جستجوی مقالات مرتبط با کلیدواژه "calibration" در نشریات گروه "جغرافیا"

In most developing countries soil georeferenced data is not yet available. The FAO prepared the global map through the Coordinated Global Soil Database. The aim of this study was to evaluate the required details of the regional map in comparison with the soil global map of Talar watershed using the SWAT model. In this model, climatic data of 2004-2017 were used to simulate runoff. The first two years were used as model warm-up period, 2005-2015 for calibration and 2016-2017 for model validation. Sensitivity and uncertainty analysis, was done in SWAT-CUP software with the help of SUFI-2 algorithm. The evaluation of the model was done using the coefficients of explanation (R2) and Nash-Sutcliffe (NSE) statistics. The available soil water capacity (SOL_AWC) parameter was determined as a sensitive parameter. Before calibration, 32.7% (global) and 29.3% (regional) precipitation was simulated as daily flow. After recalibration based on the regional soil map (NSE=0.56 and R2=0.74) and global (NSE=0.56 and R2=0.64) and in the verification stage according to the regional soil map (NSE=0.59 and R2=0.76) and global (NSE=0.62) and R2=0.75) was estimated. The results showed the acceptable performance of the model in flow simulation. Sub-basin 9 (deciduous forest) and 14 (summer pasture) had the lowest and highest share in runoff production, respectively. The regional map provided more reliable results. Although the additional information provided by the regional map, while changing the optimized parameters in the model, has no effect on the outflow of the basin, the results indicated that the regional soil map has no significant effect on the flow prediction, and if it is not available, the global soil map information can be used.

Daily flow data are a prerequisite for water resources management, but it is not possible to measure it in many upstream watersheds. In this study, different optimization algorithms have been used to evaluate the efficiency of the SIMHYD model. Therefore, the discharge data of Kouzetopraghi rive gauge station was selected as the study data (805 km2) located in Ardabil province. The daily data of rainfall, evapotranspiration of the meteorological stations in the study area were used to simulate the daily river flow data. Optimization methods including genetic algorithm, comprehensive competitive evolution, search pattern, multi-start search pattern, uniform random sampling, Rosenbrook, multi-start Rosenbrook optimization were evaluated based on statistical efficiency criteria. The mean value of discharge values by genetic algorithms, multi-year pattern search, uniform random sampling, multi-start Rosenbark, Rosenbork, comprehensive competitive evolution, search pattern were 0.031, 0.023, 0.085, 0.032, 0.024, 0.032, 0.031, respectively. The results showed that the change of optimization algorithms has a significant effect on the calibration accuracy of the model, so that the values of the Nash-Sutcliffe efficiency criteria for the employed algorithms were 0.42, 0.31, -8.55, 0.38, 0.56, 0.023, and 0.24, respectively. The Rosenbrook algorithm had higher accuracy in calibrating the SIMHYD hydrological model compared to other algorithms used. A part of the modeling error can be related to the inconsistency of precipitation and runoff data due to the multiplicity of stations.

By developing GIS and remote sensing technology, the widespread access possibility and local distribution of hydrological management parameters and variables have become practical. Runoff rainfall modeling is always an important and continuous need for practical issues in the fields of water resources evaluation, flood forecasting, engineering canals designing, and many other goals (Bone, 2001). Calculation of runoff-rainfall results has been made practical and operationalized by using GIS techniques and a distributed hydrological model. The WetSpa runoff-rainfall model is a hydrological-distribution model that was developed in Brussels in 1997 (Wange et al, 1997) and also, had been used in various research and executive projects by developing in various models. This hydrological model has the capability of performing simulations at the pixel level and because of this, it provides the possibility of using aerial and satellite images with accurate information measured at the basin level, which has a local distribution (Hooshyarypor at el, 1397). Due to the high uncertainties of hydrological parameters, the calibration model is one of the most important part of modeling whose optimization techniques are mainly are used for such purposes. There are various methods for optimization, sensitivity analysis, and also evaluation of uncertainty of models. Accordingly, this paper’s purpose is to calibrate the WetSpa hydrological model with a multi-objective optimization approach that uses the Social Spider Algorithm (SSA) and the Black Widow Spider (BWO) techniques. By this point of view, to achieve a reliable prediction, in addition to the usual discharges, the model must be able to predict high and low discharges accurately (including maximum and minimum), so the objective functions are selected in a way that the best match between observational and computational values can be achieved during the Vasanji process.

WetSpa Model: WetSpa is a continuous local and temporal model in which all of the simulations are conducted continuously. The WetSpa model displays the water and energy balance for each calculation cell, considers rainfall processes, vegetation, snowmelt, wetting, infiltration, evapotranspiration, leakage, surface runoff, wall flow, and groundwater flow. The hydrological system simulated by this model consists of four layers: vegetation, soil surface, root zone, and saturated groundwater table.The Optimization algorithms: The Social Spider Optimization (SSO) algorithm is a new optimization approach which is proposed in 2013 by Kause et al. Another optimization approach used in this paper is the Black Widow Spider (BWO) optimization algorithm. During the day, the black widow spider is out of sight and is mostly nocturnal, and rotates its network during the night. Generally, the widow spends most of her adult life on the same site (Andrite and Banta, 2002).Objective functions and model evaluation: In this paper, to evaluate the model, five statistical indices have been used of correlation coefficient (r), Root Mean Square Error (RMSE), mean absolute error (MAE), Nash-Sutcliffe index, and Nash-Sutcliffe logarithmic index. To increase the accuracy of the model in predicting the minimum and maximum flows, two alogarithm Nash-Sutcliffe and Nash-Sutcliffe logarithmic criteria were used.Zashk basin and model data: Zashk Basin is located in Khorasan Razavi province and in the west of Mashhad with an area of 65.56 square kilometers.

In this part of the paper, the calibration results of the WetSpa model using social spider and black widow spider algorithms are presented. The problem decision variables are the 11 global parameters illustrated in Table 1. Objective functions must be selected in a way that at the end of the calibration process the best match between the observed and computational values can be obtained. Some of these functions give more weight in high flows, while others consider more weight in low flows and have more emphasis on them. In this regard, Nash-Sutcliffe (NS) criterion and its logarithmic form (NS-Log) have been used. In this paper, the results obtained based on these two functions are illustrated. After determining all the necessary local networks in basin modeling, precipitation, evaporation, temperature, and discharge information from 2009 to 2011 were used to calibrate the model and 2012 to 2014 data were used to validate the results. Each of the optimization algorithms was conducted with an initial population size of 100 people and over 100 generations (number of times the optimization model was executed). As it was observed, the answers obtained by BWO are better than the answers of SSO due to its higher NS values. According to the obtained results, NS and NS-Log values are generally from -2.3 to 0.75 and from -0.165 to -0.01, respectively. This problem illustrates that the calibrated model has been more successful in simulating low discharges. In fact, since the model has been executed continuously, the simulation results in 2008 are considered as the Warm-Up period.

This paper calibrated the WetSpa distributed rainfall-runoff model. To calibrate the model, two evolutionary optimization algorithms of social spider (SSO) and black widow spider (BWO) were used in the Zashk basin of Mashhad. The results obtained from the usage of the model in this basin illustrated the satisfactory capability of these algorithms in calibrating the WetSpa model. Comparing the results obtained from the SSO and BWO algorithms illustrated that in the multi-objective calibration problem, the BWO algorithm was slightly more successful than the SSO model. Also, the results indicated that the simulation quality of low discharges was higher than the high ones. The reason for this problem, firstly, can be due to the lower abundance of high discharges in the evaluated data set and secondly, the relatively slow response of the model to changes in hydrological conditions in flood conditions in the catchment basin, because the temporary groundwater storage coefficient (K5) allocated a large amount for itself that can directly affect the reduction of surface runoff. On the other hand, the weakness of the results in predicting some low discharges can be related to the optimal value of groundwater recession coefficient (K2), which has taken a small amount in the calibration process. The results of this study illustrated that the effect of the surface runoff coefficient on the model results is much greater than other parameters (about 36%).

Hydrological simulation of watersheds applies for estimating peak discharge and runoff volume from rainfall, flood routing in rivers and flood hydrograph analysis. The purpose of this study is application of soil moisture accounting (HMS SMA) and Neuro-fuzzy models in daily flow, The purpose of this study is application of soil moisture accounting (HMS SMA) and Neuro-fuzzy models in daily flow. runoff volume and hydrograph analysis of the simulated rainfall - runoff in the Zola Chay watershed. In this study after of Zola Chay watershed modeling with HEC-GeoHMS Extension, In this study after of Zola Chay watershed modeling with HEC-GeoHMS Extension. the model entered to HEC-HMS program and by parameters estimating of soil moisture accounting model, the rainfall- runoff simulation in other scales has been done. By analysis of time scales for calibration and optimization of HMS SMA model parameters we can claim that the monthly time scale rainfall - runoff simulation accurate than annual, seasonal, semiannual and annual time scales can be better than the other time scales of flow to estimate peak. Comparing the calibration and optimization soil moisture and Neuro-fuzzy methods revealed that fuzzy method can simulate rainfall- runoff relationship better than SMA model by best statistical coefficients (E= 0.76 and RMSE= 0.18).

Proper management of catchments is one of the most important ways to make optimal use of water and soil resources. In our country, most of the catchments, especially the mountainous catchments, do not have enough hydrometric and sedimentation stations. This fact makes any development and management plans difficult. Hydrologists and water resources researchers have come up with various solutions but none of them have been completely successful (Roustamiyan et al., 1999; 588 & Shaygan et al., 2011; 2). On the other hand, the limited methods of measurement in hydrology and the need to have a method to generalize the available statistics to areas without statistics or places where measurement is not possible. Also, simulating future hydrological changes is one of the main reasons for hydrological simulation (Beven & Binley, 2001; 46). The ability of the SWAT model to simulate the complex hydrological processes of watersheds in the GIS environment distinguishes this model from integrated models in which larger user units are the basis of operation. 

The study area is part of the Qizil Üzan River. Shahar Chai basin along with other rivers such as Zanjan Chai, Aydughmush, and Qaranquchay is one of the sub-branches of Qizil Üzan that flows northwest and north of the basin and joins near the Myaneh city. The data used in this study include a digital elevation model of 1: 10000 of mapping organization, land use, soil, precipitation, minimum and maximum temperature, wind speed, solar radiation, relative daily humidity of synoptic stations, Sarab, Heris, Bostan Abad, Charoymaq and Runoff and the sediment of Shahar Chai station. In the watershed of Shahar Chai, a soil map prepared by natural resources of East Azerbaijan province has been used. Based on these maps, 21 soil texture classes can be distinguished in the whole basin. Also, based on the land use map, six land use classes in the area were identified.

After parameterization and data entry, the simulation was performed for 20 years from January 1, 2000, to December 31, 2019, based on a monthly time step. To determine the degree of sensitivity of flow parameters in the SWAT model, sensitivity analysis was performed using the SUFI-2 method for 25 selected runoff parameters and 15 selected sedimentation parameters. Using validation results to remove parameters that are less sensitive from the calibration process, it is decided that finally the parameters with lower sensitivity were removed and 13 parameters for runoff and 7 parameters for sediment were selected that were more sensitive. The calibration model for runoff and sediment was done in one step with 1500 simulations in three replications. The calibration process ends when, based on the objective function, the coefficients required for evaluation are acceptable. According to the obtained results, all the evaluation criteria of the model in the simulation of runoff and sediment are allowed.

Examination of the results of the SUFI-2 method in the Shahar Chai basin showed that, based on the evaluation criteria of the coefficients of determination and Nash-Sutcliffe, both in the calibration and validation stages, it has good results in this basin. But they can't predict peak discharge and sediments well. To better determine the performance of the model, first of all, it is recommended that the statistics of stations and numerous and daily runoff and sedimentation measurements should be used instead of monthly, if any, in a basin, to compare their results. Secondly, to achieve the desired results, this model should be used in comparison with other simulation models in this basin and adjacent basins.

In recent years, urbanization has been one of the most significant processes of change in society, which is usually accompanied by the destruction of agricultural and natural lands. In their decision-making processes to protect the urban environment, managers need to properly consider the extent and direction of urban growth. The purpose of this study is to predict changes in urban land use in the city of Tabriz, using the SLEUTH urban growth model. The output of the model predicts the growth rate and direction of the city by 2050. The five coefficients obtained for the study area show that according to the historical scenario, the birth rate and the diffusion coefficient are dominant. The high rate of fertility in this area indicates that the probability of converting each urban cell to a city center diffusion cell is high, and as a result, the growth rate of the new diffusion center in the covered area is also high. The high emission coefficient indicates the high probability of new urban spots resulting from spontaneous growth and their transformation into new centers of urban growth. The results of validation using Kappa coefficient show that the modeling has an accuracy of 97.72%. The obtained results can be used to predict the change of urban land use. The obtained results are the outcome of instrumental rationality, and therefore their application requires a critical approach to them.

The amount of precipitation measured by the radar is different from the amount of precipitation received on the ground. This difference has many causes, some of which are related to the nature of the radar and others to the climate of each region. As a result, radar data needs to be corrected for radar data based on terrestrial data to determine the amount of ground-level rainfall received from the radar data. Weather radar used for estimation of rain in the large areas. The relationship between rain and reflectivity radar is exponential Z = aRb. Radar estimated rainfall amount is incorrect if the coefficients of this model are wrong. Drop size and distribution of rainfall is Effective on the coefficient of this model. The change in the coefficients of this model is very high. In this study, to calibrate radar data, rain from 2 to 3 December 2016 and 11 to 13 February 2018 at the stations, Kermanshah, Eslamabad, Sarpol, Ghasre Shirin, Harsin, Javanroud, Tazabad, Songhor, Ravansar, Ghilan Gharb and Soumar at distance of 30 to 100 kilometers from Kermanshah’s radar are investigated. In the first rain, using soft Rainbow for each of the stations and radar beam elevation angle optimization and correction factors relating to the extraction station, respectively. With this relationship, the radar rainfall estimates from 31 percent to 96 percent Increased and the average total rainfall from 8.9 to 32.4 millimeter increased an average radar rainfall estimated only 1 millimeter less than actual rain by gauge. In the second rain, using data from all stations, only one equation and correction factors were obtained. The results rainfall radar will be accepted at this stage, good approximation, and the average estimate rainfall radar from 9.6 to 23.5 millimeter increased those 4 millimeters less than the actual amount by gauge. If radar coefficients are corrected correctly for different areas, precipitation can be predicted and prevented from occurring unexpected events.

Watersheds are open systems which, due to its complexity and in order to achieve the desired goals, are modeled. Through modeling, the cost of study for complex systems is reduced because large-scale field trials are very costly or impossible. Also, by analyzing the results of the model, we can manage the watersheds well. In this research, the performance of the IHACRES rainfall-runoff model was evaluated in the simulation of runoff in the Lanbarn basin.  The monthly data on rainfall and temperature of  Varzaghan station as input variables for flow simulation and observation data of runoff at Cassin hydrometric station were used to measure the accuracy of the IHACRES model. Based on available years, data from 2002-2000 were used for warming up the model and data from 2012- 2012 were used for calibration and data from 2016-2013 were used for validation purposes. To evaluate the ability of the IHACRES model in runoff simulation, the Nash-Sutcliff coefficient was used. The results showed that the coefficient was 0.71 and 0.74 for calibration and verification, respectively. Therefore, according to the results of the evaluation of the IHACRES model using different performance criteria and because of easy access, less inputs and a reduction in the time spent, it can be advised to use the model to simulate and predict runoff in a monthly scale in the Lanbarn watershed and to use it in order to study surface runoff and river flow in future periods.

In order to manage watersheds and prevent inconsistencies in measures taken at the catchment area, a model is needed which, according to the existing information and conditions, has the efficiency of simulating the outflow of the region (Yong et al., 2014:47). Integrated models require less information than distributed and semi-distributed models, and, on the other hand, they run faster than other models (Golshan et al., 2017:966). The IHACRES model is an integrated concept model that includes a nonlinear reduction model and a linear lattice model. Despite the relatively recent development of IHACRES, this model has been widely accepted among hydrological models (Sriwongsitanon & Taesombat, 2011). The number of parameters in this model is low, while simultaneously compared with distributed models, we have tried to provide more details of the internal processes (Croke & Jakeman, 2008, Golshan, et al., 2017:966).

To do this research, the monthly data on rainfall and temperature of Varzaghan station as input variables for flow simulation and observation data of runoff at Cassin hydrometric station were used to measure the accuracy of the IHACRES model. Based on available years, data from 2002-2000 were used for warming up the model and data from 2012- 2012 were used for calibration and data from 2016-2013 were used for validation purposes. The IHACRES model is an integrated metric conceptual model for rainfall-run simulation. This model was developed by Jackman in 1990. The model needs 5 to 7 variables for calibration and is suitable for implementation in large scale basins. In this study, version 2 of this software has been used, which is applicable for basins with continuous data of rainfall, temperature and runoff. This model consists of two nonlinear and linear interconnected segments that are
respectively defined for calculation of losses and effective rainfall conversion to runoff.

Based on the results, Nash-Sutcliff coefficient was 0.71 and 0.74 for calibration and verification, respectively. Therefore, it can be stated that the model of low discharge simulates well, but in simulating the maximum discharge, it has little ability and simulates lesser amounts of observational flow. In general, due to low model deviations and good simulation of minimum discharge values, it can be argued that the performance of the IHACRES model in the Lanbaran catchment area is satisfactory.

Given the diversity of rainfall-runoff models, selecting an appropriate model for watersheds is important for increasing the efficiency of planning and managing water resources. Hence, in this study, IHACRES model performance was evaluated in runoff simulation in the Lanbaran watershed. According to the results of the calibration and verification of the model in runoff simulation based on different performance criteria, the model was found to have a high accuracy in simulating runoff at the station under study. It also simulates the amount of monthly flow, which is consistent with the results of studies of Zarei et al. in the basin of Kasaliyan, Lotfirad et al. in the Nawarud basin and the studies of Croke and Jakkman. Therefore, according to the results of the evaluation of the IHACRES model using different performance criteria and because of easy access, less inputs and a reduction in the time spent, it can be advised to use the model to simulate and predict runoff in a monthly scale in the Lanbarn watershed and to use it in order to study surface runoff and river flow in future periods.

Conservation of soil and water resources is one of the most important principles of proper management of catchments. Therefore, erosion and changes in land use concerns make the importance of predicting the effects of these actions on soil water resources even more important. Therefore, it is necessary to model and evaluate their results. In order to better manage the water balance of the catchment areas, it is essential that the modeling of hydrological phenomena in the catchment area can be an optimal solution for them because of the time it consumes and the costly measurement of water balance components (Zarehkarizi & Talbi, 2016). Therefore, accurate knowledge of the hydrologic behavior of catchment areas can help to better simulate this environment in order to control the main components of the water table (Mojenazadeh, Gahraman, & Davari, 2016). On the other hand, the limitation of measurement methods in hydrology and the need for a method for generalizing the statistics to untapped basins or places that cannot be measured, as well as the simulation of future hydrological changes are among the main reasons for hydrological simulation (Beven, 2001). Many models have been proposed for describing and forecasting the hydrology of the rivers that are very different from the point of view of the time scale and spatial scale (Setegn, Dargahi, Srinivasan, & Melesse, 2010). One of these models is the recent SWAT hydrological model. This model is a semi-distributive model designed to simulate the hydrology of the catchment area on a daily scale. In order to investigate the effect of different management strategies on flow, sediment, nutrients and chemical shale in different watersheds, Land is developed (Arnold et al., 1998).

The Lanbarn watershed is located on the eastern side of the Aharchay River. The area of this sub-basin is 20118 hectares and is the main axis of the Aharchi River. This basin is located in Sina subdivision from the central part of Varzaqan City of Eastern Azarbaijan Province. The SWAT model was used to study runoff in this basin. The SWAT is an example of basic physics models that solves the fundamental physics equations to simulate the processes of the catchment system. This model is semi-distributed and temporally connected in terms of spatial scale. The SWAT model simulation can be divided into two main parts: terrestrial and aqueous phase. Terrestrial phase is related to land surface processes and water, sediment and chemical elements to the main waterways of each sub basin. The aqueous phase simulates the processes of waterways and canals involving the movement of water, sediment, and chemicals.  The smallest unit in this model is the HRU Hydraulic Response Unit, which is derived from the combination of slope, soil and land use maps. Soil water, surface runoff, sediment and chemicals are first calculated for each HRU and then for each sub-basin and finally for the entire catchment. The data used in this study include topographic map, land use, soil, precipitation, minimum and maximum temperature, wind speed, solar radiation and daily relative humidity of synoptic stations of Ahar, evapotranspiration of Varzgan and Rain gauges of Eilagh and Dubai Cassine Station. The study area was divided into 17 sub-basins and 469 hydrological units. From 2000 to 2003, the model was warmed up 10 years for calibration and 4 years for validation.

In order to determine the degree of sensitivity of the flow parameters in the SWAT model, two methods of SUFI-2 and GLUE sensitivity tests for the 22 selected parameters were performed. Of the 15 critical parameters of the SWAT model, the density of the soil mass, the soil hydraulic conductivity in the saturation state, the coefficient of evaporation of groundwater, the constant flow rate from the canal, the snowfall temperature, and the snow melting temperature are more sensitive. In terms of 15 sensitive parameters, the swat model is more sensitive to soil mass density factors, saturated hydraulic conductivity, ground water evaporation coefficient, canal discharge constant, snowfall temperature, snow melting temperature. All model assessment criteria in runoff simulation are allowed. But the comparison of the two methods shows that the SUFI-2 method has a better performance than GLUE in this basin. The comparison of graphs, real discharge and the monthly simulated values shows that SWAT model underestimates runoff underestimates. Most streams that the model could not simulate were in late winter and spring. One of the weaknesses of the model in estimating the maximum runoff is the use of the SCS model in the calculation of runoff, which does not simulate the runoff from snowmelt appropriately.   

The results of the application of two methods of SUFI-2 and GLUE in the Lanbran watershed were investigated. Based on the evaluation criteria of the SUFI-2 method, both calibration and validation stages have good results as compared with the GLUE method in this basin. Also, both methods could not predict peaks because they predicted both methods in Dubai sky-highs to be less real than actual Dubai. Although it is easier to use the GLUE method than the SUFI-2 method, the number of simulations is higher for the solution in the GLUE method, Therefore, according to the results, it can be concluded that the SUFI-2 method with low simulation numbers is better than GLUE in this basin.

  Kermanshah Province is one of the western mountainous provinces located in the middle Zagros mountains.The rainfall in this province is similar to other mountainous regions orographic and rugby.
Forecasting rainfall in terms of severity, amount and continuity in the usual way is often not precisely possible and requires very expert forecaster and familiarity with local conditions.This leads to severe, destructive and sometimes catastrophic floods in the province.
Today, weather radars can be predicted by experts as a valuable tool for forecasting rainfall, provided that they are calibrated in accordance with local conditions and calibrated over time with climate change.
If the calibration of weather radar is good, radar can estimate the amount of rain over the vast areas with good accuracy. Relationship between rain and reflectivity radar exponential Z=aRb, where a and b are coefficients radar. And the amount of R depends on factors such as: the type of rain, rain season, latitude and topography. Variation range of a is few tens to few hundred, and the range of variation b is 1 to 3. Drop size and distribution of rainfall, the coefficient of this. The purpose of this study is to measure the Kermanshah weather radar with the conditions of the province, so that the specialists predict that using this radar can predict the characteristics of rainfall before its occurrence, provide warnings to the people and authorities and the damage to the dwellings Historic buildings, administrative centers, urban and rural facilities, farms, humans and animals to the extent possible
In this study, rain from 17 to 18 November 2015 and 30 November to 2 December 2016 at the stations, Kermanshah, Eslamabad, Sarpol, Ghasre Shirin, Harsin, Javanroud, Tazabad, Songhor, Ravansar, Ghilan Gharb and Soumar at distance of 30 to 100 kilometers from Kermanshah’s radar are investigated. Linear regression method using hourly rain data and the amount of reflectivity, linear equations and the coefficient R2, reflectivity, respectively. For rainfall of 17 to 18 November 2015 for all stations different angle radar beam and the reflectance was measured. And the amount of rain gauges in the same period was obtained. The radar beam elevation angle optimized for each station, a separate line equation was obtained. Using the coefficients of the equation and radar, rain intensity level was determined Surface Rainfall Intensity (SRI) and the total rainfall was an hour and finally total rain was estimated for each station. Radar estimated rainfall amounts for the first part was more than the amount measured by rain gauges.
Because the error was found in all stations, it is assumed that the size and distribution of rainfall in the first part of rainfall vary with the next step. So to solve this problem, rain at all stations was divided into two parts. For the first part of the conflict between rainfall radar and rain gauge rainfall, there was a common linear equations and coefficients a and b were obtained again for all stations. The amount of rainfall was estimated again. A result showed that the amount of rainfall was estimated in this way is better than before.
Use this relationship to estimate the amount of rain 31 percent to 96 percent and the average total rainfall radar estimated that 8.9 to 32.4 millimeter Increased than before calibration. and only was 1 millimeter less than of the actual average obtain by gauge. Since acquiring the optimum beam angle the radar for any location, time-consuming and difficult. So when the time is not enough, it is better for each rainfall radar obtained a relationship. So in the following for rain 30 November to 2 December 2016, using rainfall data of all stations, for correction factors radar, only one equation was obtained. and The results of this way was good, and the mean rain radar to estimate rainfall radar calibration 9.6 to 23.5 millimeter increased and only 4 millimeter less than of the actual rain that obtain by gauge. The results showed that the coefficients radar for any location and at any time is different. So to increase the accuracy of radar rainfall it is better for each separate equation obtained. However, to obtain a separate equation for each location is the best. Finally, it is suggested that the radar equation coefficients for each region of Iran, which is covered by the weather radar, are calculated, so that they can accurately predict the precipitation and give warnings to the different centers.

The present work investigated the modification and optimization project for the water transmission and distribution system, based on the Georefereced and smart management of pressure zones in Amlash city. In order to calibrate the distribution network, data was obtained by remote sesing and data loger of ultrasonic flowmeters and pressure gauge. Therefore, the results of the research emphasize the separation of the distribution network in the area of independent measurement based on Geospatial Information System (GIS) for the improvement of the facility. The results of the executive activities affected by the current research in 1397 resulted in a decrease of production and increase of of the city's water income

Introduction
Climate change is recognized as a major environmental problem by a majority of the international scientific community. According to the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (IPCC, 2007), “global atmospheric concentrations of carbon dioxide, methane and nitrous oxide have increased markedly as a result of human activities since 1750 and now it exceeded pre-industrial values”. This report further suggests that most of the observed increase in global average temperatures since the mid-twentieth century is very likely resulted from rising anthropogenic greenhouse gas concentrations and that, if not controlled, climate effects such as rising sea level, disruption to weather patterns, and ocean acidification pose serious harms to human health, water supplies, agricultural systems, economic performance, and global security. Such projections have triggered calls for prompt and coordinated action to reduce greenhouse gas emissions and adapt to changes in the climate system. Paying attention to climate change event affecting all sections of hydrologic cycle, the goal of this research is to study these phenomena on actual evapotranspiration and soil humidity that play important role in this cycle, with available water for plant, decrease or increase in annual runoff. This can affect all sections of the environmental factors.
Materials and methods
Watershed models are essential for studying hydrologic processes and their responses to both natural and anthropogenic factors, but due to model limitations in representation of complex natural processes and conditions, these models usually must be calibrated prior to application to closely matching with SWAT (Soil and Water Assessment Tool). This is a comprehensive and semi-distributed river basin model that requires a large number of input parameters, which complicates model parameterization and calibration. Several calibration techniques have been developed for SWAT, including manual calibration procedures and automated procedures using the shuffled complex evolution method and other common methods. In SWAT, a basin is delineated into sub-basins, which are then further subdivided into Hydrologic Response Units (HRUs). HRUs consist of homogeneous land use and soil type (also, management characteristics) and based on two options in SWAT, they may either represent different parts of the sub-basin area or a dominant land use or soil type (also, management characteristics). With this semi-distributed (sub-basins) set-up, SWAT is attractive for its computational efficiency as it offers some compromise between the constraints imposed by other model types such as lumped, conceptual or fully distributed, and physically based models. For this goals in the boundary of Talar watersheds of Mazandaran province, we selected 8 stations for precipitation, 5 for temperature and discharge, with Shirgah-Talar station in output. After preparing maps and necessary weather data, we conducted output of SWAT model for this watershed. In this research, we used water year of 2003-2004 until 2006-2007 by a duration of 4 years for calibration and water year of 2008-2009 by duration of 2 years for validation. For calibration and validation of this model, we also used SWAT-CUP package software and SUFI2 program. The entire Talar watershed is divided into 219 Hydrologic Response Unite in 23 sub-watersheds. For assessment of SWAT model from climate change on actual evapotranspiration and available soil water, the SWAT model, further run for this area with new condition. In this stage with definition of HRU for the model, only variated precipitation and temperature are entered into the model to study the influence of these effects on assessment factors in output of the model. To do so, we used variable precipitation and temperature, forecasted by LARS-WG model as one of the important model output for random data of weather condition. After change of daily temperature and precipitation for these stations, variation values enter into SWAT model for second run. It can be concluded that the mean daily evapotranspiration (to year) in the time of calibration and validation, is increased for all duration and higher evaporation in majority of future month. This can be compared with present time that is high index evaporation in May, June, July and August. Study about available water shows unregularly process in decrease or increase of this factor and at least available water in May, June, July and August in the future time that affected hydrologic regularity of the watershed. This can provide water for plant in any month where water is necessary as another environmental factor of area.

Climate change is one of the most important challenges that has affected various parts of human life on Earth. In the present study, in order to investigate the climate change, three synoptic stations of Karaj, Mehrabad and Dashan Tepeh with the help of the statistical statistic downscaling model (SDSM) model were used to predict the statistical period of 2016-2045. Finally, the effects of climate change on the hydrologic conditions of the basin with the help of the model (SWAT) was simulated by the Soil and Water Assessment Tool. The amount of surface runoff and runoff at the study area is 10.59 mm in the studied observation period, but this rate was estimated to be 21.27 mm for the predicted period due to the increase of urbanization and changes in utilization. The results of the research, while highlighting the importance of the effects of climate change, are necessary for their application in applying proper management to adapt to climate change in the future policies of the basin management.

Global solar radiation is considered one of the most important clusters in the world. Today, the use of solar energy as a new energy is one of the fundamental tools for optimal exploitation of global climate-related climatic capabilities. This study aims to calibrate and validate the existing model In order to estimate the amount of radiation of the global sun and the mapping of its zoning maps, it is in the province of Mazandaran. The study used in this study was a field-library. In this research, data from 5 stations of synoptic meteorology of Mazandaran province have been reported daily since the beginning of the year 2000 to January 1, 2010 was used In this study, Angstrom and Prescott solar models were used to calibrate and validate the data of the weather stations of the province. For this purpose, the most important statistical parameters such as equilibrium error (MBE) and least square error (RMSE) and correlation coefficient (r) was used to estimate the radiation and evaluate the accuracy of the estimated data. Finally, the solar energy of the study area was used to generate Atlas maps. Several models were used in this way. ArcGIS9.2 was used in this way. The results showed that according to the solar radiation model, Angstrom and Prescott, the highest radiation was observed in the central and eastern regions of the province It is estimated at 220 to 354 watts per square meter.

Erosion and sediment are one of the most important problems in the watershed management of Iran. In order to carry out the conservation programs, soil erosion control and sediment yield decreasing, estimating the total of the sediment volume, erosion intensity in watershed and determined the sensitive areas are necessary. In this research, the study area is located in the mountainous watershed in Gheshlagh Dam. Before the arrival of Gheshlagh river to the city of Sanandaj, Gheshlagh dam has been constructed over it, which is the source of drinking water of Kurdish citizens and also water supply for agriculture, industry and services of the area . One of the problems in this reservoir is organic load with upstream sediments through surface currents in the tanks. This issue that is caused by road construction, dry farming on the steep slope, use unprincipled upstream land and the excessive use of chemical fertilizers, in addition to reduce the capacity of the reservoir and raising the costs of cleaning tanks, can cause other side effects such as algal bloom in the water tank which is followed by stink and aversive water. So the aim of this study is modeling and estimating the amount of erosion in Gheshlagh basin and then erosion intensity mapping and identify sensitive areas to control erosion and sediment in these sub basins.
Methods and Material: In this research for estimating the amount of erosion in Gheshlagh dam basin, the Soil and Water Assessment Tool (SWAT) and Geographic Information System (GIS), were used. After preparing and present hydrological data and the required basin plans, model was ruined for 1987 to 2007 years. In order to calibrate and validate the results, SWAT-CUP programs and SUFI2 algorithms were used and sediment discharge data of Chehelgazi and Khalifetarkhan hydrometric stations were applied.

In the calibration and validation of the runoff and sediment, R2, NS, p-factor and r-factor coefficients in outlet of two main rivers have good results. The R2, NS, r-factor and p-factor coefficients for monthly runoff calibration in Chehelgazi station were estimated 0.80, 0.72, 0.78 and 0.52 respectively and in Khalyfetarkhan station 0.82, 0.74, 0.80 and 0.54. Also the R2, NS, r-factor and p-factor coefficients for monthly sediment yield calibration in Chehelgazi station were estimated 0.71, 0.69, 0.60 and 0.55 and in Khalyfetarkhan station 0.74, 0.70, 0.63 and 0.60 respectively. Based on the results, SWAT model has the suitable potential to identify critical areas. Based on the intensity erosion map, the basin was divided in to five classes of erosion with very high, high, medium, low and very low intensity and in general the results of this study showed that from 102 sub basins that have been considered, fifteen sub basins create 55% of the total sediment yield in watershed. The most critical areas are in northern and northeastern of basin and have rangeland and dry farming on sloping lands.

The results of the sensitivity analysis test, calibration and validation of the model using SUFI-2 model showed that using this model, the time it takes to optimize parameters and calibration model is reduced from a few months to a few weeks and the ability to achieve maximum calibrated parameters is more certainty. The model has evaluated erosion condition of basin with the 16.2 ton per hectare for especially amount of sediment. One of the significant results of this study was identification of 15 sedimentation sub basins; therefore management of these sub basins can play significant roles in reduction of imported sediments into Gheshlagh dam. By compliance of land use and slope maps it seems that the erosion in that watersheds affected by soil erodibility due to farmland use and slope of these sub-basins. Based on the results, SWAT model has the suitable potential to identify critical areas. The results of this study can be used in management of sediment in sub basins that are susceptible to erosion.

Present research in order to reduce non-revenue water through cluster testing of meters was arranged in the Rasht city's water plant. In this study, rapid data intercommunication model based on Geography Information System GIS were considered in District Metering Area DMA. During the study, the consumption curve, Minimum Night Flow MNF and pressure distribution curves by water distribution network hydraulic model was investigated. The hydraulic model in compliance with GIS and WATERGEMS8.2 software in the form WATERGEMS8.2 was defined. The results of research ordered the change of 4058 meters with a negative measuring error.

Rainfall prediction at regional and global scales is mostly as principle component of hydro-meteorological studies in un-gauged regions. Ground-based measurements of precipitation are available with high accuracy in synoptic stations. Spatial distribution of operational stations is now as one of the biggest problems in the developing countries such as Iran, which the spatial distribution of stations are not enough. In recent decades, remote sensing data have been widely used by many researchers in the world for drought monitoring and management of water resources. The satellites data can be utilized as compensation for temporal and spatial distribution of rainfall. The satellite-based rainfall estimates provided by the Tropical Rainfall Measuring Mission (TRMM) satellite at global scale, are now available freely as only data source at regions without in-situ measurements. Most regions of Iran have arid and semi-arid climates. The evaluation and calibration of TRMM data in different regions of Iran at daily and monthly time scales is very important before those data are used by researchers, experts, climate scientist, hydrologist, etc. Therefore, a comprehensive evaluation and calibration of the TRMM 3B43 and 3B42 dataset at 87 synoptic stations in Iran including six climatic zones, is the main objective of present research.
This research was carried out in Iran. It is located between 44˚14’ to 63˚20 E longitude and 25˚03’ to 39˚47 N latitude, with an area of more than 1.6 million Km2. Alijani et al. (2008) classified Iran’s climate according to climatological parameters to six separate climatic classes: desert, semi desert, mountainous, semi- mountainous, coastal wet and coastal desert. This study aims to evaluate the accuracy of the Tropical Rainfall Measuring Mission (TRMM) satellite and its calibration on the daily, monthly, seasonal and annual scales at the synoptic stations located in climate zones of Iran. The daily TRMM-3B42 and monthly TRMM-3B43 collection data were downloaded from the NASA website and processed. After early processing, a comparative analysis was carried out for satellite data and observed rainfall data at 87 synoptic stations during a 12-year data period of 2009-1998. The Desert, semi desert, mountain, semi-mountain, coastal desert and coastal wet climate zones are included 22, 19, 19, 12, 8 and 7 stations, respectively. We utilized different error measures (R, ME, MAE and RMSE), and agreement indices (POD, FAR, CSI and TSS) for satellite data evaluation. Since there were noticeable errors, regional mean data were calibrated in the daily and monthly scales and finally two correction coefficients were introduced based on regression analysis.
Day-to-day rainfall comparisons showed that the TRMM rainfall estimates are very similar to the observed data values, even if a general overestimation in the satellite products must be highlighted. We found out a high similarity between two sources of rainfall data at 87 synoptic stations in most of climatic zones. Furthermore, The TRMM showed the highest error at Ramsar, Bandar Anzali, Rasht and Babolsar stations, and the lowest errors at Zahedan, Bam and Esfahan stations. In other words, the TRMM revealed the highest error in coastal wet zone and the lowest error in desert zone. The False Alarm ratio (FAR) indicator has the lowest amount in coastal wet zone that shows TRMM applicability to predict rainfall amount at these stations. The highest correlation coefficients at 0.01 significance level on monthly and daily scales, were 0.86 and 0.998 in the semi mountainous zone, respectively, while the lowest values as 0.49 and 0.78 were in the humid zone, respectively. After applying the calibration coefficients, The RMSE values were significantly reduced at monthly scale. This indicates that the calibrated TRMM data is mostly similar with observed rainfall data at different time scales and climatic zones.
In recent years, the accurate measurement of precipitation and its spatial and temporal distribution frequently at un-gauged regions have been addressed in the world. At present, the estimation of rainfall by the TRMM satellite is only data source, which is available freely at global scale. The main purpose of present study is to evaluate the TRMM rainfall data and to provide the correction coefficients in desert, semi-desert, mountainous, semi-mountainous, coastal wet and coastal desert climatic zones, on daily and monthly scale. The main advantage of this work is to apply various statistical error criteria and newly introduced agreement indicators, to evaluate TRMM data. The results reveal that the TRMM overestimates rainfall on daily and monthly scales at 68% of stations. In general, The TRMM could detect most of rainy days in the climate zone and Iran during 1998-2009 period. The calibrated data were very similar with the measured values. Therefore, our research findings showed that the calibration process could improve rainfall estimates at most of climatic zones, significantly.

Simplification and automation of the process of visual and geometric reconstruction is one of the issues considered in 3D modeling of environment, especially in urban areas. A stereo camera, as the positions of its lenses are fixed relative to each other, can be used to facilitate the modeling process. This article shows that using stereo camera calibration data, producing 3D environment model can be facilitaded without needing for matching process, especially in the areas that the matching has problem because of unsufficient information need for it. Moreover, using camera calibration information, geometric information and depth map of the environment can be extracted and produced without the need to define the specified scale between features. In the following, the results of investigations carried out for the reconstruction of urban environment are expressed.