mozhdeh Jamei; mohammad mousavi; Amin Alizadeh; parviz irannejad
Abstract
Introduction: Surface soil moisture is one of the most important variables in the hydrological cycle, and plays a key role in scientific and practical applications such as hydrological modelling, weather forecasting, climate change studies and water resources managements. Microwave radiometry at low ...
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Introduction: Surface soil moisture is one of the most important variables in the hydrological cycle, and plays a key role in scientific and practical applications such as hydrological modelling, weather forecasting, climate change studies and water resources managements. Microwave radiometry at low frequencies (1.4GHz) is an established technique for estimating global surface soil moisture with a suitable accuracy. In recent years, soil moisture measurements have become increasingly available from satellite-based microwave sensors. The ESA’s Soil Moisture and Ocean Salinity (SMOS) satellite was launched in November 2009. It carries the first L-band 2-D synthetic aperture microwave radiometer to provide global estimates of soil moisture with an averaged ground resolution of 43 km over the field of view. The main objective of this research was to validateSMOS soil moisture retrievals over the west and south west of Iran.
Materials and Methods:The study area is located in the west and southwest of Iran which contains five areas belongingto the Ministry of Power. For the validation of SMOS dataover the study area, the SMOS soil moisture retrievals from MIR_SMUDP2 productswere compared with ground-based insitu measurements. The validation process was carried out using Collocation techniquefor the period 2012-2013. Collocation technique is a method used in the field of remote sensing to verify compliance measurements from two or more different instruments. In this study, the collocation codes were developed in Matlab Linux programming language. The ground-based in situ measurements included direct soil moisture measurements at the 5cm depth which were collected from five meteorological stations in the study area. We prepared a file for each station which contained daily soil moisture, date and time, geographical coordinates of metrological stations as input for validation model. The SMOS Level 2 Soil Moisture User Data Product (MIR_SMUDP2 files) version 551, which were provided through the ESA, contains the retrieved soil moisture and simulated TB, dielectric constants, etc. In this work, the ESA’s SMOS Matlab tool on RedHat Linux was used to read and derivesoil moisture data from MIR_SMUDP2 files.Four statistical metrics and Taylor diagram were used for the evaluation error of validation; the Root Mean Squared Difference (RMSD), the centered Root Mean Square Difference (cRMSD), the Mean Bias Error or bias and the correlation coefficient (R).
The Taylor diagrams wereused to represent three different statistical metrics (R, centered Root Mean Square Difference (cRMSD) and standard deviation) on two dimensional plots to graphically describe how closely SMOS dataset matched ground-based observations .
Results and Discussion: Based on the research algorithm and using MATLAB, the Validation model for SMOS soil moisture data was obtained. This model was appliedfor five metrological stations and the collocated soil moisture data from SMOS data and in situ data was saved as output of model to error evaluation. The results of validation errorshoweda good correlation between the SMOS soil moisture andin situ measurements. The highestand lowest correlation coefficientswere shown at Ahvaz (R=0.88) and Sarableh(R=0.75)stations, respectively.According to the bias values, the SMOS soil moisture retrievals had underestimation atAhvaz(MBE=0.04 m3m−3),Sararod(MBE=0.011 m3m−3), Sarableh(MBE=0.048 m3m−3) stations, whereas a slight overestimation of the SMOS product was detectedatthe Darab (MBE=-0.01 m3m−3) andEkbatan (MBE=-0.031 m3m−3) stations. In addition, the Root Mean Squared Difference (RMSD) values between the SMOS data and in situ data varied from 0.02 to 0.062 m3m−3 and at Ahvaz station withRMSD=0.048 m3m−3is close to the targeted SMOS accuracy of 0.04 m3m−3.Based on the Taylor diagrams, SMOS data had the highest correlation (R=0.88) with in situ measurements at Ahwaz stationand the lowest difference (cRMSD=0.008 m3m−3) between two data setswas found at Darab station.
Conclusions:The objective of this paper was to validateESA’s SMOS (Soil Moisture and Ocean Salinity) satellite products in the west and southwest of Iran for the period of 2012-2013. The validation of SMOS soil moisture retrievals from MIR_SMUDP2 products was done by using soil moisture measurements from five meteorological stations. The SMOS soil moisture retrievals showed underestimations at Ahvaz, Sararod andSarableh stations, whereas a slight overestimation werefound at Darab, Ekbatan stations. The validation results and Taylor diagrams showed thatthe SMOS soil moisture retrievals with R=0.88, RMSD=0.048 m3m−3, cRMSD=0.021 m3m−3at Ahvaz stationwasvery close to the targeted SMOS accuracy objectiveof 0.04 m3m−3 and then at Darab station SMOS data with R=0.82, RMSD=0.028 m3m−3,cRMSD=0.008 m3m−3indicateda good agreement with ground soil moisture measurements. Overall, the SMOS soil moisture data hadan acceptableaccuracy and agreement with in situ data at all stations. Therefore, we can use these data sets as a tool to derive soil moisture maps at study areas.
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.
Z. Aghashariatmadary; M.A. Khalili; P. Irannejad; A.M. Liaghat
Abstract
Abstract
Angstrom-Prescott equation is one of the most commonly used methods for the estimation of global solar radiation (Rs) based on sunshine hours. The critical step in the application of this method's is the calibration of its coefficients for each region. Although the coefficients of the equation ...
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Abstract
Angstrom-Prescott equation is one of the most commonly used methods for the estimation of global solar radiation (Rs) based on sunshine hours. The critical step in the application of this method's is the calibration of its coefficients for each region. Although the coefficients of the equation have been calibrated in different parts of the World, the effect of different time scales has not been considered clearly. In this article, variations of the coefficients of A-P equation in different time scales and their effects on the estimation of global solar radiation are studied. For this purpose data for the 15-year period of 1992-2006 from the Tehran-North (Aghdasieh) station in daily and monthly time scales are used. The values of the coefficients derived from the daily and monthly data were clearly different, and the equation based on monthly data has higher coefficient of determination (R2=0.92) compared to that based on the daily data (R2=0.48). We also found that the daily total solar radiation incident at the surface can be estimated well by using the A-P equation derived based on monthly data.
Keywords: Calibration of Angstrom-Prescott equation, Global solar radiation estimation, North of Tehran station, Time scales
L. Parviz; M. Kholghy; P. Irannejad; Sh. Araghinejad; Kh. Valizadeh
Abstract
Abstract
Land surface hydrological models has importance in the determination of soil moisture and temperature, the rate of evapotranspiration, stream flow by emphasis on the land surface physical and dynamic process descriptions. In this research, VIC land surface hydrological model has been used for ...
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Abstract
Land surface hydrological models has importance in the determination of soil moisture and temperature, the rate of evapotranspiration, stream flow by emphasis on the land surface physical and dynamic process descriptions. In this research, VIC land surface hydrological model has been used for the land surface temperature and stream flow determination. The VIC runoff simulation in each cell is based on both the infiltration excess and saturation runoff. Also for within-grid and between-grids routing, VIC model was coupled to the routing model. For running VIC model, Sefidroad River basin based on DEM of basin was divided in to 18 cells with 57 km resolution. The comparison of observed and simulated stream flow in the outlet of basin hydrometery station, indicated that Nash coefficient increased by using the inverse distance method that is corrected to the height for using interpolation of meteorological variables in each cell. The land surface temperature estimation in the energy mode of VIC model has accurate results than the water mode. The VIC model in the runoff simulation is more sensitive to the infiltration shape parameter. The infiltration shape parameter is effective in the surface and subsurface runoff simulation but the high influence of this parameter is related to the surface runoff. Ws and Ds play an important role in the subsurface runoff simulation. Comparison between observed and simulated stream flow using calibrated parameters in some of hydrometery stations indicated the ability of model in stream flow simulation.
Keywords: Land surface hydrological model, VIC model, Sefidroad River basin, Infiltration shape parameter
