I Simpósio da Bacia Hidrográfica do rio São Francisco, 5/9 Junho, PETROLINA (PE) e JUAZEIRO (BA), Brazil
Estudo dos Processos de Erosão e Transporte Sedimentos em Regiões SemiÁridas *
Studies of Erosion and Sediment Transport Processes in Semi-Arid Regions 1 & José C. de Araújo 2 Axel Bronstert Ramon J. Batalla3, Alexandre C. Costa 6, Till Francke1, Andreas Güntner4, Jose Lopez-Tarazon3, George L. Mamede6, Eva Paton1
1 University of Potsdam, Germany
2
Univ. Federal do Ceará, Fortaleza, Brazil
3 Univ. of
Lleida, Spain
4
Deutsches Geo ForschungsZentrum Potsdam, Germany
5
Forestry Technology Center of Catalonia
6
University of Intern. Integration of the Afro-Brazilian Lusophony, Fortaleza, 1 Brazil
Assessment and modelling of erosion and sediment transport in dryland river basins: from the Hillslopes via the River System to Reservoirs
Outline Hydrological Peculiarities of drylands II. An integrated hydro-sedimentological model III. Results from Research Catchments IV. Applications examples to Large River Basins V. Conclusions and outlook I.
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I Hydrological Peculiarities of drylands Episodic runoff processes trigger rather sudden sediment mobilisation and deposition
Peculiarities of drylands … Soil losses and sediment deposition is the major threat for sustainable landscape and water resources functions
Sedimentation in the Barasona reservoir, Isábena/Èsera River [Bronstert, 200
Peculiarities of drylands ‌ water & sediment events: highly variable in time
and space
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II An integrated hydrosedimentological model: WASASED WASA-SED: A meso-scale hydro-sedimentological model: Ø Catchment
River System
Reservoirs
Ø spatially distributed and catena-based, Ø process-oriented, n Spatial resolution:
hillslope to meso-scale
n Temporal resolution:
hourly or daily time steps
n Model Availability: Code freely available http://uni-
potsdam.de/sesam/reports.php#software Manual http://unipotsdam.de/sesam/download/wasa/WASA_SED_Manual.pdf
Code in Fortran90, currently ca. 50 sub-routines
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Catchment Processes: multi-scale structure of modelling units
Landscape Units (LU)
Terrain components (TC)
Profile
WASA-Sed: Hydrological model approaches at the Hillslope Scale Process Interception
Evapotranspiration Infiltration unsaturated soil water flow Lateral surface/ subsurface flow Groundwater percolation
Spatial scale/ model unit
Approach / equation
Reference
Plot scale / soil- vegetation comp. Plot scale / soil- vegetation comp. Plot scale / soil profile Plot scale / soil profile
overflow model
e.g. Güntner (2002)
Extended (2 layer) Penman-Monteith
Shuttleworth and Wallace (1985)
Modified GreenAmpt approach Unsat. Darcy equation
Peschke (1987)
Hillslope scale / terrain comp.
empirical distribution
Güntner (2002)
e.g. Bronstert and Plate (1997)
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Plot scale / vertical Darcy soil- vegetation equation
e.g. Güntner (2002)
WASA-Sed: Process Representation at the channel scale and in the reservoir
A : C o n n e c t iv it y b e t w e e n h ills lo p e s , v a lle y b o t t o m s a n d t h e r iv e r
B : T r a n s m is s io n lo s s e s a n d t e m p o r a r y s t o r a g e in t h e r iv e r
C : R e t e n t io n in a n d t r a n s f e r t h r o u g h r e s e r v o ir s
I n t e g r a t e d m e s o - s c a le c a t c h m e n t m o d e l
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WASA-Sed: Model approaches for the river system and the reservoirs
Process
River discharge Water balance of small reservoirs Water balance of large reservoirs
Spatial Approach / scale/ model equation unit River system Kinematic wave / extended Muskingum Generalized Aggregated water reservoir balance for classes reservoir classes Reservoir
Full water balance for each individual reservoir, incl. operation rules
Reference
e.g. Chow et al. (1988) GĂźntner et al. (2004)
GĂźntner et al. (2004)
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Sedimentological model approaches and spatial scales in the WASA-SED model
Process Surface soil erosion
Spatial scale/ model unit Hillslope scale (catena) / LU
Soil deposition
Field scale / TC
Suspended sediment transport (incl. deposition or degradation) in the river Bedload transport in the river
River reach
River reach
5 transport formulae (for optional use)
Sediment transport in small reservoirs Sediment transport in large reservoirs
Generalized reservoir classes
Aggregated sediment budget for reservoir classes Full sediment budget for each individual reservoir, incl. sediment
Reservoir
Approach / equation
Reference
USLE + 3 modifications: MUSLE, Onstad-Foster, MUST (for optional use) sediment transport capacity limitation Suspended sediment transport capacity assessment
Wischmeier and Smith (1978), Williams (1995)
Meyer-Peter and MĂźller (1948); Schoklitsch (1950); Bagnold (1956); Smart and Jaeggi (1983); Mamede (2008); Mamede et al. (2014)
Everaert (1991) e.g. Arnold (1995) / Neitsch et al. (2002)
Mamede (2008) 14
Hillslope erosion approaches in the WASA-SED model c = EI
(USLE)
c = 0.646 EI + 0.45 (Qsurf qp)0.33 E = c K LS C P ROKF A Â
(Onstad-Foster)
c = 1.586 (Qsurf qp)0.56 A0.12
(MUSLE)
c = 2.5 (Qsurf qp)0.5 (MUST) EI rainfall energy factor (MJ.mm.ha-1.hr-1)
E (gross) erosion (t) K soil erodibility factor (t.ha.hr.ha-1.MJ-1.mm-1) Qsurf LS length-slope factor (-) C vegetation and crop qp management factor (-) P erosion control factor (-) ROKF coarse fragment factor (-) A area of the scope (ha)
surface runoff volume (mm) peak runoff rate (mm/h) (after Williams, 1995)
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Erosion and sediment transport in the river Erosion/ depositio n
RSEDdep = (Cs,max – Cactual ) · V
Transport capacity
C s ,max
5 different transport formulae
Susp. sedi ment
Bedload
RSEDero = (Cs,max–C actual)·V·K·C
a v peak
b
RSEDdep amount of sediment deposited (t) RSEDero amount of sediment in the reach segment (t) V water in the reach (m3) K channel erodibility (cm/hr/Pa) C channel cover factor (-) vpeak peak channel velocity (m/s) Cs,max maximum sediment conc. for river stretch (t/m3) A, b user-definrd coefficients Meyer-Peter and Müller 1948, Schoklitsch 1950, Bagnold 1956, Smart and Jaeggi 1983, Rickenmann 2001 16
Reservoir Processes: three conecptual sediment layers Stage (m)
350
Top Layer Deposition
345
Original bed material 50
100
Erosion Intermediate Layer Lowest layer
Compaction 150
200
250
300
350
Width (m)
Sediment laden flow
Sediment laden flow
Top Layer
(from cross section 6)
(to cross section 8)
Intermediate Layer
Deposition
Erosion
Lowest Layer Compaction
6
7
Original Bed Material
8
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Reservoir Module: Spatial representation of the reservoir
River subreach
Reservoir subreach
Stage (m)
Inflow
1 2 3
4 5
6 7
8
460 455 450 Outflow 445 440 435 430
9 10 11 12 13 14
Distance (km) 14 13 12 11 10
9
8
7
6
5
4
3
2
1
0
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Connectivity: the special challenge of dryland regions Connectivity: transfer, storage and re/ entrainment processes of water and sediments among different landscape components A: Connectivity between hillslopes, valley bottoms and the river
B: Transmission losses and temporary storage in the river
C: Retention in and transfer through reservoirs
D: Integrated meso-scale catchment model 19
III
Results from Research Catchments
Ø Northeast Brazil (Ceará): semi-arid climate with
a pronounced seasonality Ø Northeast Spain (Catalonia and Aragón): subhumid or semi-arid climate These research regions include of a set of individual (but nested) catchments of different spatial scales
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Uppe Yaguaribe (NE Brazil) Vรกrzea do Boi
Bengue hillslopes
Aiuaba
exp.
Upper Jaguaribe
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Hydrologic and sediment measurements in the Upper Jaguaribe Basin, Brazil
No.
Name
Area (km²)
Annual rainfall (mm)
B1
exp. hillslopes (part of Aiuaba, in Benguê)
2.8
~600
B2
Aiuaba experimetal catchment
12
560
B3
Benguê
933
560
B4
Várzea do Boi
1,221
~500
B5
B6
Jaguaribe, upstream Orós reservoir Jaguaribe, downstream Orós reservoir
20,700
24,600
Main Main discharge sediment measuremen measuremen ts ts (outflux) ---
sed. deposition by Cs137
Discharge flume and reservoir level Reservoir level sampling Reservoir level sensor
reservoir bathymetry reservoir bathymetry
River water level sensor
manual sampling
400 to 800 Reservoir level sensor
manual sampling
manual sampling
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Results: Upper Jaguaribe Basin, Brazil: Sediment budgets at the nested catchments
23
ร sera (NE Spain, Ebro region) Isรกbena
Villacarli
Ball
exp. badlands
Villacarli
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Hydrologic and sediment measurements in the Ésera Basin, Spain
No.
Name
Area (km²)
Annual rainfall (mm)
S1
Badland
~ 0.03
~750
S2
Ball
10
~750
S3
Villacarli
41
730
445
450-1,600
1,380
450-2,000 in the high mountains
S4
S5
Isábena (gauge Capella) Ésera (upstream Barasona reservoir
Main discharge sediment measuremen measureme ts nts (outflux) Discharge Tubidimeter; flume Isco sampling River water Tubidimeter; level sensor Isco sampling River water Tubidimeter; level sensor Isco sampling River water Tubidimeter; level sensor Isco sampling Water level sensor
Reservoir bathymetry
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Results NE Spain: Assessment of water flows and sediment yields
sediment export occurs mainly during -late summer floods very high specific sediment for badland areas (Villacarli) gauge
SSY [t/km2]
Torrelaribera
6277
Villacarli
1971
Cabecera
139
Capella
409
highly episodic sediment fluxes from headwaters are strongly attenuated towards outlet
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Results NE-Spain: Modeled Water hydrological fluxes at the Villacarli, Catchment
27 WASA-SED results for Villacarli catchment (Francke, 2009)
Results NE Spain: Modeled sediment yields
Observed and simulated sediment fluxes of the Villacarli sub-catchment Sept – Dec 2006 (Franke, 2009) 28
Results NE-Spain: Estimated Sediment transfer and deposition in the Isábena, Catchment,
Estimates of sediment transfer and deposition rates in the 29 Isábena catchment for the period 2007 – 2009 (Bronstert et al. (2014)
RIVER Modelling
Temporary river storage of sediments
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Results: Modelling of water and sediment fluxes in the river Sediment Transport in the River System Upstream River Stretch in the Mountains
30 km Downstream Reach in the Lowlands
12000
60
50
10000
50
10000
40
8000
40
8000
30
6000
30
6000
20
4000
20
4000
10
2000
10
2000
60
0 7000
7500
Time [h]
8000
0 8500
0 7000
7500
Time [h]
8000
12000
0 8500
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Reservoir Sedimentation: Observations Barasona Reservoir (Spain) (ca. 1340 km2)
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Reservoir Sedimentation: Observations
95 3
) 90 85 80 75 Storage capacity (Mm 70 1920
1940
1960
1980
2000
2020
Time (years)
comparison of bathymetric surveys of the Barasona Reservoir, Spain
RESERVOIR Monitoring & Modelling
Cross Section 40 470 a
Cross Section 50 470
initial observed modelled
460 450 440
Elevation (m)
430 100
300
500 x (m)
700
900
450 440 430 Elevation (m) 420 410 600
470 initial observed modelled
a 460
440 430 Elevation (m) 420 200
500
800 x (m)
1400
1800
Cross Section 59
470 450
1000 x (m)
Cross Section 45 a 460
initial observed modelled
a 460
1100
1400
450 440 430 Elevation (m) 420 410 250 300
initial observed modelled
350 400 x (m)
450
500
Bed elevation changes at four different cross sections of the Barasona reservoir, 1986-1993
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RESERVOIR Monitoring & Modelling
450.00 445.00 440.00 435.00 430.00 1986 1993 1993 1993 1993
425.00
m eas ured m eas ured calc. W u et al calc. T s inghua Equat ion calc. A s hida and M ichiue
Elevation (m)
420.00 415.00 410.00
12000
10000
8000
6000
4000
2000
0
D is t ance from t he dam (m )
Deposition patterns of the Barasona Reservoir (1986-1993)
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RESERVOIR Monitoring & Modelling: Storage volume changes by deposition and erosion
1st Simulation Period (1986-1993): no management
36
RESERVOIR Monitoring & Modelling: Storage volume changes by deposition and erosion
2nd Simulation Period (1995 -1997): flushing
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IV
Applications examples to Large River Basins
ØUpper Jaguaribe Basin, Brazil Ø Upper Sao Francisco River Basin,
Brazil ØMahanadi River Basin, India
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Large-scale process-based hydrol. modelling in the Upper Sao Francisco River Basin n Study area: Alto Sao Francisco, ate Tres Marias n Description: Area de drenagem do Alto rio Sao
Francisco ate a barragem de Tres Marias n Applied hydro-sedimentological model: WASASED n Data: EMPRAPA, USGS, EU ‌
Sao Francisco River Basin
Division in sub-catchments
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Data: SRTM, 2000 (USGS)
Data: EC, 2002
Vegetation Parameter derived from these data o Stomata_Resistance [s/m] o min_suction [hPa] o max_suction [hPa] o Height [m]* o Root-depth [m]* o LAI [-]* o Albedo [-]*
*seasonal
Data: EMPRAPA, 1999
Soil Parameter derived from these data
o Soil particle fraction* o Alluvium o Gravel o Organic Carbon
*for each soil horizon
Ways ahead‌ Seamless Prediction of hydrological extremes
Sources of uncertainty and concept of uncertainty analysis
Seamless Prediction Prediction of of hydrological hydrological extremes: extremes Seamless Example: Mahanadi Basin, India
Mahanadi Basin: •Area: 140 000 km •Monsoon climate: wet summers, dry winters •Annual rainfall: about 1500 mm •55% agricultural land (rice)
Mahanadi river at Mundali, June 2015
Seamless Prediction of hydrological extremes: Meteorological Forcing: 15 members of the multi-model seasonal forecasting system from the European Centre of Medium-Range Weather forecast To get regionalised meteorological forecasts the method of expanded downscaling is applied (BĂźrger et al., 2009) Era-Interim precipitatio n (black line) and ensemble simulations (gray shadow)
Seamless Prediction of hydrological extremes: Hydrological Modelling
Precipitation (black), observed discharge (blue dots) and simulated discharge (red) for Basantpur gauging station and Hirakud inflow
Station
Cal
Val
Basant pur
0.8 4
0.7 6
Hiraku d
0.8 9
0.8 6
NSE for calibration (Cal) and Validation (Val) period
Seamless Prediction of hydrological extremes Seamless Prediction of hydrological extremes: Work in progress Estimation of predictive uncertainty → Hydrological uncertainty processor (Krzysztofowicz, 1999) → Quantile regression (Weerts et al., 2011) Preliminary results for predictive uncertainty using quantile regression:
Residuals vs. simulated discharge with quantile regression (95%) in real space
Observed inflow (blue dots), simulated inflow (gray line) and 95% confidence interval (red shadow) for Hirakud reservoir
V Conclusions Ø
High relevance of “hot-spots” for sediment production
Ø
connectivity between the landscape compartments plays a very relevant role for both water and sediment transport
Ø
Varying relevance in different space-time scales !
Ø
Relative sediment retention in reservoirs is strongly dependent on the scale Reservoir sedimentation stronger affected by land use and water management than by climatic scenarios Integrated hydro-sedimentological modelling is essential to sustainable manage land and water resources in drylands New opportunities: drought forecasting; seamless
Ø
Ø
Ø
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V Outlook Ø BHSF: important and interesting Ø Water management is highly important Ø Model system WASA-Sed: o mulit-scale and process based o tailored for semi-arid conditions o water and sediment fluxes o freely available Ø Currently in Brazil under application for: o Upper Sao Francisco Basin (Trés Marias) o Seasonal drought forecasting, incl. water management o climate change impacts for water and sediment management Ø Further ideas for application are very welcome
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Studies of erosion and sediment transport in semi-arid Regions
Muito obrigado para atenção Projects funded by: DFG, BMBF (D) CAPES, CNPq (Br)
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