Diapositive 1

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Surveillance monitoring
Hydrology
Hierarchical Framework
Water quality
Operational monitoring
Land Cover structure
Land Use
Investigative monitoring
Land Cover structure
Land Use
Scenario of change
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Data requirement for HBV
Input data are observations of precipitation, air
temperature and estimates of potential
evapotranspiration. The time step is usually one
day, but it is possible to use shorter time
steps. The evaporation values used are normally
monthly averages although it is possible to use
daily values. Air temperature data are used for
calculations of snow accumulation and melt. It
can also be used to adjust potential evaporation
when the temperature deviates from normal values,
or to calculate potential evaporation. If none
of these last options are used, temperature can
be omitted in snow free areas.
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Information on HBV model
The HBV model (Bergström, 1976, 1992) is a
rainfall-runoff model, which includes conceptual
numerical descriptions of hydrological processes
at the catchment scale. The general water
balance can be described as
where P precipitation E evapotranspiration
Q runoff SP snow pack SM soil moisture
UZ upper groundwater zone LZ lower
groundwater zone lakes lake volume
The standard snowmelt routine of the HBV model is
a degree-day approach, based on air temperature,
with a water holding capacity of snow which
delays runoff. Melt is further distributed
according to the temperature lapse rate and is
modeled differently in forests and open areas. A
threshold temperature, TT, is used to distinguish
rainfall from snowfall. Although the automatic
calibration routine is not a part of the model
itself, it is an essential component in the
practical work. The standard criterion
(Lindström, b1997) is a compromise between the
traditional efficiency, R2 by Nash and Sutcliffe
(1970) and the relative volume error, RD
In practice the optimisation of only R2 often
results in a remaining volume error. The
criterion above gives results with almost as high
R2 values and practically no volume error. The
best results are obtained with w close to 0.1.
The automatic calibration method for the HBV
model developed by Harlin (1991) used different
criteria for different parameters. With the
simplification to one single criterion, the
search method could be made more efficient. The
optimisation is made for one parameter at a time,
while keeping the others constant. The
one-dimensional search is based on a modification
of the Brent parabolic interpolation (Press et
al., 1992). Description of the HBV model
captured from http//www.smhi.se/sgn0106/if/hydro
logi/hbv.htm Link to official homepage http//www
.smhi.se/foretag/m/hbv_demo/html/welcome.html
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Information on HBV output
In different model versions HBV has been applied
in more than 40 countries all over the world.
The model is used for flood forecasting in the
Nordic countries, and many other purposes, such
as spillway design floods simulation (Bergström
et al., 1992), water resources evaluation (for
example Jutman, 1992, Brandt et al., 1994),
nutrient load estimates (Arheimer, 1998).
It is possible to run the model separately for
several sub basins and then add the contributions
from all sub basins. Calibration as well as
forecasts can be made for each sub basin. For
basins of considerable elevation range a
subdivision into elevation zones can also be
made.
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Information on SCS data requirement
The data requirements for this method are very
low, rainfall amount and curve number. The curve
number is based on the area's hydrologic soil
group, land use, treatment and hydrologic
condition. The last two variables are of
greatest importance.
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Information on SCS model
The general equation for the SCS curve number
method is as follows
The initial equation (1) is based on trends
observed in data from collected sites therefore
it is an empirical equation instead of a
physically based equation. After further
empirical evaluation of the trends in the data
base, the initial abstractions, Ia, could be
defined as a percentage of S (2). With this
assumption, the equation (3) could be written in
a more simplified form with only 3 variables.
The parameter CN is a transformation of S, and
it is used to make interpolating, averaging, and
weighting operations more linear (4). Curve
numbers are available for most land-use types.
lateral
flow
return
flow
( Slide from W. Bauwens, 2006 )
Description of the SCS method captured from
http//www.ecn.purdue.edu/runoff/documentation/scs
.htm
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Information on SCS model output
The SCS curve number method is a simple, widely
used and efficient method for determining the
amount of runoff from a rainfall even in a
particular area. The SCS curve number method is
often included in more advanced hydrological
models to evaluate surface runoff (e.g. HBV and
SWAT). Although the method is designed for a
single storm event, it can be scaled to find
average annual runoff values.
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Information on TRK model
The TRK system combines 1.    Preparation of
areal distribution of different land-use
categories and positioning of point sources using
GIS 2.    Calculations of concentration and
area losses of diffuse sources (for N from
arable land by using the dynamic soil profile
model SOILNDB) 3.    Calculations of the water
balance (by using the distributed dynamic HBV
model) and N transport and retention processes
in water (by using the model HBV-N).
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Information on TRK model output
The results are presented in the GIS, and source
apportionment is made for each sub-basin as well
as for the whole river basins. The results from
the system have been used for international
reports on the transport to the sea, for
assessment of the reduction of the anthropogenic
load on the sea and for guidance on effective
measures for reducing the load on the sea on a
national scale.
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Data input for WATSHMAN

• Map themes
• Basic maps
• Sub catchments
• Streams
• Lakes
• Elevation data
• Soil maps
• Land use

• Tabular information
• Point sources
• Climate data
• Monitoring data
• Model results

Main input form
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Information on WATSHMAN
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Data output from WATSHMAN
- Data management and presentation options such
as selecting, editing, simple calculations and
usual GIS functions.
- Nutrient transport options with chains of
models such as diffuse leakage, lake retention
model etc.
- Scenario management options such as changes in
crop, landuse, sewage treatment etc.
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Data input from INCA model
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Information on INCA model
Instream processes
Land component
A.J. Wade, P. Durand, V. Beaujouan, W.W. Wessel,
K.J. Raat, P.G. Whitehead, D. Butterfield, K.
Rankinen and A. Lepisto (2002), A nitrogen model
for European catchments INCA, new model
structure and equations. Hydrol.Earth Syst.
Sci., 6(3) 559-582.
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Output data from INCA model
Land component output
Instream component output
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Data input for SWAT model
Soil Map. For each soil layer Textural
properties Physico-chemical-properties Landuse
Map Landuse information crop, water bodies
(lake,pond, etc.) Cropping information planting
and harvest date, yield, etc. Management
practices fertilizer and pesticide application
timing and amount Climate Information Daily
rainfall, minimum and maximum air temperature,
net solar radiation Monthly average wind speed
Average monthly humidity Water Quality
Information Point sources Location Average
daily flow Average daily sediment and nutrient
loading Hydrogeological Map Groundwater
abstraction timing and amount Digital Elevation
Model Monitoring Data for model
calibration Observed flows at subbasin /basin
outlet(s) Nutrient loadings at subbasin/basin
outlet (s) Sediment loadings at subbasin/basin
outlet(s) Main validation data required Observed
flows at subbasin /basin outlet(s) Nutrient
loadings at subbasin/basin outlet (s) Sediment
loadings at subbasin/basin outlet(s)
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Information on SWAT model
SWAT uses a two-level dissagregation scheme a
preliminary subbasin identification is carried
out based on topographic criteria, followed by
further discretization using land use and soil
type considerations. The physical properties
inside each subbasin are then aggregated with no
spatial significance. The time step for the
simulation can be daily, monthly or yearly, which
qualify the model for long-term simulations.
Reference Model description Neitsch S.L.,
Arnold J.G., Kiniry J.R., Williams J.R., (2001),
Soil and Water Assessment Tool Theoretical
Documentation - Version 2000, Blackland Research
Center Agricultural Research Service, Texas
USA Reference Users guide Neitsch S.L., Arnold
J.G., Kiniry J.R., Williams J.R., (2001), Soil
and Water Assessment Tool User Manual Version
2000, Blackland Research Center Agricultural
Research Service, Texas USA
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Data output from SWAT
It predicts the long-term impacts in large basins
of management and also timing of agricultural
practices within a year (i.e., crop rotations,
planting and harvest dates, irrigation,
fertilizer, and pesticide application rates and
timing). It can be used to simulate at the basin
scale water and nutrients cycle in landscapes
whose dominant land use is agriculture It can
also help in assessing the environmental
efficiency of BMPs and alternative management
policies.
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Data input for CEQUALW2 model
The model has been widely applied to stratified
surface water systems such as lakes, reservoirs,
and estuaries and computes water levels,
horizontal and vertical velocities, temperature,
and 21 other water quality parameters (such as
dissolved oxygen, nutrients, organic matter,
algae, pH, the carbonate cycle, bacteria, and
dissolved and suspended solids). Version 3 has
the capability of modeling entire river basins
with rivers and inter-connected lakes,
reservoirs, and/or estuaries.
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information on CEQUALW2 model
A predominant feature of the model is its ability
to compute the two-dimensional velocity field
for narrow systems that stratify. In contrast
with many reservoir models that are
zero-dimensional with regards to hydrodynamics,
the ability to accurately simulate transport can
be as important as the water column kinetics in
accurately simulating water quality.
Link to CE-QUAL-W2 homepage http//www.ce.pdx.edu
/w2/
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Data output from CEQUALW2 model
CE-QUAL-W2 has been in use for the last two
decades as a tool for water quality managers to
assess the impacts of management strategies on
reservoir, lake, and estuarine systems.
CE-QUAL-W2 is a two-dimensional water quality and
hydrodynamic code supported by the USACE
Waterways Experiments Station (Cole and Buchak).
W2 models basic eutrophication processes such as
temperature-nutrient-algae-dissolved
oxygen-organic matter and sediment relationships.