Showing 14 results for Validation
M. H. Mahdian, N. Ghiasi, S. M. Mousavy Nejad,
Volume 7, Issue 1 (4-2003)
Abstract
Point data of weather stations are not important in and by themselves. Therefore, it is necessary to change these point data into regional information. Undesirable distribution of weather stations and their data deficiency hinder the direct determination of the regional information, unless sufficient data in the study area could be provided. Providing extra data using the geostatistical methods is practical, scientific, simple and quick, but adopting a suitable method is the basic question. The objective of the present study is to find a suitable method to estimate monthly rainfall in the central region of Iran. In this regard, the methods of kriging (ordinary kriging, log-kriging, co-kriging), weighted moving average (WMA, with the power of 1 to 5), thin plate smoothing splines (TPSS, with the power of 2 and 3 and with covariable) were used. Cross validation technique was used to compare these methods.
Based on the variography analysis, the range of influence of monthly rainfall in the central region is about 450 km. The results show that TPSS, with the power of 2 and with elevation as a covariable, was the most accurate method to estimate monthly rainfall. In addition, it is preferable to use the selected interpolation method in the sub-basins with homogeneous climates instead of considering the whole region.
A. Majnooni-Heris, Sh. Zand-Parsa, A. R. Sepaskhah, A. A. Kamgar-Haghighi,
Volume 10, Issue 3 (10-2006)
Abstract
Agricultural investigations use computer models for simulation of crop growth and field water management. By using these models, the effects of plant growth parameters on crop yields are simulated, hence, the experimental costs are reduced. In this paper, the model of MSM (Maize Simulation Model) was calibrated and validated for the prediction of maize forage production at Agricultural College, Shiraz University in 1382 and 1383 by using maize forage yield under furrow irrigation with four irrigation and three nitrogen treatments. Irrigation treatments were I4, I3, I2, and I1, with the depth of water 20% greater than, equal to, 20% and 40% less than potential crop water requirements, respectively. Nitrogen treatments were N3, N2, and N1, with the application of N as urea equal to 300, 150, and 0 kg N ha-1, respectively. After calibration and validation of MSM, it was used to estimate suitable planting dates, forage yield and net requirement of water discharge for planting at different dates. The results indicated that the net requirement of water discharge was reduced by gradual planting at different planting dates. By considering different planting dates for maize, from Ordibehest 20th to Tir 10th, the planting area might be increased 17.9%, compared with single planting date on Ordibehesht 30th under a given farm water discharge and full irrigation.
R Rostamian, S.f Mousavi, M Heidarpour, M Afyuni, K Abaspour,
Volume 12, Issue 46 (1-2009)
Abstract
Soil erosion is an important economical, social and environmental problem requiring intensive watershed management for its control. In recent years, modeling has become a useful approach for assessing the impact of various erosion-reduction approaches. ِDue to limited hydrologic data in mountainous watersheds, watershed modeling is, however, subject to large uncertainties. In this study, SWAT2000 was applied to simulate runoff and sediment discharge in Beheshtabad watershed, a sub-basin of Northern Karun catchment in central Iran, with an area of 3860 km2. Model calibration and uncertainty analysis were performed with SUFI-2. Four indices were used to assess the goodness of calibration, viz., P-factor, d-factor, R2 and Nash-Sutcliffe (NS). Runoff data (1996-2004) of six hydrometery stations were used for calibration and validation of this watershed. The results of monthly calibration p-factor, d-factor, R2 and NS values for runoff at the watershed outlet were 0.61, 0.48, 0.85 and 0.75, respectively, and for the validation, these statistics were 0.53, 0.38, 0.85 and 0.57, respectively. The values for calibration of sediment concentration at the watershed outlet were 0.55, 0.41, 0.55 and 0.52, respectively, and for the validation, these statistics were 0.69, 0.29, 0.60 and 0.27, respectively. In general, SWAT simulated runoff much better than sediment. Weak simulation of runoff at some months of the year might be due to under-prediction of snowmelt in this mountainous watershed, model’s assumptions in frozen and saturated soil layers, and lack of sufficient data. Improper simulation of sediment load could be attributed to weak simulation of runoff, insufficient data and periodicity of sediment data.
R. Mohammadi Motlagh, N. Jalalkamali, A. Jalalkamali,
Volume 18, Issue 67 (6-2014)
Abstract
The main scope of this research is evaluation of Soil Conservation Service Procedure in derivation of initial abstraction of precipitation in watershed scale. For this purpose Dalaki watershed which is located in south east of Iran was selected then by using hec-hms and GIS models and a number of observed rainfall runoff events some parameters like CN of watershed ,K and X of Muskingam method and initial abstraction of precipitation were calibrated through two different search algorithm of univariate and Nelder & Mead methods. The early results of this research indicated the superiority of Univariate search algorithm over the Nelder&Mead method both in calibration and also validation processes. Then using calibrated CN and Initial abstraction parameters which were derived through Univariate search algorithm, the factor between initial abstraction and potential retention of surface runoff (S) in each of sub basins were estimated. 0.13, 0.43 and 0.19 were derived as the above mentioned factor respectively for Minimum, Maximum and mean of the above mentioned factor in this step of the research which showed an acceptable compatibility to the offered factor of 0.2 by SCS. Then in rainfall runoff modeling process of this watershed SCS offers a reliable method of initial abstraction estimation.
S. Dowlatabadi, S. M. A. Zomorodian,
Volume 19, Issue 71 (6-2015)
Abstract
One of the most essential and appropriate groundwater model components is accurate information of the recharge values among input data often introduced to the model as the percentage of rainfall of aquifers. The recharge values are influenced by many temporal and spatial factors. Firoozabad plain is one of the suitable plains for agriculture in the Fars province in which utilization of groundwater resources has been banned since 23 September 2002, due to the declining water level and negative balance. The main purpose of this study was to estimate the recharge values of groundwater aquifer by using SWAT in the MODFLOW model. Firstly, surface water was simulated via SWAT model, and sensitivity analysis, calibration, validation and uncertainty analysis of results were performed by SWAT-CUP software. After extraction of aquifer recharge values from the calibrated model, the groundwater of basin was simulated via MODFLOW model in both steady and unsteady conditions. Following the model calibration, the hydrodynamic coefficients of plain were determined and sensitivity of model was checked in terms of hydraulic conductivity and discharge rate of pumping wells. As for the confidence, the model was revalidated, which proved in simulating the behavior of the aquifer very well.
R. Mirzaei, K. Rahimi, H. Ghorbani, N. Hafezimoghades,
Volume 19, Issue 73 (11-2015)
Abstract
Determining the spatial distribution of different contaminants in soil is essential for the pollution assessment and risk control. Interpolation methods are widely used to estimate the concentrations of the heavy metals in the unstudied sites. In this study, the performances of interpolation methods (inverse distance weighting, local polynomials and ordinary Kriging and radial basis functions) were evaluated to estimate the topsoil contamination with copper and nickel in Golestan Province. 216 surface soil samples were collected from Golestan province, and their Cu and Ni concentrations were measured. Soil contamination was determined using different interpolation methods. Cross validation was applied to compare the methods and estimate their accuracy. The results showed that all the tested interpolation methods have an acceptable prediction accuracy of the mean content for soil heavy metals. RBF-IMQ and IDW1 methods had the lowest RMSE, whereas RBF-TPS method with the largest RMSE estimated a larger size for the polluted area. The greater the weighting power, the larger the polluted area estimated by IDW. Compared with the ‘‘sample ratio over the pollution limits” method, the polluted areas of Cu and Ni were reduced by 8.38% and 6.14%, respectively.
A. Sheikhzeinoddin, A. K. Esmaeili1 , M. Noshadi,
Volume 19, Issue 74 (1-2016)
Abstract
Chemical fertilizers have important role in modern agriculture, and in the other hand led to rigid environmental pollution. Urea fertilizer is one of the most widely used and least expensive nitrogen fertilizers in Iran. Since it is high solubility in water a significant of it, if irrigation or precipitation is heavy, easily washed and led to change to change the quality of groundwater, rivers or seas. Hence, in this study the effects of deficit irrigation and fertilization on pollution using SWAT for Tashk-Bakhtegan basin (land area between Dorudzan dam and Khan Bridge) were simulated. This model by comparing model outputs with actual observations of hydrological, crop yield (wheat, barely, corn and rice) and nitrate by using SUFI2 algorithm in SWAT_CUP software were calibrated and validated. Then the calibrated model used to evaluate different management strategies (e.g. irrigation and fertilizer amount). When the impacts of different levels of urea (0 to 70 percent reduction in urea application) were modeled, yield of these crops reduced between 1 to 27, 0.8 to 24, 0.42 to 21 and 0.47 to 9 percent for wheat, barely, corn and rice, respectively. However, these tends to decline nitrate leaching 16-81, 18-80, 15-85 and 12.5 to 83.6 percent, respectively for these crops. Therefore, by comparing yield and nitrogen loss changes, this result can conclude that a significant reduction in nitrogen loss by minimum cost on yield can achieved by optimize fertilizer application.
Sh. Zand-Parsa, S. Parvizi, A. R. Sepaskhah, M. Mahbod,
Volume 20, Issue 77 (11-2016)
Abstract
In agricultural development many factors such as weather conditions, soil, fertilizer, irrigation timing and amount are involved that are necessary to be considered by the plant growth simulation models. Therefore, in this study, the values of soil water content at different depths of soil profile, dry matter production and grain yield of winter wheat were simulated using AquaCrop and WSM models. The irrigation treatments were rain-fed, 0/5, 0/8, 1 and 1/2 times of full irrigation conducted in Agricultral College of Shiraz University during 2009-2010 and 2010-2011. The models were calibrated using measured data in the first year of experiment and validated by the second year data. The accuracy of soil water simulation was used to refer to the accuracy of simulated evapotranspiration. The accuracy of soil water content at different layers of root depth in the validation period was good for the WSM model (Normalized Root Mean Squer Error, NRMSE= 0/14). But the AquaCrop model showed less accuracy for soil water content (NRMSE=0/26). However, the values of predicted and measured crop evapotranspiration were close together at full irrigation treatment, the accuracy of AquaCop predictions was decreased with inceasing water stress. WSM model has had a good estimation of the dry matter and grain yield simulation with NRMSE of 0/15 and 0/18, respectively. However, they were simulated with less accuracy in the AquaCrop model with NRMSE of 0/19 and 0/39.
A. Honarbakhsh, M. Fathi, M. Rostami,
Volume 23, Issue 4 (12-2019)
Abstract
In general, rivers are one of the best and most accessible water resources at the disposal of mankind. So, given the effect of the force of water and changes on the flow patterns and consequently, on river morphology changes, the analysis of the flow in the river is important and necessary to organize projects, flood control and water supply structures downstream. In this study, by using numerical models CCHE2D hydraulic conditions Dimeh River Bridge between Oregon Bridge Sudjan was investigated. CCHE Model is a mathematical model capable of simulating the flow patterns and sediment transport in rivers and canals laboratory network. The numerical model in 1998, based on the calculations by the National Centre for Water Science and Engineering, University of Mississippi (NCCHE), was developed and has been applied in many research projects related to water engineering. At the outset, the input data required model provides and numerical model was implemented. In the next step, the results of the model were calibrated and validated using field data measurements; eventually, they were extracted and their model results were compared; it was confirmed that CCHE model could still simulate the flow pattern.
H. Mahmoudpour, S. Janatrostami, A. Ashrafzadeh,
Volume 24, Issue 3 (11-2020)
Abstract
Given the fact that the DRASTIC index is ineffective in addressing the saltwater uprising issue in coastal plains, in the present study, three factors including land use, distance to shoreline, and differences between groundwater and sea level were added to the DRASTIC index. The proposed modification to DRASTIC was validated using the measured electrical conductivity (EC) data gathered from groundwater monitoring wells throughout the Talesh Plain. The results showed that the coefficient of correlation between the map of EC over the region and the modified DRASTIC was 0.52, while for the original DRASTIC, the coefficient was 0.45, thereby implying a stronger relationship between EC and the modified DRASTIC in the Talesh Plain. Sensitivity analysis also showed that DRASTIC and the modified DRASTIC were the most sensitive to, respectively, depth to groundwater (D) and land use (Lu). According to the single-parameter sensitivity analysis results, depth to water table and net recharge were the most effective parameters in DRASTIC, whereas the modified DRASTIC was the most sensitive to land use and depth to groundwater. It could be concluded that modifying the DRASTIC index would result in decreasing the area of very high and high vulnerable classes, and the area classified as low and moderate vulnerable could be increased.
M. Abedinzadeh, A. Bakhshandeh, Mr B. Andarziyan, Mr S. Jafari, M Moradi Telavat,
Volume 25, Issue 3 (12-2021)
Abstract
Iran is located in the dry belt of the earth and is predicted to face water stress in the next half-century. Currently, the area of sugarcane cultivation in Khuzestan is over 85,000 hectares and due to the high water needs of sugarcane and drought conditions, optimization of water consumption and irrigation management is necessary to continue production. Therefore, in this study, the values of soil moisture, canopy cover, biomass yield in five treatments and irrigation levels (start of irrigation at 40%, 50%, 60%, 70%, and 80% soil moisture discharge) during 2 planting dates in the crop year 2015-2016 on sugarcane cultivar CP69-1062 in Amirkabir sugarcane cultivation and industry located in the south of Khuzestan was simulated by AquaCrop model. The measured data on the first culture date (D1) and the second culture date (D2) were used to calibrate and validate the model. The results of NRMSE statistics in canopy cover simulation in calibration and validation sets with values of 2.1 to 15.6% and 3.8 to 18.3%, respectively, and in biomass simulation with values of 6.2 to 15.2%, and 9.5 to 12.6%, respectively and coefficient of determination (R2), range 0.98 to 0.99 indicated that the high ability of the AquaCrop model in simulation canopy cover and biomass yield. whereas, the values of NRMSE of soil depth moisture in the calibration and validation sets ranged from 11.6 to 23.8, and 12.2 to 22.7, respectively, with a coefficient of determination (R2), 0.73 to 0.96 (calibration) 0.8 to 0.93 (validation) showed less accuracy of the model in the simulation. The best scenario is related to the third proposal that water consumption, water use efficiency, and yield are 1710 mm, 1.53, and 42.27 tons per hectare, respectively, which shows a reduction in water consumption of 360 mm.
F. Daechini, M. Vafakhah, V. Moosavi, M. Zabihi Silabi,
Volume 26, Issue 2 (9-2022)
Abstract
Surface runoff is one of the most significant components of the water cycle, which increases soil erosion and sediment transportation in rivers and decreases the water quality of rivers. Therefore, accurate prediction of hydrological response of watersheds is one of the important steps in regional planning and management plans. In this regard, the rainfall-runoff modeling helps hydrological researchers, especially in water engineering sciences. The present study was conducted to analyze the rainfall-runoff simulation in the Gorganrood watershed located in northeastern Iran using AWBM, Sacramento, SimHyd, SMAR, and Tank models. Daily rainfall, daily evapotranspiration, and daily runoff of seven hydrometric stations in the period of 1970-2010 and 2011-2015 were used for calibration and validation, respectively. The automated calibration process was performed using genetic evolutionary search algorithms and SCE-UA methods, using Nash Sutcliffe Efficiency (NSE) and root mean of square error (RMSE) evaluation criteria. The results indicated that the SimHyd model with NSE of 0.66, TANK model using Genetic Algorithm and SCE-UA methods with NSE of 0.67 and 0.66, and Sacramento model using genetic algorithm and SCE-UA methods with NSE of 0.52 and 0.55 have the best performance in the validation period.
Miss S. Bandak, A.r. Movhedei Naeani, Ch.b. Komaki, M. Kakooei, J. Verrlest,
Volume 27, Issue 3 (12-2023)
Abstract
Soil organic carbon (SOC) is one of the most important components of soil physical and chemical properties that have an important role in sustainable production in agriculture and preventing soil degradation and erosion. Data mining approaches and spatial modeling besides machine learning techniques to investigate the amount of soil organic carbon using remote sensing data have been widely considered. The objective of the present study was the evaluation of SOC using the remote sensing technique compared with field methods in some areas of the Gonbad Kavous and Neli forests of Azadshar. The soil samples were collected from the soil surface (0-10 cm depth) to estimate the SOC. Data were categorized into two categories: 70% for training and 30% for validation. Three machine learning algorithms including Random forest (RF), support vector machine, extra tree decision, and XGBoost were used to prepare the organic soil carbon map. In the present study, auxiliary variables for predicting SOC included bands related to Lands 8 OLI and sentinel 2 measurement images, topography, and climate. The results showed that the extraction of the components related to the bands along with the calculation of indicators such as normalized vegetation difference, wetness index, and the MrVBF index as auxiliary variables play an important role in more correct estimation of the amount of soil organic matter. Comparison of different estimation regressions showed that the Sentinel 2 random forest model and in Landsat8 with the values of coefficient of determination (R2), root mean square error (RMSE), and mean absolute error (MEA) of 0.64, 0.05, and 0.17, respectively, was the best performance ratio compared to other approaches used in the study to estimate the organic carbon content of surface soil in the study area. In general, the results of this study indicated the ability of remote sensing techniques and learning models in the spatial estimation of soil organic carbon. So, this method can be used as an alternative to laboratory methods in determining soil organic carbon.
A. Mahdavi, S. Soltani Koopaei, R. Modares, M. Samiei,
Volume 27, Issue 4 (12-2023)
Abstract
Land use changes are one of the main factors in the amount of surface runoff changes in watersheds. Therefore, it is necessary to investigate it to reduce the damages (human and financial) caused by floods and to modify watershed management. The watershed of Nahre Azam is located in the north of Shiraz city and a lot of loss of life and money to the residents of Shiraz due to floods has occurred in previous years. The present research was conducted to investigate the relationship between land use change and runoff in the Nahre Azam watershed in Shiraz using the SWAT model in the period of 2004-2020. The model was calibrated using data from 2004 to 2014 and validated for 2015 to 2020. These images were classified into 6 main land uses using the supervised classification method after performing necessary pre-processing, and a land use map was prepared for 2040 using the Markov chain method. Then, the effect of the land use change in 2003 and 2040 on the amount of simulated runoff was evaluated with the recalibrated model. The calibration results of Nahre Azam watershed for the values of statistical parameters in the calibration step for the coefficient of determination, P-Facor and R-Facor are 0.77, 0.72, and 2.43, respectively, and for the validation step we obtained 0.69, 0.65, and 2.3 respectively. The analysis of the land use map showed that the main land use change in the region related to the conversion of pastures to agricultural land and urban land, which caused a decrease in pastures. Also, the results of the model simulation using the land use maps of 2003 and 2040 indicated that the amount of runoff decreased. The results revealed that if all the uncertainties are minimized, the calibrated SWAT model can produce acceptable hydrological simulation results for the user, which is useful for water resource and environmental managers and politicians as well as city managers of Shiraz.
