Use of Meta-Heuristic Techniques in Rainfall-Runoff Modelling

Use of Meta-Heuristic Techniques in Rainfall-Runoff Modelling

by MDPI AG

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Overview

Use of Meta-Heuristic Techniques in Rainfall-Runoff Modelling by MDPI AG

Each year, extreme floods, which appear to be occurring more frequently in recent years (owing to climate change), lead to enormous economic damage and human suffering around the world. It is therefore imperative to be able to accurately predict both the occurrence time and magnitude of peak discharge in advance of an impending flood event. The use of meta-heuristic techniques in rainfall-runoff modeling is a growing field of endeavor in water resources management. These techniques can be used to calibrate data-driven rainfall-runoff models to improve forecasting accuracies. This book, being also a Special Issue of the journal Water, is designed to fill the analytical void by including fourteen articles concerning advances in the contemporary use of meta-heuristic techniques in rainfall-runoff modeling. The information and analyses are intended to contribute to the development and implementation of effective hydrological predictions, and thus, of appropriate precautionary measures.

Product Details

ISBN-13: 9783038423263
Publisher: MDPI AG
Publication date: 04/19/2017
Pages: 258
Product dimensions: 6.69(w) x 9.61(h) x 0.70(d)

Table of Contents

1) Use of Meta-Heuristic Techniques in Rainfall-Runoff Modelling

2) Regional Patterns of Baseflow Variability in Mexican Subwatersheds

3) A CN-Based Ensembled Hydrological Model for Enhanced Watershed Runoff Prediction

4) Application of the Entropy Method to Select Calibration Sites for Hydrological Modeling

5) Coupled Heuristic Prediction of Long Lead-Time Accumulated Total Inflow of a Reservoir during Typhoons Using Deterministic Recurrent and Fuzzy Inference-Based Neural Network

6) Estimation of Rainfall Associated with Typhoons over the Ocean Using TRMM/TMI and Numerical Models

7) An Hourly Streamflow Forecasting Model Coupled with an Enforced Learning Strategy

8) Applying a Correlation Analysis Method to Long-Term Forecasting of Power Production at Small Hydropower Plants

9) Heuristic Methods for Reservoir Monthly Inflow Forecasting: A Case Study of Xinfengjiang Reservoir in Pearl River, China

10) Daily Reservoir Runoff Forecasting Method Using Artificial Neural Network Based on Quantum-behaved Particle Swarm Optimization

11) Daily Runoff Forecasting Model Based on ANN and Data Preprocessing Techniques

12) Parameter Automatic Calibration Approach for Neural-Network-Based Cyclonic Precipitation Forecast Models

13) Spatial Disaggregation of Areal Rainfall Using Two Different Artificial Neural Networks Models

14) Subgrid Parameterization of the Soil Moisture Storage Capacity for a Distributed Rainfall-Runoff Model

15) Grey Forecast Rainfall with Flow Updating Algorithm for Real-Time Flood Forecasting

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