evaluation of snowmelt contribution to streamflow in a ... · snowmelt periods (march to april) for...

Konkuk University, Seoul, South Korea

Hyung Jin SHIN Post-doctoral researcher, Konkuk Univ., South Korea

Min Ji Park / Rim Ha / Jae Eung Yi / Gwang Seob Kim

Post-doctoral researcher / Researcher / Professor / Professor Univ. of Massachusetts / KICT / Ajou Univ. / Kyungbook National Univ.

Seong-Joon KIM Professor, Dept. of Civil & Environmental System Eng., Konkuk Univ., South Korea

Evaluation of snowmelt contribution to streamflow in a heavy snowfall watershed of South Korea using SWAT model

17 June 2011


Contents

1. Introduction

2. SWAT model description

3. Model setup 1. Study area description

2. Map data, weather and dam inflow data

3. Terra MODIS snow cover information

4. Snow depth distribution data

5. Snow parameter

6. Model calibration and validation

4. Assessment of the snowmelt discharge to dam inflow during 5 months (December - April)

5. Conclusions


We have snowfall from the beginning of November to the first period of April.

Three areas (Southwest-plain area, Northeast-mountainous area, and far East

island) of South Korea usually have big snowfall up to 50 cm, 100 cm, 200 cm

respectively. Recently since 2000, we suffer some unexpected heavy snowfall

events in other areas except the above three areas.

In our case, the heavy snowfall is treated as a natural disaster not for use as water

resources. Thus, we have few studies for the snowmelt impact on streamflow

(contribute about less than 5 %) as a part of hydrology.

SWAT has algorithms and parameters related with the snowmelt.

We need our own snowmelt parameters. So, here by using the ground measured snowfall data and satellite snow cover area information, we can determine our parameters to simulate the snowmelt driven streamflow.

The objective of this study

Is to determine the SWAT snowmelt related parameters using 9 years

snowfall and Terra MODIS data and calibrate the streamflow during the

snowmelt periods (March to April) for a mountainous watershed located

in the northeastern part of South Korea.

Introduction


Flowchart of Study

Observation data

DEM, Landuse, Soil Map

Weather and dam inflow

Terra MODIS satellite images, Ground snowfall data

SAWT Hydrological Model

Calibration and Validation

Impact Assessment of

Snowmelt on Streamflow

Snow depletion

characteristics


Algorithm of snowmelt simulation in SWAT model (Degree-day

Method )

M is depth of melt water (mm)

R1 is melt rate (mm/day/℃)

Ta is mean air temperature (℃)

Tc is critical temperature (usually, 0 ℃)

Temperature & Precipitation

Interception

Snow pack

Degree-day Melt

Eq : M= R1(Ta-Tc)

Rain or Snow

Runoff

Evapotranspiration

R S

Fast Storage

Slow Storage

Evapotranspiration

Model Description


Study Watershed

2004. 3. 7

MODIS image

Study area: 2,694.4 km2 forest-dominant (93 %) watershed

The annual average precipitation is 1,359.5 mm, and the mean temperature is 9.4 ℃ over the last 30 years (1977 - 2006).

Korea


Elevation, Soil, Land Cover Data

Land use

•The 9 categories

•prepared by 2000 Landsat TM (Thematic Mapper) supervised classification with NOAA NDVI

Elevation

• range : 155 - 1,639 m

•average : 643.9 m

Soil

• loam (52.4 %), and loamy sand (42.4 %)


Material and Method

Input Datasets for Calibration and Validation of the SWAT Model

Meteorological data

•Daily weather data (temperature, relative humidity, wind speed, sunshine hour) were collected from five stations (1998-2008)

•Daily precipitation data were collected from eighteen stations (1998-2008)

Streamflow data

•Daily streamflow data at the three water level stations were obtained (1998-2008) from the Ministry of Construction and Transportation.


Terra MODIS Snow Cover Area

MODIS (Moderate Resolution Imaging Spectroradiometer)

MODIS is one of four sensors carried on-board NASA's first Earth Observing System

(EOS) satellite 'Terra‘.

The automated MODIS snow-mapping algorithm uses at-satellite reflectances in

MODIS bands 4 (0.545-0.565 ㎛) and band 6 (1.628-1.652 ㎛) to calculate the

normalized difference snow index (Hall, Riggs, & Salamonson, 1995)

SNOW COVER (Normalized Difference Snow Index)

1 day interval & 500 m resolution

64

64

MODISMODIS

MODISMODISNDSI


Sample of Terra MODIS Snow Cover Area

Legend

Snow Free

Snow Cover Area

0 6030 km

2002.01.12 2002.01.11 2002.01.09

2001.12.30 2002.01.02 2002.01.06 2001.12.28

The generated snow depth distribution within the MODIS snow

cover extent

Konkuk University, Seoul, South Korea Spatial distribution map of snow depth using

GIS interpolation and MODIS SCA IDW (Inverse Distance Weighting)

76 point data of

snowfall IDW

Interpolation

DEM

Spatial distribution of snow

depth

Snow cover area

by MODIS


2001.12.25 2001.12.29 2001.01.02 2002.01.10

2001.12.25 2001.12.29 2001.01.02 2002.01.10

IDW

Interpolation

Considering elevation

effect

Spatial distribution of snow depth considering

elevation effect


The generated snow depth distribution within the MODIS snow

cover extent using the ground-measured snowfall data

2001-2002 Spatial distribution of snow depth

0 6030 km

Snow Depth (cm)

0

1-5

5-10

10-15

15-20

0

0-5

5-10

10-15

15-20

2002.01.12 2002.01.11 2002.01.09

2001.12.30 2002.01.02 2002.01.06 2001.12.28


The watershed snow depth summary (1998-2008)

Average snow depth and temperature

Maximum (old-gray) and average (new-black) snow depth

-90

-80

-70

-60

-50

-40

-30

-20

-10

0

10

0

20

40

D J F M A D J F M A D J F M A D J F M A D J F M A D J F M A D J F M A D J F M A D J F M A D J F M A

1998-1999 1999-2000 2000-2001 2001-2002 2002-2003 2003-2004 2004-2005 2005-2006 2006-2007 2007-2008

Te

mp

era

ture

(℃)

Sn

ow

De

pth

(c

m)

Max. Snow Depth Ave. Snow Depth Mean Temperature (℃) Min. Temperature (℃) Max. Temperature (℃)


0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Fra

cti

on

of a

rea

l c

ove

rag

e

Snow volume

2000-2001

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Fra

cti

on

of a

rea

l c

ove

rag

e

Snow volume

2001-2002

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Fra

cti

on

of a

rea

l co

ve

rag

e

Snow volume

2002-2003

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Fra

cti

on

of a

rea

l c

ove

rag

e

Snow volume

2003-2004

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Fra

cti

on

of a

rea

l co

ve

rag

e

Snow volume

2004-2005

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Fra

cti

on

of a

rea

l co

ve

rag

e

Snow volume

2005-2006

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Fra

cti

on

of a

rea

l co

ve

rag

e

Snow volume

2006-2007

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Fra

cti

on

of a

rea

l co

ve

rag

e

Snow volume

2007-2008

The snow depletion curves from the fraction of snow cover area

and snow volume of each data set (heavy snowfall year: 2000-2001, 2002-

2003, 2007-2008)

Derivation of snow depletion curve


0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Fra

cti

on

of a

rea

l c

ove

rag

e

Snow volume

SNO50COV_Mean

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Fra

cti

on

of a

rea

l c

ove

rag

e

Snow volume

SNO50COV_Min

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Fra

cti

on

of a

rea

l c

ove

rag

e

Snow volume

SNO50COV_Max

Derivation of snow depletion curve

Maximum, minimum and mean snow depletion curve ( I chose the

most left curve after calibration)

As the curve goes to the left, the snow is melt slowly.

0.1

0.7


Model Calibration and Validation for the Streamflow

Parameter Description Calibration Range Soyanggang Dam

Default

Soyanggang Dam

Optimal value

SFTMP Snowfall temperature (℃) - 5 ~ +5 1 1

SMTMP Snow melt base temperature (℃) - 5 ~ +5 0.5 0

SMFMX Maximum snow melt factor (mm H2O/ºC-day) 0 - 10 4.5 2

SMFMN Minimum snow melt factor (mm

H2O/ºC-day) 0 - 10 4.5 1

TIMP Snow pack temperature lag factor 0 - 1 1 0.05

SNOCOVM Threshold depth of snow, above which there is

100% cover [mm] 0 ~ 500 50 500

SNO50COV Fraction of SNOCOVMX that

provides 50% cover 0-1 0.5 0.1

PLAPS Precipitation lapse rate (mm H2O/km) 0 5.33

TLAPS Temperature lapse rate (°C/km) 0 -5.10

SWAT model setup process

No. of Subbasin : 20

No. of HRU : 348

The calibrated model parameters

Model Calibration and Validation for the Study Watershed


Calibration period (1999-2003: Full period)

Validation period (2004-2008: Full period)


0

100

200

300

400

500

600

700

8000

10

20

30

40

50

60

70

80

90

100

D J F M A M J J A S O N 12D J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N

1999-2000 2000-2001 2001-2002 2002-2003

Pre

cip

itat

ion

(mm

)

Stre

amfl

ow

(m

m)

Streamflow P. Sim. Obs.

0

100

200

300

400

500

600

700

8000

10

20

30

40

50

60

70

80

90

100

D J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N

2004-2005 2005-2006 2006-2007 2007-2008

Pre

cip

itat

ion

(mm

)

Stre

amfl

ow

(m

m)

Streamflow P. Sim. Obs.

Year R2 RMSE

(mm/day) NSE

C

2000-01 0.75 2.9 0.74

2001-02 0.86 1.9 0.97

2002-03 0.66 5.5 0.66

2003-04 0.64 5.3 0.64

V

2005-06 0.55 3.0 0.21

2006-07 0.82 5.6 0.80

2007-08 0.69 4.3 0.67

2008-09 0.69 3.9 0.68

Average 0.71 4.1 0.67


0

50

100

150

200

250

300

350

4000.01

0.10

1.00

10.00

100.00

1000.00

10000.00

Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov

Pre

cip

itat

ion

(mm

)

Stre

amfl

ow

(m

m)

2000-2001

Obs. Sim. (considering snowmelt parameters)

The 2001 calibrated streamflow considering the snowmelt

parameters



0

50

100

150

200

250

300

350

4000.01

0.10

1.00

10.00

100.00

1000.00

10000.00

Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov

Pre

cip

itat

ion

(mm

)

Stre

amfl

ow

(m

m)

2002-2003

Obs. Sim. (considering snowmelt parameters)

The 2001 calibrated streamflow considering the snowmelt

parameters



Summary and Conclusions

This study tried to identify the SWAT snow depletion characteristics for

a mountainous watershed (2,694.4 km2) located in the northeastern part

of South Korea using the 8 years (2000-2008) sets of snow depth

distribution information.

Through understanding the characteristics of our snow depletion using

Terra MODIS data, we could simulate the snowmelt driven streamflow

better than before.


Thank you

For your attention

evaluation of snowmelt contribution to streamflow in a ... · snowmelt periods (march to april) for...

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