2 on Uncertainty Analysis and Parameter Estimation urvey

18
Annual Report by Work Group 2 Annual Report by Work Group 2 on Uncertainty Analysis and Parameter Estimation Parameter Estimation Tom Nicholson, U.S. Nuclear Regulatory Commission M Hill USG l i lS Mary Hill, U.S. Geological Survey 2012 ISCMEM Annual Public Meeting November 9 2012 November 9, 2012 USGS - Reston, VA 1

Transcript of 2 on Uncertainty Analysis and Parameter Estimation urvey

Page 1: 2 on Uncertainty Analysis and Parameter Estimation urvey

Ann

ualR

epor

tby

Wor

kG

roup

2A

nnua

l Rep

ort b

y W

ork

Gro

up 2

on U

ncer

tain

ty A

naly

sis

and

Para

met

erEs

timat

ion

Para

met

er E

stim

atio

nTo

m N

icho

lson

, U.S

. Nuc

lear

Reg

ulat

ory

Com

mis

sion

M

Hill

US

Gl

ilS

Mar

y H

ill, U

.S. G

eolo

gica

l Sur

vey

2012

ISC

ME

M A

nnua

l Pub

lic M

eetin

gN

ovem

ber9

2012

Nov

embe

r 9, 2

012

US

GS

-R

esto

n, V

A

1

Page 2: 2 on Uncertainty Analysis and Parameter Estimation urvey

Out

line

•W

ork

Gro

up 2

(WG

2) O

bjec

tive

and

Goa

ls

•M

embe

rs a

nd P

artic

ipan

ts

•Ac

tiviti

esan

dTe

chni

calP

roje

cts

•Ac

tiviti

es a

nd T

echn

ical

Pro

ject

s

•Se

min

ars

at th

e W

G2

Mee

tingsg

•M

etho

dolo

gies

, Too

ls a

nd A

pplic

atio

ns

•Fo

rwar

d St

rate

gy

2•

Rec

omm

enda

tions

for F

Y201

3

Page 3: 2 on Uncertainty Analysis and Parameter Estimation urvey

Wor

k G

roup

Obj

ectiv

e

Cdi

ti

dh

dt

d

Coo

rdin

ate

ongo

ing

and

new

rese

arch

con

duct

ed

by U

.S. F

eder

al a

genc

ies

on:

tti

tipa

ram

eter

est

imat

ion

unce

rtain

ty a

sses

smen

ti

fi

ld

lid

in s

uppo

rt of

env

ironm

enta

l mod

elin

g an

d ap

plic

atio

ns

Ft

ti

dt

hi

Fo

cus

on s

trate

gies

and

tech

niqu

es

Incl

udes

sen

sitiv

ity a

naly

sis

Wh

id

dhi

hibj

i?

Wha

t is

need

ed to

ach

ieve

this

obje

ctive

?C

oord

inat

ion

of re

sear

ch s

taff

and

thei

r man

agem

ent

thffi

it

dt

td

fli

itd

3

thru

effi

cien

t and

targ

eted

use

of o

ur li

mite

d re

sour

ces.

Page 4: 2 on Uncertainty Analysis and Parameter Estimation urvey

Wor

k G

roup

Goa

ls•

Basi

cs:

B

th

l

Dev

elop

a c

reat

ive,

col

labo

rativ

e en

viro

nmen

t to

adva

nce

pa

ram

eter

est

imat

ion

in th

e co

ntex

t of m

odel

dev

elop

men

t .

sour

ces

of u

ncer

tain

ty in

the

cont

ext o

f mod

el p

redi

ctio

ns.

Bat

ch s

cale

(0

.01m

)

Cl

l

Dev

elop

a c

omm

on te

rmin

olog

y.

Iden

tify

inno

vativ

e ap

plic

atio

ns.

Col

umn

scal

e (0

.1 m

)

•Ex

istin

g To

ols:

Ide

ntify

, eva

luat

e, a

nd c

ompa

re a

vaila

ble

anal

ysis

stra

tegi

es, t

ools

and

sof

twar

e.

Inte

rmed

iate

sc

ale

(2m

)

•N

ew T

ools

: D

evel

op, t

est,

and

appl

y ne

w th

eorie

s an

d m

etho

dolo

gies

.E

lect

rical

C

ondu

ctiv

ity

Trac

er te

st s

cale

(1

-3m

)

•Ex

chan

ge:

Faci

litat

e ex

chan

ge o

f tec

hniq

ues

and

idea

s th

ru t

elec

onfe

renc

es, t

echn

ical

wor

ksho

ps, p

rofe

ssio

nal

But

ler e

t al

Geo

phys

ics

(2-2

00m

)

4

mee

tings

, int

erac

tion

with

oth

er W

Gs

and

ISC

MEM

Web

site

link

s: h

ttps:

//iem

hub.

org/

grou

ps/is

cmem

. P

lum

e sc

ale

(200

0m)

Page 5: 2 on Uncertainty Analysis and Parameter Estimation urvey

Mem

bers

and

Par

ticip

ants

from

U.S

. Fed

eral

age

ncie

s,un

iver

sitie

s, a

nd in

dust

ry

•To

m N

icho

lson

, NR

C, c

o-C

hair

•M

ary

Hill

, US

GS

, co-

Cha

ir•

Todd

And

erso

nD

OE

•Y

akov

Pac

heps

ky, U

SD

A-A

RS

•To

m P

uruc

ker,

EP

A-A

then

s•

Yor

amR

ubin

UC

Ber

kele

yTo

dd A

nder

son,

DO

E•

Tom

my

Boh

rman

n, E

PA

•G

ary

Cur

tis, U

SG

S•

Bru

ce H

amilt

on, N

SF

Yor

am R

ubin

, UC

Ber

kele

y•

Bria

n S

kahi

ll, U

SA

CO

E•

Mat

t Ton

kin,

SS

PA

•G

ene

Whe

lan

EP

AA

then

s•

Gen

e W

hela

n, E

PA

-Ath

ens

•S

teve

Yab

usak

i, P

NN

L•

Min

g Y

e, F

lorid

a S

tate

U•

Min

gZh

uD

OE

•M

ing

Zhu,

DO

E•

Larr

y D

esch

aine

, Hyd

roG

eolo

gic,

In

c.•

Bor

is F

aybi

shen

ko, L

BN

Ly

,•

Pie

rre G

lynn

, US

GS

•P

hilip

Mey

er, P

NN

L•

Can

dida

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t, E

PA

5

•D

ebra

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nhar

t, N

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•Y

ou?

Page 6: 2 on Uncertainty Analysis and Parameter Estimation urvey

Act

iviti

es: C

onfe

renc

e S

essi

ons

•20

11 F

all A

GU

: Mar

y H

ill, W

G2

Co-

Cha

ir or

gani

zed

sess

ion

“Ut

it

At

Oti

iti

dS

itiit

Al

ii

“Unc

erta

inty

Ass

essm

ent,

Opt

imiz

atio

n, a

nd S

ensi

tivity

Ana

lysi

s in

In

tegr

ated

Hyd

rolo

gic

Mod

elin

g as

App

licat

ion

of H

ydro

info

rmat

ics.

•20

11N

SF

Sta

tistic

alan

dA

pplie

dM

athe

mat

ical

Sci

ence

sIn

stitu

te•

2011

NS

F S

tatis

tical

and

App

lied

Mat

hem

atic

al S

cien

ces

Inst

itute

(S

AM

SI):

WG

2 C

o-C

hair

M. H

ill c

o-or

gani

zed

“Wor

ksho

p on

U

ncer

tain

ty in

the

Geo

scie

nces

,” R

esea

rch

Tria

ngle

Par

k, N

C

•20

12 S

ocie

ty o

f Tox

icol

ogy/

EP

A “C

onte

mpo

rary

Con

cept

s in

To

xico

logy

Wor

ksho

p” W

G2

Co-

Cha

ir T.

Nic

hols

on p

rese

nted

in

vite

dpa

per

volu

ntee

red

post

eran

dpa

rtici

pate

din

tech

nica

lin

vite

d pa

per,

volu

ntee

red

post

er, a

nd p

artic

ipat

ed in

tech

nica

l se

ssio

ns. F

ocus

ed o

n ex

posu

re, d

ose-

resp

onse

, eco

syst

em

impa

cts,

life

cyc

le/c

ost-b

enef

it, a

nd in

form

atio

n te

chno

logy

.

6

Page 7: 2 on Uncertainty Analysis and Parameter Estimation urvey

Act

iviti

es: C

onfe

renc

e S

essi

ons

•20

12 F

all A

GU

: Co-

chai

r Mar

y H

ill o

rgan

ized

ses

sion

“Com

plex

ity,

yg

py,

Fals

ifiab

ility

, Tra

nspa

renc

y, a

nd U

ncer

tain

ty in

Env

ironm

enta

l M

odel

ing”

•20

12 G

eolo

gica

l Soc

iety

of A

mer

ica

Ann

ual M

eetin

g: C

o-C

hair

Tom

Nic

hols

on p

rese

nted

invi

ted

pape

r co-

auth

ored

with

M

arH

illW

G2

Co

Cha

iron

“Fed

eral

Wor

kG

rop

onU

ncer

tain

tM

ary

Hill

, WG

2 C

o-C

hair

on “F

eder

al W

ork

Gro

up o

n U

ncer

tain

ty

Ana

lysi

s an

d P

aram

eter

Est

imat

ion”

in te

chni

cal s

essi

on “T

103.

G

roun

d-W

ater

Mod

el C

alib

ratio

n an

d U

ncer

tain

ty A

naly

sis”

i

db

Mi

YFl

idS

tt

Ui

itd

WG

2b

orga

nize

d by

Min

g Y

e, F

lorid

a S

tate

Uni

vers

ity a

nd W

G2

mem

ber.

7

Page 8: 2 on Uncertainty Analysis and Parameter Estimation urvey

Act

iviti

es: T

elec

onfe

renc

es

We

cond

uct

tele

conf

eren

ces

to:

Trac

er a

pplic

atio

n ar

ea

Obs

erva

tion

wel

l

We

cond

uct

tele

conf

eren

ces

to:

•re

view

and

dis

cuss

ong

oing

rese

arch

stu

dies

an

d so

ftwar

e de

velo

pmen

t•

form

ulat

e pr

opos

als

for f

ield

app

licat

ions

Gro

undw

ater

Uns

atur

ated

soi

l

pp

pp

Wha

t m

easu

re-

men

tsw

ould

men

ts w

ould

he

lp

disc

rimin

ate

betw

een

two

mod

els?

mod

els?

from

2/

22/2

012

sem

inar

byse

min

ar b

y Ya

kov

Pac

heps

ky,

US

DA

, on

mod

el

8

mod

el

abst

ract

ion

Page 9: 2 on Uncertainty Analysis and Parameter Estimation urvey

Act

iviti

es: T

elec

onfe

renc

es

We

cond

uct

tele

conf

eren

ces

to:

•re

view

and

dis

cuss

ong

oing

rese

arch

st

udie

s an

d so

ftwar

e de

velo

pmen

t•

form

ulat

epr

opos

als

forf

ield

appl

icat

ions

form

ulat

e pr

opos

als

for f

ield

app

licat

ions

How

doe

s m

oist

ure

trave

l in

the

atm

osph

ere

and

lead

to b

ig s

torm

s?

9fro

m 9

/21/

2012

sem

inar

by

Mik

e D

ettin

ger,

US

GS

, on

atm

osph

eric

rive

rs

Page 10: 2 on Uncertainty Analysis and Parameter Estimation urvey

Sem

inar

s at

WG

2 Te

leco

nfer

ence

s in

FY

2012

•M

ulti

Sca

leA

sses

smen

tofP

redi

ctio

nU

ncer

tain

tyin

•M

ulti-

Sca

le A

sses

smen

t of P

redi

ctio

n U

ncer

tain

ty in

C

oupl

ed R

eact

ive

Tran

spor

t Mod

els

by G

ary

P. C

urtis

, U

SG

S; M

ing

Ye,

Flo

rida

Sta

te U

nive

rsity

; Phi

lip D

. Mey

er

and

Ste

ve B

. Yab

usak

i, P

NN

L to

dis

cuss

the

use

of a

B

ayes

ian

mod

el a

vera

ging

met

hod

to a

sses

s pa

ram

etric

an

d m

odel

unc

erta

inty

for i

mpr

ovem

ent o

f pre

dict

ive

yp

ppe

rform

ance

.

•B

riefin

g on

the

Che

rnob

yl C

oolin

g P

ond

Dec

omm

issi

onin

g an

d R

emed

iatio

n P

ropo

sal (

ISC

ME

M C

ase

Stu

dy fo

r Im

prov

ing

Sci

entif

icB

asis

forM

ultim

edia

Env

ironm

enta

lIm

prov

ing

Sci

entif

ic B

asis

for M

ultim

edia

Env

ironm

enta

l M

odel

ing

and

Ris

k A

sses

smen

t) by

Bor

is F

aybi

shen

ko,

Law

renc

e B

erke

ley

Nat

iona

l Lab

orat

ory,

to p

rovi

de

com

men

tsan

dqu

estio

nsfo

rthe

inte

rnat

iona

lmee

ting

in10

com

men

ts a

nd q

uest

ions

for t

he in

tern

atio

nal m

eetin

g in

K

iev,

Ukr

aine

on

rem

edia

tion

deci

sion

-mak

ing.

Page 11: 2 on Uncertainty Analysis and Parameter Estimation urvey

Che

rnob

yl C

oolin

g Po

nd D

ecom

mis

sion

ing

and

Rem

edia

tion

Prop

osal

(IS

CM

EM

Cas

e S

tudy

for I

mpr

ovin

g S

cien

tific

Bas

is fo

r Mul

timed

ia

Ei

tlM

dli

dR

ik

At)

bB

iF

bih

kE

nviro

nmen

tal M

odel

ing

and

Ris

k A

sses

smen

t) by

Bor

is F

aybi

shen

ko,

Law

renc

e B

erke

ley

Nat

iona

l Lab

orat

ory

on O

ctob

er 2

011.

11

Page 12: 2 on Uncertainty Analysis and Parameter Estimation urvey

Sem

inar

s at

WG

2 Te

leco

nfer

ence

s(c

ontin

ued)

(con

tinue

d)•

Trai

ning

Ran

ge E

nviro

nmen

tal E

valu

atio

n an

d C

hara

cter

izat

ion

Sys

tem

(TR

EE

CS

) by

B. J

ohns

on, M

. D

ortc

h an

d B

. Fay

bish

enko

to d

iscu

ss a

n ad

vanc

ed s

patia

lly

inte

grat

ed, m

ulti-

scal

e, m

ulti-

path

way

sim

ulat

ion

capa

bilit

y fo

reva

luat

ion

ofdi

strib

uted

sour

ces

ofco

ntam

inan

tsfro

mfo

r eva

luat

ion

of d

istri

bute

d so

urce

s of

con

tam

inan

ts fr

om

both

on-

site

as

wel

l as

off-s

ite s

ourc

es w

ith a

pplic

atio

ns to

th

e B

orsc

hi W

ater

shed

, and

milit

ary

train

ing

rang

e.

•Th

e “H

ow” o

f Env

ironm

enta

l Mod

elin

g: T

owar

d E

nhan

ced

Tran

spar

ency

and

Ref

utab

ility

byM

ary

Hill,

US

GS

,to

Tran

spar

ency

and

Ref

utab

ility

by M

ary

Hill

, US

GS

, to

disc

uss

adva

ntag

es o

f est

ablis

hing

a b

ase

set o

f mod

el

sens

itivi

ty a

naly

sis

and

unce

rtain

ty e

valu

atio

n m

easu

res,

to

beus

edal

ong

with

any

othe

rper

form

ance

mea

sure

sof

12

be u

sed

alon

g w

ith a

ny o

ther

per

form

ance

mea

sure

s of

in

tere

st.

Page 13: 2 on Uncertainty Analysis and Parameter Estimation urvey

M

odel

Ade

quac

y•H

ow t

o in

clud

e m

any

data

type

s w

ith

vari

able

qua

lity?

Err

or-b

ased

wei

ghtin

g an

d SO

O,M

OO

*

Sens

itiv

ity

and

Unc

erta

inty

•Is

mod

el m

isfit

/ove

rfit

a pr

oble

m?

Are

pri

or k

now

ledg

e an

d da

ta s

ubse

ts in

cons

iste

nt?

Vari

ance

of w

eigh

t-st

anda

rdiz

ed re

sidu

als,

resi

dual

gra

phs

and

spac

e/tim

e pl

ots,

MO

O*

•How

non

linea

r is

the

prob

lem

? M

odifi

ed B

eale

’s m

easu

re, E

xplo

re o

bjec

tive

func

tion*

, TSD

E*

•Wha

t par

amet

ers

can

be e

stim

ated

wit

h th

e ob

serv

atio

ns?

b/SD

b, C

SS&

PCC,

SV,

OAT

*, D

oE*,

FA

ST*,

M

CF(R

SA)*

Sobo

l’*

MCM

C*IR

*

•Whi

ch p

aram

eter

s ar

e im

port

ant

and

unim

port

ant

to p

redi

ctio

ns?

PSS,

FAST

*•H

owce

rtai

nar

eth

epr

edic

tion

s?

Para

met

ers

Obs

erva

tion

sPr

edic

tion

sPa

ram

eter

sSe

nsit

ivit

y an

d U

ncer

tain

ty

MCF

(RSA

)*, S

obol

,* M

CMC*

, IR*

•Whi

ch o

bser

vati

ons

are

impo

rtan

t an

d un

impo

rtan

t to

pa

ram

eter

s?Le

vera

ge, C

ook’

s D

,CV*

, MO

O*

•Are

any

par

amet

ers

dom

inat

ed b

y on

e ob

serv

atio

n an

dth

usit

ser

ror?

Leve

rage

DFB

ETA

SCV

*

•How

cer

tain

are

the

pred

icti

ons?

z/SD

z, Pr

edic

tion

unce

rtai

nty

inte

rval

s# , M

MA

*•W

hich

par

amet

ers

cont

ribu

te m

ost

and

leas

t to

pre

dict

ion

unce

rtai

nty?

PPR

,FA

ST*,

Sob

ol’,*

M

CMC*

Obs

erva

tion

s Pr

edic

tion

s•W

hich

exis

ting

and

pote

ntia

lobs

erva

tion

sar

eim

port

ant

toth

epr

edic

tion

s?O

PRCV

*

and,

thu

s, it

s er

ror?

Lev

erag

e, D

FBET

AS,

CV*

•How

cer

tain

are

the

para

met

er v

alue

s? b

/SD

b,

Para

met

er u

ncer

tain

tyin

terv

als#

MCM

C*

•Whi

ch e

xist

ing

and

pote

ntia

l obs

erva

tion

s ar

e im

port

ant

to th

e pr

edic

tion

s? O

PR, C

V•W

hich

mod

els

in M

MA

are

like

ly to

pro

duce

the

bes

t pr

edic

tion

s?

For

indi

vidu

al m

odel

eva

luat

ions

:AIC

, AIC

c, B

IC, K

IC, C

V*

13

Com

puta

tiona

lly fr

ugal

met

hods

(ofte

n 10

s to

1,0

00s

of m

odel

runs

)C

ompu

tatio

nally

dem

andi

ng m

etho

ds (o

ften

10,0

00s

to 1

,000

,000

s of

mod

el ru

ns)*

Page 14: 2 on Uncertainty Analysis and Parameter Estimation urvey

Met

hodo

logi

es, T

ools

and

App

licat

ions

•P

roce

edin

gs o

f the

Inte

rnat

iona

l Wor

ksho

p on

Unc

erta

inty

, S

ensi

tivity

and

Par

amet

er E

stim

atio

n fo

r Mul

timed

ia

yE

nviro

nmen

tal M

odel

ing

(NU

RE

G/C

P-0

187)

•Jo

intU

nive

rsal

Para

met

erId

enTi

ficat

ions

and

•Jo

int U

nive

rsal

Par

amet

er Id

enTi

ficat

ions

and

Ev

alua

tion

of R

elia

bilit

y A

pplic

atio

n Pr

ogra

mm

ing

Inte

rfac

e (J

UPI

TER

API

) for

pro

gram

min

g co

mpu

ter

prog

ram

sde

sign

edto

anal

yze

proc

ess

mod

els

join

tpr

ogra

ms

desi

gned

to a

naly

ze p

roce

ss m

odel

s, jo

int

US

GS

and

EP

A p

roje

ct (B

anta

and

oth

ers,

200

6)

•H

ydro

logi

c C

once

ptua

l Mod

el, P

aram

eter

and

Sce

nario

U

ncer

tain

ty M

etho

dolo

gy, c

oope

rativ

e pr

ojec

t by

the

Uni

vers

ity o

f Ariz

ona,

PN

NL

and

NR

C s

taff

(NU

RE

G/C

R- 14

y,

(69

40)

Page 15: 2 on Uncertainty Analysis and Parameter Estimation urvey

Met

hodo

logi

es, T

ools

and

App

licat

ions

(con

tinue

d)(c

ontin

ued)

•M

odel

Abs

tract

ion

Tech

niqu

es fo

r det

erm

inin

g an

d id

entif

ying

conc

eptu

alm

odel

stru

ctur

ean

dpa

ram

eter

iden

tifyi

ng c

once

ptua

l mod

el s

truct

ure

and

para

met

er

estim

atio

n st

rate

gies

, joi

nt U

SD

A/A

gric

ultu

ral R

esea

rch

Ser

vice

and

NR

C s

taff

(NU

RE

G/C

R-7

026)

•A

ppro

ache

s in

Hig

hly

Par

amet

eriz

ed In

vers

ion:

PE

ST+

+,

a P

aram

eter

ES

Tim

atio

n co

de o

ptim

ized

for l

arge

p

gen

viro

nmen

tal m

odel

s by

D. W

elte

r, J.

Doh

erty

, R. H

unt,

C. M

uffe

ls, M

. Ton

kin,

and

W. S

chre

uder

. An

obje

ct-

orie

nted

para

met

eres

timat

ion

code

that

inco

rpor

ates

orie

nted

par

amet

er e

stim

atio

n co

de th

at in

corp

orat

es

bene

fits

of o

bjec

t-orie

nted

pro

gram

min

g te

chni

ques

for

solv

ing

larg

e pa

ram

eter

est

imat

ion

mod

elin

g pr

oble

ms.

(U

SG

ST

hi

dM

thd

7C

5)15

(US

GS

Tec

hniq

ues

and

Met

hods

: 7-C

5)

Page 16: 2 on Uncertainty Analysis and Parameter Estimation urvey

Forw

ard

Stra

tegy

Ene

rgiz

e th

e sc

ienc

e an

d te

chno

logy

thru

cl

oser

linka

geto

deci

sion

mak

ing:

clos

er li

nkag

e to

dec

isio

n m

akin

g:

be

tter u

nder

stan

d th

e m

etho

ds b

eing

use

d in

pa

ram

eter

est

imat

ion

and

unce

rtain

ty a

naly

ses

es

tabl

ish

a ba

se s

et o

f mod

el s

ensi

tivity

ana

lysi

s an

d un

certa

inty

eva

luat

ion

mea

sure

s, in

add

ition

to

the

othe

r per

form

ance

mea

sure

s

ddi

fft

thd

iti

l

use

and

com

pare

diff

eren

t met

hods

in p

ract

ical

si

tuat

ions

16

Page 17: 2 on Uncertainty Analysis and Parameter Estimation urvey

Rec

omm

enda

tions

for F

Y201

3•

Ass

istd

evel

opm

enta

ndcr

eatio

nof

othe

rwor

king

grou

ps•

Ass

ist d

evel

opm

ent a

nd c

reat

ion

of o

ther

wor

king

gro

ups

–Ta

ke a

dvan

tage

of t

he re

leva

nce

of u

ncer

tain

ty a

nd p

aram

eter

es

timat

ion

to a

ll en

viro

nmen

tal m

odel

ing

and

mon

itorin

g fie

lds.

–D

evel

opan

dco

nduc

tjoi

ntIS

CM

EM

tele

conf

eren

ces

–D

evel

op a

nd c

ondu

ct jo

int I

SC

ME

M te

leco

nfer

ence

s •

WG

1 (S

oftw

are

Sys

tem

Des

ign;

des

ign

of u

ncer

tain

ty a

nd p

aram

eter

es

timat

ion

softw

are

and

dat

a fu

sion

)•

WG

3(R

eact

ive

Tran

spor

tMod

els

and

Mon

itorin

g;su

ppor

tdec

isio

nW

G3

(Rea

ctiv

e Tr

ansp

ort M

odel

s an

d M

onito

ring;

sup

port

deci

sion

m

akin

g)

–A

ct a

s an

incu

bato

r to

build

sup

port

for n

ew id

eas

•P

ropo

sed

WG

on

mon

itorin

g ba

sed

on th

e im

porta

nce

of m

onito

ring

pG

gp

gto

unc

erta

inty

and

par

amet

er e

stim

atio

n, a

nd v

isa

vers

a•

Spo

nsor

tech

nica

l wor

ksho

ps o

n en

dors

ed s

tudi

es

–U

Sst

udie

s:N

atur

itaC

O;H

anfo

rd-3

00A

rea;

OP

E3

Bel

tsvi

lleM

DU

.S. s

tudi

es: N

atur

ita, C

O; H

anfo

rd30

0 A

rea;

OP

E3

Bel

tsvi

lle, M

D

–In

tern

atio

nal s

tudy

on

mon

itorin

g an

d re

med

iatin

g C

hern

obyl

Coo

ling

Pon

d•

ISC

ME

MW

ebsi

te

17

ISC

ME

M W

ebsi

te

–U

se E

PA

’s ie

mH

UB

to e

nhan

ce In

form

atio

n Tr

ansf

er o

f Tec

hnic

al

Rep

orts

and

Dat

a S

ourc

es

Page 18: 2 on Uncertainty Analysis and Parameter Estimation urvey

http

s://i

emhu

b.or

g/gr

oups

/iscm

em

18