mostafa yaghoobzadeh; Saeid Boroomand Nasab; Zahra Izadpanah; Hesam Seyyed Kaboli
Abstract
Introduction: Accurate estimation of evapotranspiration plays an important role in quantification of water balance at awatershed, plain and regional scale. Moreover, it is important in terms ofmanaging water resources such as water allocation, irrigation management, and evaluating the effects of changing ...
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Introduction: Accurate estimation of evapotranspiration plays an important role in quantification of water balance at awatershed, plain and regional scale. Moreover, it is important in terms ofmanaging water resources such as water allocation, irrigation management, and evaluating the effects of changing land use on water yields. Different methods are available for ET estimation including Bowen ratio energy balance systems, eddy correlation systems, weighing lysimeters.Water balance techniques offer powerful alternatives for measuring ET and other surface energy fluxes. In spite of the elegance, high accuracy and theoretical attractions of these techniques for measuring ET, their practical use over large areas might be limited. They can be very expensive for practical applications at regional scales under heterogeneous terrains composed of different agro-ecosystems. To overcome aforementioned limitations by use of satellite measurements are appropriate approach. The feasibility of using remotely sensed crop parameters in combination of agro-hydrological models has been investigated in recent studies. The aim of the present study was to determine evapotranspiration by two methods, remote sensing and soil, water, atmosphere, and plant (SWAP) model for wheat fields located in Neishabour plain. The output of SWAP has been validated by means of soil water content measurements. Furthermore, the actual evapotranspiration estimated by SWAP has been considered as the “reference” in the comparison between SEBAL energy balance models.
Materials and Methods: Surface Energy Balance Algorithm for Land (SEBAL) was used to estimate actual ET fluxes from Modis satellite images. SEBAL is a one-layer energy balance model that estimates latent heat flux and other energy balance components without information on soil, crop, and management practices. The near surface energy balance equation can be approximated as: Rn = G + H + λET
Where Rn: net radiation (Wm2); G: soil heat flux (Wm2); H: sensible heat flux (Wm2); and λET: latent heat flux (Wm2). Simulations were carried out by SWAP model for two different sites in Faroub and Soleimani fields. The SWAP is a physically based one-dimensional model which simulates vertical transport of water flow, solute transport, heat flow and crop growth at the field scale level. The period of simulation covered the whole wheat growing season (from 1st of December2008 to 30th of July2009. 16 MODIS images was used to determine evapotranspiration during wheat growing season. Inverse modeling of evapotranspiration (ET) fluxes was followed to calibrate the soil hydraulic. While SWAP model has the advantage of producing the right amount of irrigation and evapotranspiration at high temporal resolution, SEBAL can estimate crop variables like leaf area index, NDVI index, net radiation, Soil heat flux, Sensible heat flux and evapotranspiration athigh spatial resolution.
Results and Discussion: Actual and potential evapotranspiration were estimated for SWAP Model during the whole wheat growing season around669.5 and 1259.6 mm for Farub field and 583.7 and 1331.2 mm for Soleimani field, respectively. In contrast with NDVI and net radiation,spatial distribution of SEBAL parameters indicated that soil heat flux, sensible heat flux, and surface temperature of land have the same behavior. At the planting date, evapotranspiration was low and about 1 mm/day, but at the peak of plant growth, it was about 9 mm/day. Moreover, evapotranspiration declined at late growing season to about 3 mm/ day. SWAP model has been calibrated and validated with meteorological data and the data of field measurements of soil moisture. The amount of RMSE of 0.635 and 0.674 (mm/day) and MAE of 0.15 and 0.53 (mm/day) and also coefficient of determination (R2) of 0.915 and 0.964 obtained from comparison of SEBAL algorithm with SWAP model for Farub and Soleimani fields showed that no significant differences was seen between results of two models.
Conclusion: The present study supports the use of SEBAL as the most promising algorithm that requires minimum input data of ground based variables. Results of comparison of SEBAL and SWAP model showed that SEBAL can be a viable tool for generating evapotranspiration maps to assess and quantify spatiotemporal distribution of ET at large scales. Also, it feels that SEBAL and SWAP models can be applied in a wide variety of irrigation conditions without the need for extensive field surveys. This helps significantly in identifying performance indicators and water accounting procedures in irrigated agriculture, and to obtain their likely ranges.
H. Ahmadzadeh; saeed morid; M. Delavar
Abstract
Streamflows, actual evapotranspiration and crops’ yield are the main variables to estimate agricultural water productivity. Thus, simulation of these variables is of great importance in evaluation of different measures to increase water productivity. For this, application of conceptual models is a ...
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Streamflows, actual evapotranspiration and crops’ yield are the main variables to estimate agricultural water productivity. Thus, simulation of these variables is of great importance in evaluation of different measures to increase water productivity. For this, application of conceptual models is a relevant approach and SWAT (soil and water assessment tool) is one of the well known models in this regard. The present paper aims to assess SWAT in simultaneous simulation of streamflows, actual evapotranspiration and the main crops’ yield of the Zarineh Rud basin. The reason for selection of this basin as the study area relates to its role to meet the Urmia Lake’s water requirement. The lake faces with serious water shortage in recent years and escalating water inflow depend to increase water productivity in the upper catchments. To setup SWAT, the basin was divided to 11 subbasins and 908 hydrological response units, which enables us to introduce more accurately the basin’s cropping pattern and water resources, which meet the requirements of the agricultural area. For simulation of the river flows, data from 6 gauging stations were used for calibration and validation of the model for periods of 1987 to 1999 and 2000 to 2006 respectively that resulted R2 and RMSE between 0.49 to 0.71 and 3.9 to 44.9 (m3/sec) for calibration period, and values of 0.54 to 0.77 and 2.07 to 55.7(m3/sec) for validation period respectively. There is no observed data for actual evapotranspiration in the basin. So, it was verified in the wet years by maximum evapotranspiration reported in National Water Document that results presented the values of 0.97 and 52.5(mm/year) for R2and RMSE respectively. Finally, the estimated yields of the 7 staple crops by the model were compared with the recorded data that showed very close values(R2=0.9 and RMSE=1.65(ton/ha)).
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.
