جستجوی مقالات مرتبط با کلیدواژه « energy balance » در نشریات گروه « آب و خاک »

This study compared three different snowmelt scenarios using a monthly water balance model in the Taleghan-Alamut Basin in north of Iran. Three scenarios were tested in this study: a temperature-based, a net radiation-based, and an energy balance-based. Remote sensing data were utilized to mitigate the challenges of modeling snowmelt in a basin with limited ground information. The calibration and validation processes were carried out in a two-stage method. First, snow modeling was conducted grid-based throughout the basin, and the model parameters were validated. Using snow cover observed by the MODIS sensor, the model dispcipancy between computed and observed snow accumulation was calculated by comparing the percentage of to the calculated snow storage in each cell of the basin. In the second stage, the other model parameters were calibrated as a lumpt hydrologic model across the basin. Ultimately, the net radiation-based and energy balance-based models showed superior performance compared to the temperature-based model. During the validation period, the Kling-Gupta efficiency metric for the temperature-based snowmelt model was 0.72, while for the net radiation-based and energy balance-based models were 0.78 and 0.86, respectively. Additionally, the correlation coefficient between MODIS snow cover data and snow storage calculated in the three models ranged from 0.62 for the energy balance-based model to 0.72 for the temperature-based model. According to the results, the proposed methodology is suitable for assessing snow budget and the snow hydrology in mountainous areas with limited data availability.

Actual evapotranspiration (ET) is one of the most important and complex components of the water balance. In recent years, various remote sensing techniques and algorithms have been developed which provide a cost‐effective and reliable estimate of actual ET. In this research, the spatial distribution of actual ET at the basin scale was estimated based on SEBS algorithm and world-known information data sources which are rarely used in Iran. The estimated actual ET values were compared to the results of well-known SEBAL algorithm and the SWAT hydrological model. The study shows that the SEBS algorithm has overestimated actual ET in comparison with SEBAL algorithm. The primary cause of differences between two models is in their algorithms for calculating sensible heat. Moreover, SEBS algorithm is highly sensitive to the air temperature. SEBAL is a more complex and reliable method, but it needs reliable ground-based weather data. On the other hand, SEBS does not depend on ground-based data and its results could be acceptable under limited data condition.

The growing world population needs more food, with less water available for agriculture. This pinching situation can only improve if water is managed more effectively leading to increased crop yield per unit of water consumed. Crop yield is the ultimate indicator for describing agricultural response to water resources management. The need to monitor crop growth and assess the relationships between crop yield and hydrological processes is elementary for improving the productivity of water. Crop yield forecasts a few months before harvest can be of paramount importance for timely initiating food trade secure the national demand and timely organize food transport within countries. Managers and policy markers need information about agricultural products yield at different scales for devise suitable management strategies. These strategies include product prices and market in import or export. But always estimating crop yield due to the lack of sufficient ground information and existing problems was very difficult and costly. The most appropriate strategies are using satellite data and remote sensing. This study was conducted to evaluate the sugarcane crop yield using landsat 8 satellite data in 2013.
In this study a composite model was used to estimate the volume of sugarcane crop. This combined model includes Monteith model, Carnegie Institution Stanford model and the surface energy balance algorithm for land (SEBAL). Monteith’s model is used for the calculation of absorbed photosynthetically active radiation (APAR), the Carnegie Institution Stanford model is used for determining the light use efficiency, and the surface energy balance algorithm for land (SEBAL) is used to describe the spatio _ temporal variability in land wetness conditions. The new model requires a crop identification map and some standard meteorological measurements as inputs. In surface energy balance algorithm for land (SEBAL) method, all fluxes of the energy balance at the earth's surface including net radiation, soil heat flux, and sensible heat flux are calculated from satellite images and finally evaporative fraction is computed based on the energy balance at the earth's surface. The accumulation of biomass is according to the Monteith model proportional to accumulated APAR. Yield mapping was conducted with the implementation of this algorithm in 2013 and with the usage of 10 landsat 8 satellite images. The biomass development and crop yield computations have been executed in a GIS environment. The annual cycle has been split up into 10 discrete intervals to comply with the 10 Landsat 8 images. The time step varies, depending on cloudiness, and is 16 days on average. Each image is representative for a discrete time interval. All calculations are repeated for 10 different Intervals in an independent manner. The total biomass development of a crop lifetime is approximated by integrating the biomass growth over the cropping season using the cropping calendar.
The yield obtained from satellite images was compared and eraluated with the actual measured yield product in the to sugarcane field. Average sugarcane crop yield estimated to 56 tons per hectare. The yield estimation by the composite model revealed correlation and good distribution of farms actual yield. Then the effect of age and varieties on the model accuracy rate for sugarcane yield estimating was examined. It was found among the different varieties, calculated yield in the varieties cultivated fields CP57- 614 have correlation with the yield actual volues that is due to prematurity and better match to the last image. It was also observed with the aging of sugarcane cultivation until the fourth raton, yield dropped, the estimated yield decreased, solidarity and distribution becomes less that the sugarcane actual yield and correlation value is reduced to %51

One of the most effective techniques to reduce evaporation rate is to use suspended shade covers to create shadow on the water bodies. Black polyethylene is a material that can be used for covering as porous fabric like sheets. In this study, energy balance analysis was used to evaluate the effects of using this type of covers in dam reservoirs on evaporation rate. Minab dam was selected as case study and energy modeling was conducted with respect to different scenarios. Results show that the use of black porous polyethylene can reduce evaporation by an average of 77% and 83% in the case of using single-layer and double-layer, respectively. This amount of evaporation reduction could be lead to reduce 11, 22 and 33 million cubic meters for 30%, 60% and 90% covering scenarios, respectively, for Minab dam reservoir.

The purpose of this study was to evaluate the accuracy of SEBS remote sensing algorithm to determine the actual evapotranspiration of an alfalfa field located in Isfahan province. An automatic weather station was installed in the alfalfa field to measure and to record the required weather data for the calculation of reference evapotranspiration by the Penman-Monteith equation. Daily and hourly grass reference evapotranspiration (ETr) were calculated by FAO Penman-Monteith equation (FAO56), using the meteorological data measured during the satellite passing time. The FAO 56 crop coefficient was used to obtain alfalfa evapotranspiration from ETr. The actual hourly alfalfa evapotranspiration (ETc-h) from an extensive alfalfa field surface at the time of the passage of the LANDSAT 8 from the study area was computed by SEBS algorithm and at the same time it was measured by a Scintillometer and they were found to be 0.7 and 0.65 (mm/hr), respectively. The actual ET obtained by SEBS usually overestimated values measured by the Scintillometer (LAS). The actual hourly and daily alfalfa evapotranspiration values obtained from SEBS algorithms were compared with the corresponding values measured by the Scintillometer (LAS) and values calculated by the FAO Penman-Monteith equation and R2 of 0.75( p<0.01) ,0.86( p<0.01) and RMSE 0.04 (mm/hr) , 0.43 (mm/day) were obtained , respectively.

Soil surface temperature has a key role in the mass and energy interchange between soil and atmosphere and it is an important input parameter to running the heat, water and carbon balance estimating models in the soil-plant-atmosphere system and weather and climate simulating models as well at the regional and global scales and the whole soil surface energy balance components are affected by soil surface temperature. Instead of the high important and remarkable application of soil surface temperature, its measurements is performed just in the synoptic meteorological stations and in an imperfect manner (just the minimum daily soil surface temperature) and so, it is essential to simulate this important variable by appropriate methods. In this research, two methods including soil surface energy balance model and
satellite images were used to estimating daily mean soil surface temperature in the Sararoud-Kermanshah agro-meteorological station which has the recorded data of both maximum and minimum soil surface temperature at the 2013 to 2014 time period. Estimating daily mean soil surface temperature based on the satellite images was performed by considering the MODIS sensor images at four different times including 22:30, 1:30; 10:30 and 13:30 using the MRT software and to running the soil surface energy balance model, the daily meteorological data including air temperature, wind speed, sunshine and relative humidity along with some soil physical properties were used as the model inputs and the efficiency of these methods was evaluated using some evaluating error indices. By applying the MODIS sensor images, the results showed that from different combination cases of soil surface temperature at the mentioned imaging times, calculating daily mean soil surface temperature based on the averaging of soil surface temperatures at 22:30, 1:30 and 10:30 times was led to gaining the highest agreement with soil surface temperature observations and the absolute error and determination coefficient of this method to estimating daily mean soil surface temperature were 2.1 °C and 0.93, respectively. by applying the soil surface energy balance model to estimating daily mean soil surface temperature, the absolute error and determination coefficient were 1.8°C and 0.96, respectively. The results of the seasonal time series analysis showed that by using the soil surface energy balance model and satellite images, the highest agreement between calculated and observed values was occurred at summer and winter, respectively. The overall results of this research showed reasonable and appropriate accuracy of both applied methods but the soil surface energy balance model is suggested because of its higher accuracy. Therefore, it is possible to adopt the applied methodology of this research to simulate the mean soil surface temperature in different regions and the estimated values of the daily mean soil surface temperature could be used to different applications such as soil temperature and moisture simulating models as an input variable.

The determination of maize water requirement and crop coefficient in Babol agrigultural research station in Mazandaran province using Landsat images and SEBAL algorithm was considered in the current study. Therefore, 11 satellite images of Landsat8 and Landsat7 during maize growth period in 2014 and 2015 were prepared. For using SEBAL, each band data was calibrated according to their corresponding coefficients. Then, net radiation flux on the ground surface and soil heat flux was calculated based on input and output radiation fluxes and computation of albedo, surface emissivity, ground surface temperature, and crop indices such as NDVI, SAVI and LAI. Sensible heat flux is also calculated by computation of friction velocity, aerodynamic resistance to heat transport and consideration of cold and hot pixels and atmospheric stability conditions. Finally, maize water requirement maps during growth period were prepared which had RMSE equals to 0.99, 1.09 and 0.65 mm/day compared to Reference Book, National Water Document and FAO56. Then, by computing reference evapotranspiration, maize crop coefficient in different growth stages was determined. This coefficient was 1.24 for mid stage which had 28, 8 and 3 percent difference with Reference Book, National Water Document and FAO56.

Due to advection phenomenon, energy balance in vegetation covered field's changes and some additional energy is transferred from the barren lands to vegetation covered sites by air sensible heat flux. This phenomenon increases the evapotranspiration. The present study was conducted to investigate the advection occurrence in the field of maize as a spring crop, and winter wheat as a fall crop at the Agriculture Faculty Research Station of Tabriz University. Mentioned crops for were planted in a 1.6 hectares’ farm, equipped with a lysimeter at its middle, for two years. These crop's evapotranspiration was measured by the lysimeter during the growing season of each plant. The advection phenomenon occurrence was investigated using the methods of energy balance in the field surface, Priestly-Taylor coefficient, the ratio of evapotranspiration obtained from advection energy to vegetation surface evapotranspiration (Rad) and Bowen's ratio () on different days after planting of each crop. Observation data of the temperature showed that there was a sensible heat gradient between the lysimeter and surrounding areas. Negative values of the sensible heat flux, Rad and Bowen ratio on some days of plants growing season showed that the advection extra energy had affected the crops evapotranspiration values. Results showed that the advection effect on maize evapotranspiration was more than that on wheat evapotranspiration. In the study region except of regional advection, local advection could be occurred due to small size of cropped fields, different irrigation schedule and depth of adjacent farms, and fallow duration of some farms.

This study was designed to investigate the possibility of using the surface energy balance algorithm for land (SEBAL) and mapping evapotranspiration at high resolution with internalized calibration (METRIC) models to estimate evapotranspiration (ET) in Shahrekord plain (Chaharmahal va Bakhtiari province, Iran). Two sets of Landsat ETM data dated June 30th and August 21st, 1999 were provided to estimate and compare reference evapotranspiration (alfalfa) at regional scale using Landsat ETM data to ET estimations by five mathematical methods (experimental and combined) known as standardized Penman-Monteith by American Society of Civil Engineers (ASCE-stPM), Penman-Monteith (F56PM), Blaney-Cridle (F24BC), Hargreaves-Samani (HS) and evaporation pan (F24P). Results showed that ET at cold anchor pixel for SEBAL were 6.97 and 6.77 millimeters per day and for METRIC were 10.27 and 9.31 millimeters per day, on days when the satellite passed over. Hargreaves-Samani ET values, as the suitable mathematical model for the studied area, were 8.0 and 7.5 millimeters per day, respectively, on two satellite passes. Results showed that, in the first pass all statistical indices for SEBAL were less than the second pass, maybe due to higher air temperature and wind speed. On the other way, statistical indices in METRIC on the alternate pass, however, showed higher values over the corresponding values in SEBAL. ET values on two satellite passes for anchor pixels were 5.65 and 5.93 mm/day in SEBAL, and 5.22 and 6.65 mm/day in METRIC, respectively. ET values on the same days of satellite overpass for Hargreaves – Samani (HS) were 8.0 and 7.5 mm/day. Consequently, based on the results, both RS-ET models were comparable to empirical models such as (HS). Generally, the results showed that SEBAL had higher accuracy than METRIC, presumably due to lack of accurate weather data (hourly data), so SEBAL is recommended in similar conditions. Generally, the results showed that SEBAL had higher accuracy in comparison to HS and lysimeters data than METRIC, so SEBAL is recommended in similar conditions.

Since a significant amount of precipitation in the agricultural watersheds is used by evapotranspiration¡ so this parameter plays an important role in water budget and water resources management. Therefore¡ accurate estimation of this component is very important. SEBAL (Surface Energy Balance Algorithm for Land) belongs to the methods of estimating the actual evapotranspiration (ETact) which is based on remote sensing technique. In the structure of this algorithm several indices and empirical coefficients are used¡ each of them is effective for estimating actual evapotranspiration. In this study the effect of the uncertainty caused by the soil adjusted vegetation index (SAVI) values in the form of SEBAL algorithm was investigated on ETact prediction on the part of Neyshabour watershed. To determine the optimize value of SAVI¡ 2013 and 2014 MODIS satellite images were used and the effect of SAVI values uncertainty on ETact prediction was discussed in 2014. Comparison between estimated values and microlysimeter measurements of ETact in the discussed polygon showed that the minimum and maximum error of ETact estimation has been obtained for the amount of 0.2 (R2=0.99¡ RMSE=0.07) and 1 (R2=0.12¡ RMSE=0.6) for L coefficient in the SAVI index structure. The results of t-test also showed the significant differences at 95% (p

Water when harvested is commonly stored in dams, but approximately up to half of it may be lost due to evaporation leading to a huge waste of our resources. Estimating evaporation from lakes and reservoirs is not a simple task as there are a number of factors that can affect the evaporation rate, notably the climate and physiography of the water body and its surroundings. Several methods are currently used to predict evaporation from meteorological data in open water reservoirs. Based on the accuracy and simplicity of the application, each of these methods has advantages and disadvantages. Although evaporation pan method is well known to have significant uncertainties both in magnitude and timing, it is extensively used in Iran because of its simplicity. Evaporation pan provides a measurement of the combined effect of temperature, humidity, wind speed and solar radiation on the evaporation. However, they may not be adequate for the reservoir operations/development and water accounting strategies for managing drinking water in arid and semi-arid conditions which require accurate evaporation estimates. However, there has not been a consensus on which methods were better to employ due to the lack of important long-term measured data such as temperature profile, radiation and heat fluxes in most lakes and reservoirs in Iran. Consequently, we initiated this research to find the best cost−effective evaporation method with possibly fewer data requirements in our study area, i.e. the Doosti dam reservoir which is located in a semi-arid region of Iran. Our study site was the Doosti dam reservoir located between Iran and Turkmenistan borders, which was constructed by the Ministry of Water and Land Reclamation of the Republic of Turkmenistan and the Khorasan Razavi Regional Water Board of the Islamic Republic of Iran. Meteorological data including maximum and minimum air temperature and evaporation from class A pan were acquired from the Doosti Dam weather station. Relative humidity, wind speed, atmospheric pressure and precipitation were acquired from the Pol−Khatoon weather station. Dew point temperature and sunshine data were collected from the Sarakhs weather station. Lake area was estimated from hypsometric curve in relation to lake level data. Temperature measurements were often performed in 16−day periods or biweekly from September 2011 to September 2012. Temperature profile of the lake (required for lake evaporation estimation) was measured at different points of the reservoir using a portable multi−meter. The eighteen existing methods were compared and ranked based on Bowen ratio energy balance method (BREB). The estimated annual evaporation values by all of the applied methods in this study, ranged from 21 to 113mcm (million cubic meters). BREB annual evaporation obtained value was equal to 69.86mcm and evaporation rate averaged 5.47mm d-1 during the study period. According to the results, there is a relatively large difference between the obtained evaporation values from the adopted methods. The sensitivity analysis of evaporation methods for some input parameters indicated that the Hamon method (Eq. 16) was the most sensitive to the input parameters followed by the Brutsaert−Stricker and BREB, and radiation−temperature methods (Makkink, Jensen−Haise and Stephen−Stewart) had the least sensitivity to input data. Besides, the air temperature, solar radiation (sunshine data), water surface temperature and wind speed data had the most effect on lake evaporation estimations, respectively. Finally, all evaporation estimation methods in this study have been ranked based on RMSD values. On a daily basis, the Jensen−Haise and the Makkink (solar radiation, temperature group), Penman (Combination group) and Hamon (temperature, day length group) methods had a relatively reasonable performance. As the results on a monthly scale, the Jensen−Haise and Makkink produced the most accurate evaporation estimations even by the limited measurements of the input data. This study was carried out with the objective of estimating evaporation from the Doosti dam reservoir, and comparison and evaluation of conventional method to find the most accurate method(s) for limited data conditions. These examinations recognized the Jensen−Haise, Makkink, Hamon (Eq. 17), Penman and deBruin methods as the most consistent methods with the monthly rate of BREB evaporation estimates. The results showed that radiation−temperature methods (Jensen−Haise and Makkink) have appropriate accuracy especially on a monthly basis. Also deBruin, Penman (combination group), Hamon and Papadakis (temperature group) methods produced relatively accurate results. The results revealed that it is necessary to calibrate and adjust some evaporation estimation methods for the Doosti dam reservoir. According to the required input data, sensitivity and accuracy of these methods, it can be concluded that Jensen−Haise and Makkink were the most appropriate methods for estimating the lake evaporation in this region especially when measured data were not available.

There are different methods for evaporation estimation that are applied according to the type of application and the required accuracy. Different remote sensing methods have been in the concern of many researchers recently. It is believed that these methods could provide more accurate results in watershed studies. On the other hand، there is an increasing demand for spatial and temporal evapotranspiration estimation. We used SEBAL and METRIC models to investigate the feasibility of their application for Mashhad watershed and also compared the results obtained from these two models. Surface flux was calculated for each pixel by applying these two models and ASTER images، then actual evapotranspiration was calculated as a residual of the energy balance equation. The results showed that SEBAL algorithm underestimates actual daily evapotranspiration in the order of %8. 398/93 in relation to METRIC model. It was also concluded that both of the models are capable to estimate actual evapotranspiration by considering spatial and topographic conditions and also vegetation cover of the catchment.

An experiment to study the effect of advection on energy balance in process of canola field evapotranspiration was designed and conducted at the Agricultural Research Station of Tabriz University in spring of 2010. For this research canola was planted in a lysimeter located in the middle of a 1.6 hectare experimental field. Evapotranspiration rate, leaf area index and plant height were determined inside the lysimeter. The advection phenomenon was investigated using the energy balance in the field surface, Priestley-Taylor coefficient (α) and the ratio of evapotranspiration obtained from advection energy to vegetation surface evapotranspiration (). Bowen’s ratio (β), and ratio of lysimetric evapotranspiration to received net radiation in the fields on different days after planting in the canola field were also determined. Negative values of sensible heat flux confirmed the advection occurrence from 39 days after planting and values of α and showed that advection affected evapotranspiration process as significantly in this region. The values of reached more than 60 percent in some days of the growing season. This issue clearly proved the influence of advection energy on canola field evapotranspiration. In the study region except regional advection, local advection could occur across large fields due to the existance of small farms, different timings and amounts of irrigation and fallow duration of some farms. Results showed that, when leaf area index and plant height reached to 1 and 15 cm respectively, temperature gradient between the farm and the surrounding area were increased due to increment of LAI and plant height which increased the transpiration in turn. In this stage the resulted negative values of β and H confirmed the occurance of advection phenomenon.

Water productivity Increase is one of the water management solutions in agriculture and increasing its efficiency. The accurate determination of plants water requirement and the accurate value estimate of evapotranspiration is essential for improving water productivity in irrigation network that it can help to improve water management in agriculture. This research was performed to determine the water requirement and crop coefficients of winter Gascogne wheat in station of estimating evaporation within three lysimeter in Ferdowsi university of Mashhad in Aban 1389. In general، the enough growth period of water was available to the plants and the amount of the water potential in soil was always at field capacity. The necessary data for measuring evapotranspiration was obtained the energy balance method at all stages of plant phenology in one-hour intervals from Aban to mid-khordad using energy balance device (DIK-2500). Based on the results، water requirement of wheat in growth period using energy balance and lysimeter methods was estimated respectively 536. 5 and 544. 5mm. Also، the water requirement of the reference plant was obtained 865. 5 mm. The average of the crop coefficients of wheat was estimated 0. 3، 0. 8، 1. 14 and 0. 4 for the four growth stages.

Evapotranspiration is one of the important elements of the hydrologic cycle in agricultural projects. Energy balance (the bowen ratio) is a method for estimating evapotranspiration of plant which is based on measurements of temperature and humidity gradients in two different heights of a plant. An experiment was conducted in agriculture faculty of Ferdowsi university of Mashhad by using three Lysimeter to estimate evapotranspiration of Gascogne wheat and the resulting were compared with direct method. Required data for measuring the amount of evapotranspiration using energy balance method was obtained throughout plant phenology with one hour intervals using energy balance (model 5200 – DIK) estimation device of evapotranspiration was daily calculated. The rate of daily evapotranspiration that obtained by using energy balance method amounted to 2. 4 mm which is in a high correlation (0. 98) with the Laysimeter result that was 2. 4 mm. The range of Bowen ratio changes was between -1. 5 to 1. 9 during the day which the negative values occurs after sunset that is the sensible heat flux begins to decrease. The value of Boven ratio gradually increase so that it''s maximum value between 8 AM to 9 AM، and then followed a decreasing trend until the afternoon.