sebal algorithm

The intricate choreography of evaporation and transpiration plays a fundamental role in the delicate ballet of the water cycle, serving as a linchpin for ecological equilibrium. Regrettably, more than 0.72% of a nation's water reservoirs slip through our fingers due to this natural process. The significance of precise predictions for evaporation and transpiration reverberates across a myriad of applications, encompassing agriculture, water resource management, irrigation planning, and the intricate modeling of plant growth. Robust studies on evapotranspiration, especially within the domains of climate change, sustainable development, and the management of water resources, underscore its indispensable importance. Nevertheless, the scarcity of meteorological stations and the resource-intensive nature of ground-based data collection have propelled an exploration into the realm of remote sensing techniques. Remote sensing techniques, when armed with accurate and fitting outputs, emerge as invaluable instruments for unraveling the intricacies of actual evaporation and transpiration.Among the plethora of algorithms residing within remote sensing, the Sabal algorithm stands out as a beacon of precision. Executing an instantaneous surface energy balance for each pixel in a satellite image, this algorithm becomes a powerful instrument for crafting accurate estimations. This investigation centers on the vibrant city of Tabriz, nestled in the western expanse of East Azerbaijan Province, Iran.

To unravel the enigmas of evaporation and transpiration in Tabriz, the Sabal algorithm and Landsat satellite images in sensors ("OLI_TIRS") spanning from 2013 to 2021 were enlisted. These images, procured from NASA, became the canvas for the meticulous strokes of remote sensing and geographic information systems (GIS). The harmonious fusion of thermal remote sensing techniques and GIS was orchestrated with precision, employing ARC GIS 10.8 and Envi 5.3 software for the intricate processes of data manipulation, analysis, and visualization.

The findings of this research unveiled a visual metamorphosis since 2017, as the orange and red tones of Land Surface Temperature (LST) underwent a discernible escalation. Prevailing pixels exhibited temperatures spanning from 315 to 320 degrees and 320 degrees and above, marking a conspicuous warming trend in the surveyed area. The Normalized Difference Vegetation Index (NDVI) echoed this narrative, with yellow and red pixels (0.2-0.4) and (<0.6) illustrating an upward trajectory. The Brightness Temperature (BT) index joined the symphony of change, portraying an upward shift, as pixels in the 310-315 range yielded ground to 315-320 and 320 degrees and above. The tangible correlation between vegetation cover (NDVI) and land surface temperature resonated in the accurate depiction of the ascending trend in evaporation-transpiration from 2017 to 2021, particularly in the regions beyond the city center.

In conclusion, this research illuminates the surge in evaporation-transpiration beyond Tabriz's city center, notably in regions experiencing a documented temperature increase. The documented correlation underscores the profound influence of climate variations on this indispensable process. It is recommended that, considering the research results indicating noticeable changes in evapotranspiration outside the city center in the years 2017, 2019, and 2021, future investigations utilize daily, monthly, and annual formulas. Factors such as land-use changes and meteorological variables like temperature statistics, precipitation, etc., should be thoroughly examined in upcoming research. And this topic is of utmost importance for sustainability.

The sun is known as the source of energy, the beginning of life and the source of all other energies. The global radiation of the sun is considered one of the fundamental structures of every climate. Therefore, knowing the characteristics and predicting these basic structures has a great impact on energy-related planning. The use of satellite images and remote sensing models as a suitable and low-cost tool for estimating solar radiation has been in recent years. In order to carry out this research, the images of 2020 Landsat 8 satellite, OLI sensor, TIRS sensor and Sabal algorithm were used. ENVI software was used for geometrical, atmospheric and radiometric corrections of satellite images, as well as the execution of calculations related to the Sabal model, and ArcGIS software was used for creating a database, spatial analysis, cartographic operations and finally implementing the model. The results show that the average of the highest incoming shortwave radiation was 904 watts per square meter on 09/08/2020 and the lowest value was 500 watts per square meter on 10/9/2020. Meanwhile, the highest amount of net radiation on 09/08/2020 was calculated as 320 km and the lowest amount on 10/09/2020 as 39 km. The difference in the amount of net radiation reaching the ground in the studied area, It is caused by the difference in the angle of the sun and the number of sunny hours in different months of the year. Finally, it can be concluded that the solar radiation in the region has the necessary potential for the implementation of solar photovoltaic projects in the year under review.

The sun is known as the source of energy, the beginning of life and the source of all other energies. The global radiation of the sun is considered one of the fundamental structures of every climate. Therefore, knowing the characteristics and predicting these basic structures has a great impact on energy-related planning. The use of satellite images and remote sensing models as a suitable and low-cost tool for estimating solar radiation has been in recent years. In order to carry out this research, the images of 2020 Landsat 8 satellite, OLI sensor, TIRS sensor and Sabal algorithm were used. ENVI software was used for geometric, atmospheric and radiometric corrections of satellite images, as well as the execution of calculations related to the Sabal model, and ArcGIS software was used for creating a database, spatial analysis, cartographic operations and finally implementing the model. The results show that the average maximum incoming shortwave radiation was 918 watts per square meter on 08/09/2020 and the lowest value was 370 watts per square meter on 10/28/2020. Meanwhile, the highest amount of net radiation on 09/08/2020 was calculated as 232 km and the lowest amount was calculated as 13 km on 28/10/2020. The difference in the amount of net radiation reaching the ground in the studied area, It is caused by the difference in the angle of the sun and the number of sunny hours in different months of the year. Finally, it can be concluded that the solar radiation in the region has the necessary potential for the implementation of solar photovoltaic projects in the year under review.

Accurate estimation of dam lake evaporation is of great importance in reservoir water management. This factor has led to the installation of meteorological stations in most dams. At the meteorological station, the rate of evaporation from the lake surface is measured using an evaporation pan. Remote sensing methods are cost effective and can be generalized to the whole area. In this study, the daily evaporation rate from the surface of Suleiman Shah Lake was calculated using a combination of SEBAL algorithm and meteorological data and using five Landsat 8 satellite images. The obtained results were compared with the evaporation rate obtained from different methods. The results showed that among the combined methods, Penman Kimberly 1996 method, among other methods, Blanche-Kridel method had the highest agreement and Hafner method had the least agreement with the measured data indicated with R2, RMSE and MAE equal to 0.96, 2.78 and 5.66, respectively. The results of this study can be used to estimate evaporation in other regions with similar climates.

The use of satellite imagery and remote sensing models has been a convenient and inexpensive tool for estimating solar radiation in recent years.images related to the two years 2019 and 2020 of Landsat 8 satellites, OLI sensors, TIRS sensors and Sabal algorithm were used. The results show that the average of the highest input shortwave radiation was 914 watts per square meter in June and the lowest in November was 548 watts per square meter. The highest amount of net radiation in June was 505 watts per square meter and the lowest in February was 467 watts per square meter. Finally, the highest amount of net radiation reached the earth's surface in June at an average of 505 watts per square meter, the lowest average amount was in November at 296 watts per square meter. The difference in the amount of net radiation reaching the earth in the study area is due to the difference in the angle of the sun and the number of hours of sunshine in different months of the year. Finally, it can be concluded that solar radiation in the region, in the two years under study has the necessary potential to implement solar photovoltaic projects.

Introduction Traditional orchards are the gardens that are mostly outside the city. Typically, traditional orchards surrounding the city of Qazvin can be mentioned. The traditional Qazvin orchards, known for their 1400 years of existence, are one of the examples of optimal use of nature. The construction of traditional Orchards around the city of Qazvin shows that the person considered the way of peaceful living with nature more than ever, and pursued sustainable development, albeit with a slow process (Akhavizadegan, 2002). The features of traditional orchards, mixed cultivation, customs and traditions related to the division of gardens, the division of water and property. Traditional Orchards have been designed with a few goals. The first objective of the construction of this garden has been the direct and economical use of these gardens. The second cause has been the creation of green spaces around cities. This greenery encompassed the cities and made the cities appear as good-weather islands, even in arid and semi-arid regions (such as Isfahan, Shiraz and Qazvin). The third reason for the construction of traditional Orchards was to control the upstream floods and to prevent flood damage to farms and lower villages. The results of various research studies indicate that the use of remote sensing techniques due to capabilities such as wide and integrated vision, the variety of data forms, digitally Data, providing timely and integrated data, wide and easy data availability, rapid access to remote locations and their high accuracy, can be used in large-scale planning in the water and environment study. (Aynew, 2003; Timmermans et al., 2007; Sun et al., 2011; Giorgos et al, 2017). Considering the historical importance of traditional orchards, providing and identifying its water needs is one of the most important issues regarding the maintenance of gardens. However, due to the presence of traditional orchards on the outskirts of the city and the deviation of the outflow of flood during recent years, the debate has focused on the need to supply traditional alternative gardens to the traditional orchards. Hence, the first step in preserving and reviving these gardens is to estimate its water requirement. In this regard, due to the irregular cropping pattern of the mentioned gardens, estimating the need for traditional orchards using remote sensing facilities is considered. Materials & Methods The traditional orchards in Qazvin great importance due to historical dates and habitat of drought resistant species, frostbite, pests and diseases. On the other hand, such as seasonal flood management in these gardens, the importance of preserving these gardens has been doubled. The traditional orchards of Qazvin have spread in three directions in the east, south and west of this city, which in the past few days (less than half a century) has an area of more than 3,000 hectares of productive gardens (Akhavizadegan, 2002). Providing water for gardens has been one of the most important issues for gardeners since the past. Water scarcity has been indicative of the central role of water in the sustainability of gardens since the past and has been mentioned in historical records. The traditional orchards in Qazvin are irrigated from four rivers called Arenjak, Bazar, Zoyar, Dalichay and a flood river called Weshteh in winter and spring. The waters of these rivers are mostly covered by melting of winter snow and spring rains from the northern mountains of Qazvin. The irrigation of traditional orchards mostly occurs twice a year, one in winter and one in spring. Due to the development of the city of Qazvin and the problems of exploitation and lack of attention to them, the area of traditional orchards around the city of Qazvin has declined in recent years. In this research, ecological law is estimated in traditional orchards of Qazvin using remote sensing techniques and SEBAL algorithm, because SEBAL is an intermediate method that uses both empirical and physical parameters simultaneously (Terreza, 2006). The components of the SEBAL algorithm are more empirical and require less grounding information. The model includes a number of computational steps for image processing, the final calculation of evapotranspiration and energy exchange between the earth and the atmosphere (Kinoti et al, 2010). In the SEBAL algorithm, by using solar radiation reflections recorded by satellite sensors and using aerodynamic relationships, the amount of energy remaining is calculated as the energy necessary for the occurrence of the evapotranspiration process, followed by the amount of evapotranspiration at the moment Satellite passes will be obtained. Landsat 8 satellite imagery is used in this research. Landsat satellite images are Path= 165 and Row= 35 are the main input data. The spatial resolution of the Landsat images is 30 meters and the width of the cover strip is 185 kilometers per image. The reason for the selection of the satellite images mentioned above was the high precision of the location and the availability of the images. The images were selected on days without clouds and dust. However, the important feature of the images used is that at the time of maximum water supply needs of the garden has been to provide water. Satellite imagery used to estimate the vegetation index of traditional orchards on dates 2013/06/19, 2013/7/21, 2014/7/21, 2014/7/24, 2015/06/25 and 2015/07/27 for the region studied. Since remote-sensing raw images always have errors in geometry (geometric errors) as well as values recorded for pixels (radiometric errors). Operations related to pre-processing, processing, performing corrections and calculations of image bands using ENVI software. To carry out the SEBAL algorithm, we need air humidity to obtain the temperature of the dew point and wind speed in the study area, which is also provided by Qazvin Synoptic Station. Discussion of Results & Conclusions The study of the level and density of vegetation index in traditional orchards around the city of Qazvin showed that despite the fact the area of green and semi-green gardens (in terms of the threshold of vegetation density) has been greatly reduced. The spatial distribution map of the vegetation index in the traditional orchards area showed that vegetation density index variations are very variable in the study area. In other words, on the basis of the vegetation map of the southern region of Baghestan, it is in a juicy situation. In the western and eastern parts of Qazvin, about 800 hectares of traditional gardening, despite the maintenance of land use, have very poor vegetation, thinness and in some cases it does not have vegetation. The results of this research and the researches have shown that remote sensing technologies can play an effective role in determining the maps of urban and suburban green spaces, vegetation density analysis, estimating the water requirement and providing an optimal model of water resources utilization. Make Estimated initial water requirement using remote sensing capabilities in traditional orchards that have ancient trees, different vegetation densities, varieties of crops and orchards and irregular crop types are important and effective in managing water resources and comprehensive management of green spaces. The results of satellite data show that if the accuracy of the images used is accurate when selecting the time, using the remote sensing data, factors such as classification and vegetation density and the amount of water requirement can be analyzed. Several studies have confirmed this (Jiang et al, 2010; James et al, 2009 Kundu et al, 2018; Grosso et al, 2018).