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1 INTEGRATION OF WATER QUANTITY AND QUALITY MODELS FOR ASSESSMENT OF WATERSHED CONTAMINANT LOADS INTO TRIBUTARIES OF PARANOA LAKE
Diana Jimena Monsalve Herrera
Conceição de Maria Albuquerque Alves
Ricardo Tezini Minoti
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Introduction
Riacho Fundo sub-basin
“Água DF”
Increasing
Population
Pollution
Land use
and
occupation
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Introduction
Echevarria , 2007
Physicochemical
studies
Geochemical
Sediments
Quality problems caused for:
Increase in urbanization
Sewage discharge and
nutrient loads
Menezes, 2010
Evolution of land use
and occupation-DF
2009
87% intensive use
urban and agriculture areas
Consequences:
Increased runoff
Hydrological cycle modified
CODEPLAN , 2011
Average annual growth
rate of population
DF
2.3% (2000-2010)
Rate Riacho Fundo:
(2004-2011)
Riacho Fundo II: 11.41%
Aguas Claras: 14.12%
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Introduction
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General objective
Assess the availability
and quality of water in
the Riacho Fundo subbasin
using
the
integration of SWAT and
WEAP
models
to
support the decision
making, planning and
management of water
resources in the Federal
District.
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Objectives
.
To model hydrological processes and nutrient
loads in watersheds with predominant use of
urban land using the SWAT model.
Specific Objectives
To evaluate the use of WEAP as a decision
support
system
to
water
resources
management in the DF
To integrate SWAT and WEAP models for the
simulation of water quantity and quality
scenarios in the Riacho Fundo watershed.
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Objectives
Generate information related to the availability
and quality of water in the study area from
different scenarios based on land use changes,
demand increase and different wate water
treatment efficiencies of the Riacho Fundo
WWTP
Specific Objectives
Evaluate the contaminant loads from Riacho
Fundo basin into the Paranoá lake.
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Simulation
Analysis
Future scenarios:
Tool for IWRM.
Use node and link
network to represent
the WR system
Availability
Quality
Demands
Others
Demand priorities
and
Water availability
www.themegallery.com
Allows the modeling of
physical
processes
associated
with
the
movement
of
water,
sediment, vegetation growth
cycle, nutrients, etc..
information:
climatic conditions;
soil properties;
topography, vegetation;
conditions and management
practices in the basin
(Neitsch, et al., 2002).
HRU
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Methodology
Point
Pollution
NPS Pollution
Hydrology
Manual
Calibration
SWAT
results
Quality
Module
Future
Scenarios
Water (quality and
availability) P&M
Quantity
and
allocation
module
Obtenção e processamento de dados para o SWAT
Manual Calibration
Simulation of land use changes scenarios
Simulation
Insertion of climate data INMET: 1962-2012
Data precipitation: Riacho Fundo WWTP
Sensitivity analysis
HRU
Urban Area 1: Urban Low-density (URLD)
Urban Area 2:Urban Average density (URMD)
Urban Area 3: Urban High density (URHD)
Selection of the number of
sub-basins and definition
of slope
Definition of the
direction of outgoing
and incoming flow
Land Use
Data- soil types
DEM DF- Riacho Fundo
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• Scenario 1: change of use of
agricultural land to urban land
uses of high urban density.
Scenarios
SWAT
• Scenario 2: change of uses
of urban low-density land for
urban high density land.
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Current Account: represents the current
conditions of Hydric system.
Integration
of SWAT
and WEAP
• Reference Scenario: inherits the
characteristics of the current scenario
and has similar evolutions the current
system without intervention.
• Future scenarios: They are created to
answer the question "what if?".
The Reference Scenario is altered
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Population
consumption per capita
Daily capacity
Consumption (%)
Consumption
Average annual growth
Total Nitrogen Removal
p
rate of p
population
Priority
Total Phosphorus Removal
SCENARIOS – Water Quantity Analysis
Scenario 2
weap
Scenario 1
weap
Future Scenarios
 Increase in the rate of population
growth of 4.6% for the localities of
Vicente Pires and Riacho Fundo
II
 Increase in the rate of population
growth of 4.6% for the localities of
Águas
Claras,
Núcleo
Bandeirante e Candangolândia.
Scenarios – Water Quality Analysis
 River flow and
quality
 River flow and quality of
Scenario 1 of SWAT.
 River flow and
quality
 River flow and quality of
Scenario 2 of SWAT.
 20% increase in
Total
Nitrogen
removalRiacho
Fundo WWTP
 Streamflow values and
quality introduced in the
Reference Scenario,
Scenario 1 and 2.
Efficiency of
WWTP
Without WWTP
Scenario 1
weap
Data used from SWAT
Scenario 2
weap
Changes
Efficiency of
WWTP
Without WWTP
SCENARIO
2 weap
SCENARIO
1 weap
SCENÁRIOS – Water Quality Scenarios
Assessment
Lamparelli, 2003:
Limits: Trophic
Classification (SP)
CONAMA 357/05:
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0,000
Data
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Nov 93
Sep 93
Jul 93
Mai 93
Mrz 93
Jan 93
Nov 92
Sep 92
Jul 92
Mai 92
Mrz 92
Jan 92
Nov 91
Sep 91
Jul 91
Mai 91
Mrz 91
Jan 91
Nov 90
Sep 90
Jul 90
Mai 90
Mrz 90
Jan 90
Nov 89
Sep 89
Jul 89
Mai 89
Mrz 89
Jan 89
Nov 88
Sep 88
Jul 88
Mai 88
Mrz 88
Vazão (m³/s)
Best streamflow calibration (1988-1993)
21,000
18,000
Q observada
Q simulada
15,000
12,000
9,000
6,000
3,000
Data
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Dez 96
Nov 96
Okt 96
Sep 96
Aug 96
Jul 96
Jun 96
Mai 96
Apr 96
Mrz 96
Feb 96
Jan 96
Dez 95
Nov 95
Okt 95
Sep 95
Aug 95
Jul 95
Jun 95
Mai 95
Apr 95
Mrz 95
Feb 95
Jan 95
Dez 94
Nov 94
Okt 94
Sep 94
Aug 94
Jul 94
Jun 94
Mai 94
Apr 94
Mrz 94
Feb 94
Jan 94
Vazão (m³/s)
Validation (1994-1996)
20,00
Q observada
16,00
Q simulada
12,00
8,00
4,00
0,00
Stage
Statistics
Value
Classification
25
Moriasi et al., 2007
Calibration
1988-1993
NSE
PBIAS %
0.73
-15.63
Good
Satisfactory
Q simulada (m³/s)
Q simulada
20
Linha de tendência
15
10
5
0
0,000
RSR
0.51
y = 1.1656x
R² = 0.8612
5,000
Good
10,000
15,000
Q observada (m³/s)
20,000
Validation
1994-1996
NSE
PBIAS %
0.615
14.48
Satisfactory
Q simulada (m³/s)
Q simulada
12
8
0.62
y = 0.8225x
R² = 0.6987
4
Good
0
0,00
RSR
Linha de Tendência
Satisfactory
5,00
10,00
Q observada (m³/s)
15,00
Data
Data
Apr 10
80000
70000
60000
50000
40000
30000
20000
10000
0
Sep 08
Mai 08
140000
Mrz 10
Jan 08
Sep 07
Mai 07
Jan 07
Sep 06
Mai 06
Jan 06
Sep 05
Mai 05
Jan 05
Sep 04
Mai 04
Jan 04
N total (Kg/mês)
160000
Feb 10
Jan 10
Dez 09
Nov 09
Okt 09
0
Sep 09
Data
Aug 09
2000
Jul 09
4000
Jun 09
6000
Mai 09
8000
Apr 09
10000
Mrz 09
Validation PT:
Feb 09
P total obs
P total sim
N total (Kg/mês)
Okt 08
Jul 08
Apr 08
Jan 08
P total obs
P total sim
Jan 09
Apr 10
Mrz 10
Feb 10
Okt 07
Jul 07
Apr 07
Jan 07
Okt 06
Jul 06
Apr 06
Jan 06
Okt 05
Jul 05
Apr 05
Jan 05
Okt 04
Jul 04
Apr 04
Jan 04
P total (Kg/mês)
18000
16000
14000
12000
10000
8000
6000
4000
2000
0
Jan 10
Dez 09
Nov 09
Okt 09
Sep 09
Aug 09
Jul 09
Jun 09
Mai 09
Apr 09
12000
Mrz 09
14000
Feb 09
Jan 09
P total (Kg/mês)
Best Calibration of Total Phosphorus and Total
Nitrogen Calibration NT:
Calibration PT:
N total obs
N total simu
120000
100000
80000
60000
40000
20000
0
Data
Validation NT:
N total obs
N total sim
Scenarios SWAT
Comparação de cenários-ano 2003
Q original
Cenario1
Cenario2
Vazões (m³/s)
10
8
6
Q original
4
Cenario1
2
Cenario2
0
1
1
2
3
4
5
6
7
8
9
10
11
2
3
4
12
5
6 7
Meses
8
9
10 11 12
Meses
Comparação de cenários- Ano 2011
25
Vazão (m³/s)
Vazões (m³/s)
Comparação de cenários -ano 1988
16
14
12
10
8
6
4
2
0
20
15
Q original
10
Cenario1
5
Cenario2
0
1
2
3
4
5
6
7
Meses
8
9
10
11
12
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Scenarios SWAT
Cenários para Fósforo Total-ano 1988
Cenários para Fósforo Total-ano 2003
4000
Cenario2
3000
CENARIO1
2000
PT_original
1000
0
1
2
3
4
5
6 7
Meses
8
9
20000
Carga Fosforo Total
(Kg/mês)
5000
Carga Fosforo Total
(Kg/mês))
Carga Fosforo Total
(Kg/mês)
6000
4000
3000
2000
Cenario2
CENARIO1
1000
PT_original
0
1
10 11 12
2
3
4
5
6 7
Meses
8
9
10 11 12
Cenários para Fósforo Total- ano 2011
15000
10000
Cenario2
CENARIO1
5000
PT_original
0
1
2
3
4
5
6
7
Meses
8
9
10
11
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Scenarios SWAT
Cenarios para Nitrogênio Total-ano 2003
25000
20000
Cenario2
15000
Cenario1
10000
NT_original
5000
0
1
2
3
4
5
6 7
Meses
8
9
18000
16000
14000
12000
10000
8000
6000
4000
2000
0
Carga Nitrogênio Total
(Kg/mês)
30000
10 11 12
Cenario2
Cenario1
NT_origina
1
2
3
4
5
6 7
Meses
8
9
10 11 12
Cenarios para Nitrogênio Total-ano 2011
90000
80000
70000
60000
50000
40000
30000
20000
10000
0
Carga Nitrogênio Total
(Kg/mês)
Carga Nitrogênio Total
(Kg/mês)
Cenarios para Nitrogênio Total-ano 1988
35000
Cenario2
Cenario1
NT_original
1
2
3
4
5
6 7
Meses
8
9
10 11 12
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2011
2025
2025
Nutrient
NT
PT
Maximum value
Node WWTP (mg/L)
6.68
0.23
Value in the outlet basin
Scenario
1.68
0.12
2
2
The integration of SWAT and WEAP provides good results in the case
of simulation of water quality. Since the WEAP can not simulate diffuse
pollution, SWAT is a very useful model that provides this kind of results
in a detailed way, and it consider all the features of the basin as land
use, management, soil type, among others.
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Integration of models depends on the level of detail of the
study
SWAT
provides
very
detailed
simulations of hydrology and quality
The integration SWAT-WEAP needs a defined approach to
establish a link between changes in land use in SWAT and
the rate of population growth in the demand nodes in WEAP
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The WWTP node (WEAP) showed the highest concentrations especially
for the Nitrogen, but the contribution of the tributaries helped on the
reduction of the concentrations along the Riacho Fundo River.
The presence of phosphorus was mainly affected by the sediment loads
from the watershed. The final concentration at the outlet of the basin
approached the regulated limit defined by the CONAMA Resolution
357/05, showing the vulnerability of the lake.
The NT and PT values in sub-basin outlet classified the water source as
meso-eutrophic, representing intermediate levels of productivity
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The scenario without release of treated sewage from the WWTP
Riacho Fundo, showed good results in improving the quality of the river
The scenario increasing the NT removal efficiency of the WWTP Riacho
Fundo reported significant improvement in the water quality of the River
Riacho Fundo
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Acknowledgements
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Stage
Statistics
Value
Calibração
2004-2008
NSE
-3.43
Classification
( Moriasi et al. , 2007 )
unsatisfactory
PBIAS %
-133.8
unsatisfactory
Verificação
2009-2010
Best Calibration of Total Phosphorus
RSR
NSE
2.10
-7.31
unsatisfactory
unsatisfactory
PBIAS %
-95.88
unsatisfactory
RSR
2.88
unsatisfactory
 Low efficiency in the simulation
 Overestimation of simulated loads
 High dispersion of data.
Statistics
Value
NSE
0.45
Classification
( Moriasi et al. , 2007
)
unsatisfactory
PBIAS %
24.70
Very Godd
RSR
NSE
0.73
-0.85
unsatisfactory
PBIAS %
20.47
Very Good
RSR
1.36
Verificação
2009-2010
Stage
Calibração
2004-2008
Best Calibration of Total Nitrogen
unsatisfactory
unsatisfactory

Low efficiency in the simulation
 Underestimation of simulated loads
 High dispersion of data
 Better results than the PT.
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Based on the results obtained from WEAP about Descoberto Lake, it
was observed that the reservoir has the capacity to supply the towns
that currently make use of this water.
Decreased storage
Vulnerability of
Lake
Important!! take care
of water sources
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