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The main purpose of this study is to estimate the water requirement of crops such as wheat, barley, alfalfa, lentils, and chickpeas in the northern half of Ardabil province, Iran. For this purpose, remote sensing methods such as SEBAL (Surface Energy Balance Algorithm for Land) and SEBS (Surface Energy Balance System) were used, and the results were compared with Penman-Monteith, Hargreaves-Samani, and pan evaporation methods. The results showed that wheat yield at 2018.11.30 with numerical values of 1.52 in SEBAL method and 1.09 mm/day in SEBS method had the lowest and lentil product at 2013.7.3 with numerical values of 7.86 and 8.14 mm/day had the highest water requirement among the studied products. Also, based on the results, the SEBAL method has the lowest error with RMSE of 0.893 and MAD of 0.843 compared to Penman-Monteith and Hargreaves-Samani methods; it has the highest error rate with RMSE of 1.112 and MAD of 1.215. The SEBS method also has the lowest error rate with RMSE of 0.930 and MAD of 0.833 compared to Hargreaves and the highest error rate with RMSE of 1.691 and MAD of 1.49 compared to the Penman-Monteith method. [ABSTRACT FROM AUTHOR]

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Three subsystems including an atmospheric regional forecast and analysis system, satellite data retrieval and processing, and a surface energy balance model have been employed in a 24/7 operational system to measure and simulate some primary agricultural variables, including evapotranspiration, biomass production, and other associated productivity metrics such as NDVI and Albedo. The final products are generated in a daily routine, covering Iran as the domain of simulation. The WRF atmospheric model, VIIRS, and SENTINEL2 satellite data, as well as the SEBAL model (implemented in pySEBAL) are the main components of the operational system, with products in two different spatial resolutions of 375 m and 100 m. The output products can be used by farmers and stakeholders to manage agricultural water requirements and monitor biophysical parameters. [Display omitted] • 24/7 automated agricultural monitoring and analysis system in a country scale. • Utilization of High Performance Computing (HPC) in agriculture. • Regional weather forecasting over the simulation domain. • Daily satellite data retrieval and processing. [ABSTRACT FROM AUTHOR]

Highlights • Spatial and temporal distribution of evapotranspiration and irrigation water requirement in Urmia Lake River Basin. • Identification of agricultural areas that affected by significant climate changes. • Prioritization of agricultural areas to reduce irrigation water consumption and irrigation plicies planning. • Identification and investigation of natural and unnatural factors that affect on irrigation water consumption changes. Abstract Urmia Lake River Basin (ULRB) is one of the most important habitats in the world and one of the major agricultural regions in Iran. On average, the ratio of irrigation to evapotranspiration in this basin is more than 73%. Investigating the irrigation water requirement pattern changes and the spatial distribution of evapotranspiration during the basin development period on a regional scale play important roles in understanding the basin situation. In this study, the actual evapotranspiration has been estimated by SEBAL model. By estimating the precipitation distribution in the basin, the agricultural irrigation water requirement pattern has been calculated using the land use map in 1995, 2010 and 2014 in the total agricultural lands and in its 7 major subbasins where ET changes from 369 to 1000 mm. The maximum irrigation water consumption were 535 million cubic meters in Urmia subbasin (2010) and then 469 million cubic meters in Miandoab Subbasin (2014), While its average was 2108 million cubic meters in the basin. Furthermore, the maximum and minimum levels of evapotranspiration pattern in the total agricultural lands were 765 and 555 mm in 2010 and 1995, respectively. This study included (1) a comparison between regional irrigation water requirement in the basin and (2) investigating the causes of (including natural and anthropogenic) changes in the amount of irrigation water consumption over the years. The study approach provided a simple but powerful assessment to describe the irrigation water consumption pattern in the subbasins using the minimum ground data and to identify the water management strategies in basin agriculture and climate changes. [ABSTRACT FROM AUTHOR]

Groundwater markets improve the agricultural economy by transferring water entitlements from low-efficient users to high-efficient ones to maximize productivity. Aiming at developing an efficient groundwater market, the environmental effects of the market mechanism should be assessed, and a reliable method for monitoring water consumption needs to be employed. Toward this end, this paper proposes three annual smart groundwater market mechanisms to maximize water net benefits, minimize groundwater withdrawal, and precisely measure water consumption in agricultural fields. To guarantee the aquifer's safe yield in each mechanism, a groundwater simulation model (i.e., Groundwater Modeling System (GMS)) is used to control groundwater table drawdown at the end of the planning horizon. In addition, the fields' evapotranspiration (ET) is estimated using Surface Energy Balance Algorithm for Land (SEBAL) and Mapping Evapo Transpiration at high Resolution with Internalized Calibration (METRIC) algorithm to measure the net groundwater consumption during the market. In this regard, we evaluated the algorithms' performances using observed data from a local lysimeter. They are applied to the Nough plain in Iran to assess the effectiveness of the proposed market framework. The findings illustrate their efficiency in recovering approximately 80% (23.33 million cubic meters (MCM)) of groundwater loss due to overexploitation in the study area and increasing the users' annual benefits by 10.6% compared to the non-market condition. In addition, results imply that the METRIC model approximates daily crop ET with a higher accuracy level than the SEBAL model with RMSE, MAE, and Percentage Error of 0.37 mm/day, 0.32 mm/day, and 14.92%, respectively. This research revealed that the proposed market framework is a powerful tool for reallocating water entitlements and increasing water productivity in arid and semi-arid regions. • A groundwater market is proposed to promote economic and environmental situation. • The uncertainty of available water is incorporated in the proposed methodolgoy • Designed market mechanisms recover nearly 85% of groundwater loss in the study area. • The market framework raises the economic benefit by 128.7 billion rials annually. • METRIC algorithm approximates daily crop evapotranspiration with RMSE of 0.37 mm. [ABSTRACT FROM AUTHOR]

North-western Iran experiences high surface temperatures - a situation that is likely to become increasingly severe due to both climate change and the growing area of sealed surfaces as a result of socio-economic development. Land surface temperature (LST) is a key parameter with respect to land use and land cover (LULC). In this study, the Surface Energy Balance Algorithm for Land (SEBAL) method has been applied to Landsat Enhanced Thematic Mapper (ETM+) imagery for Maraqeh County in north-western Iran (East Azerbaijan Province), in order to model the spatial variation of LST and to determine its quantitative relationship with LULC. The LST was found to be low for orchards and water bodies, while pasture lands and areas currently under cultivation had moderate LSTs. The results suggest that LST can be significantly increased by urbanisation, desertification, and any other processes that result in an increase in non-vegetated surfaces. High LST values were found to be associated with rural and urban settlements, and also with several bare areas of exposed soil, while the maximum LST values were associated with areas of rock outcrop. Our results indicate that LST has an inverse relationship with moisture content and biomass. [ABSTRACT FROM AUTHOR]

Scarcity of water is now the biggest threat in many parts of the world, specially in arid and semi arid regions. Establishing balance between water resources and the demands in a catchment scale basis could be one of the most important strategies to overcome this problem. In this regard, determination and analysis of water balance components (inputs and outputs) would be necessary. This study has focused on estimation of water balance components in arid-mountainous catchment of Manshad in Yazd province of Iran, during the year 2006-2007 using remote sensing and GIS techniques. To estimate actual evapotranspiration (ET) of the catchment, time series of MODIS images were obtained and used via Surface Energy Balance Algorithm for Land (SEBAL) approach. Measured precipitation (P) and runoff (R) data of the catchment were also used to calculate water balance equation components. Results indicated that a large volume of catchment water (about 70%) is wasted through evapotranspiration, while the rainfall is not enough to compensate this volume of water during the year. It seems that the negative (descending) trend has become dominant to the water budget of the area and gradually moves to harsh conditions of water shortage in future decades. Therefore, some actions would be necessary to overcome the problem. Water conservation strategies' improvement of water use efficiency, and control on agricultural field expansions are some solutions that could be advised for the studied catchment. [ABSTRACT FROM AUTHOR]