Combined Hydraulic and Black-Box Models for Flood Forecasting in Urban Drainage Systems

Abstract

Rapid urbanization and its implications for both water quality issues and floods have increased the need for modeling of urban drainage systems. Many operational models are based on deterministic solutions of hydraulic equations. Improving such models by adding a "black-box" component to deal with any systematic structure in the residuals is proposed. In this study, a conventional deterministic stormwater drainage network model is first developed for a rapidly developing catchment using the HYDROWORKS ͑now called Infoworks͒ package, from Wallingford Software in the United Kingdom. However, despite the generally satisfactory results, the HYDROWORKS model tended to underestimate the flow volume. In this paper, a black-box or "systems" model is fitted to the hydraulic urban drainage model in order to improve its overall efficiency. A study was conducted of suitable black-box models, which included the nonlinear artificial neural network model ͑ANN͒, and the linear time series models of Box and Jenkins in 1976. They were added to either the output ͑in simulation mode͒ or, in updating mode, to the residuals ͑i.e., difference between modeled and measured output͒ of the deterministic hydraulic model. The updating procedure provided a considerable improvement in the overall model efficiency for different lead-time forecasting. In simulation mode, however, only the nonlinear ANN model gave better performance in calibration, and a slight improvement in validation.

Self-Coupling Black Box Model of a Dynamic System Based on ANN and Its Application

“…ANN, which simulates the human nervous system, is a powerful method to solve regression and classification problems [9,10]. ANN has been successfully applied for the nonlinear modeling of time series [11][12][13][14][15][16][17][18][19]. It has the ability to model complex nonlinear relations in data without any prior assumptions about the nature of such relations [20].…”

Simulation of Drainage Capacity in a Coastal Nuclear Power Plant under Extreme Rainfall and Tropical Storm

“…Numerical simulation is an important method used for predicting and assessing overland flooding and underground network drainage [6][7][8][9][10][11][12][13]. A number of combined models have been widely used to analyze inundation by flooding in recent years.…”

Artificial Neural Networks for the prediction of the trapping efficiency of a new sewer overflow screening device

“…In addition, experimental work involves significant cost and time. To overcome such problems experimental results were analyzed and used to train an ANN model that had already been used successfully in similar kinds of environmental problems like water level predictions, flood forecasting and control in combined sewers (Chiang et al, 2010, Bruen et al, 2006and Weyand, 2002. Willems et al (1999) demonstrated a number of uncertainties involved in the modeling of a sewer system.…”