Prediction of droughts over Pakistan using machine learning algorithms

  title={Prediction of droughts over Pakistan using machine learning algorithms},
  author={Najeebullah Khan and D. A. Sachindra and Shamsuddin Shahid and Kamal Ahmed and Mohammed Sanusi Shiru and Nadeem Nawaz},
  journal={Advances in Water Resources},

Estimation of SPEI Meteorological Drought Using Machine Learning Algorithms

A combination of machine learning with the Standardized Precipitation Evapotranspiration Index (SPEI) is proposed for analysis of drought within a representative case study in the Tibetan Plateau, China, for the period of 1980–2019.

Prediction of Combined Terrestrial Evapotranspiration Index (CTEI) over Large River Basin Based on Machine Learning Approaches

Drought is a fundamental physical feature of the climate pattern worldwide. Over the past few decades, a natural disaster has accelerated its occurrence, which has significantly impacted agricultural

Drought Prediction and Validation for Desert Region using Machine Learning Methods

  • Azmat RajaG. T.
  • Computer Science
    International Journal of Advanced Computer Science and Applications
  • 2022
Drought prediction serves as an early warning to the effective management of water resources to avoid the drought impact and DNN is suitable to predict drought in all the four types of desert region.

Prediction of meteorological drought by using hybrid support vector regression optimized with HHO versus PSO algorithms

The results indicate that the hybrid SVR-HHO approach can be utilized for reliable EDI predictions in the study area and showed a better performance of SVR -HHO compared to SVR/PSO in replicating the median, inter-quartile range, spread, and pattern of the EDI estimated from observed rainfall.

Temporal Hydrological Drought Index Forecasting for New South Wales, Australia Using Machine Learning Approaches

Droughts can cause significant damage to agriculture and water resources leading to severe economic losses. One of the most important aspects of drought management is to develop useful tools to

Evaluation of drought events in various climatic conditions using data-driven models and a reliability-based probabilistic model

Due to a wide range of socio-economic losses caused by drought over the past decades, having a reliable insight of drought properties plays a key role in monitoring and forecasting the drought

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In agroecosystems, drought is a critical climatic phenomenon that affects evapotranspiration and induces water stress in plants. The objective in this study was to characterize and forecast water

Drought prediction using hybrid soft-computing methods for semi-arid region

Drought is one of the most significant natural disaster and prediction of drought is a key aspect in effective management of water resources and reducing the effect of a drought with preliminary

Droughts across China: Drought factors, prediction and impacts.

Development and evaluation of pre and post integration techniques for enhancing drought predictions over India

Accurate estimation and prediction of drought events are highly essential for implementing effective planning and management strategies to handle this complex natural phenomenon. Application of



Ensemble prediction of regional droughts using climate inputs and the SVM–copula approach

In this study, the climate teleconnections with meteorological droughts are analysed and used to develop ensemble drought prediction models using a support vector machine (SVM)–copula approach over

Reservoir Drought Prediction Using Support Vector Machines

In Taiwan, even though the average annual rainfall is up to 2500 mm, water shortage during the dry season happens sometimes. Especially in recent years, water shortage has seriously affected the

Artificial Neural Network–Based Drought Forecasting Using a Nonlinear Aggregated Drought Index

AbstractDrought forecasting plays an important role in the planning and management of water resources systems, especially during dry climatic periods. In this study, a nonlinear aggregated drought

Drought forecasting: A review of modelling approaches 2007–2017

This paper aims to review drought forecasting approaches including their input requirements and performance measures, for 2007-2017 according to their respective mechanism: regression analysis, stochastic, probabilistic, artificial intelligence based, hybrids and dynamic modelling.

Drought projection based on a hybrid drought index using Artificial Neural Networks

The Tarim River Basin is a special endorheic arid drainage basin in Central Asia, characterized by limited rainfall and high evaporation as common in deserts, while water is supplied mainly by

Drought forecasting using artificial neural networks and time series of drought indices

Drought forecasting is a critical component of drought risk management. The paper describes an approach to drought forecasting, which makes use of Artificial Neural Network (ANN) and predicts