# Presentation: 149100

## BEGIN

- Overview of Models & Modeling Concepts

## 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

## 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

## 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.....

## 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?

## Small Scale -vs.- Large Scale

- Basin scale :  Muddy Run to Mississippi!
- What components are important?
- What would change for small or large basins?

## 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!

## 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!

## 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!

## 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.

## 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!

## 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...

## 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.**

## What is ESP?

## 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.

## General Goal of Most Models

**Process**

**OUTPUT**

- INPUT

## General Goal of Most Hydrologic Models

**Basin Process Representation**

**Infiltration**
**Excess Precip.**
**Interception**
**Storage**

**Precipitation**

**Hydrologic**
**Phenomena**

**We must begin to think of the basin as a “whole”**

## General Goal of Most Continuous Simulation Hydrologic Models

**Basin Process Representation**

**Infiltration**
**Excess Precip.**
**Interception**
**Storage**

**Precipitation- Time Series**

**Hydrologic Quantities- Time Series**

**While the process is continuous – we often represent it in discrete fashion!**

## Discrete Representations

- A continuous storm represented as discrete intervals.

## The Basic Process....

**Excess Precip. Model**

**Excess Precip.**

**Excess Precip****.**

**Runoff Hydrograph**

**Runoff Hydrograph**

**Stream and/or Reservoir “Routing”**

**Downstream Hydrograph**

**Basin “Routing” UHG Methods**

- Necessary for a single basin

## From A Basin View

**Excess Precip. Model**

**Excess Precip****.**

**Basin “Routing”**
**Unit Hydrograph**

**Stream “Routing”**

**Runoff Hydrograph**

## Models vs. Systems

- Let’s Talk
- What is it to you?

## Forecast System Elements

- Data Collection Networks

- Data Storage

- Data Preprocessors

- Computer Model(s)

- Forecast
- System

- The Forecast

- _Other Items:_
- Maintenance
- Training
- Etc...

## The Various Models

- Precipitation (QPF, etc...)
- Data Preprocessors (e.g. precipitation)
- Runoff
- Transformation (hydrograph out)
- Reservoir Routing (hydrograph out)
- Stream Routing (hydrograph out)

## END

- Overview of Models & Modeling Concepts