Drought forecasting: a review and assessment of the hybrid techniques and data pre-processing

MA Alawsi, SL Zubaidi, NSS Al-Bdairi, N Al-Ansari… - Hydrology, 2022 - mdpi.com
Drought is a prolonged period of low precipitation that negatively impacts agriculture,
animals, and people. Over the last decades, gradual changes in drought indices have been …

Modeling potential evapotranspiration by improved machine learning methods using limited climatic data

RR Mostafa, O Kisi, RM Adnan, T Sadeghifar, A Kuriqi - Water, 2023 - mdpi.com
Modeling potential evapotranspiration (ET0) is an important issue for water resources
planning and management projects involving droughts and flood hazards …

Modeling various drought time scales via a merged artificial neural network with a firefly algorithm

B Mohammadi - Hydrology, 2023 - mdpi.com
Drought monitoring and prediction have important roles in various aspects of hydrological
studies. In the current research, the standardized precipitation index (SPI) was monitored …

Substantial increase in abrupt shifts between drought and flood events in China based on observations and model simulations

Y Zhang, Q You, S Ullah, C Chen, L Shen… - Science of the Total …, 2023 - Elsevier
Drought-flood abrupt alternation (DFAA) refers to the rapid transformation between droughts
and floods, posing serious threats to ecological security, food production, and human safety …

[HTML][HTML] Performance of machine learning techniques for meteorological drought forecasting in the Wadi Mina Basin, Algeria

M Achite, N Elshaboury, M Jehanzaib… - Water, 2023 - mdpi.com
Water resources, land and soil degradation, desertification, agricultural productivity, and
food security are all adversely influenced by drought. The prediction of meteorological …

Modeling multistep ahead dissolved oxygen concentration using improved support vector machines by a hybrid metaheuristic algorithm

RM Adnan, HL Dai, RR Mostafa, KS Parmar… - Sustainability, 2022 - mdpi.com
Dissolved oxygen (DO) concentration is an important water-quality parameter, and its
estimation is very important for aquatic ecosystems, drinking water resources, and agro …

[HTML][HTML] Evaluating the BFAST method to detect and characterise changing trends in water time series: A case study on the impact of droughts on the Mediterranean …

MP Mendes, V Rodriguez-Galiano… - Science of the Total …, 2022 - Elsevier
Mediterranean climate regions are facing increased aridity conditions and water scarcity,
thus needing integrated management of water resources. Detecting and characterising …

Climate transition risk and bank performance: Evidence from China

S Li, Z Pan - Journal of Environmental Management, 2022 - Elsevier
Under the “carbon peaking and carbon neutrality goals”, China's commercial banks are
facing a severe climate transition risk. This paper proposes a climate transition risk …

A novel global solar exposure forecasting model based on air temperature: Designing a new multi-processing ensemble deep learning paradigm

M Jamei, M Karbasi, M Ali, A Malik, X Chu… - Expert Systems with …, 2023 - Elsevier
The total quantity of solar energy falling on a horizontal plane surface is the global solar
exposure (GSE, ie, total solar energy). Precise forecasting of GSE is important in many fields …

Multi-step ahead hourly forecasting of air quality indices in Australia: Application of an optimal time-varying decomposition-based ensemble deep learning algorithm

M Jamei, M Ali, C Jun, SM Bateni, M Karbasi… - Atmospheric Pollution …, 2023 - Elsevier
Recently, researchers have prioritized the accurate forecasting of the particulate matter (PM)
air quality indicators PM 2.5 and PM 10 in urban and industrial locations due to their …