the Fournier index in 28 stations throughout North-Khorasan Province during the period of 1987 to 2006 by using the Mann-Kendall test. In addition, the SPI and precipitation trend were comprehensively investigated for better characterization of erosivity trend analysis. Results showed that Noushirvan, Faruj, Ayerqayeh and Gholaman stations had decreasing trend and other study stations (71.85%) had increasing trend in the modified Fournier erosivity index. The SPI and precipitation in the study area indicated that most of the stations (89.28%) excluding Khartot, Noushirvan, Faruj and Ayerqayeh had increasing trend. The maximum and the minimum values of modified Fournier erosivity index with 70.97 and 33.44 mm were also assigned to Darkesh and Abiary Bojnourd stations, respectively.
yasin salehi; Alireza vaezi
Abstract
IntroductionSoil erosion is the most important aspect of land degradation and one of the most important environmental, agricultural and food production problems in the world. More than half of the agricultural lands in semi-arid regions are under rainfed cultivation, and the tensions caused by erosion ...
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IntroductionSoil erosion is the most important aspect of land degradation and one of the most important environmental, agricultural and food production problems in the world. More than half of the agricultural lands in semi-arid regions are under rainfed cultivation, and the tensions caused by erosion and destruction of land are important in terms of the effects within the field of erosion, such as soil fertility, and the effects outside the field, such as soil pollution. Information about the size distribution of eroded particles is a substantial step for managing the loss of nutrients and the transfer of pollutants from the soil. For this purpose, this study was conducted to investigate the particle size distribution of sediments resulting from interrill erosion under the influences of slope gradient and soil texture in some soils of the semi-arid region of Zanjan Province. Materials and methodsToward this, four hillslopes having different soil textures (sandy loam, silty loam, sandy clay loam and clay loam) in four north-south slope percent (five, 10, 15 and 20%) were investigated using a simulated rainfall with an intensity of 60 mmh-1 for 60 minutes. In order to monitor the runoff and sediment samples from the beginning of the runoff until reaching a stable state, were taken at 5-min intervals from the initiation of runoff. The particles size distribution of sediment was determined by the method of particle separation using a series of sieves with diameters of 75, two, one, 0.5, 0.25, 0.1 and 0.05 mm. Also, the percentage of finer particles (silt and clay) was calculated by hydrometer method. Then the sediment particles are divided into eight categories: gravel (1-75 mm), very coarse sand (1-2 mm), coarse sand (0.5-1 mm), medium sand (0.25-0.5 mm), fine sand (0.1-0.25 mm), very fine sand (0.05-0.1 mm), silt (0.002-0.05 mm) and clay (<0.002 mm) were categorized. Results and discussionThe results showed that, with the increase in the slope of the land surface, the size distribution of sediment particles changed in all soils. So that, the transport of particles larger than 0.1 mm (including very coarse sand, coarse sand, medium sand and fine sand) increased with increasing slope. While the percentage of silt particles (0.002-0.05 mm) decreased in all textures. Also, particles with the size class of medium sand and fine sand formed between 40 and 50% of the sediment particles for each texture and did not change significantly with the increase of the slope. The highest ratio of particles in the sediment to the main soil was related to silt particles and in silty loam texture (4.33 times) and the lowest was related to clay particles and in silty loam texture (0.26 times). Sand and silt particles in different textures, had high transmission ratios. Silt particles in three textures of sandy loam, clay loam and silty loam had a ratio of more than one and clay particles less than one. Except in clay loam soil, sand particles changed in the range of 0.83 to 1.24 times compared to the main soil and the overall average ratio of its availability in sediment to original soil was 0.98 times. ConclusionIn general, this research showed that with increasing slope, the selectivity of fine particles decreases and the share of coarse particles increases. The effects of these changes are more visible in fine-textured soils. Due to the increase in the destruction of aggregates and flow rate with the increase of the surface slope, it is very important to prevent the removal of vegetation and observe the principles of tillage in order to reduce the direct impact of raindrops on the soil surface and reduce the transportability of particles by the flow. Also, the results show that the ratio of particles in the soil texture and the characteristics of soil structure (abundance and stability of aggregates) are the determining factors of particle transport and it is necessary to consider these characteristics in choosing soil conservation methods.
Abdulvahed Khaledi Darvishan; Jalal Faraji; Leila Gholami; Mohsen Khorsand
Abstract
The dynamics of rainfal erosivity (R), crop management (C) and soil erodibility (K) factors compared to the others (topography-LS and land management-P) is the most important note for the correct estimate of soil erosion at different time bases. Spatio-temporal estimates of soil erosion in the representative ...
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The dynamics of rainfal erosivity (R), crop management (C) and soil erodibility (K) factors compared to the others (topography-LS and land management-P) is the most important note for the correct estimate of soil erosion at different time bases. Spatio-temporal estimates of soil erosion in the representative paired watersheds are of particular importance due to their educational functions as well as the possibility of generalizing the results to larger areas of the country. Therefore, in the present study, while examining the dynamics of R, C and K factors in the Khamsan representative paired watershed, the distribution map of soil erosion in seasonal and annual time scales were prepared using RUSLE model for two water years of 2015-2016 and 2017-2018. The results showed that soil erosion in winter with values of 3.94 and 4.95 t ha-1 y-1 accounted for about 49 and 74% of the total erosion of the year, respectively. Considering the melting conditions in calculating the K factor for the winter along with the lack of vegetation in this season led to a higher estimate of soil erosion than other seasons. These results are in consistent with plots soil loss data recorded in different seasons and the higher concentration of suspended sediments in the rivers especially in March. In the water year of 2015-2016, the distribution of rainfalls in the autumn was much higher than in the spring, so that soil erosion in the autumn accounted for about 33% of the total erosion of the year. In the water year of 2017-2018, although the average annual soil erosion was less, but due to more distribution of erosive rainfalls in winter at the same time with the lack of vegetation on the soil surface and the soil melting, the rate of winter erosion was very high.
Mitra Tanhapour; Mohammad Ebrahim Banihabib
Abstract
Debris flow is one of the natural hazards that threats people's lives in the mountainous populated areas. Thus, it is necessary to determine the rainfall thresholds for debris flow occurrence in order to develop an effective forecasting system. In this study, the empirical thresholds of rainfall for ...
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Debris flow is one of the natural hazards that threats people's lives in the mountainous populated areas. Thus, it is necessary to determine the rainfall thresholds for debris flow occurrence in order to develop an effective forecasting system. In this study, the empirical thresholds of rainfall for the occurrence of debris flow by Hirano method were assessed in a part of Alborz mountainous basins including Gorganrood, Navrood, Neka and Babolrood. For this purpose, the rainfall hyetographs of recording rain gauges were used from the period of 1983-2004. Then, the intensity-duration rainfall thresholds (I-D threshold) for selected basins were estimated and compared with previous studies from the local, regional and global scale. The examination of rainfall thresholds for the initiation of debris flow showed that the rainfall of more than 27.2 and 14.8 mm, respectively, in the Navrood and Gorganrood watersheds and rainfall more than 37.84 and 66.12 mm, respectively, in the Babolrood and Neka basins are able to trigger debris flow during their concentration time. Comparison of the I-D threshold of this study with the results of previous studies showed I-D threshold of the studied basins generally are lower than the thresholds of local and regional but higher than global thresholds. In other words, there are some areas in the world that need smaller rainfalls for initiation debris flow in comparison to the study area. The difference among threshold of debris flow occurrence in the world’s basins comes from their variety in climatic, geographical, physiographic and geological factors.
Mohammad Sedighi; amir shahrokh amini
Abstract
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, ...
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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.
Nasrin Mirzaee; Amirpouya Sarraf
Abstract
River runoff forecasting in watersheds has a special place in the management and planning of water resources for the design of water facilities, water intake from rivers, consumption management and etc. In the present study, the performance of some data integration models including simple averaging, ...
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River runoff forecasting in watersheds has a special place in the management and planning of water resources for the design of water facilities, water intake from rivers, consumption management and etc. In the present study, the performance of some data integration models including simple averaging, weighted averaging and integrated artificial neural network model in monthly discharge modeling has been evaluated and compared. For this purpose, monthly flow prediction in upstream basin of Jiroft Dam was examined using Artificial Neural Network (ANN) models, Adaptive Neural-Fuzzy Inference System (ANFIS), ARIMA model and Support Vector Regression (SVR) model as an individual model. Then, the individual models were trained and validated using selected predictor variables and their results were selected for use in the integration process. Large-scale climatic signals including NAO, ENSO and PDO are also used in hydrological forecasts of river flow and the performance of single and integrated models in two modes with and without considering these signals has been compared based on the evaluation of three criteria Nash-Sutcliffe (NSE), Coefficient of determination (R2) and Mean Square Error (MSE). Results of this study indicated that the integrated approach significantly increases the accuracy of predictions. In addition, large-scale climatic signals were found to improve results, especially during the test period. For example, the results of the integrated model of artificial neural network with large climatic scale signals show that this model has the best performance among the integrated models. Also, the NSE criterion has improved by 0.04 in training compared to the integrated model of artificial neural network without large-scale signals and the MSE error has been reduced by 0.001.
Masoud Eshghizadeh; Ali Talebi; Mohammad-Taghi Dastorani; Hamidreza Azimzadeh
Abstract
In this research, LAPSUS model is introduced as a suitable model to surface runoff rutting by Multiple Flow Direction (MFD) algorithms. Flow distribution algorithms grouped into two main types including Single Flow Direction (SFD) and MFD algorithms. LAPSUS model is a landscape evolution and a multi-module ...
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In this research, LAPSUS model is introduced as a suitable model to surface runoff rutting by Multiple Flow Direction (MFD) algorithms. Flow distribution algorithms grouped into two main types including Single Flow Direction (SFD) and MFD algorithms. LAPSUS model is a landscape evolution and a multi-module dynamic landscape evolution model. Studied processes included overland erosion, land sliding, tillage erosion and tectonics. Input data in LAPSUS model was DEM, rainfall, runoff coefficient and convergence factor. This model has written in C++. This model has been used for runoff rutting in Kakhk watershed of Gonabad, Iran, for the first time. For this purpose, surface runoff resulted from 34 rainfall events was simulated for multiple flow direction analysis between 2008 and 2018. Results showed that LAPSUS model can simulate total volumes of events with a high accuracy by MFD with the amount of nRMSE of 3.9 percent.
Ramin Salmasi; Mohsen Farahbakhsh; Hossein Asadi
Abstract
High soil phosphorus (P) can increase the amount of runoff P and cause pollution of P in water bodies. In this paper, to select the best method between laboratory extracting and rainfall simulator method for determining environmental threshold level of P concentration was compared. For this purpose, ...
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High soil phosphorus (P) can increase the amount of runoff P and cause pollution of P in water bodies. In this paper, to select the best method between laboratory extracting and rainfall simulator method for determining environmental threshold level of P concentration was compared. For this purpose, surface soil was sampledfrom 30 points of Talkherood Watershed inEastern Azerbayjan with widely available P contents. After determining some of general properties, four soil P tests comprising Olsen, Mehlich-3, Iron oxide, and Soltanpour were used. Water soluble P in lab was measured and runoff soluble P of soils was determined with using rainfall simulator by applying 75 mm h-1 rainfallfor 30 minutes. Relationship between P concentrations determined by four methods with a) water soluble soil P, as P loss index, and b) runoff soluble P, showed that environmental soil P concentration can be estimated by both lab extracts and rainfall simulation methods for lime soils of this region. As the lab extracts method are easier and less time-consuming, this method is recommended for threshold concentration estimation. Since in iron oxide method, slope difference between the two split-lines was greater than other methods and high correlation coefficients were obtained for all of the methods, as a result iron oxide method is better than others for threshold concentration estimation of available P concentration. Since changing point for dissolved reactive P was seen in 0.36 mg l-1 concentration, as a result this concentration is lower than environmental P concentration for eutrophication phenomenon.
Ali Akbar Davoodirad; Davood Nikkami; Mehdi Mardian
Abstract
Increasing in production and welfare of rural household along with soil erosion mitigation are the most important objects of a watershed management program. Land use optimization is an efficient approach that leads to a sustainable development plan. In this research, the land use optimization was applied ...
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Increasing in production and welfare of rural household along with soil erosion mitigation are the most important objects of a watershed management program. Land use optimization is an efficient approach that leads to a sustainable development plan. In this research, the land use optimization was applied using a two-objective linear programing model and geographic information systems by Lingo 11.0 software in Adineh-Masjed Shahzand watershed of Markazi province, Iran. The model was defined with three scenarios of current conditions, applying management conditions, and standard conditions for two objectives of maximizing net benefits and minimizing soil erosion. Results showed that the annual soil erosion decreased by 1.27, 18.69 and 26.93% in current land use, land use management, and standard land use conditions, respectively. Also annual net income decreased by 18.56% in current land use; but increased by 48.01 and 220.07% in land use management and standard land use conditions, respectively. Considering weighting value of decreased soil erosion of 1.27% that is less than weighting value of decreased net income in current conditions, land use optimization with no management practices or land standardization is not justifiable.
Alireza Habibi; Samad Shadfar; Younes Daghigh
Volume 2, Issue 1 , May 2010, , Pages 18-24
Abstract
Recognition from coverage amount of country present conditions in a watershed is unavoidable necessity for optimal and permanent development and utilization. In this research, we choose Fashand watershed in north-eastern of Hashtgerd city. First have recognized independent variables to predicting country ...
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Recognition from coverage amount of country present conditions in a watershed is unavoidable necessity for optimal and permanent development and utilization. In this research, we choose Fashand watershed in north-eastern of Hashtgerd city. First have recognized independent variables to predicting country power. Then prepared various weight maps as informational layers using field studies and Geographical Information Systems (GIS), and classified and composed them together using coverage index. In next stage, coverage predicting agriculture power map with present country conditions map and calculate correlation matrix. Results showed that predicted area with much week and week talent include intermediate rangelands with 19.47 percent coverage areas with medium talent for agriculture intensity have 0.3 percent stratification. And good and very good predicted areas for agriculture intensity include 39.7 percent, good rangelands 2 percent, poor rangelands 29 percent. Unfortunately 994 Hectares of very good agriculture rascals have specialized to civic areas that shows having no comprehensive programs in this base. Prediction shows that 9259 ha of rascals with 53.17 percent of total areas include very good agriculture lands and medium, week and very week areas include less than 23 percent of total Fashand area. Finally, we suggest that programmers and propagators present a model for each area regard to ecological power of area and present intensities conditions, to have in mind area with optimal utilization and suitable intensity use.
Reza Talaee
Abstract
In this research, a spatial prediction model (a quantitative method) and the fuzzy sets theory (a semi-quantitative method) have been used for landslide hazard and risk assessment, respectively. A procedure, compring two analytical stages, has been proposed to show the location of future slope instability. ...
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In this research, a spatial prediction model (a quantitative method) and the fuzzy sets theory (a semi-quantitative method) have been used for landslide hazard and risk assessment, respectively. A procedure, compring two analytical stages, has been proposed to show the location of future slope instability. In the first step, 75% of the pixels with landslide have been entered to the model as the estimation set, in which new landslides have occurred with a moderate to high intensity or at least have displaced once or more in the last 50 years. At the second stage, the accuracy of prediction map has been examined by ROC curve (Receiver Operating Characteristic curve) based on 25% of the landslide pixels that have not been entered in the model. Landslide risk evaluation was considered by combination of the hazard potential and resource damage potential and using the fuzzy algebraic product operator in the region. The hazard potential and resource damage potential obtained typically from the hazard zonation map and the land cover/land use map. The area under the ROC curve is 0.795 for hazard zonation map, equivalent to an accuracy of 79.5%. In the base of multi-method approach results, 13.8% of the region is located in a high and very high risk level zone, and 78.1% of the area is placed in low and very low risk categories. Proposed method was used for landslide risk assessment in Hashtchin region and the results could be used to established land use planes, developmental activities, displacement and extension of settlement area, and patterns of building regulations.
Seyed Saeed Eslamian; Mohammad Hadi Bazrkar; Seyed Farhad Mousavi
Abstract
The most important factor of drought analysis is rainfall. All resources which are supported by rainfall, such as, surface streams; groundwater and lakes, are affected by deficit of rainfall. Analysis of past rainfall statistics indicates a pattern. Forecasting future rainfall can be used in water resources ...
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The most important factor of drought analysis is rainfall. All resources which are supported by rainfall, such as, surface streams; groundwater and lakes, are affected by deficit of rainfall. Analysis of past rainfall statistics indicates a pattern. Forecasting future rainfall can be used in water resources planning. This opportunity can be provided by time series patterns. The aim of this research is drought forecasting of Isfahan Province, by fitness of various models with rainfall data. Studied models are included in monthly, monthly-seasonally, annual-exponential, moving average (3, 5, 7) and sinusoidal. 24 meteorology stations have been studied in the time series analysis. The at-site statistic period ranges between maximum 44 years (1957-2000) to minimum 11 years (1987-1997). By regarding ARIMA model fitness, the results indicate that the studied stations are divided to three groups as high, medium and low quality. These groups are included 9, 5, 4 stations, respectively. Although Isfahan and Kashan have been owned long-term rainfall data, they have less suitable fitness than the other stations. Therefore, by only having long-term rainfall data, it cannot be expected the better fitness of time series. Using ARIMA for annual moving average modeling can be effective in drought pattern analysis and have been presented the good patterns.
