Mohammad Sadegh Porhemmat; Jahangir Porhemmat; Mehdi Mirzaee
Abstract
Karstic springs, as the main resources of rivers such as Karkheh, have encountered scarcity in the western of Iran during past years. It is necessary to consider the effects of climatic and human co-factors to prepar a rehabilitation plan in watershed scale. The present study was carried out to evaluate ...
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Karstic springs, as the main resources of rivers such as Karkheh, have encountered scarcity in the western of Iran during past years. It is necessary to consider the effects of climatic and human co-factors to prepar a rehabilitation plan in watershed scale. The present study was carried out to evaluate this phenomenon in the case of Sarab-e Niloufar, in Kermanshah Province. Two methods including Standard Precipitation Index (SPI) and Moving Average (MA) are used in this study. Four wet and dry periods were occured, including wet periods from 1980-1981 to 1997-1998 and from 2003-2004 to 2005-2006, dry periods from 1998-1999 to 2002-2003, and from 2006-2007 to 2014-2015 water years. The SPI results showed two main periods from 1989 to 2015, include 1989 to 1999 and 2000 to 2015. The first period is wet or normal, but the second period is very dry to normal and is characterized by persistence and severity of dryness. Also, the results showed that spring discharge has been stable in a-29 years period from 1969 to 1988 with fluctuations by seasonal rainfall, but a sharp decrease over the second period. The average spring discharge was 1100 ls-1 during the first period, but 337 ls-1 in the next 19 years. Other results showed a harmony period between decreasing of the spring discharge with drought cycles resulted from MA and SPI, except for the wet period of 2003-2004 to 2005-2006. Nevertheless, the spring discharge had decreasing rate in the wet period of 2003-2004 to 2005-2006. In addition, spring decreasing discharge rate was greater than rainfall. Therefore, despite the fact that the effects of drought are recognized as a major factor of spring deficit, other factors such as decreasing in water table of adjacent aquifers are also important to consider for rehabilitation of the spring.
Ata Amini; Jahangir Porhemmat; Hossein Sedri
Abstract
Virtual water concepts and water productivity are considered as powerful tools for analyzing issues related to water resource management. This research was conducted to use the indicators of physical and economic productivity of water, in water resources management in Talvar Watershed, Kurdistan, Iran. ...
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Virtual water concepts and water productivity are considered as powerful tools for analyzing issues related to water resource management. This research was conducted to use the indicators of physical and economic productivity of water, in water resources management in Talvar Watershed, Kurdistan, Iran. The data from field observation, meteorological and climatic, water resources, agriculture, irrigation and watershed management were collected. The crop area of the irrigated products in the watershed was identified and their cultivation percentage was determined. Data on the growth of these products and their water consumption were calculated using CROPWAT software and field data. Using the results of data analyzing, management indicators such as physical productivity and economic productivity of products were calculated. Results showed that five crops of wheat, potato, barley, alfalfa and clover make up more than 93% of the irrigated products area of the watershed. It was found that the potato and wheat were with highest and lowest physical efficiency, respectively. The potato is with highes productivity as 3.46 and wheat was with lowest one as 0.43 kg m-3. Despite of low physical efficiency for wheat, the major part of water consumption in this crop was from green water, while the potato is using the lowest rate of green water. In terms of economic productivity, barley and potato products were with most net economic benefits. The results of this research can lead to proper management and appropriate water resources in the basin.
Rahim Kazemi; Jahangir Porhemmat
Abstract
Understanding the base flow can be useful in river flow analysis, rainfall-runoff modeling, calibration of models, water resource management in low flow conditions and determination of the amount of water storage in watershed. In this research, 22 stations were selected with the appropriate data and ...
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Understanding the base flow can be useful in river flow analysis, rainfall-runoff modeling, calibration of models, water resource management in low flow conditions and determination of the amount of water storage in watershed. In this research, 22 stations were selected with the appropriate data and common period of the years of 1982-2012. The trend of flow changes during the months of the year was determined for all hydrometric stations in the study area and the driest month was determined. Then, the calibration of six recursive digital algorithms was performed using the long-term data of the driest month of the year and after obtaining optimal parameters of the models, the base flow separation for the whole period was performed. The performance evaluation of the models was done using root mean square error. The results showed that the major part of the river flow in the study area was related to the base flow and the minimum, maximum and average annual base flow index for the whole period was equal to 0.48, 0.62 and 0.56, respectively, representing more than 50% of ground water contribution to stream flow of the studied watersheds. Results of the evaluation of the models using the root mean square error showed that the mean error in the research area for all the methods ranged from 0.025 to 0.044. The minimum was related to Lynie and Holick, and the maximum related to the One-parameter digital filter. Over all, conclusion of the results of the calibration process and investing the correlation between calculated and measured data showed that there was a correlation with a coefficient of explanation of more than 80%. Calibration method with dry season data in the absence of tracer-based methods is suggested as the most suitable method for calibrating digital separation filters in the study area.
Rahim Kazemi; Jahangir Porhemmat; Forood Sharifi
Abstract
The Flow Duration Curve (FDC) is a classical method used to graphically represent the relationship between the frequency and magnitude of stream flow and is required as a prerequisite for water resources management projects. In this study, by analyzing daily data of hydrodynamic stations, 47 stations ...
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The Flow Duration Curve (FDC) is a classical method used to graphically represent the relationship between the frequency and magnitude of stream flow and is required as a prerequisite for water resources management projects. In this study, by analyzing daily data of hydrodynamic stations, 47 stations with the appropriate statistics and the common period between 1976 and 2011 was selected in a semi-arid region of the country. Using a topographic map with a scale of 1: 50000 and determining the position of the stations, the study area was determined and 11 physiographic parameters influencing the flow duration curve including: average height, basin area, gravilillus coefficient, basin slope, main river length and hydrological parameters including annual rainfall, Base flow index, hydrograph recession constant, curve number, permeability and the number of rainy days were extracted for each basin. The flow duration curve indices were then extracted using daily flow data. Then factor analysis was performed and independent factors influencing the flow duration curve were determined. Finally, homogeneity was performed based on independent main factors and the regression relations of the curve indices were extracted in each homogeneous region.In order to investigate the validity and accuracy of the models in homogeneous regions, error-independent test methods, normal distribution of errors and control stations were used. The results showed that the selected factors for factor analysis in semi-arid climatic zone (75.875 percent) of the variance of data were explained. The six parameters of precipitation, curve number, slope, rainy days, permeability and area were known as the most effective parameters. The results of the accuracy assessment of the models using the control stations showed that the relative error of the relations presented in the homogeneous region was 0.17, 2.17, 2.73, 1.53 and 1.94, respectively. The normal distribution of errors, the coefficient of determination of more than 0.90 and the Durbin Watson coefficient between 1.5 to 2.5 also Nash-Sutcliff near "one" indicate the reliability of the regression relations presented for estimating the flow duration curve indices in the ungagged catchments in semi-arid areas of the country.
Seyed Vahid Shahoei; Jahangir Porhemmat; Hossein Sedghi; Majid Hosseini; Ali Saremi
Abstract
Soil and Water Assessment Tool (SWAT) is a continuous and semi-distributive model which can simulate the hydrological processes in basins on daily, monthly and yearly time scales through a wide range of information such as physical data of basins (soil, land use, slope) as well as weather information ...
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Soil and Water Assessment Tool (SWAT) is a continuous and semi-distributive model which can simulate the hydrological processes in basins on daily, monthly and yearly time scales through a wide range of information such as physical data of basins (soil, land use, slope) as well as weather information such as precipitation, temperature, wind, relative humidity, solar radiation and connectivity to geographic information systems (GIS). In this research, the monthly runoff of Ravansar Sanjabi basin (1260 ), in Kermanshah Province of Iran is simulated through SWAT hydrological model. Runoff simulation is done in a period of nine years from 2002 to 2010, where the first seven years of this period (2002-2008) is selected as a calibration period by using 14 various parameters and the two end years (2009 to 2010) as a validation period of model. The results of simulations during the calibration and validation periods are evaluated through two statistical indices namely Nash–Sutcliffe coefficient (NSE) and coefficient of determination (R2). According to compared simulated and observed monthly flow hydrographs and also calculated statistical coefficients, the SWAT model has acceptable results in simulating monthly runoff during both calibration and validation periods, so that the NSE and R2 coefficients are calculated equal to 0.7, 0.8 and 0.81, 0.9 for calibration and validation periods, respectively.
Rahim Kazemi; Jahangir Porhemmat
Abstract
Estimating the runoff coefficient that is influenced by morphometric, geologic and hydro-climatologically factors are the most important issues in hydrology and information of its role in the planning and management of water resources is more important. Clustering catchments is the best method for the ...
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Estimating the runoff coefficient that is influenced by morphometric, geologic and hydro-climatologically factors are the most important issues in hydrology and information of its role in the planning and management of water resources is more important. Clustering catchments is the best method for the analysis of hydrological parameters in the absence of full coverage of hydrological data. In this research, twenty two hydrometric stations with common period from 1974 to 1999 were selected. Physiographic parameters of the catchments were extracted. Runoff coefficient was calculated and then base flow was extracted from using one parameter recursive digital filters. Lithological units using digital geological map, with the scale of 1: 250,000, based on expert opinion divided on two classes and area covered by each unit in each catchment were calculated. Factor analysis using 15 parameters were conducted. Catchments using independent factors in different hierarchy methods includes: nearest neighbor, furthest neighbor, median clustering, centroid clustering and Ward method were classified. Then, the regional equations using linear regression at 1% significant level were determined. To compare and evaluate the accuracy and efficiency of the models, independence errors, colinerity and normal distribution of error were tested. The results of factor analysis showed that all variables are to be classified in terms of five factors which 85.9% of the variance was included. Results of homogeneity showed that the basins in homogeneous methods of nearest neighbor, furthest neighbor, centroid clustering and median clustering, were all the same and classified in two groups with the similar components. The results of accuracy assessment showed that the accuracy of nearest neighbor methods was more accurate, and because of low relative error (25.4%) and MAE of 7.85 and RMSE of 9.62 was diagnosed as the best method for regional analyzing of runoff coefficient in the study area.
Rahim Kazemi; Amir Safari; Amir Karam; Jahangir Porhemat
Abstract
Estimation of Base Flow Index (BFI), has always been one of the most important issues in hydrology. Base flow separation process, often is done using daily stream flow data. Lack of full coverage of daily data for the whole country, may lead to some errors for estimating the base flow and its index. ...
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Estimation of Base Flow Index (BFI), has always been one of the most important issues in hydrology. Base flow separation process, often is done using daily stream flow data. Lack of full coverage of daily data for the whole country, may lead to some errors for estimating the base flow and its index. In this research, base flow index in some catchments of Karkhe basin based on daily and monthly stream flow data and using six algorithms were extracted. Three based on recursive digital filter (One-parameter, two parameter and Lynie & Hollick algorithms), and the others on simple smoothing including, Local minimum, Fixed interval and sliding interval methods. Results were analyzed using different statistical methods such as standard deviation, mean absolute error, relative error and other descriptive methods. The results showed that minimum relative error of monthly data compared to daily data was related to two parameter algorithm with 2.45% and the maximum was related to Lynie & Hollick algorithm with 84.19 percent .In overall conclusion, two parameter algorithms because of low relative error, minimum Mean Absolute and Root Mean Square Error was recognized as a suitable method for the extraction of base flow using monthly data in the absence of appropriate data daily.
Jahangir Porhemmat; Hadi Nazaripooya
Abstract
Infiltration is one the most important components of hydrologic cycle for utilization and managements of water resources. This phenomenon is affected by several factors and its measurement is difficult. Therefore, several models have been introduced for the simulation of infiltration. Previous studies ...
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Infiltration is one the most important components of hydrologic cycle for utilization and managements of water resources. This phenomenon is affected by several factors and its measurement is difficult. Therefore, several models have been introduced for the simulation of infiltration. Previous studies in evaluation of infiltration models show that each model can be preferred over others in a specific condition. Considering this fact, six infiltration models including Philip, Horton, Green-Ampt, SCS, Kostiakov and Luise-Kostiakov and thier parameters were evaluated. Gonbad catchment in Hamedan province was selected and it was divided into four homogenous hydrologic units. Then infiltration was measured during the dry season by double ring. The results showed that Philip model was the most accurate for estimating of the infiltration and Kostiakov model is also the second one. Regression coefficients of Philip model were betwean 0.975 to one, mean error -0.017 to +0.017 and the maximum root mean square error was 0.22. Regression coefficients of Kostiakov model were between 0.956 to 0.998, mean error -9.3 to +0.003 and the maximum root mean square error was 14.25. In addition, the correlation relations between parameters of these models and two soil texture indices were carried out. The findings show that except for SCS model, the other parameters correlate with these two indices in a 5% level and at least one parameter of each model has high correlation with them. Regression coefficient for A in Philip model, B in Green-Ampt, k in Horton, b in Kostiakov and b in Luise-Kostiakov were 0.99, 0.95, 0.99, 0.999 and 0.96 respectively. Results show a lower correlation between the other parameters and the percentage of clay and sand. Based on these results, it is suggested that the regression relations of models’ parameters for different conditions of soil texture and antecedent moisture in a variety of basins should be evaluated and determined.
Ravanbakhsh Raeisian; Jahangir Porhemmat
Abstract
Various models have been used for snow melt computation. From which degree-day model is one of the most common one that estimates snow melt based on one of temperature’s parameters. In this model, in addition to temperature, degree-day factor is used by calibration in each region and derivation ...
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Various models have been used for snow melt computation. From which degree-day model is one of the most common one that estimates snow melt based on one of temperature’s parameters. In this model, in addition to temperature, degree-day factor is used by calibration in each region and derivation of model factor based on gained data with correlation. This investigation was executed in Chari region in Chaharmahal va Bakhtiari province as "Snow gauge representative area” in Central Zagross. Seven sites were determined for snow operations and three indexes were installed with rectangular triangle arrangement with 20 m length in the sides in each site. Scale-density methods were used to determine the amount of snowmelt. The average daily temperature in each site was calculated based on information of weather stations around the region and thermal gradient relations. From November 2005 to May 2011, snow depth and density were recorded weekly and its water equivalent was measured simultaneously. The amount of snow melt was calculated due to the depth of equivalent snow water of two consequent records (with no rain periods). Data from four different temperature index including 1) sum of the average temperature of the period, 2) sum of the positive mean temperature of the period, 3) mean of the average temperature of the period, and 4) mean of the average positive temperature of the period , were analyzed and degree–day factor (K) was calculated. The results showed that the highest correlation coefficient (r2=0.63) was related to correlation between the sum of positive temperatures of the period (2nd index) and snow melt. The K value was 4.2 mm per degree–day for the study area which shows the rate of four mm per day of snow melt for each degree of positive temperature. This result is similar to the previous studies and it is proposed for application in central Zagross zone.
Alireza Eslami; Jahangir Porhemmat; Nadergholi Ebrahimi
Abstract
Quantitative analysis of runoff and estimates of stream flow in gauged basins and its transferring to ungauged sites has special importance for water resources planning, watershed and agricultural lands management, as the layout and optimal design of diversion structures and flow control need runoff ...
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Quantitative analysis of runoff and estimates of stream flow in gauged basins and its transferring to ungauged sites has special importance for water resources planning, watershed and agricultural lands management, as the layout and optimal design of diversion structures and flow control need runoff information with different probability levels. In this research, runoff information of hydrometric stations which located in river catchments of Isfahan, Markazi, Qom, Tehran, Hamadan and Qazvin provinces was collected and investigated. In this regard, such stations which included data with the appropriate quality and quantity were selected in a common period of time. In this case study, results of cluster analysis concluded three homogeneous regions of watershed based on independent variables. According to mean annual runoff probability analysis; the best statistical distribution was fitted and runoff values were determined with return periods of 2 to 100 year. Also, regional runoff models based on hydrological and morphometric parameters were extracted with different return periods for each homogeneous region. In each homogeneous region, evaluation of regression models obtained was carried out using a number of hydrometric stations control. In this case study, area, average slope, main river slope, length and gravilus coefficient of watershed were detected as the most influential parameters in estimation of runoff. Root Mean Square Error (RMSE) for models represented minimum values of 1.2, 5, 7.6 with two years return period and maximum values of 14.4, 32.8 and 18 with 100 years return period in the first, second and third homogeneous groups , respectively.
