Neurocomputing intelligence models for lakes water level forecasting: a comprehensive review

V Demir, ZM Yaseen - Neural Computing and Applications, 2023 - Springer
Hydrological processes forecasting is an essential step for better water management and
sustainability. Among several hydrological processes, lake water level (LWL) forecasting is …

Uncertainty quantification of granular computing-neural network model for prediction of pollutant longitudinal dispersion coefficient in aquatic streams

B Ghiasi, R Noori, H Sheikhian, A Zeynolabedin… - Scientific reports, 2022 - nature.com
Discharge of pollution loads into natural water systems remains a global challenge that
threatens water and food supply, as well as endangering ecosystem services. Natural …

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 …

Drought indicator analysis and forecasting using data driven models: case study in Jaisalmer, India

A Elbeltagi, M Kumar, NL Kushwaha, CB Pande… - … Research and Risk …, 2023 - Springer
Agricultural droughts are a prime concern for economies worldwide as they negatively
impact the productivity of rain-fed crops, employment, and income per capita. In this study …

Prediction of meteorological drought and standardized precipitation index based on the random forest (RF), random tree (RT), and Gaussian process regression (GPR …

A Elbeltagi, CB Pande, M Kumar, AD Tolche… - … Science and Pollution …, 2023 - Springer
Agriculture, meteorological, and hydrological drought is a natural hazard which affects
ecosystems in the central India of Maharashtra state. Due to limited historical data for …

[HTML][HTML] Multi-steps drought forecasting in arid and humid climate environments: Development of integrative machine learning model

M Karbasi, M Jamei, A Malik, O Kisi… - Agricultural Water …, 2023 - Elsevier
In the current study, the Standardized Precipitation Evaporation Index (SPEI) was forecasted
using a combination of the empirical wavelet transform (EWT), discrete wavelet transforms …

[HTML][HTML] Long-term trend analysis of extreme climate in Sarawak tropical peatland under the influence of climate change

Z Sa'adi, ZM Yaseen, AA Farooque… - Weather and Climate …, 2023 - Elsevier
Extreme climate is one of the important variables which determine the capability of tropical
peatland to act as either carbon sink and/or carbon source. The purpose of this study is to …

Evaluation of machine learning techniques for hydrological drought modeling: A case study of the Wadi Ouahrane basin in Algeria

M Achite, M Jehanzaib, N Elshaboury, TW Kim - Water, 2022 - mdpi.com
Forecasting meteorological and hydrological drought using standardized metrics of rainfall
and runoff (SPI/SRI) is critical for the long-term planning and management of water …

Comparative assessment of improved SVM method under different kernel functions for predicting multi-scale drought index

CB Pande, NL Kushwaha, IR Orimoloye… - Water Resources …, 2023 - Springer
This paper focus on the drought monitoring and forecasting for semi-arid region based on
the various machine learning models and SPI index. Drought phenomena are crucial role in …

Combination of data-driven models and best subset regression for predicting the standardized precipitation index (SPI) at the Upper Godavari Basin in India

CB Pande, R Costache, SS Sammen, R Noor… - Theoretical and Applied …, 2023 - Springer
Standardized precipitation index prediction and monitoring are essential to mitigating the
effect of drought actions on precision farming, environments, climate-smart agriculture, and …