Irrigation
Sh. Nourinezhad; M.M. Rajabi; T. Fathi
Abstract
Introduction Simulation of quantity and quality of surface runoff in mountainous watersheds is one of the most challenging topics in modeling due to its unique features, such as unusual topography and complex hydrological processes. One of the lesser-known aspects of modeling such catchments is ...
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Introduction Simulation of quantity and quality of surface runoff in mountainous watersheds is one of the most challenging topics in modeling due to its unique features, such as unusual topography and complex hydrological processes. One of the lesser-known aspects of modeling such catchments is the uncertainty analysis of water quality predictions, especially about the vital phosphorus parameter. Phosphorus is one of the important quality variables in water, and its increase in water resources can cause eutrophication phenomena in streams and reservoirs of dams. Due to the importance of the phosphorus parameter and the fact that water quality modeling has not been employed in the Karaj catchment area so far, in this research, total phosphorus has been modeled as a water quality parameter along with the flow and sediment discharge. This study aims to identify the most sensitive parameters of the model to flow, sediment, and total phosphorus discharge and calibrate, validate and analyze the parametric uncertainty of the SWAT model in predicting these three variables in a mountainous catchment. The case study was the catchment area of the Karaj River upstream of Bileqan pond, which is one of the mountainous watersheds in Iran. There are two critical water structures along the Karaj River, namely Amirkabir dam and Bilqan pond. Amirkabir dam (Karaj) is a multi-purpose project that is constructed to supply drinking water to Tehran and regulate water for irrigation and agriculture in the suburbs of Karaj. The Bileqan pond is also the essential point of supply and transfer of drinking water in Tehran. Given the importance of this region in supplying water for different uses, providing a calibrated model for quantitative and qualitative variables of water can be the basis for decisions to apply future management scenarios in this basin.Materials and Methods The case study was the Karaj River catchment area upstream of Bilqan Basin, which with an average height of 2880 meters, is one of the mountainous areas located in the Alborz Mountains. This basin with an area of 1076 square kilometers in the north, includes parts of Mazandaran province. In the east and south of the catchment area includes parts of Tehran province and most of it is located in Alborz province. The average annual temperature and rainfall in this basin are 12.1 °C and 480 mm, respectively, and the average of 117 glacial days during the year is observed in this area. The long-term daily data of synoptic stations adjacent to the study area from the beginning of 1998 to the end of 2018 (21 years in total) was introduced to the model. Also, daily data of relative humidity, rainfall, minimum and maximum temperature, solar radiation hours, and wind speed as meteorological parameters measured at stations in the study area were introduced to the model. It should be noted that there was a lot of missing data in meteorological information, especially for daily temperature data. In addition to the above information, daily flow data discharged from Amirkabir dam and technical specifications of the dam were introduced to the model. In addition, orchard management information, including irrigation periods and information related to phosphate fertilizers used in regional orchards, were presented to the model. The global sensitivity analysis method was used to determine the sensitive parameters of the model. Furthermore, the SUFI2 algorithm was used in SWAT_CUP software to calibrate and analyze the parametric uncertainty of the SWAT model. This algorithm quantifies the output uncertainty by 95% prediction uncertainty boundaries.Results and Discussion According to the results of sensitivity analysis, the parameters Baseflow alpha-factor (ALPHA_BF), Manning’s “n” value for overland flow (OV_N), and Precipitation Laps rate (PLAPS) were the most sensitive parameters to flow, sediment, and total phosphorus, respectively. The best Nash-Sutcliffe (NS) coefficients for runoff, sediment, and total phosphorus simulation obtained in all stations and after full calibration and validation periods were equal to 0.76, 0.56, and 0.92, respectively. Simulation of the peak points of the diagram of all three quantities was also associated with increased uncertainty and decreased model prediction accuracy, but due to the placement of more than 70% of the measured runoff and sediment values and nearly 60% of the measured total phosphorus values in the prediction uncertainty boundaries generated by SUFI2 algorithm the final value of the parameters used in the calibration process can be appropriate for simulating future scenarios in similar mountain catchments. The main weakness of the model is simulating the peak points of flow and sediment discharge. In the case of flow and sediment discharge, the liability of modeling can be generalized due to the lack of accurate prediction of the snowmelt inflow to the river in spring, which begins to increase in February and reaches the peak point in May. A considerable number of missing data in meteorological stations can effectively reflect the lack of accurate model prediction at the peak points. In this region, missing daily temperature data compared to other meteorological parameters has been significant. The dependency of the SWAT model on many experimental and quasi-experimental models such as SCS-CN and MUSLE can be another factor affecting the weakness in predicting the peak points of the sediment discharge, as well.Conclusion According to the uncertainty analysis results, most of observed flow, sediment and total phosphorus discharge values were within the uncertainty prediction boundaries generated by the SUFI2 algorithm. The NS coefficient for all three variables has met the satisfactory modeling threshold. Therefore, it seems that the sensitive parameters identified and used in the calibration process in this study and their final values can be appropriate for modeling future scenarios for this study area and similar mountain catchments. One of the limitations of the present study was a large number of missing data in meteorological stations, especially for the temperature variable. Thus, providing required measured meteorological data to the model may emhance the simulation, especially at peak points.
Irrigation
M. Fouladi Nasrabad; M. Amirabadizadeh; M. Pourreza-Bilondi; M. Yaghoobzadeh
Abstract
IntroductionThe watershed acts as a hydrological unit regulating the quantity and quality of the water cycle, and human beings have incurred high costs due to ignorance of this complex cycle and lack of planning of projects in terms of the relationship between water management and community development.Knowledge ...
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IntroductionThe watershed acts as a hydrological unit regulating the quantity and quality of the water cycle, and human beings have incurred high costs due to ignorance of this complex cycle and lack of planning of projects in terms of the relationship between water management and community development.Knowledge of features such as maximum flood discharge is essential for the design of hydraulic structures, such as dams, spillways, bridges, and culverts, in order to reduce potential damages and predict when peak discharges will be reached in the downstream areas when discussing flood warning. Rainfall-runoff modeling is one of the key tools in hydrology to achieve flood characteristics, such as peak rate and peak time. In current research, the performance of IHACRES model using "Hydromad" R package has been implemented to simulate flow in the Shoor river basin in Ghaen on a monthly scale. The model simulation was done to investigate the effect of selecting "ARMAX" and "EXPUH" methods in the linear part of the target function. Also, the modeling process and the optimized values of the model parameters were investigated.Materials and MethodsThe Shoor river basin with an area of 2412.92 square kilometers located in Ghaen between 59 degrees and 12 minutes to 59 degrees and 14 minutes east longitude and 33 degrees and 42 minutes to 33 degrees and 45 minutes north latitude. The study catchment with an average altitude of 1420 m above sea level and an average long-term annual rainfall of 173 mm has a dry climate. This river is the largest river in Ghaenat city which flows into Khaf Salt field. In this research, the IHACRES model was implemented using the Hydromad R package. To perform the flow simulation, precipitation, flow rate and temperature data on a monthly scale during the years 1998 to 2017 were used. The IHACRES model has two parts: the first part, which converts precipitation into effective precipitation at each time stage and the second part, which converts effective precipitation into modeled flow. These sections are called nonlinear and linear modules, respectively. To implement each of the sections of nonlinear modules and linear modules according to the data and conditions in the study area, methods with different parameters can be used. In this research, in the non-linear module section, the "CWI" method and in the linear module section, "ARMAX" and "EXPUH" methods have been used for proper routing in the "reverse" calibration section. In the validation section of the "ls" method, the performance criteria of KGE, NS and R2 were used to evaluate the performance of the model in both calibration and validation process. Result and DiscussionComparison of obtained results in this study with previous studies showed that in terms of examining the performance of the model with the EXPUH linear method, the obtained results are consistent with the results of Sadeghi et al. (2015) and Lotfi Rad et al. (2015) and the model with the EXPUH linear method. The NS criteria has shown acceptable performance. According to the results of the model in the calibration section, in terms of evaluation criteria NS, KGE and , and in terms of simulation of peak flow values and the time to peak using EXPUH method in the linear part showed better performance than ARMAX method. The value of these criteria in EXPUH method is equal to 0.86, 0.93, and 0.86 and in ARMAX method are equal to 0.7, 0.85 and 0.73, respectively. In the validation section, the evaluation criteria in EXPUH method were equal to 0.51, 0.63, and 0.54 and in ARMAX method were equal to 0.55, 0.73 and 0.65, respectively, indicating better performance of the model by ARMAX method. Comparison of the EXPUH method, and also the model with ARMAX method showed more accurate performance in terms of peak discharges, quantity and time of occurrence. The values of NS, KGE and evaluation criteria in this section were 0.51, 0.63, and 0.54 using EXPUH method and 0.55, 0.73 and 0.65 with ARMAX method, respectively.ConclusionAccording to the results, the IHACRES model using ARMAX method in the linear section resulted in more accurate performance than EXPUH method in simulation of peak flow values and time to peak.
M. R. Emdad; A. Tafteh
Abstract
Introduction: SALTMED model is one of the most practical tools for simulating soil salinity and crop production yield. Growth models are important and efficient tools for studying and evaluating the impact of different management conditions and scenarios on water, soil and plant relationships and can ...
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Introduction: SALTMED model is one of the most practical tools for simulating soil salinity and crop production yield. Growth models are important and efficient tools for studying and evaluating the impact of different management conditions and scenarios on water, soil and plant relationships and can be used to make or predict appropriate management scenarios according to the region's conditions and to predict plant performance in the field. Since the performance of irrigation scenarios in field conditions are costly and time consuming, and due to the limited water resources in the country and the necessity of optimal water use in agriculture, using the efficient and generic models can be useful tool for simulating crop production and soil salinity variations. This research has been conducted in order to simulate soil salinity and yield production using SALTMED model in Azadegan Plain of Khuzestan province. Materials and Methods: This study was carried out in wheat fields of Azadegan plain in Khuzestan province during 2014-2015 in three regions including Ramseh (as saline soil), Atabieh (as very saline soil) and Hamidieh (as control, non-saline soil). Three 10-hectare plots were selected in each area and a pilot with area of 2000 m2 was used for evaluation and measurement in each plot. First year data were used to calibrate the SALTMED model and second year field data were used to validate the model and to achieve the results in three conditions. The dominant soil texture in the area was clay loam. The quality of used irrigation water with average salinity of 2 dSm-1 was classified as C3-S1(high salinity with low sodium absorption ratio) and had no effect on wheat yield loss. In this study, version 3-04-25(2018) of SALTMED model was used and after calibrating in the first year, the results of simulated wheat grain yield and soil salinity variation values were used for model validation in different regions and in soils with different degrees of salinity, in the second year. Results and Discussion: The average measured and simulated biomass yield in the first year were 6.6 and 6.1 t/ha, respectively. Furthermore, the average of measured and simulated of wheat grain yield was 2.9 and 2.6 t/ha, respectively. Some statistical indices including mean bias error, normalized root mean square error, and root mean square error for grain yield were 0.11, 0.04, and 0.12 t/ha, respectively. The values of the same statistical parameters for biomass were -0.49, 0.1, and 0.61t/ha, respectively. These results showed that the measured values of grain yield and wheat biomass were in good agreement with the simulated values using SALTMED model. The simulated and measured variations of soil salinity at three soil depths of 0-30, 30-60, and 60-90 cm, showed close agreement with each other in three layers. Root mean square error, normalized root mean square error, and mean bias error for soil salinity values were 1.3, 0.20, and -0.06, respectively. After calibrating the model in the first year, to validate this model in the second year, the results of three pilots locations in three regions of Ramseh (saline), Atabieh(very saline) and Hamidieh(non-saline) were used. Comparison of simulated and measured wheat grain yield and biomass values showed that there was no significant difference between simulated and measured values. The simulated values of grain yield and wheat biomass in the three non-saline, saline and very saline soils had high correlation with the measured values, indicating high accuracy and efficiency of this model in simulating grain and biomass yield in different degrees of soil salinity. Moreover, the trend of soil salinity changes simulated by the SALTMED model in three highly saline, saline and non-saline soils (for three soil layers) was close to the measured values. The SALTMED model with normalized root mean square error and mean bias error of 0.18 and -0.13, respectively, showed good accuracy in different salinity conditions. There was no significant difference (5% level) between the measured and simulated salinity values of the different soil layers. The mean standard error at the 0-30, 30-60, and 60-90 cm layers was 1.1, 1.05, and 0.81 dSm-1, respectively. Therefore, based on the results and statistical indices, it was found that SALTMED model had good accuracy and efficiency in simulating yield, biomass and soil salinity under different salinity conditions. Conclusion: According to the results and statistical indices, SALTMED model had good performance and accuracy in simulating grain yield, biomass and soil salinity variations in different soil salinity conditions and so it can be used to predict wheat yield, yield components and soil salinity in different soil condition with different degrees of soil salinity to sustain soil and water and improve water productivity in similar areas.
MohammadAmin Amini; Ghazaleh Torkan; Saeid Eslamian; Mohammad Javad Zareian; Ali Asghar Besalatpour
Abstract
Introduction: Understanding the concept of water balance is one of the most important prerequisites for sustainable management of water resources in the watersheds. Therefore, the components of water resources in a catchment system should be compared at different time periods, and also the effect of ...
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Introduction: Understanding the concept of water balance is one of the most important prerequisites for sustainable management of water resources in the watersheds. Therefore, the components of water resources in a catchment system should be compared at different time periods, and also the effect of each of them should be identified on varied hydraulic components of the hydrological systems. The SWAT model is an example of a physically based hydrologic model which can be used for large-scale simulating and monitoring of water cycle processes based on the characteristics of the catchment area and its climatic conditions. The main object of this study is the hydrologic simulation and water balance estimation for the period 2000-2009 in the Zayandeh-Rud River Basin.
Materials and Methods: The Zayandeh-Rud River Basin is located in the arid and semi-arid central region of Iran. This area is very variable in terms of rainfall. As well as the state of water resources and water consumption is very complicated in this catchment. In the present study, the soil and water assessment tool (SWAT) used to simulate water balance in the Zayandeh-Rud River Basin. The input required data included digital elevation model, land use map, soil texture map and meteorological information including daily rainfall data and minimum and maximum temperature data were introduced to the model and the model was implemented with these data. The sensitivity of the flow-effective parameters was determined using the p-value and t-state criteria by the SUFI2 algorithm in the SWAT-CUP program. The model was calibrated monthly and validated with the selected parameters in the sensitivity analysis using the Nash-Sutcliff criteria and the coefficient of determination by the application of the data of six stations including. Calibration of the model was conducted for 2000-2006 and validation of the model for the years 2007-2009.
Results and Discussion: The results of sensitivity analysis showed that considering the characteristics of the study area, the SWAT model is more sensitive to the 17 effective parameters on runoff. The selected parameters also confirm the results of previous research carried out in the region. The sensitive parameters selected in the sensitivity analysis step were used to calibrate the model. In the next step, the parameters of SWAT-CUP software were entered. After that, these parameters were repeated 1000 times with the SUFI2 algorithm, and the optimal value for each parameter was determined. The Nash-Sutcliff coefficient and the coefficient of determination in the six hydrometric stations are greater than 0.56 and 0.69 in calibration and verification periods respectively, which indicates that the model has a satisfactory ability to run in runoff simulation. The contribution of the components of the water balance including evapotranspiration, surface runoff, lateral flow, groundwater flow, and deep aquifer recharge was calculated from annual basin precipitation. The amount of extracted water from the hydrological components indicated that the largest share of the water balance was related to actual evapotranspiration, the range of variations in the type of precipitation in the study area ranged from 60.1% (2000) to 92.7 % (2007). After evapotranspiration, surface runoff with a change of 22.2% (2005) to 8.6% (2009) and groundwater flow with a change of 14.2% (2000) to 20.5% (the year 2007) had relatively high fluctuations and a large share in the basin balance. These results indicate that the lateral flow with a range of 3.1 to 1.9% had no significant change in these years. Also, the deep aquifer recharge with the range of 1.2 to1.5% was the lowest in 2003 and 2009, respectively.
Conclusion: The results showed that the calibrated model for the Zayandeh-Rud River Basin had a desirable performance for both calibration and validation periods. Therefore, the SWAT model has acceptable performance for simulating the water balance of the area. In addition, the results of this study showed that 65.98% of the total annual precipitation in the basin is in form of evapotranspiration, which compares to the other water balance components has the highest part. As well as surface runoff with 15%, groundwater flow with 13.7%, lateral flow with 1.5%, and deep aquifer recharge with 0.8% have other parts of the water balance components in Zayandeh-Rud River Basin. The results also indicate that the highest water losses in the soil and groundwater resources of the basin are due to evapotranspiration. Therefore, serious measures to prevent the loss of water through evapotranspiration in the region to be necessary. The results of this research can be used to predict the effects of climate change and the applicable management practices in the region, which are presented in scenarios to the model.
Farshid Ramezani; Abbass Kaviani; Hadi Ramezani Etedali
Abstract
Introduction: AquaCrop model was developed to simulate crop response to water consumption and irrigation management. The model is easy to use, works with limited input, and has acceptable accuracy. In this study, the data of an alfalfa field (as a perennial fodder plant) in the Iranian city of Ardestan ...
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Introduction: AquaCrop model was developed to simulate crop response to water consumption and irrigation management. The model is easy to use, works with limited input, and has acceptable accuracy. In this study, the data of an alfalfa field (as a perennial fodder plant) in the Iranian city of Ardestan was used to calibarate and validate the performance of AquaCrop model to simulate the crop productivity in relation to water supply and irrigation management.
Materials and Methods: The data of Fajr-e Esfahan Company farms of Ardestan County were used for calibration and validation of the AquaCrop model, simulating the alfalfa performance in different harvests and over different years. The farms are 1004 m above sea level and located in 33°2' to 33°30' North and 55°20' to 55°22' East. The farm under investigation included ten plots of alfalfa field, with an area of 280 hectares. The data of two plots were used for calibration and, two others used for validation.
Considering that alfalfa is a perennial plant, the data regarding the first harvest was defined as sowing, and transplanting was used to refer to the next harvests. Considering the physiological changes of plants over a year and during different harvests, the numerical value of different parameters, including primary vegetation, maximum vegetation, the depth of primary root development, the maximum depth of primary root development, crop coefficient, germination date, flowering, vegetation senescence, and physiological maturity, were defined for the model. The CRM, NRMSE, R2, and EF indices were used for verification of the calibration results. The CRM index determines the overestimation or underestimation of the model. The EF index is variable between 1 and 0, where 1 indicates optimal performance of the model. If all estimated and measured values were equal, the value of CRM and NRMSE would be zero, and EF would be one.
Results and Discussion:After calibration, validation was performed to examine the performance of the model. Hence, the actual performance rate for different harvests and the results of simulations were compared. Lower NRMSE value is indicative of high accuracy of the model in estimation of the performance. The value of CRM was mostly positive, showing the underestimation of the model in most of the simulations. The maximum performance happened during the first harvest year. The annual harvest decreased with an average rate of 1.2, compared to former years. The evaporation and transpiration rate was calculated by the model and the results were compared with potential evapotranspiration (FAO Penman-Monteith) and National Document of Irrigation (NET WAT). The reference crop evapotranspiration (ET0) had the highest value, and was calculated through FAO Penman-Monteith equation. The numerical value of potential crop evapotranspiration (ETc), which is the result of multiplication of crop coefficient by reference crop evapotranspiration (ET0), was greater than the results of the model, i.e. the estimated actual evapotranspiration. The discrepancy between them is the result of stress coefficient (ET0×Kc×Ks), which the model takes into account in estimation of actual plant water requirement. Evapotranspiration refers to two factors, namely the water lost by transpiration from plants and by evaporation from the soil. The plant transpiration and green cover are considered to be the generating part; AquaCrop is able to examine and improve transpiration efficiency through managerial statements. The values of transpiration from plants and evaporation from the soil for alfalfa were differentiated from the values estimated by the model. The productivity of evaporation, transpiration, and evapotranspiration were calculated by the model. The difference in the productivity values of the plots during different years was the result of difference in chemical composition, harvest index, and transpiration rate.
Conclusion:The AquaCrop model performed well in simulation of crop performance compared to actual annual, and even monthly, performance, and its results were very close to the actual performance. The model is sensitive to temperature changes, and it is suggested to use the Growing Degree Days (GDD) instead of Calendar Days section. . The Version 5 of AquaCrop model can, in addition to moisture stress, include salinity stress in calculations; this is evident in the variation of actual evaporation and transpiration values estimated by the model. In this study, the annual evaporation and transpiration rate was predicted by the model. The higher rate of evaporation can lead to a 27 to 44 percent decrease in the efficiency of evapotranspiration (Y ET-1), compared to transpiration efficiency (Y T-1).
iman babaeian; Maryam Karimian; Hamed Ashouri; Rahele Modirian; Leili Khazanedari; Sharare Malbusi; Mansure Kuhi; Azade Mohamadian; Ebrahim Fattahi
Abstract
Introduction: Southeast watersheds of Iran including Great Karoon, Karkheh, Jarrahi and Zohreh have the most significant contribution in the water supply of the agriculture, industry, drinking water and hydroelectric power plants over Iran. 25 percent of the country’s electricity is produced from ...
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Introduction: Southeast watersheds of Iran including Great Karoon, Karkheh, Jarrahi and Zohreh have the most significant contribution in the water supply of the agriculture, industry, drinking water and hydroelectric power plants over Iran. 25 percent of the country’s electricity is produced from hydroelectric power plants located in this region. The existence of a monthly relatively high resolution gridded precipitation dataset is of the most important needs of water resources management for such as deciding on the suitable time of dewatering and discharge of dams, calibration of dynamical monthly forecasting models and drought early warning. Even considering all observation stations governed by Meteorological Administration and Ministry of Power, the density of stations is not so enough to use them for calibration of hydro-climate model outputs. To overcome this deficiency, one way to fill the gap is using bias corrected global gridded precipitation dataset such as APHRODITE, CMORPH, PRESIANN and other newly generated data.
Material and Methods: Watershed of Karkheh, great Karoon, Jarrahi and Zohreh are the area of study which covers southwest provinces of Khuzestan, Kermanshah, Ilam, Chaharmohal-Bakhtiari, Kohkiluyeh and Buyerahmad, Isfahan, Hamadan, Fars and Lorestan, which is shown in figure 2. There are 135 observation station in the area of study which governs by Iran Meteorological Organization and Ministry of Power. Area of study covers by 75 grids of 0.5×0.5 degree latitude and longitude. For each grid there is an APHRODITE precipitation data. In the 34% of grids, there is no observation station. The main goal of this study is to attribute a reliable monthly precipitation data to all grids without any observation station. Period of APHRODITE data set is 1987-2007, which is same to observation period. Firstly regional bias of APHRODITE data set has been computed by comparing observed precipitation with APHRODITE one. Then bias corrected APHRODITE precipitation (Composite APHRODITE Observation dataset) has been placed in non-observation grids. Efficiency of composite precipitation data has been determined by statistical parameters of bias, correlation and Nash-Sutcliff indices.
Results and Discussion: In this research the results have been evaluated at monthly and seasonal time scales. In the case of seasonal time scale, we found that the minimum APHRODITE’s bias of 1.2 mm has been occurring in summer, while the maximum bias has been occurring in winter by 40.9mm. It means that the bias is high in the rainy season. Seasonal correlations were statistically acceptable in 0.05 significant levels, showing same seasonal fluctuations in APHRODITE and rain gage data. To provide seasonal composite APHRODITE-Observed precipitation gridded data set, mean seasonal bias of APHRODITE has been removed, while preserving seasonal fluctuation. The highest spatial correlation of 0.8 was detected in autumn, while it was about 0.7 for spring and winter. The minimum seasonal correlation was in summer by 0.5. There were also a good agreement between area averaged observation and APHRODITE data, when considering statistical indices of bias, Nash-Sutcliff and relative percentage errors. Results show the cumulative distribution function of APRODITE data is behind of the observed cumulative distribution function data, meaning that APHRODITE reaches its maximum earlier than observation data. This implies that APHRODITE cannot capture well the extreme monthly precipitation. Monthly correlations are approximately greater than 0.9, but the only exception is September with a correlation coefficient of 0.52. All correlations are significant in 0.05 levels. The highest spatial correlation was occurred in Novembers. Monthly Nash-Sutcliff was 0.96 in monthly time series. The categorical percentage score was 94.1%. These results strongly confirm that APHRODITE precipitation data is a good option for replacement in grid cells without observations. The number of observation stations per cell is varied from 1 to 7. We found that the maximum monthly correlations occur in grid cells of 0.5×0.5 degree latitude and longitude which having at least 3 observation stations. The three-station bias has been applied to APHRODITE data, then bias-removed data has been replaced with grid cells without observations. Spatial patterns of new composite APHRODITE-observation data set has good agreement with observation in the areas having intense observation stations. They also can capture well the spatial precipitation distribution of rainy areas located in the center of basin and low rainfall areas located in the southwest of the region. The results of this research can be used in calibration of dynamical seasonal forecasting outputs, drought early warning and rain-runoff simulation.
Hamid Kardan Moghaddam; Mohammad Ebrahim Banihabib
Abstract
Introduction: Due to the increase in water consumption resulting from climate change and rapid population growth, overexploitation of groundwater resources take place particularly in arid regions. This increased consumption and reduced groundwater quality is a major problem especially in arid areas of ...
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Introduction: Due to the increase in water consumption resulting from climate change and rapid population growth, overexploitation of groundwater resources take place particularly in arid regions. This increased consumption and reduced groundwater quality is a major problem especially in arid areas of concern among water resources managers and planners. The use of modern simulation tools to evaluate the performance of an aquifer could help the managers and planners to decide. In this research, finite difference method was used to simulate the behavior of the quality and quantity of groundwater.
Materials and Methods: Increasing the concentration of salts in the groundwater aquifers intensifies with severe water withdrawing and causes the uplift of salt water in aquifers. This is much more severe in adjacent aquifers of saline aquifers in deserts and coastal areas. Front influx of saltwater into freshwater aquifers causes interference and disturbance in water quality and complex hydro-chemical reactions occurs in the joint border area including the process of cation, groundwater flow, the reduction of sulfate, the reaction of Carbonatic and changes in the dolomitic calcite. Sarayan Aquifer has a negative balance and the annual groundwater table drawdown of 62 cm.
In this study, Total Dissolved Solids (TDS) as a groundwater quality factor was simulated to investigate the effect of the overexploitation on the saline interface of desert aquifer using MT3D module of GMS model for a period of 5 years with time steps of 6 months. One of the most important steps of the simulation of groundwater quality is to use qualitative model to predict the groundwater level which in this study were performed by quantitative models in two steady and unsteady flow states with time steps of 6 months The four basic steps of a proper modeling of the groundwater quality are sensitivity analysis of the input parameters, calibration of the sensitive parameters of the model, validation of the time step and groundwater quality forecast for the future periods. These modeling steps were carried out for steady and unsteady states by GMS software.
Aquifer hydraulic conductivity and the specific yield of aquifers were selected as two critical parameters of quantitative model in steady and unsteady states. The model was calibrated based on these two parameters and then using pest method, the value of these parameters was finalized. In order to evaluate the response of the aquifer to different periods of droughts, the verification of the model was conducted during the ten periods. The results show that observed water level has suitable correlation with simulated water level. In the same period, the simulation of water quality for TDS parameter carried out using the results of the quantitative model. After identification of sensitive parameters in the model, calibration of the model was carried out taking into account the factor of 0.5 for the ratio of horizontal to vertical distribution, vertical diffusion length of 0.2, 1 meter for effective molecular diffusion coefficient, and 20 for longitudinal diffusion.
Results and Discussion: In the total area of the aquifer, the water demand of all sectors are supplied using groundwater resources. This water withdrawal trend exacerbated the decline in groundwater levels and reduced water quality. Also in the southern strip of the aquifer, there is a desert saline groundwater aquifer, which causes the intrusion of salt water to the aquifer and negative effects on its quality. The factors influencing the salinity of groundwater in the Sarayan Aquifer are geological formations, supplying the aquifer from salty formations in the region, evaporation from the shallow part of the aquifer especially in the southern strip that leaves salt and reducing the volume of water, existence of fine soil in the media of groundwater flow. Front influx is from saltwater desert aquifer to the Sarayan Aquifer. Due to the osmotic pressure of the soil layers in the aquifer, the pollutants transferred from the higher concentration to lower concentration and an influx of salt water into the aquifer will occur from outside of the aquifer. Since the direction of groundwater flow is from the north to the south of the aquifer and salt water intrusion is from the south to the north, the velocity of saltwater intrusion dropped so quickly water. However, overexploitation of groundwater and negative aquifer balance caused uplift of the salt water in aquifer.
Conclusion: Review of the result of forecasted TDS concentration in Sarayan Aquifer, shows an increase in TDS concentration. This increase indicates that there is no potential for more water withdrawing in the southern parts of the aquifer by urban and agricultureal sectors. The variaty of TDS changes between 712 mg/lit in the northern strip of the aquifer to 8500 mg/lit in the southern strip shows that due to the increased concentration of TDS, the border area of water users will be changed. The forecasting of the future status of aquifer water quality showed that continuing withdrawing of water intensifies salt water interference from the desert and concentration of TDS will increase during the next 5 years. To manage aquifer quality and quantity, three scenarios of water withdraw reduction were used. The results are shown restoration of the aquifer quality and quantity using these scenarios.
Therefore the result of this research shows that the management of groundwater is necessary to improve the quality of desert aquifers and prevent salt water interference from desert considering recent droughts.
M. Shafiei; B. Ghahraman; B. Saghafian; K. Davary; M. Vazifedust
Abstract
Uncertainty analysis is a useful tool to evaluate soil water simulations in order to get more information about the models output. These information provide more confidence for decision making processes. In this study, SWAP model is applied for soil water balance simulations in two fields which are planted ...
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Uncertainty analysis is a useful tool to evaluate soil water simulations in order to get more information about the models output. These information provide more confidence for decision making processes. In this study, SWAP model is applied for soil water balance simulations in two fields which are planted by wheat and maize in an arid region. First the amount of uncertainty is estimated and compared for soil moisture simulation by using Generalized Likelihood Uncertainty Estimation (GLUE) in the two fields. Then based on the computed parameter uncertainty, the effect of uncertainty in soil moisture simulation is evaluated on soil water balance components. Results indicated that in arid regions with irrigated agricultural fields, prediction of actual evapotranspiration is relatively precise and the coefficient of variation for the two fields are less than 4%. Moreover, the prediction of deep percolation for the two fields are influenced by the uncertain hydraulic conductivity and showed lower precision according to the actual evapotranspiration.
R. Lalehzari; Saeid Boroomand Nasab; Hadi Moazed; A. Haghighi
Abstract
Introduction: Groundwater is the largest resource of water supplement and shortages of surface water supplies in drought conditions that requires an increase in groundwater discharge. Groundwater flow dependson the subsurface properties such as hydraulic gradient (water table gradient or head loss in ...
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Introduction: Groundwater is the largest resource of water supplement and shortages of surface water supplies in drought conditions that requires an increase in groundwater discharge. Groundwater flow dependson the subsurface properties such as hydraulic gradient (water table gradient or head loss in artesian condition) and hydrodynamic coefficients. The flow treatment is analyzed with an accurate estimation of effective parameters in groundwater equation. This function is obtained using the continuous equation. Inlet and outlet flows of a cell are equal to storage amounts in the continuous equation. Analytical solution of this equation is complex, so numerical methods are developed including finite element and finite difference methods. For example, Feflow is a groundwater modeling tool that makesuse of finite element method (Reynolds and Marimuthu, 2007). Modflow as a finite difference three-dimensional model simulated underground flow under steady and unsteady conditions in anisotropic and non-homogeneous porous media. Modflow is designed to simulate aquifer systems in which saturated-flow conditions exist, Darcy’s Law applies, the density of groundwater is constant, and the principal directions of horizontal hydraulic conductivity or transmissivity do not vary within the system. In Modflow, an aquifer system is replaced by a discretized domain consisting of an array of nodes and the associated finite difference blocks. Groundwater modeling and water table prediction by this model have the acceptable results, because many different informations of water resource system are applied. Many people and organizations have contributed to the development of an effective groundwater monitoring system, as well as experimental and modeling studies (Lalehzari et al., 2013). The objective of this paper is investigation of hydraulic and physical conditions. So, a numerical model has to be developed by PMWIN software for Bagh-i Malek aquifer to calculate hydrodynamic coefficients and predict water table in the future.
Materials and Methods: Bagh-i Malek aquifer located in Khuzestan province is mainly recharged by inflow at the boundaries, precipitation, local rivers and return flows from domestic, industrial and agricultural sectors. The discharge from the aquifer is through water extraction from wells, springs, and qanats as well as groundwater outflow and evapotranspiration. In this study, conceptual model of Bagh-i Malek aquifer on the framework of finite difference numerical approach has been used in simulating groundwater flow treatment. Water table data of 8 piezometers was collected for the 10 year duration from 2002 to 2012. The study years are divided into 40 seasonal stress periods with daily time step. Hydraulic conductivity, specific yield and recharge were calibrated in these periods. Verification was made between the simulated and measured hydraulic heads in the next calibration year. To simulate the groundwater table elevation in this study area, the PMWIN model is used. Bagh-i Malek aquifer is considered as a single layered aquifer, and therefore only the horizontal hydraulic conductivity is estimated. Modflow was used to simulate both steady state and transient flow systems. In steady conditions it is assumed that the total of time simulation is a time period and it does not change inlet data in the modeling duration. In unsteady conditions,the duration of study is divided into some stress periods that data is changed in every period.
Results and Discussion: Estimation of hydraulic conductivity is the first step of calibration process at steady state conditions. The correct assignment of hydraulic conductivity has a main effect on other parameters accuracy. Hydraulic conductivity mapping indicated that the maximum values are in the Eastern North (6-7 m/day) of the aquifer. The twice calibrated parameter is specific yield in unsteady conditions. Specific yield mapping indicated that the values vary from 0.03 to 0.08 and are maximum in the Southern regions of the plain similar to hydraulic conductivity. The results confirm that the flow model has the tolerable simulation accuracy by variances of 3.1 and 3.84 in calibration and verification processes, respectively. The sensitivity of the flow model to decreasing the hydraulic conductivity is more than increasing it. 50 percentage declined into the hydraulic conductivity causes the increase of the variance from 3.1 of initial value to 44.
Conclusions: Mapping of calibrated hydraulic conductivity showed that the Eastern North of aquifer has the higher transmissivity and discharge capability in comparison to Southern parts. At last, the result show that the Bagh-i Malek aquifer model is sensitive to recharge, hydraulic conductivity and specific yield, respectively.
Y. Khoshkhoo; parviz irannejad; ali khalili; Hassan Rahimi; A. Liaghat; P. Erik Jansson
Abstract
In this research calibration and uncertainty analysis of COUP model with focus on soil temperature simulation for 3-hours time scale have been performed for Hamedan synoptic station. The Generalized Likelihood Uncertainty Estimation (GLUE) was used for this object. In order to simulate the soil temperature, ...
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In this research calibration and uncertainty analysis of COUP model with focus on soil temperature simulation for 3-hours time scale have been performed for Hamedan synoptic station. The Generalized Likelihood Uncertainty Estimation (GLUE) was used for this object. In order to simulate the soil temperature, 22 parameters were chosen and by using the Monte Carlo stochastic sampling method from the uncertainty space of the parameters, 25000 scenarios were produced and model simulations were implemented. For separate behavioral and non-behavioral simulations, 3 criteria including Nash-Sutcliff, Mean Bias Error, and Root Mean Square Error were considered and acceptable thresholds for each criterion were defined. With applying the acceptable thresholds, 253 behavioral simulations were detected and used for calibration and uncertainty analysis of the model. Based on posterior parameter distributions some parameters were recognized as sensitive parameters. The median of behavioral simulations was considered for model calibration and the uncertainty analysis of the model was performed based on 90% confidence levels of behavioral simulation errors. The results showed that calibration of the model has considerably improved the performance of the model in comparison to default parameter values. In addition, the uncertainty analysis showed that the uncertainty of parameters has been considerably decreased in most cases with application of the GLUE method. Other differences between simulated and observed values were attributed to other sources of model uncertainty.
zahra nameghi
Abstract
Simulation of rainfall-runoff process in the watershed has a significant importance from various points of view, such as better understanding of hydrological issues, water resources management, river engineering, flood control structures and flood storage. Therefore in this study, the river flow and ...
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Simulation of rainfall-runoff process in the watershed has a significant importance from various points of view, such as better understanding of hydrological issues, water resources management, river engineering, flood control structures and flood storage. Therefore in this study, the river flow and surface runoff are simulated using the distributed hydrological model, WetSpa. In the WetSpa model runoff process of the basin is simulated using diffusive wave approximation method based on gradient, flow rate and distributed features along the flow routes. Atrak watershed with about 11639 km2 area is one of the largest watersheds of Iran and average annual precipitation is about 283mm. Meteorological data from 1383 to 1390 consisting of rainfall in 25 stations, temperature and evaporation measurements in 5 stations were used as model input data. To run the model three base maps including DEM, land use and soil type with cell size of 100m were provided. Simulation results show a relatively good agreement between calculated hydrographs and measurements at the basin outlet. The model estimates daily hydrographs, with an accuracy of over 60% and 53% based on Nash-Sutcliff criterion, for calibration and validation periods, respectively. And based on Nash-Sutcliff criterion adapted for the maximum flow rate, the model accuracy was evaluated as 77%. According to model output and hydrological factors with spatial distribution at each time step, the model has the ability to analyze topographic effects, soil texture and land use in hydrological behavior of basin.
V. R. Verdinejad; H. Ebrahimiam; H. Ahmadi
Abstract
A transient drainage simulation model, SWAP, was used to evaluate the performance of subsurface drainage system. SWAP model was calibrated by measured daily data including water table depth, drain discharge rate and soil and water drain salinity collected from Behshahr Ran drainage system for 120 days ...
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A transient drainage simulation model, SWAP, was used to evaluate the performance of subsurface drainage system. SWAP model was calibrated by measured daily data including water table depth, drain discharge rate and soil and water drain salinity collected from Behshahr Ran drainage system for 120 days during 1385. Calibration of SWAP model was done by inverse modeling via linking with WinPEST model. In order to calibrate drainage quantity parameters, two objective functions were defined to minimize difference between measured and simulated values of the water table depth and drain discharge rate, simultaneously. To calibrate drainage quality parameters, another objective function was also defined to minimize difference between measured and simulated values of soil salinity. There were good agreements between measured and simulated values of drain discharge rate and water table depth. The absolute error of estimation was 7 and 4 % for water table depth and drain discharge rate, respectively. Measured cumulative drainage was 7.5 % (5.3 mm) greater than its simulated value. The SWAP model could also simulate soil and drainage water salinity with a reasonable accuracy. The results of this study indicated that the performance of the SWAP model could be considerably improved using inverse modeling.
