بررسی وضوح فضایی نقشه های تبخیر و تعرق واقعی در حوضه زاینده رود

تبخیر و تعرق به عنوان عامل مهم در اتلاف آب در مناطق خشک و نیمه خشک، پدیده پیچیده‌ای است کهبه عوامل و داده‌های زیادی بستگی دارد. بنابراین برآورد دقیق میزان آن، بسیار مشکل وپرهزینه است.هدف از این مطالعه، بررسی اثرات ریزمقیاس ‌نمایی کوکریجنگ دمای سطح زمین (lst)،برای برآورد تبخیر و تعرق واقعی (aet)، در ژوئن 2017 در حوضه زاینده ‌رود است. در این راستا،در روش اول،ریزمقیاس ‌نمایی کوکریجینگ به محصول lst حاصل از ماهواره modis اعمال شد. سپس با استفاده از سیستم  بیلان انرژی سطح (sebs)،aet روزانه با وضوح متوسط ​​(250 متری) به دست آمد. در روش دوم، نقشه aet به وضوح متوسط ​​(250 متری) ریزمقیاس ‌نمایی شد. اعتبار سنجی با استفاده از محصولات حاصل ازlandsat 8 صورت پذیرفت. نتایج نشان داد مقادیر میانگین aet-sebs ریزمقیاس ‌نمایی (12/56mm/day)وaet مرجع (13/11mm/day) دارایاختلاف ناچیزهستند. rmseمیانaetمرجع و aetریزمقیاس ‌نمایی شده برابر با 1/66 میلیمتر/روز (r = 0/73) و میانlstمرجع و ریزمقیاس‌ نمایی شده معادل 4/36k و (r=0/78)  بود. این مطالعه نشان داد که مقادیر aet حاصله از دو روش ریزمقیاس ‌نمایی، مشابه یکدیگر هستند، اما aet بدست آمده از lst ریزمقیاس ‌نمایی شده، یک تغییرپذیری فضایی بالاتری را از خود نشان می‌دهد. مقایسه aet-sebs با aet حاصل از روش پنمن مانتیث فائو نشان دهنده rmse برابر با 26/2است. بنابراینlst اثر زیادی در تولید نقشه‌های aet از روی تصاویر سنجش از دور دارد و ریزمقیاس ‌نمایی  کوکریجینگ برای ارائه  نقشه‌های aet روزانه  با  وضوح فضایی متوسط ​​مفید بوده است. در مجموع یافته‌های پژوهش نشان داد با به کارگیری روش ریزمقیاس نمایی و sebs، می‌توان تبخیر و تعرق واقعی را در حوضه زاینده ‌رود و برای مناطق خشک و نیمه خشک با دقت مطلوب محاسبه نمود.

Investigating the spatial resolution of actual evapotranspiration maps in the ZayandehRud basin

Introduction Evapotranspiration is one of the most important parts of the water cycle (Boegh and Soegaard 2004). Precise prediction of actual evapotranspiration () is essential for various fields, such as agriculture, water resource management, irrigation planning and plant growth modeling. Therefore, accurate determination of actual evapotranspiration has always been a major concern of experts in these fields. Due to the limited number of weather stations and the fact that collecting ground information is both time consuming and expensive, remote sensing and satellite imagerycan be a suitable tool in determination of actual evapotranspiration (Brisco et al., 2014). Satellite productions are usually divided into images with low, medium and high spatial resolution (Rao et al., 2017). Surface energy balance is a method usually used in combination withremotely sensed spatial data for estimation. Information collected from various sources, such as remotely sensedimageries and meteorological data, are used in this method. The present studyinvestigatesspatial distribution on different scales (from field to regional) using remotely sensed imagerieswithdifferent spatial and temporal resolution. TheSurface Energy Balance System (SEBS) is one of the most important methods used for the estimation of in remotely sensed images (Ochege et al., 2019). This model needs thermal maps produced using satellite images. Daily maps produced with RS are usually very large, and their pixelsize is usually so large that it can provide the spatial diversity found in the basins with respect to the errors (Mahour et al., 2017).   Material and Methods In order to estimate the actual evapotranspirationin satellite images collected from Zayanderud basin,the effects of CoKriging downscaling of surface temperature (LST) were investigated in June 2017 using two different methods.To reach this aim, we first applied a cokriging downscaling method to a lowpower LST product collected from MODIS at 1000 meters. Then based on the results and using the SEBS system, the daily  was obtained from images with average spatial resolution (250 m).In the second method, map produced usinghigh resoultion satellite imageswas downscaled to medium resolution (250 m). For both methods, 250 m resolutionMODIS NDVI products were used as covariables.Then, validation was performed using Landsat8 imagery, and land surface temperature was extracted from its thermal bands. SEBS algorithm was used to determine in Landsat 8 30meter resolutionimagery. Accuracy of measurements wasexamined based on a comparison between down scaledLST and maps (250 meterresolution).   Results and Discussion In the present study, mean LST equals 3/312 K (SD = 1.74) and average daily equals 12.5 mm / day (SD = 0.86). In the downscaling phase, the relationship between LST parameters and and vegetation index(as a covariable)was investigated.Moreover, to investigate the relation betweenhigh resolution variables and NDVI, we resampled LST and   variables from a 1000 mresolution to 250 mresolution.In250 mresolution, there is a negative linear relation (r=0.85) between LST and NDVI, but the relation betweenand NDVI is positive (r = 0.80). Thus, lower LST (> 305k) indicates more vegetation (NDVI >0.3) inthe region, while higher LST results in lower NDVI or lack of vegetation. As a result, more vegetation can be observed in regions with higher(12 mm/day). Results indicated that the difference between average  downscaledSEBS (12.56 mm/day) and reference  (13.11 mm/day) is negligible. The RMSE between the reference and the downscaled  equaled 1.66 mm/day (r = 0.73), and RMSE between the reference LST and the downscaled LST equaled4.36 K (r = 0.78). Thus,values obtained from two downscaling methods were similar, but the  obtained from downscaled LST showed a higher spatial variation. Therefore, LST has greatly influenced the production of maps using remotely sensing images, and CoKriging downscaling has been useful for providing daily  maps with intermediate spatial resolution.   Conclusion Evapotranspiration downscaling using the cokriging method is not significantly different from the SEBS product and the results are similar. The results of SEBS method isalso acceptable, but the  derived from the SEBS algorithm is more variable due to the LST downscaling.