Fatma Bunyan Unel^1,*, Lutfiye Kusak¹, Murat Yakar¹, Abdullah Sahin², Hakan Dogan³, Fikret Demir⁴

Revue Internationale de Géomatique, Vol.34, pp. 433-460, 2025, DOI:10.32604/rig.2025.065502 - 29 July 2025

Abstract This study aimed to create a model for calculating the total reference crop evapotranspiration (ETo) in Mersin Province from May 2015 to 2020 and to generate maps using spatial analysis. Lemons from citrus play a significant role in Mersin’s agriculture, and because of lemons’ sensitivity to temperature, ETo is essential for them. It was observed that the ETo value () calculated using the Penman-Monteith (PM) method increased over the years. A model was developed using data from 36 Automated Weather Observing Systems (AWOS) in Mersin, Türkiye, which is located in a semi-arid climate zone. The… More >

Bushra Tayyaba¹, Muhammad Usman Ghani Khan^1,2,3, Talha Waheed², Shaha Al-Otaibi⁴, Tanzila Saba^3,*

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 2851-2864, 2025, DOI:10.32604/cmc.2025.060365 - 16 April 2025

Abstract Reference Evapotranspiration (ETo) is widely used to assess total water loss between land and atmosphere due to its importance in maintaining the atmospheric water balance, especially in agricultural and environmental management. Accurate estimation of ETo is challenging due to its dependency on multiple climatic variables, including temperature, humidity, and solar radiation, making it a complex multivariate time-series problem. Traditional machine learning and deep learning models have been applied to forecast ETo, achieving moderate success. However, the introduction of transformer-based architectures in time-series forecasting has opened new possibilities for more precise ETo predictions. In this study,… More >

Moein Tosan¹, Mohammad Reza Gharib^2,*, Nasrin Fathollahzadeh Attar³, Ali Maroosi⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.2, pp. 1109-1154, 2025, DOI:10.32604/cmes.2025.058595 - 27 January 2025

Abstract Accurate estimation of evapotranspiration (ET) is crucial for efficient water resource management, particularly in the face of climate change and increasing water scarcity. This study performs a bibliometric analysis of 352 articles and a systematic review of 35 peer-reviewed papers, selected according to PRISMA guidelines, to evaluate the performance of Hybrid Artificial Neural Networks (HANNs) in ET estimation. The findings demonstrate that HANNs, particularly those combining Multilayer Perceptrons (MLPs), Recurrent Neural Networks (RNNs), and Convolutional Neural Networks (CNNs), are highly effective in capturing the complex nonlinear relationships and temporal dependencies characteristic of hydrological processes. These… More >

Rab Nawaz Bashir¹, Imran Sarwar Bajwa², Muhammad Waseem Iqbal^3,*, Muhammad Usman Ashraf⁴, Ahmed Mohammed Alghamdi⁵, Adel A. Bahaddad⁶, Khalid Ali Almarhabi⁷

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1915-1930, 2023, DOI:10.32604/iasc.2023.030844 - 05 January 2023

Abstract Soil salinity is a serious land degradation issue in agriculture. It is a major threat to agriculture productivity. Extra irrigation water is applied to leach down the salts from the root zone of the plants in the form of a Leaching fraction (LF) of irrigation water. For the leaching process to be effective, the LF of irrigation water needs to be adjusted according to the environmental conditions and soil salinity level in the form of Evapotranspiration (ET) rate. The relationship between environmental conditions and ET rate is hard to be defined by a linear relationship… More >

Wafa Difallah^1,2,*, Fateh Bounaama², Belkacem Draoui², Khelifa Benahmed³, Abdelkader Laaboudi⁴

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1749-1767, 2022, DOI:10.32604/cmc.2022.019071 - 07 September 2021

Abstract Water conservation starts from rationalizing irrigation, as it is the largest consumer of this vital source. Following the critical and urgent nature of this issue, several works have been proposed. The idea of most researchers is to develop irrigation management systems to meet the water needs of plants with optimal use of this resource. In fact, irrigation water requirement is only the amount of water that must be applied to compensate the evapotranspiration loss. Penman-Monteith equation is the most common formula to evaluate reference evapotranspiration, but it requires many factors that cannot be available in… More >

Jingxin Yu^1,3, Wengang Zheng^1,*, Linlin Xu³, Lili Zhangzhong¹, Geng Zhang², Feifei Shan¹

Intelligent Automation & Soft Computing, Vol.26, No.5, pp. 989-1003, 2020, DOI:10.32604/iasc.2020.010130

Abstract Accurate estimation of reference evapotranspiration (ET0) is a critical prerequisite for the development of agricultural water management strategies. It is challenging to estimate the ET0 of a solar greenhouse because of its unique environmental variations. Based on the idea of ensemble learning, this paper proposed a novel ET0i estimation model named PSO-XGBoost, which took eXtreme Gradient Boosting (XGBoost) as the main regression model and used Particle Swarm Optimization (PSO) algorithm to optimize the parameters of XGBoost. Using the meteorological and soil moisture data during the two-crop planting process as the experimental data, and taking ET0i More >

Xianghui Lu¹, Junliang Fan², Lifeng Wu^1,*, Jianhua Dong³

CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.2, pp. 699-723, 2020, DOI:10.32604/cmes.2020.011004 - 12 October 2020

Abstract It is important for regional water resources management to know the agricultural water consumption information several months in advance. Forecasting reference evapotranspiration (ET₀) in the next few months is important for irrigation and reservoir management. Studies on forecasting of multiple-month ahead ET₀ using machine learning models have not been reported yet. Besides, machine learning models such as the XGBoost model has multiple parameters that need to be tuned, and traditional methods can get stuck in a regional optimal solution and fail to obtain a global optimal solution. This study investigated the performance of the hybrid extreme… More >

Cargnel MD¹, AL Orchansky², RE Brevedan², SS Baioni², MN Fioretti²

Phyton-International Journal of Experimental Botany, Vol.86, pp. 181-189, 2017, DOI:10.32604/phyton.2017.86.181

Abstract Two field experiments were carried out in a semiarid region of Argentina over a soybean (Glycine max L. Merrill) field. The sites of study were San Adolfo (39˚ 23’ S, 62˚ 22’ W, 22 m.a.s.l.) and Nueva Roma (38˚ 29’ S, 62˚ 39’ W, 70 m.a.s.l.). Soybeans were planted on Jan 4 (San Adolfo) and Nov 27 (Nueva Roma) in 0.75 m wide rows and at 400000 pl/ha during two consecutive growing seasons. Energy balance and evapotranspiration (ET) were estimated during the reproductive stages from full bloom (R2) to full maturity (R8). In Nueva Roma ET… More >

Yescas CP¹, MA Segura C¹, L Martínez C², VP Álvarez R¹, JA Montemayor T¹, JA Orozco V¹, JE Frías R¹

Phyton-International Journal of Experimental Botany, Vol.84, No.2, pp. 272-279, 2015, DOI:10.32604/phyton.2015.84.272

Abstract The scarcity of water in arid and semiarid regions of the world is a problem that every day increases by climate change. The subsurface drip irrigation (SDI) and changes in population density of plants are alternatives that can be used to make a sustainable use of water. Therefore, the objectives of this study were to determine the combination that allows for an increased corn performance and efficient use of water without losing the quality of forage. Three different irrigation levels were applied through a system of a SDI at three different densities of forage maize… More >