BEGIN

1. BEGIN Overview of Models & Modeling Concepts

2. What is a Model? • It is a representation of a system. • Generally, it is a simplified representation of a complex system….. • Why simplified and complex? • Often used to answer “what if’s” • Used for prediction and forecasting

3. Hydrologic Processes Modeled • Rainfall-Runoff – the basin runoff process due to a precipitation event – or lack of precipitation! • Channel Processes – Open channel flow • Pipe or Conduit Flow – Generally pressurized flow in closed conduits. • Sediment – Aggradation and degradation processes

4. Model Classifications • There are many classification schemes. • Many models or models routines fall into multiple categories. • Hydrologic model classifications are generally based on the method of representation of the hydrologic cycle or a component of the hydrologic cycle. • Many (if not most) hydrologic models and tools fall into multiple model classifications…..

5. Short Term –vs.- Long Term • Short Term - hours to days maybe a week or so… • Long Term – Weeks to months to years. Often focusing on volumes only. • What components are or are not important for the short and long term modeling time frames?

6. Small Scale -vs.- Large Scale • Basin scale : Muddy Run to Mississippi! • What components are important? • What would change for small or large basins?

7. Forecasting –vs.- Predicting • Forecasting in the hydrometeoroligical sense, is a prior estimation of future hydromet. phenomena in a real-time mode… • Prediction is often thought of as a design mode. For example one would predict the magnitude of a 100-year event for the purposes of designing a bridge or dam. • A forecast is essentially a prediction!

8. Physical –vs.- Mathematical • A very basic and simplistic classification: • Physical attempt to simulate the actual physical processes, often by similitude (i.e. – a 1:10 physical model of a stream channel. • Mathematical models utilize mathematical statements (equations) to represent. • Mathematical equations may be based on physical characteristics!

9. Continuous –vs.- Discrete • Continuous models are often referred to as “continuous simulation” models because they represent a continuous process in nature – i.e. the runoff process which leads to a streamflow hydrograph. The forecasting process basically requires a continuous model. • Discrete models are often referred to as “single-event” models. These models are most often used in a predictive mode. • Many continuous models or attempts to model a continuous function are broken into discrete time steps!

10. Descriptive –vs.- Conceptual • Descriptive models account for observed phenomena utilizing empiricism and basic fundamentals, while, • Conceptual models tend to rely on theory to represent a process rather than to actually represent the physical process – for example a model that is based on probability theory.

11. Lumped –vs.- Distributed • Lumped models do not allow for variation in model states and parameters throughout the system. • Distributed models allow for or account for behavior variations throughout the system. Often on point to point basis. • Subdividing a watershed is an attempt to make a semi-distributed model!

12. Deterministic –vs.- Stochastic • Deterministic models generally use inputs that are known with a reasonable degree of certainty, whereas, • Stochastic models may have input that is generated or synthesized – perhaps from a probability distribution – i.e. ESP…

13. What is ESP? • Ensemble Streamflow Production (ESP) • Inputs the current moisture level of soil and the precipitation from previous years into a model which produces the diagram seen above. • For example, the moisture content of today would be inputted, along with the precipitation that occurred over the next week, but 50 years ago. • This would then be repeated for 49 years ago, 48, etc., and then an average discharge based on history can be determined.

14. What is ESP?

15. Models Overview • Many models are combinations of the aforementioned types. • For example: a conceptual or probabilistic model may use the output from a continuous descriptive model to produce a forecast.

16. General Goal of Most Models OUTPUT Process INPUT

17. General Goal of Most Hydrologic Models Infiltration Excess Precip. Interception Storage Basin Process Representation Precipitation Hydrologic Phenomena We must begin to think of the basin as a “whole”

18. General Goal of Most Continuous Simulation Hydrologic Models Infiltration Excess Precip. Interception Storage Basin Process Representation Precipitation- Time Series Hydrologic Quantities- Time Series While the process is continuous – we often represent it in discrete fashion!

19. Discrete Representations A continuous storm represented as discrete intervals.

20. The Basic Process…. Necessary for a single basin Excess Precip. Model Excess Precip. Basin “Routing” UHG Methods Runoff Hydrograph Excess Precip. Stream and/or Reservoir “Routing” Downstream Hydrograph Runoff Hydrograph

21. From A Basin View Excess Precip. Excess Precip. Model Runoff Hydrograph Basin “Routing” Unit Hydrograph Stream “Routing”

22. Models vs. Systems Let’s Talk What is it to you?

23. Forecast System Elements Data Collection Networks Data Storage Data Preprocessors Computer Model(s) Other Items: Maintenance Training Etc… Forecast System The Forecast

24. The Various Models • Precipitation (QPF, etc…) • Data Preprocessors (e.g. precipitation) • Runoff • Transformation (hydrograph out) • Reservoir Routing (hydrograph out) • Stream Routing (hydrograph out)

25. END Overview of Models & Modeling Concepts