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Evaluation of SWAT streamflow components for
the Araxisi catchment(Sardinia, Italy)
Maria Grazia Badas1*, Mauro Sulis2, Roberto Deidda1, Enrico Piga1,
Marino Marrocu2 and Claudio Paniconi3
1. Dipartimento di Ingegneria del Territorio, Università di Cagliari, Italy.2. CRS4 (Center for Advanced Studies, Research and Development in
Sardinia), Cagliari, Italy3. INRS-ETE (Institut National de la Recherche Scientifique – Eau, Terre et
Environnement), Université du Québec, Canada
Outline
• Aims of the study• Description of the watershed and
dataset• Baseflow separation• Yearly calibration• Daily calibration• Conclusions
Aim of the study
• A classification made by the Sardinian Hydrological Survey, designated the basin as almost impermeable
• Pre-processing of measured data has suggested that this proposed classification has to be interpreted as absence of water loss to deep aquifer recharge
• Comparison between separation methods (related to response times), and streamflow components provided by the model (obtained from physically based equations)A reliable simulation of streamflow components is an important step in the adoption of a correct schematization of watershed characteristics
Case study: the Araxisi catchment
Overview of the watershed• Sardinian mountain
basin• Area=125km2
• Averageelevation=804 m
• Average steepness=30%
• DEM 100 m• 41 sub-basins (tr.
area=200 ha)
%[
%[%[
%[%[
$Z
$Z
']
&\
D e m
2 6 5 - 4 9 8
4 9 8 - 7 3 2
7 3 2 - 9 6 6
9 6 6 - 1 2 0 0
1 2 0 0 - 1 4 3 4
1 4 3 4 - 1 6 6 8
W a t e r s h e d
S t r e a m s
%[ R a i n g a g e s
$Z T e m p g a g e s
'] S o l a r g a g e s
&\ W e a g a g e s
Model Dataset1946-1975
• daily values of precipitation (5 gages), and maximum and minimum temperatures (2 gages ) supplied by the Sardinian Hydrological Survey
• solar radiation daily values from NCEP-NCAR analyses (National Centers for Environmental Prediction and for Atmospheric Research).
• daily discharge values supplied by the Sardinian Hydrological Survey
W a t e r s h e d
S w a t L a n d U s e C l a s s
A G R L
A P P L
F R S D
F R S E
F R S T
P A S T
U I D U
U R L D
U T R N
W A T R
S t r e a m s
Land Use Classification• obtained by a
satellite image with a resolutionof 400 m
• Prevalent land use classes:– 36% evergreen forest
(FRSE)– 26% mixed forest
(FRST) – 28% pasture (PAST)
Soil Classification• lacking of a detailed soil
map…
• main soil characteristicsfor the whole basin: – Clay 5%– Silt 25%– Sand 70%
•sandy loam soil (SL) according to the USDA soil texture triangle classification•soil stratification: two different configurations(single and multiple layers)
STREAMFLOW ASSESSMENT
• hydrograph components: surface runoff, subsurface flow and baseflow
• practically only two streamflow components are recognized: quick flow and recession flow, on the basis of response times, without any reference tothe underlying physical processes
Application of two separation techniques to the daily records for
baseflow estimation
1. A classical separation technique:• Qb=Qtot during interstorm periods;• logQb=linear trend during storm periods
2. A digital filter technique• proposed by the SWAT developers based on
the filtering of high and low frequency signals(surface runoff and baseflow)
• three passes: forward, backward, forward, with a decreasing baseflow rate at each pass[Arnold et al. (1995) and Arnold & Allen 1999)]
115 120 125 130 135 1400
2
4
6
8
10
12
observed rainfall observed streamflow manual baseflow filtered baseflow (forward) filtered baseflow (backward)filtered baseflow (forward)
Comparison of “classical” separation and digital filter technique
the first pass provides results comparable to those of the classical technique at an annual time step
1 2 3 4 5 6 7 8 9 10100
200
300
400
500
600
700
800
900
t (years)
observed streamflow manual baseflow filtered baseflow (forward) filtered baseflow (backward)filtered baseflow (forward)
Daily step Annual step
Baseflow recession factor (α)
• Manual technique: α = the average slope of linear trend of logarithmic streamflowswithin interstorm periods = 0.06 on a sample of 33 manual selected recession periods
• Digital filter method: it considers streamflow separation given by the filter, baseflow recession slopes computed only in low ET months and combined with the Master Recession Curve (MRC) method;α = 0.0143 calculated on 18 events
results are quite different!!
tt eQQ α−= 0
1 2 3 4 5 6 7 8 9 100
200
400
600
800
1000
1200
1400
1600
t(years)
observed rainfall observed streamflow simulated streamflowmanual baseflow filtered baseflow simulated baseflow lateral flow
Yearly calibration (1)(on the first decade of streamflow data)
Many likely sets of
parameters were
hypothesized,
but none of them led
to a realistic
separation.
EXAMPLE(RESULTS FOR ONE SIMULATION)
baseflow component practically absent in all the simulations!!!
Simulated baseflow
Observedrainfall
Simulated streamflow
Simulated lateral flow
Observed streamflow
Classical tech. baseflow
Filtered baseflow (I pass)
Yearly calibration (2)• incorrect calculation of the slope length
parameter (Lhill) in the AVSWAT interface
• lateral flow (kinematic wave approximation) is in inverse proportion to Lhill
• a reliable value is Lhill=50 m
• but the AVSWAT interface fixes Lhill= 0.05 m
overestimation of the lateral flowshortage of available soil water for groundwater recharge
1 2 3 4 5 6 7 8 9 100
200
400
600
800
1000
1200
1400
1600
t(years)
observed rainfall observed streamflow simulated streamflowmanual baseflow filtered baseflow simulated baseflow lateral flow
Yearly calibration (3)Correcting this parameter to50 m led to a considerable improvementin the streamflow separation
Lhill=50 m
Simulated baseflow
Observedrainfall
Simulated streamflow
Simulated lateral flow
Observed streamflow
Classical tech. baseflow
Filtered baseflow (I pass)
EXAMPLE(RESULTS FOR ONE SIMULATION)
1 2 3 4 5 6 7 8 9 10200
400
600
800
1000
1200
1400
1600
1800
2000
t (years)
Sensitivity to rainfall data
spatial distributionof the input rainfall:an important influence on the model response fora mountain basin
five gages could be unable to correctly reproduce the actual rainfall patterns
Observedrainfall (5 gages)
Simulated streamflow (5 gages)
Observed streamflow
Observedrainfall (1 gage)
Simulated streamflow (1 gage)
Daily calibration
superimposition of
– spikes during
storms
– smooth behaviour
during interstorm
periods
3200 3220 3240 3260 3280 3300 3320 3340 3360 3380 34000
2
4
6
8
10
12
14
16
18
20
Observed streamflow
Observed rainfall
Filtered baseflow (I pass)
Simulated streamflow
Simulated baseflow
Classical tech.baseflow
Conclusions and future work• Comparison between “classical” and digital
filter technique– Baseflow estimation– Baseflow recession factor (α)
• Incorrect calculation of Lhill in AVSWAT interface
• Work in progress…– Daily calibration– Validation of the model– Application of other separation techniques