A. Sam Khaniani; X. Nikraftar
Abstract
Introduction: Water vapor, as one of the most important greenhouse gases in the atmosphere, plays a key role in hydrological cycles, climate change, and the global climate. Many parameters for the expression of water vapor in the atmosphere have been proposed by meteorologists, one of which is Precipitable ...
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Introduction: Water vapor, as one of the most important greenhouse gases in the atmosphere, plays a key role in hydrological cycles, climate change, and the global climate. Many parameters for the expression of water vapor in the atmosphere have been proposed by meteorologists, one of which is Precipitable Water Vapor (PWV). There are many ground-based and space-based methods to measure PWV. Meanwhile, radiosonde is considered as one of the most common and traditional tools for measuring this parameter. However, low temporal resolution, high cost, and lack of uniform coverage across the globe are some of the limitations of this technique. In the last two decades, GPS Meteorology due to unique features such as usability in any weather conditions, long-term stability, continuous observations with very high resolution, low cost, and PWV estimation with an accuracy level of about 2 millimeters has received a lot of attention. Although radiosonde and GPS are precise methods for estimating water vapor in the atmosphere, their observations are limited to the land. While satellite remote sensing methods can provide continuous observations of the distribution of water vapor on a regional and global scale. MODIS is one of the sensors capable of measuring atmospheric water vapor measurements, which is onboard the Terra and Aqua satellites. However, PWV products obtained from remote sensing data should be evaluated with respect to the reliable in situ data before application. The main purpose of this study was to use PWV estimates obtained from ground-based GPS receivers in order to statistically evaluate the accuracy of MODIS water vapor products in IR and Near-IR bands and different times of the day over Iran. Materials and Methods: The MODIS sensor, which is on board of the Terra and Aqua satellites, is able to provide water vapor products in the IR (both night and day) and Near-IR (day-only) bands. In order to evaluate MODIS PWV products over Iran, one year data of high temporal resolution GPS PWV values in 38 different stations in the country were considered as reliable values. For statistical analysis, water vapor values were extracted from the pixels with cloud-free conditions. Also, among the cloud-free pixels, that with the closest distance to the GPS station was selected. Moreover, the corresponding PWV values of GPS and MODIS with a maximum time difference of 10 minutes were selected for comparison. Results and Discussion: Initially, Near-IR PWV products were assessed separately for Terra and Aqua satellite data. The results showed a good agreement between the two sets of PWV measurements. The correlation values between the GPS PWV and the corresponding values of the MODIS Near-IR products varied in the range of 0.90 to 0.98. Average bias values indicated that MODIS Near-IR overestimated PWV in comparison with GPS over Iran. In addition, a comparison of Near-IR water vapor values extracted from Terra and Aqua datasets separately showed that the data quality of both satellites in this band is almost at the same level in terms of the correlation coefficient, average bias, and RMSE. In the next step, the MODIS IR PWV products were evaluated separately during the day and night with respect to the corresponding values obtained at the GPS stations. The maximum correlation between GPS and IR PWV products during the day and night was 0.7 and 0.64, respectively. Furthermore, the average bias of MODIS IR PWV data in the study area for day and night was found to be -0.38 and 3.11 mm, respectively. In other words, MODIS IR PWV products in the study area had, on average, a positive bias with a small amount during the day and a significant negative bias during the night. On the other hand, a comparison of daytime MODIS IR and Near-IR water vapor products revealed that the quality of IR PWV data was significantly lower than the Near-IR band and requires a suitable calibration method. Conclusion: The results of this study indicate that the MODIS Near-IR water vapor products had a high agreement with GPS PWV values with an average correlation coefficient of 0.95 in the study region. The mean bias and RMSE error of (GPS-MODIS Near-IR) PWV differences were -2.2 and 3.3 mm, respectively. A similar analysis of MODIS Near-IR PWV data from the Terra and Aqua satellites showed that almost both sets of water vapor data had the same accuracy. The average bias values of the MODIS IR PWV data compared to the GPS PWV for day and night were also investigated. Results showed that in the study area, MODIS IR products had a small positive bias during the day and significant negative bias at night. Examining the efficiency of the daytime MODIS water vapor products during the day, we found that the accuracy and precision of these data in the Near-IR band are much better than the IR band. Therefore, proper calibration should be made before employing the IR band.
M. Fashaee; Seied Hosein Sanaei-Nejad; K. Davary
Abstract
Introduction: Numerous studies have been undertaken based on satellite imagery in order to estimate soil moisture using vegetation indices such as NDVI. Previous studies suffer from a restriction; these indices are not able to estimate where the vegetative coverage is low or where no vegetation exists. ...
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Introduction: Numerous studies have been undertaken based on satellite imagery in order to estimate soil moisture using vegetation indices such as NDVI. Previous studies suffer from a restriction; these indices are not able to estimate where the vegetative coverage is low or where no vegetation exists. Hence, it is essential to develop a model which can overcome this restriction. Focus of this research is on estimation of soil moisture for low or scattered vegetative land covers. Trapezoidal temperature-vegetation (Ts~VI) model is able to consider the status of soil moisture and vegetation condition. It can estimate plant water deficit for weak or no vegetation land cover.
Materials and Methods: Moran proposed Water Deficit Index (WDI) for evaluating field evapotranspiration rates and relative field water deficit for both full-cover and partially vegetated sites. The theoretical basis of this method is based on the energy balance equation. Penman-Monteith equation of energy balance was used to calculate the coordinates of the four vertices of the temperature-vegetation trapezoid also for four different extreme combinations of temperature and vegetation. For the (Ts−Ta)~Vc trapezoid, four vertices correspond to 1) well-watered full-cover vegetation, 2) water-stressed full-cover vegetation, 3) saturated bare soil, and 4) dry bare soil. WDI is equal to 0 for well-watered conditions and equals to 1 for maximum stress conditions. As suggested by Moran et al. to draw a trapezoidal shape, some field measurements are required such as wind speed at the height of 2 meters, air pressure, mean daily temperature, vapor pressure-temperature curve slope, Psychrometrics constant, vapor pressure at mean temperature, vapor pressure deficit, external radiation, solar radiation of short wavelength, longwave radiation, net radiation, soil heat flux and air aerodynamic resistance is included. Crop vegetation and canopy resistance should be measured or estimated. The study area is selected in the Mashhad plain in Khorasan Razavi province of I.R. Iran. Study area is about 1,200 square kilometers and is located around the Golmakan center of agricultural research. In this study, water deficit index (WDI) was zoning by MODIS images in subset of Mashhad plain during water year of 2011-2012. Then, based on the close relationship between WDI and soil moisture parameter, a linear relationship between these two parameters were fitted. Soil moisture is measured by the TDR and every 7 days at 5 depths of 5, 10, 20, 30 and 50 cm from the surface. Remote Sensing (RS) technology used as a tool for providing some of the data that is required. The moderate resolution imaging spectroradiometer (MODIS) instrument is popular for monitoring soil moisture because of its high spectral (36 bands) resolution, moderate spatial (250–1000 m) resolution and various products for land surface properties. MODIS products used in the present study include: MOD09A1 land surface albedo data, MOD11A1 land surface temperature data, and MOD13A1 vegetation data. Using ArcMap 9.2 and ERDAS IMAGINE 2010 softwares, WDI was calculated pixel by pixel for 18 days (non-cloudy days and simultaneous with measurement of soil moisture at the station).
Results and Discussion: The results showed that the northeastern region is predominantly rainfed and irrigated farmlands are under water stress. Conversely, the southwestern part of the area is mountainous with less water stress. Based on NDVI, there is also less crop cover in the southwestern part of the region during the year. The results showed that about 44% of the index values are in the range of 0.2-0.3. Then about 22% of the index values are in the range of 0.3-0.4. Thus it can be concluded that over 66% of the index values are in the range of 0.2-0.4. According to the maximum index value (WDI=0.59 on the 201th day of year) and the minimum values (WDI=0.0004 on the 129th day of year) during the time period of study, it seems that water stress in the study area in the six-month period of observation is moderate. To validate the results, changes in precipitation, relative humidity and WDI values were compared. As expected, after the occurrence of any significant rainfall, water stress is decreased and decreasing in relative humidity, coincided with increase in water stress. In the next step, the linear relationship between measured values of soil moisture and WDI values were fitted in 2 depth of 5 and 10 cm. It should be noted that the average values of WDI of four pixels surrounding the Golmakan station was used in calculation of the regression coefficients Similar research has shown that Ts~VI trapezoid based WDI can accurately capture temporal variation in surface soil moisture, but the capability of detecting spatial variation is poor for such a semi-arid region like Mashhad. The high correlation coefficient (93%) obtained from soil moisture (5 cm) and WDI regression showed the good mutual impacts of these two parameters on each other. The correlation coefficient between WDI index and soil moisture at a depth of 10 cm was equal to 83%. Reducing the value of the correlation coefficient was probably due to the delay in transferring the soil moisture changes to underlying depth.
Conclusion: The similarity of the mean values of rainfall and relative humidity of the air showed good compliance with the WDI. Good correlation coefficient (93%) between WDI and soil moisture (measured at depth of 5cm in the station) certifies the accuracy of the results obtained from WDI. The results showed that Ts~VI trapezoid based WDI can well capture temporal variation in surface soil moisture, while in this study, spatial zoning was avoided because of the lack of soil moisture data within the study area.
S. Noori; S.H. Sanaei Nejad
Abstract
Because most of the methods that have been proposed for estimating statues drought generate point estimate, so researchers were always looking for ways to achieve regional estimates for better manage this gradually creeping phenomenon. Recently, remote sensing and techniques proposed base on it could ...
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Because most of the methods that have been proposed for estimating statues drought generate point estimate, so researchers were always looking for ways to achieve regional estimates for better manage this gradually creeping phenomenon. Recently, remote sensing and techniques proposed base on it could estimate drought in regional scale well. In this paper, it’s tried to estimate drought and evaluation performance of the Temperature Vegetation Dryness Index (TVDI) and the Modified Temperature Vegetation Dryness Index (MTVDI) using the vegetation and temperature MODIS products in Northern Khorasan during two years 2004 and 2008 (as normal and dry years respectively). The results showed that MTVDI index has performed better than TVDI index. The result of linear correlation analyzed between indices and the cumulative precipitation of the currently 16 days, early 16 days and early 1 month, 2 month, 3 month, 5 month and 7 month showed the indices, specially MTVDI, had a close relationship with early 1 month precipitation than the others. This is due to the delayed response of vegetation to precipitation.
M.R. Tabatabaei; K. Shahedi; karim solymani
Abstract
The estimation of suspended sediment load is very important for water resources quantity and quality studies. The suspended sediment load is generally calculated by direct measurement of suspended sediment concentration (SSC) of a river or by using sediment rating curve (SRC) method. Direct measurement ...
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The estimation of suspended sediment load is very important for water resources quantity and quality studies. The suspended sediment load is generally calculated by direct measurement of suspended sediment concentration (SSC) of a river or by using sediment rating curve (SRC) method. Direct measurement of the SSC is the most reliable but it is very expensive and time consuming. Also, the efficiency of the SRC method is low because it can substantially underpredict the high and overpredict the low loads. In this research, in order to consider the possibility of estimating the fluvial SSC, using reflectance of satellite images, the correlation between red and infrared bands of MODIS sensor and SSC of Karoun river at Molasani station for a period of 9 years (2003-2011) was considered. In this relation, two models (statistical simple linear regression and feed forward back propagation ANN) were used. The evaluation of models results showed that the efficiency of ANN model with having R2 =0.89 and RMSE=122mg/l was better than the regression relation with R2 =0.49 and RMSE=204mg/l. The research results showed that MODIS sensor images and ANN can be used together to estimate fluvial daily SSC in large rivers.
