+ All Categories
Home > Documents > Lecture I Hydrological modeling requirements for Water...

Lecture I Hydrological modeling requirements for Water...

Date post: 16-Jul-2018
Category:
Upload: doque
View: 215 times
Download: 0 times
Share this document with a friend
50
Center for Hydrometeorology and Remote Sensing, University of California, Irvine Ensuring Water in a Changing World The Abdus Salam ICTP Summer School on: Climate Impact Modeling for Developing Countries: Water, Agriculture & Health Trieste, Italy: Sept. 5 th – 16 th 2011 Lecture I Hydrological modeling requirements for Water Resources Applications - Model Issues Soroosh Sorooshian Center for Hydrometeorology and Remote Sensing University of California Irvine
Transcript

Center for Hydrometeorology and Remote Sensing, University of California, Irvine

Ensuring Water in a Changing World

The Abdus Salam ICTP Summer School on: Climate Impact Modeling for Developing Countries: Water, Agriculture & Health Trieste, Italy: Sept. 5th – 16th 2011

Lecture I Hydrological modeling requirements for Water

Resources Applications - Model Issues Soroosh Sorooshian

Center for Hydrometeorology and Remote Sensing University of California Irvine

Center for Hydrometeorology and Remote Sensing, University of California, Irvine

University of California Irvine (UCI) and Arizona (UA)

and many more …

CHRS & Affiliates: A truly International Team

Center for Hydrometeorology and Remote Sensing, University of California, Irvine

Two Primary Water Resources/Hydrology Challenges:

• Hydrologic Hazards ( Floods and Droughts) • Water Supply Requirements ( Quantity and Quality)

Center for Hydrometeorology and Remote Sensing, University of California, Irvine

Hydrologic Forecasting Needs: Flash Floods

Center for Hydrometeorology and Remote Sensing, University of California, Irvine

Droughts: The Other hydrologic Extreme

Center for Hydrometeorology and Remote Sensing, University of California, Irvine

Two Primary Water Resources/Hydrology Challenges:

• Hydrologic Hazards ( Floods and Droughts) • Water Supply Requirements ( Quantity and Quality)

Center for Hydrometeorology and Remote Sensing, University of California, Irvine

Projected Regions of Water Stress

Center for Hydrometeorology and Remote Sensing, University of California, Irvine

Increasing Population: Number of Mega Cities

Global Urban population 1970: ~37% 2010: ~53%

Projected Global Population: 8.3 Billion by 2025

Center for Hydrometeorology and Remote Sensing, University of California, Irvine

Distribution of Fresh Water Use

90.8 33.4%

17.1% 49.5%

460

7.0% 6.0%

87.0%

36.47 18.6%

22.0% 59.4%

117

60.0% 17.0%

23.0%

467.34

45.2%

13.1%

41.7%

380

4.0% 3.0%

93.0% Agriculture

Industry

Domestic

Fresh Water Use (109 Cubic Meters)

Water Source

Water Use

USA China India

Russia Japan Brazil

92% 6%

2%

70.3 Iran

Center for Hydrometeorology and Remote Sensing, University of California, Irvine

Primary Solution To Meet Hydrologic Extremes and Water Resources Needs

Engineering Approach: Control, Store, Pump and Transfer

Center for Hydrometeorology and Remote Sensing, University of California, Irvine

Hoover Dam

A Century of Water Resources Development: Engineering success

Central Arizona Project Aqueduct

Center for Hydrometeorology and Remote Sensing, University of California, Irvine

1800 1900

1950

Impact on Design and Operation of Global Infrastructure

2000

More than 70,000 Dams in the U.S.

Provided by: C. J. Vörösmarty

Center for Hydrometeorology and Remote Sensing, University of California, Irvine

Short Range Long Range

hours days weeks months seasons years decades

Required Hydrometeorologic Predictions

Forecast Requirements

Short-range Mid-range Long-range

Center for Hydrometeorology and Remote Sensing, University of California, Irvine

Short Range Long Range

hours days weeks months seasons years decades

Required Hydrometeorologic Predictions

Forecast Requirements

Mid-range Long-range

Center for Hydrometeorology and Remote Sensing, University of California, Irvine

A Key Consideration:

The Link Between Climate and Hydrology

Center for Hydrometeorology and Remote Sensing, University of California, Irvine

Global Warming And Hydrologic Cycle Connection

Heating

Temperature Evaporation

Water Holding Capacity

Atmospheric Moisture

Temperature oF Satu

rate

d Va

por P

ress

ure

t t+20

Green House Effect

Rain Intensity

Drought Flood

Flood Drought

Created by: Gi-Hyeon Park

Center for Hydrometeorology and Remote Sensing, University of California, Irvine

P

E

Qs

∆ Ss

∆ Sg Qg

Ig

Coupled Ocean-Atmosphere

Models

Mesoscale Models

SVATs

Hydrologic/Routing Models

Water Resources Applications

GEWEX

CLIVAR

Hydrologic Services

Water resources management agencies

From the Global- to Watershed-Scale

CLiC

Center for Hydrometeorology and Remote Sensing, University of California, Irvine

Hydroclimate Science and Hydrologic/Water Resources Engineering

Hydrologic/Hydraulic Routing, Water Resources Models

SCIENCE ENGINEERING

Hydrologic/Hydraulic and Water Resources Engineering

Hydroclimate Science

P

E

Qs

∆ Ss

∆ Sg Qg

Ig

Mesoscale Models

SVATs

GCMs

Center for Hydrometeorology and Remote Sensing, University of California, Irvine

River Basins and Watersheds

Continental Scale:

Watershed Scale: Where hydrology happens Where stakeholders exist

Different Scales Different Issues

Center for Hydrometeorology and Remote Sensing, University of California, Irvine

Short Range Long Range

hours days weeks months seasons years decades

Climate-Scale approaches to addressing hydrologic extremes

Forecast Requirements

Long-range

•Use of climate models: down-scaling and ensemble schemes •Traditional statistical hydrology methods:

Center for Hydrometeorology and Remote Sensing, University of California, Irvine

Prec

ipita

tion

p

redi

ctio

n

Time (years) Present Future 20 40 60 80

Climate Model Downscaling to Regional/Watershed Scales

Generation of Future Precipitation Scenarios

Center for Hydrometeorology and Remote Sensing, University of California, Irvine

Ensemble Approach Generation of Future Precipitation Scenarios

Center for Hydrometeorology and Remote Sensing, University of California, Irvine

Present Future 20 40 60 80 Time (years)

Prec

ipita

tion

p

redi

ctio

n

Present Future Time (years)

Flo

w

Generation of Future Runoff Scenarios

Downscaled Precipitation to Runoff Generation

Center for Hydrometeorology and Remote Sensing, University of California, Irvine

1 0.5 0.2 0.1 0.05 0.02 0.01 0.005 0.002 0.001 Probability of Exceedance

Return Period (Years) 1 2 5 10 20 50 100 200 500 1000

600

500

400

300

200

100

0

Dis

char

ge

(100

0 cf

s)

Alternative Approach to Climate Model Downscaling

traditional statistical hydrology methods

Center for Hydrometeorology and Remote Sensing, University of California, Irvine

Probability density function

Time (years) Present

Future

10 20 30 40 50 60 70 80 90 100 -100 -75 -50 -25 0

Flo

w (

m3 /s

ec)

Past

0255075

100125150175200225250

1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000Flo

w (m

3 /sec

)

Time (years)

Statistical Hydrology: “synthetic” stream flow Generation

Center for Hydrometeorology and Remote Sensing, University of California, Irvine

Brief Review of Rainfall

Runoff modeling:

Progress in Hydrologic Modeling

Center for Hydrometeorology and Remote Sensing, University of California, Irvine

Fundamental Law

Input Output

Change In Storage

I O

∆S

I – O =∆S

Center for Hydrometeorology and Remote Sensing, University of California, Irvine

Nature’s Way Terrain

Center for Hydrometeorology and Remote Sensing, University of California, Irvine

The Watershed

Area km2 12.78Perimeter km 19.344Min Elevation m 478.00Max Elevation m 1756.00Mean Elevation 930.34Max Flow Length 8.878

Center for Hydrometeorology and Remote Sensing, University of California, Irvine

Eva

pora

tion

(Oce

an)

Eva

potra

nspi

ratio

n

Pre

cipi

tatio

n

Pre

cipi

tatio

n

Pre

cipi

tatio

n

Sub

limat

ion

Eva

pora

tion

(Lak

es &

Res

ervo

irs)

Vap

or D

iffus

ion

Lake

Infil

tratio

n

Dee

p P

erco

latio

n

River

Aquifer

Eva

pora

tion

(Lan

d S

urfa

ce)

Vegetation

Interflow

Ponce, 1989

Center for Hydrometeorology and Remote Sensing, University of California, Irvine

Trace The Water Drop

Center for Hydrometeorology and Remote Sensing, University of California, Irvine

Distributed

Physically-based

API Model A

C

D

B

Lumped Conceptual

Distributed (Mike SHE)

VIC Model

Evolution of Hydrologic R-R Models

Center for Hydrometeorology and Remote Sensing, University of California, Irvine

MODEL

PARAMETER ESTIMATION

DATA

If the “World” of Watershed Hydrology Was Perfect!

Hydrologic Modeling: 3 Elements!

Center for Hydrometeorology and Remote Sensing, University of California, Irvine

Flow in Channels: How far can we go simplifying?

V = n-1 R2/3 S1/2

n – Manning Coefficient R – Hydraulic Radius S – Energy Slope

Center for Hydrometeorology and Remote Sensing, University of California, Irvine

Hydrologic Modeling

Center for Hydrometeorology and Remote Sensing, University of California, Irvine

Observed Lumped Model

Animation Assisted by: Q. Xia

Hydrologic Modeling: “Lumped”

Center for Hydrometeorology and Remote Sensing, University of California, Irvine

UCt

UM

LM

Streamflow

Rainfall

percolation

LCt

UK

LK

PD = f(Z, X)

A look into the “heart” of R-R Models

Percolation Process is the Core element in Partitioning the rain between the various stores

PD = f(Z, X)

Center for Hydrometeorology and Remote Sensing, University of California, Irvine

Free water

Tension water

Tension water

Percolation RATE=PBASE(1+ZPERC*DEFR REXP)

NWS Soil Moisture Accounting Model: SMA-NWSRFS

Nonlinear structure with large number of parameters

Center for Hydrometeorology and Remote Sensing, University of California, Irvine

1 2

3 4

6

1 2

A

B

4 3

5

Combination

Rou

ting

Runoff

“Semi-distributed” Hydrologic Models

Center for Hydrometeorology and Remote Sensing, University of California, Irvine

Observed Lumped Model Semi-Distributed Model

Animation Assisted by: Q. Xia

“Semi-distributed” Hydrologic Models

Center for Hydrometeorology and Remote Sensing, University of California, Irvine

Large basin

Sub-basin 4

Sub-basin 2

Sub-basin 1

Sub-basin 3

Suz

Srz qv Su

z Srz

qv Suz

Srz qv

Suz

Srz qv

Suz

Srz qv Su

z Srz

qv q

v qv

Suz

Srz qv

Suz

Srz qv

Suz

Srz qv

Suz

Srz qv

Suz

Srz qv

Suz

Srz qv

Suz

Srz qv

Suz

Srz qv

Suz

Srz qv

Suz

Srz qv

Suz

Srz qv

Suz

Srz qv

Suz

Srz qv

Suz

Srz qv

Suz

Srz qv

Suz

Srz qv

Suz

Srz qv

Suz

Srz qv

Suz

Srz qv

Suz

Srz qv

Suz

Srz qv

Suz

Srz qv

Suz

Srz qv

Suz

Srz qv

Suz

Srz qv

Suz

Srz qv

Suz

Srz qv

Suz

Srz qv

Suz

Srz qv

Suz

Srz qv

Suz

Srz qv

Suz

Srz qv

qv Suz

Srz qv

Suz

Srz qv

Suz

Srz qv

Suz

Srz qv

Suz

Srz qv

qv

Suz

Srz qv Su

z Srz

qv Suz

Srz qv

Sub-basin k Rek

qv

ai grid-cell i

qv

Suz

Srz qv Su

z Srz

qv

grid-cell i

qv

qv qv

Suz

Srz qv

Suz

Srz qv Su

z Srz

qv

Suz

Srz qv

Suz

Srz qv

SDi

Funada, 2004

Example of Distributed Model Appl. in large Basins

Center for Hydrometeorology and Remote Sensing, University of California, Irvine

Observed Lumped Model Semi-Distributed Model Distributed Model

Animation Assisted by: Q. Xia

Example of Distributed Model

Center for Hydrometeorology and Remote Sensing, University of California, Irvine

Excess

Loss

Partition precipitation Loss + Runoff Transform to outlet of

Sub-watershed Rout through channel

Center for Hydrometeorology and Remote Sensing, University of California, Irvine

Cross-Validation

Continued need for Some Form of Calibration

Model Complexity Matches

System Complexity

Underfitting Overfitting

Source: Gershenfeld, 1999

Calibration

Model Complexity

Erro

r

Center for Hydrometeorology and Remote Sensing, University of California, Irvine

Reviewing some recent model evaluation studies

Center for Hydrometeorology and Remote Sensing, University of California, Irvine

DMIP-1 Findings: In a Nutshell

No Major Difference between the performance

of Lumped and distributed models

Sacramento Model

DMIP 1 Results (From Reed et al., 2004)

Center for Hydrometeorology and Remote Sensing, University of California, Irvine

Recent Assessment of Seasonal Climate Forecasts

Livezey &Timofeyeva - BAMS, June 2008.

• “About the only time forecasts had any success predicting precipitation was for winters with an El Nino or a La Nina”

Quoting from Science, Vol. 321, 15th August 2008

Drought Predictability Sp

atia

l Sca

les

Time Scales Minute Day Week Season 1 yr 10 yrs 100 yrs

1 km

10 km

100 km

1000 km

10000 km

User Needs Current Skill

Provided by Siegfried Schubert 2011

Center for Hydrometeorology and Remote Sensing, University of California, Irvine

Recent Assessment of Climate Models

Regional trends in extreme events are not always captured by current models

It is difficult to assess the significance of these discrepancies and to distinguish between model deficiencies and natural variability

Center for Hydrometeorology and Remote Sensing, University of California, Irvine

End of Lecture I

Somewhere in New Mexico, USA - Photo: J. Sorooshian


Recommended