A review of the Artificial Intelligence (AI) based techniques for estimating reference evapotranspiration: Current trends and future perspectives

P Goyal, S Kumar, R Sharda - Computers and Electronics in Agriculture, 2023 - Elsevier
Reference Evapotranspiration (ET o) is a complex, dynamic and non-linear hydrological
process. Accurate estimation of ET o has long been an eminent topic of interest in the …

A review of recent advances and future prospects in calculation of reference evapotranspiration in Bangladesh using soft computing models

MM Alam, MY Akter, ARMT Islam, J Mallick… - Journal of …, 2024 - Elsevier
Evapotranspiration (ETo) is a complex and non-linear hydrological process with a significant
impact on efficient water resource planning and long-term management. The Penman …

[HTML][HTML] Future trends of reference evapotranspiration in Sicily based on CORDEX data and Machine Learning algorithms

F Di Nunno, F Granata - Agricultural Water Management, 2023 - Elsevier
In years of increasing impact of climate change effects, a reliable characterization of the
spatiotemporal evolutionary dynamics of evapotranspiration can enable a significant …

[HTML][HTML] A research landscape bibliometric analysis on climate change for last decades: Evidence from applications of machine learning

SSM Ajibade, A Zaidi, FV Bekun, AO Adediran… - Heliyon, 2023 - cell.com
Climate change (CC) is one of the greatest threats to human health, safety, and the
environment. Given its current and future impacts, numerous studies have employed …

[HTML][HTML] A hybrid spatiotemporal deep model based on CNN and LSTM for air pollution prediction

S Tsokov, M Lazarova, A Aleksieva-Petrova - Sustainability, 2022 - mdpi.com
Nowadays, air pollution is an important problem with negative impacts on human health and
on the environment. The air pollution forecast can provide important information to all …

[HTML][HTML] Enhancing real-time prediction of effluent water quality of wastewater treatment plant based on improved feedforward neural network coupled with …

Y Xie, Y Chen, Q Lian, H Yin, J Peng, M Sheng… - Water, 2022 - mdpi.com
To provide real-time prediction of wastewater treatment plant (WWTP) effluent water quality,
a machine learning (ML) model was developed by combining an improved feedforward …

Design data decomposition-based reference evapotranspiration forecasting model: a soft feature filter based deep learning driven approach

Z Zheng, M Ali, M Jamei, Y Xiang, M Karbasi… - … Applications of Artificial …, 2023 - Elsevier
Reference evapotranspiration can cause huge discrepancies in soil moisture and runoff
which is responsible for uncertainties in drought warning systems. Reference …

[HTML][HTML] Predicting rainfall response to climate change and uncertainty analysis: Introducing a novel downscaling CMIP6 models technique based on the stacking …

MV Anaraki, M Kadkhodazadeh… - Journal of Water and …, 2023 - iwaponline.com
This study proposes a novel downscaling technique based on stacking ensemble machine
learning (SEML) to predict rainfall under climate change. The SEML consists of two levels …

[HTML][HTML] Comparison of machine learning techniques and spatial distribution of daily reference evapotranspiration in Türkiye

D Yildirim, E Küçüktopcu, B Cemek, H Simsek - Applied Water Science, 2023 - Springer
Reference evapotranspiration (ET0) estimates are commonly used in hydrologic planning
for water resources and agricultural applications. Last 2 decades, machine learning (ML) …

Prediction of groundwater table and drought analysis; a new hybridization strategy based on bi-directional long short-term model and the Harris hawk optimization …

S Farzin, MV Anaraki, M Naeimi… - Journal of Water and …, 2022 - iwaponline.com
In the present study, a new hybridization strategy for predicting the groundwater table (GWT)
and drought analysis is presented. Therefore, a hybrid of the bi-directional long short-term …