Potential of Deep Learning in drought assessment by extracting information from hydrometeorological precursors
- Environmental ScienceJournal of Water and Climate Change
This study explores the potential of the Deep Learning (DL) approach to develop a model for basin-scale drought assessment using information from a set of primary hydrometeorological precursors,…
Drought Prediction and Validation for Desert Region using Machine Learning Methods
- Computer ScienceInternational Journal of Advanced Computer Science and Applications
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.
Droughts across China: Drought factors, prediction and impacts.
- Environmental ScienceThe Science of the total environment
Artificial intelligence application in drought assessment, monitoring and forecasting: a review
- Environmental ScienceStochastic Environmental Research and Risk Assessment
Drought is a natural hazard creating havoc on economic, social and environmental aspects. As a result of its slow and creeping nature, it is problematic to establish the onset as well as the…
Drought prediction using hybrid soft-computing methods for semi-arid region
- EngineeringModeling Earth Systems and Environment
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…
Multitemporal meteorological drought forecasting using Bat-ELM
- Environmental Science, Computer ScienceActa Geophysica
The development and verification procedures of a new hybrid ML model, namely Bat-ELM for predictive drought modelling, which indicates the new model approximately 20 and 15% improves the forecasting accuracy of traditional ANN and classic ELM techniques, respectively.
Improving BP artificial neural network model to predict the SPI in arid regions: a case study in Northern Shaanxi, China
- Computer ScienceHydrology Research
A hybrid model coupled with singular spectrum analysis (SSA) and backpropagation ANN is proposed that can produce more accurate predictions than the BP-ANN model and has great potential for promoting drought early warning in arid regions.
Comparison of hybrid machine learning methods for the prediction of short-term meteorological droughts of Sakarya Meteorological Station in Turkey
- Environmental ScienceEnvironmental Science and Pollution Research
Drought is a harmful natural disaster with various negative effects on many aspects of life. In this research, short-term meteorological droughts were predicted with hybrid machine learning models…
Drought prediction based on an improved VMD-OS-QR-ELM model
- Environmental Science
To overcome the low accuracy, poor reliability, and delay in the current drought prediction models, we propose a new extreme learning machine (ELM) based on an improved variational mode decomposition…
Development of Bio-Inspired- and Wavelet-Based Hybrid Models for Reconnaissance Drought Index Modeling
- Computer ScienceWater Resources Management
The hybrid models developed in the current study, specifically W-SVR ones, can be proposed as suitable alternatives to the single SVR in modeling the RDI time series of studied locations.
SHOWING 1-10 OF 16 REFERENCES
Drought prediction based on SPI and SPEI with varying timescales using LSTM recurrent neural network
- Computer ScienceSoft Comput.
This paper compares the 1-, 6- and 12-month prediction of the ARIMA statistical model with LSTM using multivariate input in hopes of bettering said performance.
A Mixed Model Approach to Vegetation Condition Prediction Using Artificial Neural Networks (ANN): Case of Kenya's Operational Drought Monitoring
- Environmental ScienceRemote. Sens.
A model space search approach was adopted to obtain the most predictive artificial neural network (ANN) model as opposed to the traditional greedy search approach that is based on optimal variable selection at each model building step, showing the superiority of 1-month lag of the variables as compared to longer time lags of 2 and 3 months.
Drought forecasting by ANN, ANFIS, and SVM and comparison of the models
- Computer ScienceEnvironmental Earth Sciences
High accuracy of these models is shown, which indicates that the SVM model gives more accurate values for forecasting than ANN, adaptive neuro-fuzzy interface system, and support vector machine.
An investigation of drought prediction using various remote-sensing vegetation indices for different time spans
- Environmental Science, Mathematics
ABSTRACT Iran is a country in a dry part of the world and extensively suffers from drought. Drought is a natural and repeatable phenomenon definable at specified time and area. In addition, social…
Application of the Artificial Neural Network model for prediction of monthly Standardized Precipitation and Evapotranspiration Index using hydrometeorological parameters and climate indices in eastern Australia
- Environmental Science
A prototype web-based analysis platform for drought monitoring and early warning
- Environmental ScienceInt. J. Digit. Earth
The currently existing drought monitor and early warning systems are reviewed, applicable remote sensing datasets and drought indicators are discussed and the development of a web-based quasi-real-time Global Drought Monitoring & Analysis Platform (Web-GDMAP) is presented.
Drought Prediction System for Improved Climate Change Mitigation
- Environmental ScienceIEEE Transactions on Geoscience and Remote Sensing
A new intelligent system concept for drought information extraction and predictions from satellite images is developed that can be developed to a full system and is helpful for extracting the freely available satellite images for drought monitoring and climate change mitigation applications at different levels of decision making.
Comparison of the Performance of Six Drought Indices in Characterizing Historical Drought for the Upper Blue Nile Basin, Ethiopia
- Environmental Science
The Upper Blue Nile (UBN) basin is less-explored in terms of drought studies as compared to other parts of Ethiopia and lacks a basin-specific drought monitoring system. This study compares six…
Wireless sensor network based flood/drought forecasting system
- Computer Science2015 IEEE SENSORS
A novel wireless sensor network (WSN) based flood/d drought forecasting system (FDFS) for Pakistan to help authorities gain early information regarding flooding/drought possibilities and take timely measures for the relief.
MapReduce functions to remote sensing distributed data processing—Global vegetation drought monitoring as example
- Computer Science, Environmental ScienceSoftw. Pract. Exp.
An abstract data format is proposed to discretize the multidimensional remote sensing data for easy‐distributed storage and computation using MapReduce paradigm, and the complexity of remote sensing algorithms is resolved.