OHD/HL - papers: Improve hydrologic prediction

A Pathway Toward Improving Hydrologic Predictions

1. INTRODUCTION

The AHPS will build upon the following components:

1. partnerships with other water cooperators (Federal, state, multi-state, quasi-governmental, and private sector organizations);
2. the existing NWS hydrologic forecasting infrastructure including the 13 NWS River Forecast Centers (RFC) and the NWS River Forecast System (NWSRFS), a very large software system used by RFC hydrologists to produce forecasts of time series of discharges and/or stages at selected locations (approximately 4,000) along the Nation's rivers; and,
3. the NWS Modernization which is providing enhanced scientific and technological components to support the AHPS.

The fourth critical component of the AHPS is the Water Resources Forecasting System (WARFS). The WARFS initiative will provide additional resources to

1. make critical software enhancements to the NWSRFS;
2. develop a NOAA Hydrologic Data System (NHDS);
3. increase the use of short- to long-range weather and climate forecasts within the NWSRFS through appropriate hydrometeorological coupling algorithms;
4. calibrate and field-implement the advanced hydrologic/hydraulic models within the NWSRFS;
5. implement a snow estimation and updating system (SEUS) that provides gridded estimates of snow water equivalent; and,
6. provide more timely, accurate, and informative forecast products to government and quasi-government water and emergency managers and to private sector intermediaries who provide value-added services to specific industries.

This paper focuses on the principal software enhancements and developments provided under WARFS by giving a brief description of each system being enhanced as well as the new systems being developed.

2. NATIONAL WEATHER SERVICE RIVER FORECAST SYSTEM

2.1 Calibration system

The CS performs the tasks needed to process historical hydrometeorological data and to estimate model parameters for a specific basin. The models simulate snow accumulation and ablation, calculate runoff, time distribute runoff from the basin to the basin outlet, and route streamflow through reservoirs and channel systems. The NWSRFS is a modular system that allows the hydrologist to select from a variety of models and to configure them in a manner that is descriptive of the basin. All of the models are available to the Calibration, Operational Forecast, and ESP systems. As part of the calibration procedure, for a particular basin, the simulated streamflow is statistically and visually compared to the observed streamflow to determine the necessary model parameter adjustments. The ideal model parameters are those with which the model simulated streamflow most closely matches the observed streamflow. The CS will be enhanced with capabilities for Graphical User Interface (GUI)-based interactive control of the hydrologic parameter calibration process within a multiple graphical display windows environment. This together with strategic use of a multi-parameter random/shuffled evolution/pattern search optimization algorithm will significantly increase the efficiency of the calibration of hydrologic model parameters.

2.2 Operational forecast system

Once the models have been calibrated for a basin, they can be used operationally with real-time hydrometeorological data to forecast river flows and stages. The OFS contains three major components that are needed for operational river forecasting: Data Entry, Preprocessor, and Forecast. The Data Entry Component is a set of programs that transfer hydrometeorological data from a variety of sources to the observed data base. The Preprocessor Component reads raw station data, estimates missing data as required, and then uses these data to calculate mean areal time series of precipitation, temperature, and potential evapotranspiration for a particular basin. These processed time series are used by the Forecast Component to perform requested hydrologic and hydraulic simulations. The Forecast Component stores parametric data for the models, as well as information that describes the basin connectivity of the river system. In addition, the Forecast Component maintains an account of the current model states. These states describe the hydrologic condition of the basin, including the snow cover, soil moisture, and channel storage. The are needed as starting points for subsequent forecasts. Modeling components within the OFS will be enhanced; e.g., a hydrologic model will be provided with an appropriate spatially distributed structure (Lindsey 1993) and the dynamic routing model (Fread and Jin 1993) will be improved to account for the effects of multiple levee failures, dam failures, and sediment transport.

2.3 Extended streamflow prediction system

ESP is the portion of the NWSRFS which enables a hydrologist to make extended probabilistic forecasts of streamflow and other hydrological variables (Day 1985). ESP assumes that historical meteorological data are representative of possible future conditions and uses these as input data to hydrologic models along with the current states of these model obtained from the Forecast Component. A separate streamflow time series is simulated for each year of historical data using the current conditions as the starting point for each simulation. The streamflow time series can be analyzed for peak flows, minimum flows, flow volumes, etc., for any period in the future. A statistical analysis is performed using the values obtained from each year's simulation to produce a probabilistic forecast for the streamflow variable. This analysis can be repeated for different forecast periods and additional streamflow variables of interest. Short-term quantitative forecasts of precipitation and temperature can be blended with historical data to produce a more realistic transition in meteorological conditions, though this method is fairly simplistic at present. It is also possible to weight the years of simulated streamflow based on the similarity between the climatological conditions of each historical year and the current year. ESP allows flexibility in the streamflow variable which can be analyzed, the capability to make forecasts over both short and long time periods, and the ability to incorporate forecast meteorological data into the procedure. Because of the flexibility and conceptual basis of ESP, it has many applications, including water supply forecasts, flood outlooks, and drought analysis. The ESP will be enhanced to realistically account for the effects of reservoirs and flow diversions as it produces streamflow time series trace ensembles using multiple years of historical time series of precipitation and temperature as input to the OFS hydrologic/hydraulic modeling components. The forecaster, using new GUI-based multiple windows graphical display software, will statistically analyze the streamflow trace ensembles within specified future time windows to produce probabilistic streamflow forecasts.

2.4 Interactive forecast program

The major components that make up the IFP are:

1. the hydrologic models in the NWS River Forecast System;
2. the X-window protocol available on scientific workstations running UNIX;
3. the X-toolkits available to provide building blocks for applications program interface development; and
4. commercial off-the-shelf software for the development of graphical display and interactive program control modules (Page and Smith 1993).

The IFP allows the forecaster to use hydrologic expertise and judgment to develop a forecast while streamlining the tasks required to produce the forecast. The forecaster can interactively make changes to the parameters, data, or current conditions used for hydrologic simulation and quickly see the results of those changes. These changes can be categorized into those affecting time series and those affecting a specific hydrologic model. A graphical user interface allows any required changes to be made with a minimum of effort. Graphical displays consist of those for user orientation and for data presentation. An example of a user orientation display is a schematic of the forecast points being modeled in the current IFP session; the display shows the connectivity of the points and the current state of the streams in each forecast area. Examples of data presentation are model inputs and simulation results presented in graphical plot displays. The IFP is being continuously enhanced as experience in using it for real-time hydrologic forecasting accumulates.

3. NOAA HYDROLOGIC DATA SYSTEM

The data storage and retrieval system will take advantage of recent advances in computer technology; it will enable users to obtain recent historical data, add it to the historical data archive, and make it readily available to users. This system should take advantage of recent advances in computer technology for the storage and retrieval of data. A user-friendly interactive system will enable users to graphically display stations with specific types of data and station index information (e.g., period of record, reporting interval, history of moves, availability of data, and quality of data) for easy selection of stations for retrieval. An archival system for real-time data will enable these data to be used for verification (post-analysis) and re-calibration as well as continual updates to the historical data used to drive the ESP simulations. These data will increase the density of the network and thereby provide improved spatial estimates. In addition, these data will help to identify biases between the real-time and climatic networks.

A database management system (DBMS) will store and manage historical observed and processed data for development, calibration, and ESP. The DBMS takes advantage of recent advances in operating system and database technology (e.g., Geographic Information System (GIS), relational databases and object-oriented databases). Recent advanced in GIS technology will enable users to better analyze and visualize spatial data. Basic data sets (e.g., elevation, soils, land use, boundaries, rivers, seasonal precipitation, seasonal evapotranspiration, and vegetation) will be available for display and analysis. The DBMS will store time series data; i.e., raw data, estimated data, and multiple copies of processed data with the appropriate flags for identification.

The large volumes of data will require analysis techniques which are relatively automated with minimal manual intervention. The advanced mathematical/statistical analyses to be performed upon the data involve the production of high quality estimates of fields and time series of hydrometeorological physical and derived elements using multivariate analysis techniques. The data analysis required in preparation for hydrologic model calibration is critical. This includes station selection, data quality control, estimation of station means, consistency analysis (including the assessment and/or replacement of missing data), and estimation of station weights. Interactive programs with graphical displays of outputs will be used to perform these steps. Historical data analysis in mountainous areas will be improved and made more efficient by integrating hydrologic, mathematical, and statistical data analysis procedures with GIS capabilities. Mathematical/statistical techniques will be implemented for data quality control (e.g., singular value decomposition and optimal interpolation).

4. HYDROMETEOROLOGICAL COUPLING TO ESP SYSTEM

Meteorological/climatological forecasts would be the most useful if detailed quantitative precipitation forecasts (QPFs) could be directly input to streamflow prediction models. Unfortunately, current QPF models and procedures do not consistently provide sufficiently accurate values for direct input to hydrologic models. Although current QPF products provide generalized guidance information indicating rainfall amounts and locations of rainfall areas, they generally do not provide the necessary detail and accuracy required for assigning QPF values to individual watersheds, especially for time windows beyond 12 to 24 hours.

In the absence of sufficiently precise meteorological forecasts, enhanced ESP ensemble analyses approaches will be developed to objectively extract the skill contained in the meteorological forecasts through coupling of the historical time series of precipitation with the precipitation forecasts for the current year (Ingram et al. 1995). This coupling can be achieved through application of a class of mathematical procedures (Bretherton et al. 1992) called singular value decomposition (SVD). A measure of relative confidence in the QPF information for various time horizons will be applied as part of the pattern series correlation to arrive at the relative weights for use in the ESP ensemble analyses.

5. SNOW ESTIMATION AND UPDATING SYSTEM

The SEUS uses the power of a geographic information system to store, analyze and display the spatial data necessary to perform the estimation. The system is designed to develop snow water equivalent on a basin basis and provide average snow water equivalent over a basin or subarea. To accomplish these tasks, SEUS consists of three components (McManamon et al. 1993): a calibration component, an operational component and an updating component. The calibration component analyzes historical snow observation data and develops the parameters needed to estimate gridded snow water equivalent. The operational component accesses real-time data and takes advantage of the parameters developed in the calibration component to determine gridded snow water equivalent. The updating component modifies the existing snow water equivalent states of the conceptual snow model within NWSRFS based on the weighted contributions of the simulated model snow states and the estimates of the snow states developed using the snow observations. The weighting for each estimate reflects the relative uncertainty of the estimate due to such factors as model bias and measurement error.

The point snow water equivalent data are interpolated into a gridded product using data derived during the calibration step. The average snow water equivalent estimates over subareas within each basin are used to update the snow water equivalent states of the conceptual snow model. The same methodology is used to generate gridded snow water equivalent over uncalibrated basins areas by applying parameters developed for calibrated basins over areas with analogous characteristics.

REFERENCES

Page, D.I., and Smith, G.F., (1993), "National weather service operational river forecasting in a UNIX environment," Engineering Hydrology, Kuo, C.Y. (Ed.), ASCE, pp. 838-843.