SWAT

TRK

Surveillance monitoring

Investigative monitoring

Operational monitoring

Hydrology

Water quality

Scenario of change

CQW

Land UseLand Cover

structure

Land UseLand Cover

structure

HBV SCS

WTN INCA

INCA SWAT CQW

Hierarchical Framework

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.htmLink 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.

Description of the SCS method captured from: http://www.ecn.purdue.edu/runoff/documentation/scs.htm

Root zoneUnsaturated

Zone

SaturatedZone

DeepAquifer

precipitation

surfacerunoff

return flow

lateralflow

Evapo-transpiration

infiltration percolation

deep loss ( Slide from W. Bauwens, 2006 )

Information on SCS model output

The SCS curve number method is a simple, widely used and efficient methodfor 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).

LZ

UZ

AtmosphericDeposition

RuralHouseholds

respi ration manure harvest fertil izer

denitri -fication

leaching

N-litter

N-faeces

N-plant

NH4-N NO3-N

Redistribution of Nbetween layers

SOIL-N

deposition

N-humus

Forest

Pasture

Arable Land

Other Land

PointSources

AtmosphericDeposition

Lake

ilake

Rootzone leakageconcentrations

Q

N

HBV-NHBV-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

Tabular information

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

GIS data

ArcSDEGeodatabase

ArcGIS

ArcGIS with Watshman extension

ArcIMS / .NETWeb application

Import from ExcelMonitoring data

Models

Map themes• Basic maps• Sub

catchments• Streams• Lakes• Elevation data• Soil maps• Land use

Main input form

Information on WATSHMAN

Component view

Import & Quality

assurance

Modelling / Storage

Analysis & Presentation

Data collection

Activitity view

Actor view

System administator,Database administrator,

Modeller

Environmental Expert

Database administrator, Quality assurance expert,

GIS expert

Environmental expert,GIS-expert,

Decision maker

GIS data

ArcSDEGeodatabase

ArcGIS

ArcGIS with Watshman extension

ArcIMS / .NETWeb application

Import from ExcelMonitoring data

Database Forms

Models

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 MapLanduse information: crop, water bodies (lake,pond, etc.)Cropping information: planting and harvest date, yield, etc.Management practices: fertilizer and pesticide application timing and

amountClimate InformationDaily rainfall, minimum and maximum air temperature, net solar

radiationMonthly average wind speed Average monthly humidity Water Quality InformationPoint sources

LocationAverage daily flow Average daily sediment and nutrient loading

Hydrogeological MapGroundwater abstraction timing and amountDigital Elevation ModelMonitoring 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 requiredObserved 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.

rainfallTemperature

HumidityWind speed

Sun radiation

Soil characteristicsCrops

FertilizationSoil surface treatmentUse of agrochemicals

Type values for urban areas

Soils

Land cover

DEMLakes, water courses

Calibration and Validation

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 – USAReference 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-dimensionalwith 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.