Cover Image
Read Now

Artificial Intelligence Techniques in Hydrology and Water Resources Management

The sustainable management of water cycles is crucial in the context of climate change and global warming. It involves managing global, regional, and local water cycles, as well as urban, agricultural, and industrial water cycles, to conserve water resources and their relationships with energy, food...

Full description

Bibliographic Details
Main Author: Chang, Fi-John
Other Authors: Chang, Li-Chiu, Chen, Jui-Fa
Format: eBook
Language:English
Published: Basel MDPI - Multidisciplinary Digital Publishing Institute 2023
Subjects:
Machine Learning
Hydrological Modeling
Bayesian Neural Network
Geoai
Autoregressive Model
Random Forest
Forecasting
Water Quality
Regression Analysis
Smart Microclimate-control System (smcs)
Agricultural Resilience
Weather Types And Features
Markov Model
Ann
Urban Northern Taiwan
2d Inundation Simulation And Real-time Error Correction
Deep Learning
Water-energy-food Nexus
Multi-model Ensemble
Time Series
Uncertainty
Daily Temperature
Geomorphic
Stochastic Rainfall Generator
Variational Inference
Hydroinformatics
Huff Rainfall Curve
Persian Gulf
Lstm
Rainfall Time Series
Simulations Of The Gridded Rainstorms
Temperature Generator
Precipitation
Modeling
Hyperparameter
Artificial Neural Network
Deep Reinforcement Learning
Probabilistic Streamflow Forecasting
Xgboost
Telemetry Water Level
Rnn
Fluvial
Roadside Iot Sensors
Hydraulic
Early Warning
Urban Agriculture
Forecasting Uncertainty
Ensemble
Resource Utilization Efficiency
Copula
Multiple Linear Regression
Support Vector Machine
Gru
Dam Inflow
Cnn
Threshold Rainfall
Temporary Rivers
Multivariate Stochastic Model
Artificial Intelligence
Sustainability
Meteorological Feature Extraction
Hydrological
Artificial Neural Networks
Self-organizing Map (som)
Multi-step Ahead Forecasting
Anomaly Detection
Elm
Threshold Runoff
Chania
System Dynamics
Hydrological Extremes
Online Access:
Collection: Directory of Open Access Books - Collection details see MPG.ReNa
Description
Summary:The sustainable management of water cycles is crucial in the context of climate change and global warming. It involves managing global, regional, and local water cycles, as well as urban, agricultural, and industrial water cycles, to conserve water resources and their relationships with energy, food, microclimates, biodiversity, ecosystem functioning, and anthropogenic activities. Hydrological modeling is indispensable for achieving this goal, as it is essential for water resources management and the mitigation of natural disasters. In recent decades, the application of artificial intelligence (AI) techniques in hydrology and water resources management has led to notable advances. In the face of hydro-geo-meteorological uncertainty, AI approaches have proven to be powerful tools for accurately modeling complex, nonlinear hydrological processes and effectively utilizing various digital and imaging data sources, such as ground gauges, remote sensing tools, and in situ Internet of Things (IoT) devices. The thirteen research papers published in this Special Issue make significant contributions to long- and short-term hydrological modeling and water resources management under changing environments using AI techniques coupled with various analytics tools. These contributions, which cover hydrological forecasting, microclimate control, and climate adaptation, can promote hydrology research and direct policy making toward sustainable and integrated water resources management.
Item Description:Creative Commons (cc), https://creativecommons.org/licenses/by/4.0/
Physical Description:1 electronic resource (302 p.)
ISBN:books978-3-0365-7784-5
9783036577845
9783036577852

Similar Items