AutoML-Based Drought Forecast with Meteorological Variables
A precise forecast for droughts is of considerable value to scientific research, agriculture, and water resource management. With emerging developments of data-driven approaches for hydro-climate modeling, this paper investigates an AutoML-based framework to forecast droughts in the U.S. Compared with commonly-used temporal deep learning models, the AutoML model can achieve comparable performance with less training data and time. As deep learning models are becoming popular for Earth system modeling, this paper aims to bring more efforts to AutoML-based methods, and the use of them as benchmark baselines for more complex deep learning models.
Code (0)
등록된 구현이 없습니다.
Tasks
AutoMLDeep LearningManagementSimilar Papers 제목 키워드 기반
A Quantum-Empowered SPEI Drought Forecasting Algorithm Using Spatially-Aware Mamba Network
Due to the intensifying impacts of extreme climate changes, drought forecasting (DF), which aims to predict droughts from historical meteorological data, has become increasingly critical for monitoring and managing water…
MambaPrediction of short and long-term droughts using artificial neural networks and hydro-meteorological variables
Drought is a natural creeping threat with numerous damaging effects in various aspects of human life. Accurate drought prediction is a promising step in helping policy makers to set drought risk management strategies. To…
ManagementTime SeriesTime Series AnalysisEvaluating and improving crop-yield forecasting methods during extreme drought
The impact of climate variability on food production has led to the creation of various forecasting models that uses machine learning (ML), numerical weather predictors (NWP) or a hybrid of ML-NWP models to identify stru…
An AutoML Framework using AutoGluonTS for Forecasting Seasonal Extreme Temperatures
In recent years, great progress has been made in the field of forecasting meteorological variables. Recently, deep learning architectures have made a major breakthrough in forecasting the daily average temperature over a…
Quantitative Assessment of Drought Impacts Using XGBoost based on the Drought Impact Reporter
Under climate change, the increasing frequency, intensity, and spatial extent of drought events lead to higher socio-economic costs. However, the relationships between the hydro-meteorological indicators and drought impa…
Management