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Lecture – 3: Areal Estimation of Precipitation 1. Introduction: One important aspect of hydrologic modeling is the estimation of the total precipitation and its distribution within a watershed. This problem is commonly referred to as “areal estimation of precipitation” and is best described as follows: Given the coordinates of m precipitation stations along with their respective recorded precipitation values ( i P; i =1,…, m ), how can we determine the area-averaged ( avg P ) precipitation from these limited stations? This problem is illustrated below, where avg P across the entire basin has to be estimated from measured 1 P , 2 P , 3 P , and 4 P . S1 S2 S3 S4 x y Outflow Point Basin Precipitation Gaging Station We will discuss four methods: 1) Arithmetic Average, 2) Theissen Polygons, 3) Isohyetal Method, and 4) Grid Method.

Lecture 04 hydrologic measuremnts_areal estimation of precipitation

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Page 1: Lecture 04 hydrologic measuremnts_areal estimation of precipitation

Lecture – 3: Areal Estimation of Precipitation

1. Introduction:

One important aspect of hydrologic modeling is the estimation of the total precipitationand its distribution within a watershed. This problem is commonly referred to as “arealestimation of precipitation” and is best described as follows:

Given the coordinates of m precipitation stations along with their respective recordedprecipitation values ( iP ; i =1,…, m ), how can we determine the area-averaged ( avgP )precipitation from these limited stations?

This problem is illustrated below, where avgP across the entire basin has to be estimatedfrom measured 1P , 2P , 3P , and 4P .

S1

S2

S3S4

x

y

OutflowPoint

BasinPrecipitationGaging Station

We will discuss four methods:

1) Arithmetic Average, 2) Theissen Polygons, 3) Isohyetal Method, and 4) Grid Method.

Page 2: Lecture 04 hydrologic measuremnts_areal estimation of precipitation

2. Arithmetic Average:

The simplest approach is to assume that

443211 PPPP

m

PP

m

ii

avg+++==

∑= ;

This method will give reasonable results if the variability among iP is not too large. A“rule of thumb” is that if the standard deviation of iP is < 10% of avgP , then the arithmeticaverage will be an accurate estimator of avgP .

The standard deviation ( pσ ) is given by

( )m

PPm

iavgi

p

∑=

−= 1

2

σ

where avgP is given by the arithmetic average.

Hence, the arithmetic average will be accurate when avg

p

<0.1.

3. Theissen Polygons:

The Theissen polygon method assumes that each precipitation gage does not get the sameweight as in the arithmetic method.

∑=

=m

iiiavg PwP

1

where ∑=

m

iiw

1

=1. The Theissen polygon method REDUCES to the arithmetic method if

mwi

1= .

In the Theissen polygon method,

T

ii A

Aw = ; where

Page 3: Lecture 04 hydrologic measuremnts_areal estimation of precipitation

TA = Total basin or watershed area.

iA = Area defined by the Theissen polygons.

To determine iA , use the following procedure:

1. Join adjacent station locations with straight lines2. Take the PERPENDUCALR BISECTORS to those lines.3. Define the polygons bounding each station and compute its area.

S1

S2

S3S4

x

y

OutflowPoint

BasinPrecipitationGaging Station

A3

A1

A2

A4

If we apply this algorithm to each of the example shown in the INTRODUCTIONsection, we obtain the above figure. The areas 1A … 4A are shaded. The total area is

4321 AAAAAT +++= .

How to compute the polygon areas becomes a major challenge in this method.

4. Isohyetal Method

The basic formulation is also

∑=

=m

iiiavg PwP

1

, where ∑=

m

iiw

1

=1

but the weights are defined by the contour map area as shown below and iP is therepresentative contour.

Page 4: Lecture 04 hydrologic measuremnts_areal estimation of precipitation

S1

S2

S3S4

x

y

OutflowPoint

BasinPrecipitationGaging Station

300400

500

600A1 A2

Tavg A

AAP

....2

400300300 21 ++×+×=

where the 300, 400, …. are contour lines of precipitation.