Development of a Hydrological Ensemble Prediction System to Assist with Decision-Making for Floods during Typhoons

Abstract

Hydrological ensemble prediction systems (HEPSs) can provide decision makers with early warning information, such as peak stage and peak time, with enough lead time to take the necessary measures to mitigate disasters. This study develops a HEPS that integrates meteorological, hydrological, storm surge, and global tidal models. It is established to understand information about the uncertainty of numerical weather predictions and then to provide probabilistic flood forecasts instead of commonly adopted deterministic forecasts. The accuracy of flood forecasting is increased. However, the spatiotemporal uncertainty associated with these numerical models in the HEPS and the difficulty in interpreting the model results hinder effective decision-making during emergency response situations. As a result, the efficiency of decision-making is not always increased. Thus, this study also presents a visualization method to interpret the ensemble results to enhance the understanding of probabilistic runoff forecasts for operational purposes. A small watershed with area of 100 km2 and four historical typhoon events were selected to evaluate the performance of the method. The results showed that the proposed HEPS along with the visualization approach improved the intelligibility of forecasts of the peak stages and peak times compared to that of approaches previously described in the literature. The capture rate is greater than 50%, which is considered practical for decision makers. The proposed HEPS with the visualization method has potential for both decreasing the uncertainty of numerical rainfall forecasts and improving the efficiency of decision-making for flood forecasts.

Smart Installation Weather Warning Decision Support

“…According to Na-Yemeh et al [16], Oklahoma's OK-First weather DSS helped through generating $1.2 million in self-reported cost savings for 12 months. Research studies have developed user interfaces to support decision-makers with statistical summaries [17] and probabilistic forecasts [18] for rapid responses to weather conditions. Another style of DSS allows the user to reason about the impact of data, especially with the rising complexity in both the number and complexity of data sources [19].…”

Impact of Structural and Non-Structural Measures on the Risk of Flash Floods in Arid and Semi-Arid Regions: A Case Study of the Gash River, Kassala, Eastern Sudan

“…The climate change implication of soil erosion in catchment areas affects the Gash River's morphology, and potential ecological impacts have been considered [6]. Examining the Gash River's hydrology and morphology and the causes of riverbed change, case studies, field observations, and hydrological models were utilized to evaluate the effectiveness of these measures in reducing flood risks [7].…”

Comparison of Two Hydrological Models, HEC-HMS and SWAT in Runoff Estimation: Application to Huai Bang Sai Tropical Watershed, Thailand

“…Water resource management and operational hydrology require reliable predictions of water balance components including runoff, evapotranspiration, infiltration, and groundwater flow. Hydrologic models are used for the planning of water resources [1][2][3], for flood predictions [4][5][6], to understand the hydrology due to changes in land use and climate [7,8], for water quality monitoring [9], to formulate aquifer recharge management strategies [10], to design hydraulic infrastructure [11], for ecological restoration design [12], etc. The evolvement of computer technology and programming has benefited researchers, academia, and commercial-based companies to develop different software to simulate watershed processes.…”