"Assessment the impact of climate change over

heehawultraMechanics

Feb 22, 2014 (3 years and 3 months ago)

57 views

"Assessment the impact of climate change over
sediments yields in the Cesar river basin”

M.Sc.
Karen Milena Ch

Advisor
: Prof. Dr.
Rer
.
nat
.
Manfred

Koch

Department of
Geohydraulics

and Engineering Hydrology

University of Kassel

29.01.13


1

Location of study area

2

Area

Cesar

District 22.925km2

Population:

43.94 Hab/Km2

Capital

:
Valledupar


365.548 Hab

Temperature:
28C

Location
:
07º41’16’’ 10º52’14’’ N


72º53’27’’ 74º08’28’’ W

Main ecosystems
:

Sierra Nevada
de
Santa Marta
: (5300
-
1230
m.a.s.l)

Serranía

de

Perijá
:
(750
-
1350
m.a.s.l)

V
alley

of
River Cesar
: (500
-

950
m.a.s.l)

Cienaga de la zapatosa: :(
50
-
200
m.a.s.l)

Main characteristics of the Cesar region:



Important

roll

for

the

economic

in

the

region

(cotton

crop,

mining,

livestock)


I湴e湳楶i

慧a楣i汴ur慬

pr慣瑩捥s


䕸楳瑥湣n of 桹dro 浥teoro汯杩g慬a慮a 獯楬iu獥
information for the area.


Table 1:Charactetistic

of study area

Serrania

de
Perija

Sierra
nevada

de Santa
Marta

Valley
of River
Cesar

Cienaga
de la
Zapatosa

Stament

of

the

problem


For

the

district

of

Cesar,

one

of

the

most

important

water

resources

is

the

Cesar

river
.



One

of

the

major

environmental

problems

in

the

region

has

been

the

massive

deforestation

of

most

of

the

forests

to

make

way

for

agricultural

uses

that

may

lead

to

ecological

imbalances
.



3


From

the

point

of

view

of

agriculture,

inadequate

use

of

natural

resources,

such

as

the

use

of

mechanization

without

the

prior

classification

of

the

agro
-
ecological

zone
.



In

an

area,

as

the

Cesar

basin,

which

is

rich

in

topographical

and

soil

physiological

conditions,

erosion

and

sedimentation

could

occur

in

several

ways
.

Schumacher

T
.
E,

et

al
.

(
1999
),

states

that

net

soil

loss

from

tillage

erosion

occurs

on

slope

lands

as

a

result

of

gravity

acting

on

moving

soil
.


4


According

to

a

study

of

climate

modeling

in

Colombia

conducted

by

Pabón

J
.
D,

(
2006
),

in

the

Cesar

region

the

trend

of

air

temperature

might

increase

0
.
17

°
C

per

decade,

and

the

trend

of

precipitation

1
.
46
%

per

decade

for

that

region
.



From

the

agricultural

point

of

view,

the

United

Nations

system

in

its

review

of

risks

and

opportunities

associated

with

climate

change

states

that

the

effects

associated

with

this

phenomenon

could

be

the

aridity,

soil

erosion,

desertification

and

changes

in

the

hydrological

regime

as

well

as

increased

risk

of

flooding

in

agricultural

production

affecting

crops
.


5

The main objective


The

main

objective

of

this

research

is

to

assess

the

impact

of

climatic

change

over

sedimentation

yield

in

the

Cesar

basin,

which

is

located

in

the

Cesar

district

in

northern

of

Colombia

using

SWAT

(Soil

Water

Assessment

Tool)

model
.




Specific

objectives
:



Establish

the

historical

behavior

of

climatic

and

hydrological

variables

in

the

basin

of

the

Cesar

River
.


Evaluate

sedimentation

yield

in

the

basin

under

climate

change
.

6

SWAT Model
1

Soil Water Assessment Tool


SWAT

is

a

physically

based,

watershed
-
scale,

continuous

time,

distributed
-
parameter

hydrologic

model

that

uses

spatially

distributed

data

on

topography,

land

use,

soil,

and

weather

for

hydrologic

modeling

and

operates

on

a

daily

time

step

(Arnold

et

al
.
,

1998
;

Arnold

and

Fohrer
,

2005
)
.

Based

on

topography,

this

model

subdivides

a

watershed

into

a

number

of

subbasins

for

modeling

purposes
.

In

latina

América

SWAT

has

been

used

in

countries

as
:

México
2
;

Brasil
3
,

Colombia
4
;

República

Dominicana
5

Venezuela

6

7

1

http
:
//swat
.
tamu
.
edu/software/swat
-
model
/

2(Torres B. et al., 2005; Johannes,
2004
), 3(Machado, 2002; Machado et al., 2003;
Neves

et al., 2006),
4 (
Millan

and
Isaza,
2002); (Oñate and Aguilar, 2003)

5
(Camacho et al.,2003)
6
(Silva, 2004).


The soil

water balance is the primary equation used in the SWAT model, which is represented as:


SW :soil content, R, Q, ET, P and QR are daily
precipitation, runoff,
evapotranspiration
,
percolation and return
flow
,
respectly
.

Sed

:sediment yield on a given day (metric tons)

Qsurf

: the surface runoff volume (mm/ha)

q : the peak runoff rate (m3/s),

Khru

is the Universal Soil Loss Equation (USLE),

CUSLE, PUSLE, LSUSLE CFRG are factors as

function of
soil
.

The research design and methodology

1.
Literature

review

2.
Training

in SWAT model

3.
Collection

of

information



TYPE

OF

INFORMATION

CHARACTERISTIC OF

INFORMATION

SOURCE

Digital

Elevation

Model

90m x 90m

ASTER

GDEM

Use

of

soil

Scale
: 125.000

I
GAC

Soil

maps

Scale
:

125
.
000

IGAC

Physic

and

chemical

Soil

properties

Soil

type
,

Area

ratio
,

Content

of

sand
,

Content

of

clay
,

Content

of

fine

clay
,

Content

of

Organic

carbon
,

Content

of

total

nitrogen
,

Content

of

potassium
,

Content

of

total

phosphorus
.

IGAC
,
ICA

Climatic

daily

data


(
30

years)

!!!




Daily

precipitation
,
Maximum
temperature
.

Minimum
temperature
,
Solar

radiation
.

Wind

speed
,
Relative

humidity

,
Daily

Stream
.

Sedimentation

yield

Hydrology,
Meteorology
and

Environmental

Studies

Institute

(IDEAM)

8

4.
Preparation of background information of entry for the application
of the hydrological model.


5.
Analysis of the series of time.


6.
Modeling and calibration of the Cesar River basin hydrological
validation.


7.
Write final paper


9

Partial results

3.
Collection

of

information

and arrangement of data



10

Macro


Quality of available climatic data

11

5%

2%

13%

5%

6%

3%

6%

5%

4%

45%

6%

Max. T
Max. Ws
MF
MHR
MT
MaxWS
mT
TSB
TE
TP
Twt
Variable

Stations

Years

Amount

%

from

to

MaxT

9

6

1980

2010

MaxWs

3

2

1980

2009

MS

21

13

1970

2009

MRH

9

6

1980

2010

MT

9

6

1980

2010

MWs

5

3

1975

2009

mT

9

6

1980

2010

TSB

8

5

1980

2009

TE

7

4

1980

2009

TP

73

45

1980

2009

TWt

9

6

1985

2008

Max
T
:

Maximun

temperature,

MaxWs
:

Maximun

wind

speed,

MWs
:

Main

wind

speed,

MS
:

Main

Stream,

MRH
:

Main

relative

Humidity,

MT
:

Main

temperature,

mT
:

minimum

temperature,

TSB
:

Total

solar

brightness,

TE
:

Total

evaporation,

TP
:

Total

precipitation,

TWt
:

Total

wind

track
.

Figure 1: Description of available data


Delimitation of the basin with SWAT

12

Pte canoas Station
(45 m.a.s.l)

Area

Cesar Basin:
12.500km2

Range of elevation:
40

and 5300
m.a.s.l
.


(Some Problems with soil information)

13

FLOW Analysis

1.
Annual

Analysis

2.
Monthly

Analysis

3.
Flow duration

4.
Flood
Frecuency


14

Pte canoas Station
(45 m.a.s.l)

1.
Annual

Analysis

0
20
40
60
80
100
120
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
Mean Annual Flow (
m^3/seg
)

Year

Mean Annual Flow,
Pte

canoas

Station (
45m.a.s.l)
1972
-

2009

STREAM FLOW
15

16

mean+SD= 78.99

mean= 55.33

mean
-
SD= 31.67

0
20
40
60
80
100
120
Mean Annual flow (m^3/seg)

Rank of
water

year

Ranked

Mean
Annual

Flow
,
Pta

canoas
station

(45
m.a.l.s
) 1972
-

2009

RANKED MEAN ANNUAL…
0
20
40
60
80
100
120
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
Discharge (m
°
3/seg)

Year

Mean
Annual

Flow
, 5
year

Moving

mean, 11year
moving

mean
Pte

Canoas
Station


(45
m.a.l.s
) 1972
-
2009

Mean Annual Flow
5 Year Moving Mean Annual Flow
11 Year Moving Mean Annual Flow
17

2.
Monthly

Analysis

0
20
40
60
80
100
120
140
JAN
FEB
MAR
APR
MAY
JUNE
JULY
AUG
SEPT
OCT
NOV
DEC
Mean montly
flow(m^3/seg
)

Month

Mean Montly flows(m^3/seg), Pte Canoas
(45
m.a.l.s
)
1972
-
2009

18

19

0
20
40
60
80
100
120
140
160
1973
1978
1983
1988
1993
1998
2003
2008
Discharge m3/s

year

11 Year Moving Mean Monthly Flow

JAN
JUNE
NOV
0
50
100
150
200
250
300
350
0
10
20
30
40
50
60
70
80
Discharge (
m^3/seg
)

Percent

of time
that

indicated

discharge

was

equal

or

exceded
(%)

Frecuency

Distribution for 20 Equal
Classes,
Pte

Canoas station
(45
m.a.l.s
)
1972
-
2009

20

3.
Flow duration

4.
Flood

Frequency

Analysis


Log
-
Pearson

Type III
Distribution


The

Log
-
Pearson

Type

III

distribution

is

a

statistical

technique

for

fitting

frequency

distribution

data

to

predict

the

design

flood

for

a

river

at

some

site
.

Once

the

statistical

information

is

calculated

for

the

river

site,

a

frequency

distribution

can

be

constructed
.


The

probabilities

of

floods

of

various

sizes

can

be

extracted

from

the

curve
.

The

advantage

of

this

particular

technique

is

that

extrapolation

can

be

made

of

the

values

for

events

with

return

periods

well

beyond

the

observed

flood

events
.


21

1
10
100
1000
1
10
100
1000
Discharge (m^3/seg)

Return Period (years)

Flood Frequency Analysis for
Pte

Canoas Station
(
45
m.a.l.s
)
Using
Log
-
Pearson
Type III analysis Using average Daily Maximum
Streamflow

values (1972
-
2009)

22

180

2

23

0
50
100
150
200
250
300
350
0
10
20
30
40
50
60
70
80
Discharge (
m^3/seg
)

Percent of time that indicated discharge was equal or excededd (%)

Frecuency

Distribution for 20 Equal
Classes,
Pte

Canoas station
(45
m.a.l.s
)
1972
-
2009

180

Conclusions

24

Higher

flow

rates

months

are

October

and

November

and

the

lower

flow

are

January

and

February
.


There

is

evidence

that

indicates

that

the

discharge

in

the

months

of

greater

and

lower

discharge

has

been

increasing

in

recent

years
.

Thank you for your attention

25