نوع مقاله : مقاله پژوهشی
نویسندگان
چکیده
در سال‌های اخیر به دلیل افزایش مصرف آب، به میزان مصرف آب در بخش‌های مختلف توجه شده است. در بخش کشاورزی حوضة زاینده‌رود، برنج به عنوان یکی از محصولات پر مصرف مطرح می‌شود. در پژوهش حاضر تبخیر- تعرق برنج در منطقة لنجان استان اصفهان برای بررسی انتخاب و الگوریتم توازن انرژی سطحی (SEBAL) برای تعیین تبخیر و تعرق در ماه‌های خرداد تا شهریور (فصل کشت) سال 1396 روی هشت تصویر ماهوارة لندست 8 اجرا شد. همچنین روش‌های تجربی و ترکیبی برآورد تبخیر- تعرق شامل فائو- پنمن- مانتیث، کیمبرلی- پنمن، هارگریوز- سامانی، بلانی- کریدل، پنمن- مانتیث و برنامة netwat بررسی و ارزیابی شدند. بر همین اساس، مدل SEBAL در محدودة کشت برنج لنجان، بیشترین و کمترین میزان تبخیر- تعرق روزانه را در تصاویر تاریخ‌های 3 مرداد و 4 شهریور سال 1396 معادل 7.95 و 5.88 میلی‌متر بر روز برآورد کرد. همچنین از میان روش‌های تجربی یاد شده برنامة netwat کمترین برآورد و داده‌هایSEBAL با شاخص‌های RMSE، MAE و به ترتیب 0.58، 0.35 و 0.75، همبستگی بیشتری با روش هارگریوز- سامانی را داشته است.
کلیدواژه‌ها
عنوان مقاله [English]
Estimation of evapotranspiration through SEBAL model and some of empirical and calculating methods for irrigated rice fields
نویسندگان [English]
- sayyed omid mirmohammadsadeghi
- mahdi ghobadinia
- mohammad hassan rahimian
چکیده [English]
Increasing population growth leads to more food production, which requires more activities in the agricultural and industrial sectors. Therefore, regarding to lack of available water, development of effective strategies for water resources management is necessary. One of the strategies that have been considered in water resources management in recent years, especially in the agricultural sector, is increasing the accuracy of the measurement or estimation of evapotranspiration. Monitor and evaluation of changes in certain periods of time is important in determining the amount of the water consumed by plant and planning irrigation, and thus determining the irrigation systems capacity. But since direct and indirect methods of calculating this parameter have limitations, remote sensing methods for calculating evapotranspiration have been taken into consideration, recently. Also, remote sensing data combined with some meteorological data providing a tool to estimate regional ET, has given advances in remote sensing technology. One of the models based on remote sensing data is the Surface Energy Balance Algorithm for Land (SEBAL), in which these parameters have significance in estimating regional ET: land surface temperature, albedo, emissivity, and normalized difference vegetation index (NDVI).
In the present study, Lenjan region in Isfahan province, Iran, which was under rice cultivation, was selected. The model of Surface Energy Balance Algorithm for Land (SEBAL) was implemented on 8 satellite images of Landsat 8, from June to September 2017 (growing season). For this purpose, the main components of the energy balance equation (including net radiation flux, soil heat flux and sensible heat flux to the air) were calculated for each image. Also, the instantaneous evapotranspiration flux for each pixel was estimated according to the residual energy balance equation. The Net Radiation is the electromagnetic balance of all incoming and outgoing fluxes reaching and leaving a flat surface. Soil heat flux was empirically calculated using vegetation indices, surface temperature, and surface albedo. Sensible heat flux was computed applying wind speed observations, estimated surface roughness, and surface to air temperature differences. Besides, empirical methods of evapotranspiration were also evaluated in the study area, including: Blaney- Criddle, Hargraves- Samani, FAO- Pennman- Monteith and Kimberly- Pennman. Calculating ET regarding to these methods, weather data was collected from Zarrin-shahr weather station and Zefreh evaporation station. Cropwat software was applied for calculating ET by FAO-Pennman-Monteith method. To compare and evaluate the efficiency of SEBAL model with the others methods, three indices have been used included: root mean square error, mean absolute error and coefficient of determination. According to the results of this research, the SEBAL model in the studied area has the maximum and minimum daily evapotranspiration in the images of June 25 and September 11, equal to 7.95 and 5.88 mm/day, respectively. Among the various parameters affecting the SEBAL algorithm, the net radiation flux parameter had the most effect on the results of this algorithm, comparing with the other parameters such as vegetation indices, surface albedo, and incoming and outgoing of radiation. Among the different empirical methods, FAO-Pennman-Monteith, calculated with Cropwat, estimated ET more than other methods because this method considers the water depth in soil surface. Hargraves- Samani and Blaney- Criddle were in the further ranks after FAO-Pennman-Monteith. At last, NETWAT had the lowest estimation, in comparison with the other methods. Also, Hargraves- Samani and Blaney- Ciddle had the less percent error, due to its suitable correlation with SEBAL results. SEBAL algorithm has been able to estimate the temporal and spatial variation of evapotranspiration in the studied area with an acceptable accuracy. Alternatively, this algorithm can be used to replace time-consuming and costly methods of calculating evapotranspiration at different surfaces.
Regarding to outcome of this study, the volume of rice's evapotranspiration in cultivating season were estimated as in the range of 6100 – 8600 cubic meter per hectare, by different methods. Some other researchers calculated the water demand of rice as 9500 to 15000.This deference could be originated from two factors. Cultivating period is the first factor which is considered as 140 days in water need calculations and its relevant tables. Cultivating period in the studied region was 110 days, in practice. It should be noted that the earth warming and increasing in the average temperatures during cultivating period can influence the reduction of cultivating time. The second factor which can be the reason of deference in estimated water demand of rice, is neglecting that the irrigating was stopped at the end of cultivating time.
کلیدواژه‌ها [English]
- SEBAL Algorithm
- rice
- Evapotranspiration
- Remote sensing
- Landsat?
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