Abstract
ABSTRACT Real-time updating of channel flow routing models is essential for error reduction in hydrological forecasting. Recent updating techniques found in scientific literature, although very promising, are complex and often applied in models that demand much time and expert knowledge for their development, posing challenges for using in an operational context. Since powerful and well-known computational tools are currently available, which provide easy-to-use and less time-consuming platforms for preparation of hydrodynamic models, it becomes interesting to develop updating techniques adaptable to such tools, taking full advantage of previously calibrated models as well as the experience of the users. In this work, we present a real-time updating procedure for streamflow forecasting in HEC-RAS model, using the Shuffled Complex Evolution - University of Arizona (SCE-UA) optimization algorithm. The procedure consists in a simultaneous correction of boundary conditions and model parameters through: (i) generation of a lateral inflow, based on Soil Conservation Service (SCS) dimensionless unit hydrograph and; (ii) estimation of Manning roughness in the river channel. The algorithm works in an optimization window in order to minimize an objective function, given by the weighted sum of squared errors between simulated and observed flows where differences in later intervals (start of forecast) are more penalized. As a case study, the procedure was applied in a river reach between Salto Caxias dam and Hotel Cataratas stream gauge, located in the Lower Iguazu Basin. Results showed that, with a small population of candidate solutions in the optimization algorithm, it is possible to efficiently improve the model performance for streamflow forecasting and reduce negative effects caused by lag errors in simulation. An advantage of the developed procedure is the reduction of both excessive handling of external files and manual adjustments of HEC-RAS model, which is important when operational decisions must be taken in relatively short times.
Highlights
One of the greatest challenges of reservoir operation relies in our ability to anticipate future conditions of a river system
Regarding the computational efficiency, processing time was directly related to the number of HEC-RAS simulations, which in turn is linked mainly to the number of complexes in Shuffled Complex Evolution - University of Arizona (SCE-UA) algorithm
Recent technological advances and development of software packages have been facilitating the preparation of hydrodynamic models for solving a variety of water resources problems
Summary
One of the greatest challenges of reservoir operation relies in our ability to anticipate future conditions of a river system. This can be achieved through a hydrological forecast, in which variables such as streamflow and river stage are predicted with sufficient lead time to support decision-making procedures. Hydrological forecasting can be performed through a myriad of mathematical models, ranging from statistical upstream-downstream relationships to physically-based routing models described by full 1D Saint-Venant equations. The latter approach has received little attention due to its high computational burden, detailed topography requirements and greater complexity regarding statistical methods. In the Brazilian context, a partnership signed in 2013 between the Brazilian National Water Agency (ANA) and the US Army Corps of Engineers (USACE) is currently motivating the use of HECRAS and other modelling tools for water resource management, including flood control and real-time reservoir operation
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have