Surveillance monitoring
Hydrology
HBV
Hierarchical Framework
SCS
Water quality
TRK
Operational monitoring
Land Use
Land Cover
structure
Investigative monitoring
Land Use
WTN
INCA
SWAT
CQW
INCA
Scenario of change
Land Cover
structure
SWAT
CQW
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.
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/hydrologi/hbv.htm
Link to official homepage:
http://www.smhi.se/foretag/m/hbv_demo/html/welcome.html
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.
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.
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.
precipitation
surface
runoff
Evapotranspiration
Root zone
Unsaturated
Zone
infiltration
percolation
Saturated
Zone
lateral flow
return flow
Deep
Aquifer
deep loss
( Slide from W. Bauwens, 2006 )
Description of the SCS method captured from: http://www.ecn.purdue.edu/runoff/documentation/scs.htm
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.
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).
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.
Data input for WATSHMAN
Map themes
• Basic maps
• Sub
catchments
• Streams
• Lakes
• Elevation
data
• Soil maps
Tabular
information
• Point sources
• Climate data
• Monitoring data
• Model results
Main input form
• Land use
Models
Monitoring data
Import from Excel
ArcGIS with
Watshman
extension
ArcSDE
Geodatabase
GIS data
ArcGIS
ArcIMS / .NET
Web application
Information on WATSHMAN
Component view
Models
Monitoring data
Import from Excel
ArcGIS with
Watshman
extension
ArcSDE
Geodatabase
GIS data
ArcGIS
ArcIMS / .NET
Web application
Database Forms
Activitity view
Data
collection
Import &
Quality
assurance
Modelling /
Storage
Analysis &
Presentation
Actor view
Environmental
Expert
Database administrator,
Quality assurance expert,
GIS expert
System administator,
Database administrator,
Modeller
Environmental expert,
GIS-expert,
Decision maker
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.
Data input from INCA model
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.
Output data from INCA model
Land component output
Instream component output
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)
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.
DEM
Lakes, water courses
Soil characteristics
Crops
Fertilization
Soil surface treatment
Use of agrochemicals
Type values for urban areas
Calibration and Validation
Land cover
Soils
rainfall
Temperature
Humidity
Wind speed
Sun radiation
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
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 BMP’s and alternative management policies.
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.
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/
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.