Comparison between response surface models and artificial neural networks in hydrologic forecasting

Developing an efficient and accurate hydrologic forecasting model is crucial to managing water resources and flooding issues. In this study, response surface (RS) models including multiple linear regression (MLR), quadratic response surface (QRS), and nonlinear response surface (NRS) were applied to daily runoff (e.g., discharge and water level) prediction. Two catchments, one in southeast China and the other in western Canada, were used to demonstrate the applicability of the proposed models. Their performances were compared with artificial neural network (ANN) models, trained with the learning algorithms of the gradient descent with adaptive learning rate (ANN-GDA) and Levenberg-Marquardt (ANN-LM). The performances of both RS and ANN in relation to the lags used in the input data, the length of the training samples, long-term (monthly and yearly) predictions, and peak value predictions were also analyzed. The results indicate that the QRS and NRS were able to obtain equally good performance in runoff prediction, as compared with ANN-GDA and ANN-LM, but require lower computational efforts. The RS models bring practical benefits in their application to hydrologic forecasting, particularly in the cases of short-term flood forecasting (e.g., hourly) due to fast training capability, and could be considered as an alternative to ANN

Model Configuration And Data Management In The Short-Term Water Information Forecasting Tools

The Short-term Water Information and Forecasting Tools (SWIFT) is a suite of tools for flood and short-term streamflow forecasting, consisting of a collection of hydrologic model components and utilities. Catchments are modeled using conceptual subareas and a node-link structure for channel routing. The tools comprise modules for calibration, model state updating, output error correction, ensemble runs and data assimilation. Given the combinatorial nature of the modelling experiments and the sub-daily time steps typically used for simulations, the volume of model configurations and time series data is substantial and its management is not trivial. SWIFT is currently used mostly for research purposes but has also been used operationally, with intersecting but significantly different requirements. Early versions of SWIFT used mostly ad-hoc text files handled via Fortran code, with limited use of netCDF for time series data. The configuration and data handling modules have since been redesigned. The model configuration now follows a design where the data model is decoupled from the on-disk persistence mechanism. For research purposes the preferred on-disk format is JSON, to leverage numerous software libraries in a variety of languages, while retaining the legacy option of custom tab-separated text formats when it is a preferred access arrangement for the researcher. By decoupling data model and data persistence, it is much easier to interchangeably use for instance relational databases to provide stricter provenance and audit trail capabilities in an operational flood forecasting context. For the time series data, given the volume and required throughput, text based formats are usually inadequate. A schema derived from CF conventions has been designed to efficiently handle time series for SWIFT.

A radar reflectivity-runoff model for use in flood warning

This model connects directly the radar reflectivity data and hydrological variable runoff. The catchment is discretized in pixels (4 Km × 4 Km) with the same resolution of the CAPPI. Careful discretization is made so that every grid catchment pixel corresponds precisely to CAPPI grid cell. The basin is assumed a linear system and also time invariant. The forecast technique takes advantage of spatial and temporal resolutions obtained by the radar. The method uses only the measurements of the factor reflectivity distribution observed over the catchment area without using the reflectivity - rainfall rate transformation by the conventional Z-R relationships. The reflectivity values in each catchment pixel are translated to a gauging station by using a transfer function. This transfer function represents the travel time of the superficial water flowing through pixels in the drainage direction ending at the gauging station. The parameters used to compute the transfer function are concentration time and the physiographic catchment characteristics. -from Authors

Development of parallelizable flood inundation models for large scale analysis

Flood disasters are a major cause of fatalities and economic losses, and several studies indicate that global flood risk is currently increasing. In order to reduce and mitigate the impact of river flood disasters, the current trend is to integrate existing structural defences with non structural measures. This calls for a wider application of advanced hydraulic models for flood hazard and risk mapping, engineering design, and flood forecasting systems. Within this framework, two different hydraulic models for large scale analysis of flood events have been developed. The two models, named CA2D and IFD-GGA, adopt an integrated approach based on the diffusive shallow water equations and a simplified finite volume scheme. The models are also designed for massive code parallelization, which has a key importance in reducing run times in large scale and high-detail applications. The two models were first applied to several numerical cases, to test the reliability and accuracy of different model versions. Then, the most effective versions were applied to different real flood events and flood scenarios. The IFD-GGA model showed serious problems that prevented further applications. On the contrary, the CA2D model proved to be fast and robust, and able to reproduce 1D and 2D flow processes in terms of water depth and velocity. In most applications the accuracy of model results was good and adequate to large scale analysis. Where complex flow processes occurred local errors were observed, due to the model approximations. However, they did not compromise the correct representation of overall flow processes. In conclusion, the CA model can be a valuable tool for the simulation of a wide range of flood event types, including lowland and flash flood events.

Flood triggering in Switzerland: the role of daily to monthly preceding precipitation

Determining the role of different precipitation periods for peak discharge generation is crucial for both projecting future changes in flood probability and for short- and medium-range flood forecasting. In this study, catchment-averaged daily precipitation time series are analyzed prior to annual peak discharge events (floods) in Switzerland. The high number of floods considered – more than 4000 events from 101 catchments have been analyzed – allows to derive significant information about the role of antecedent precipitation for peak discharge generation. Based on the analysis of precipitation times series, a new separation of flood-related precipitation periods is proposed: (i) the period 0 to 1 day before flood days, when the maximum flood-triggering precipitation rates are generally observed, (ii) the period 2 to 3 days before flood days, when longer-lasting synoptic situations generate "significantly higher than normal" precipitation amounts, and (iii) the period from 4 days to 1 month before flood days when previous wet episodes may have already preconditioned the catchment. The novelty of this study lies in the separation of antecedent precipitation into the precursor antecedent precipitation (4 days before floods or earlier, called PRE-AP) and the short range precipitation (0 to 3 days before floods, a period when precipitation is often driven by one persistent weather situation like e.g., a stationary low-pressure system). A precise separation of "antecedent" and "peak-triggering" precipitation is not attempted. Instead, the strict definition of antecedent precipitation periods permits a direct comparison of all catchments. The precipitation accumulating 0 to 3 days before an event is the most relevant for floods in Switzerland. PRE-AP precipitation has only a weak and region-specific influence on flood probability. Floods were significantly more frequent after wet PRE-AP periods only in the Jura Mountains, in the western and eastern Swiss plateau, and at the outlet of large lakes. As a general rule, wet PRE-AP periods enhance the flood probability in catchments with gentle topography, high infiltration rates, and large storage capacity (karstic cavities, deep soils, large reservoirs). In contrast, floods were significantly less frequent after wet PRE-AP periods in glacial catchments because of reduced melt. For the majority of catchments however, no significant correlation between precipitation amounts and flood occurrences is found when the last 3 days before floods are omitted in the precipitation amounts. Moreover, the PRE-AP was not higher for extreme floods than for annual floods with a high frequency and was very close to climatology for all floods. The fact that floods are not significantly more frequent nor more intense after wet PRE-AP is a clear indicator of a short discharge memory of Pre-Alpine, Alpine and South Alpine Swiss catchments. Our study poses the question whether the impact of long-term precursory precipitation for floods in such catchments is not overestimated in the general perception. The results suggest that the consideration of a 3–4 days precipitation period should be sufficient to represent (understand, reconstruct, model, project) Swiss Alpine floods.

Flood plain information, Spring Valley Creek, San Diego County, California /

Mode of access: Internet.

Techniques for estimating flood peaks, volumes and hydrographs on small streams in South Dakota /

Mode of access: Internet.

Information for local officials on flood warning systems /

May 1979.

Methods for estimating peak discharge and flood boundaries of streams in Utah /

624-B

Improvement of flood-frequency estimates for selected small watersheds in eastern Kansas using a rainfall-runoff model /

Mode of access: Internet.

Flood warning system : does your community need one? /

Mode of access: Internet.

Hypothetical flood computation for a stream system /

Mode of access: Internet.

Flood fighting.

"January, 1985."

Governor's Workshop on the Great Flood of 1993 : long term approaches to the management of the Mississippi and Illinois rivers including lessons learned and information gaps.

"ILENR/RE-94/08."

Flood operation forecast : Hydrologic Engineering Center computer program 24-J2-L230.

At head of cover title: Generalized computer program.