Coupmodel - Bayern

17
Freising, 27.-28. 04. 2010 Workshop water balance models Coupmodel Coupled heat and mass transfer model for soil-plant-atmosphere systems Lorenz Walthert and Elisabeth Graf-Pannatier Swiss Federal Institute for Forest, Snow and Landscape Research (WSL)

Transcript of Coupmodel - Bayern

Page 1: Coupmodel - Bayern

Freising, 27.-28. 04. 2010 Workshop water balance models

Coupmodel

Coupled heat and mass transfer model

for soil-plant-atmosphere systems

Lorenz Walthert and Elisabeth Graf-Pannatier

Swiss Federal Institute for Forest, Snow and Landscape Research (WSL)

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Freising, 27.-28. 04. 2010 Workshop water balance models

Coupmodel - some general information

What is Coupmodel– coupled heat and mass transfer model

– consists of different coupled sub-models

– has been developed for modeling hydrological or thermal processes in the soil-plant-atmosphere systems

Central part of Coupmodel are two coupled differential equations for water and heat flow, that consider– the law of conservation of mass and energy and

– Darcy's law (water flows occur as a result of gradients in water potential) and Fouriers's law (energy flows occur as a result of gradients in temperature)

The soil is integrated in Coupmodel as soil profile with one ore several layers

Single- or multirun-mode is possible

The model has been developed by Per-Erik Jansson et al. (1979-2010)

Coupmodel is available on the Internet (free of charge):– http://www.lwr.kth.se/Vara%20Datorprogram/CoupModel/index.htm

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Freising, 27.-28. 04. 2010 Workshop water balance models

Coupmodel - data input I

The calculations of water and heat fluxes are based on soil properties such as

– the water retention curve

– functions for the unsaturated and the saturated hydraulic conductivity

– missing hydraulic soil properties can be derived from a database, that is integrated in Coupmodel (Coup-internal PTF)

Important plant properties are

– how the plants regulate water uptake from the soil and transpiration

– how the plant cover influences both aerodynamic conditions in the atmosphere and the radiation balance at the soil surface

– the development of leaf area in the course of the year

Meteorological data are the driving variables to the model (time series)

– most important are precipitation and air temperature

– air humidity, wind speed and cloudiness are also of interest

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Freising, 27.-28. 04. 2010 Workshop water balance models

Coupmodel - data input II

How can you enter data into the Coupmodel?

Switch: is a tool to define the configurations of Coupmodel for a given simulation

Switches are grouped in 21 modules each with several options and values e.g.:

Module Option Values

Soil Hydraulic Hydraulic Functions VanGenuchten/Brooks&Corey

Plant Root Distribution linear/exponential/table

Parameter: is a single input constant with a default value and a potential range of values for each parameter. Parameters are grouped in 19 Modules, e.g.:

Module Parameter Value Default Min Max

Interception WaterCapacityPerLAI (mm/m2) 0.5 0.2 0.05 1.0

Meteorol. Data Reference Height (m) 40 2 1 100

Parameter Table: is a table that includes one or more parameters (constants). Parameter tables are grouped in 9 modules, e.g.:

Module Parameter Table Values_Theta_s (%) Values_alpha (kPa-1) Values_n (-)

Soil Hydraulic Van Genuchten

layer 1 65 0.154 1.533

layer 2 52 0.176 1.425

layer n 43 0.233 1.563

Model File: data input with a data file, e.g.,Filename.BIN with daily values of temperature and precipitation

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Coupmodel - data input III

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Freising, 27.-28. 04. 2010 Workshop water balance models

Coupmodel - data output

Some results of a simulation are obtained as time series (e.g. daily values) for all individual layers of the soil, such as

– soil temperature

– water content and water potential

– water uptake by roots

Other results are emitted as time series for the whole site, such as

– snow depth

– surface runoff

– drainage

Soil profile x, depth 12-20 cm; daily values, 1976-2006, May-October

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0

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Matric

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Pa

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Own experiences with Coupmodel (2007-2010)

We model the water balance of selected Swiss forest sites with two approaches, differing in quality and quantity of the available data

High quality data– 5 Level II plots in Switzerland

– the main goal is to estimate mass balances and drought stress on the Level II plots

– many measured parameters for parametrisation, calibration and validation of the Coupmodel are available

– the data time series cover the last 10 years

– 2 meteo stations, one in the forest and one in the open land, record air temperature, precipitation, radiation, relative air humidity and wind speed

– matric potential is measured biweekly with tensiometers equipped with suction cups (water content only since 2009)

– throughfall is measured biweekly

– many other measured parameters like soil matrix data or leaf area index are available

– for the calibration and validation of Coupmodel, we use time series of matric potential and interception

– Elisabeth Graf-Pannatier is responsible for this high end approach

Standard quality data– 1000 Swiss forest sites

– the main goal is to assess the water availability for trees and herbs on these 1000 sites

– we use the same model calibration than on the Level II plots

– no measured data of time series are available

– available are the data of a soil profile and the data of a floristic inventory according to Braun-Blanquet on all sites

– daily meteorological input-data has been modeled with Daymet in a 100 m resolution for the period 1930-2006 (air temperature, precipitation, radiation and relative air humidity)

– Lorenz Walthert is responsible for this standard approach

interception loss

(bulk precipitation - throughfall)

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Own experiences – plausibilisation of output data

We try to plausibilize the results of our water balance simulations

When we started to work with Coupmodel, we soon realized that it is not only necessary to calibrate and to validate the model with our own data but also to plausibilize the results with data from the literature.

We plausibilize our results with data from the following literature:

– Literature-study of L. Walthert (2009, written in German)• forest-canopy-conductance (gc_max), stand-transpiration, reduction of transpiration due to

drought stress (AT/PT)

• results from sap-flow-measurement-projects, catchment-studies, and eddy-covariance-plots

– Van der Salm et al. (2007): Water balances in intensively monitored forest ecosystems in Europe

• interception, evapotranspiration

– Richard et al. (1978-1987): Physikalische Eigenschaften von Böden der Schweiz (Lokalformen)

• saturation level (water level) in hydromorphic soils (gley and pseudogley)

– Hydrologischer Atlas der Schweiz (1992-2010)• Runoff-coefficients (runoff/precipitation) from more than 1000 hydrological catchments of

Switzerland

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Own experiences – Coupmodel configuration

Some details of our model configuration (switches)

Model structure

– snowpack: on

– groundwater flow: on

• lower boundry: no flow - we control the drainage with a drainage pipe (depth, distance)

• lateral water input: off

Soil hydraulic

– conductivity function: Mualem

– hydraulic function: Van Genuchten

Water uptake

– basic equation: pressure head response

Plant

– root distribution: exponential

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Freising, 27.-28. 04. 2010 Workshop water balance models

Own experiences - meteorology

Meteorology

we compared the modeled daily meteorological parameters (Daymet) with

the measured ones on 6 Swiss Level II plots

– the quality of modeled temperature and precipitation is good

– the quality of modeled radiation and air humidity is moderate

• in regions with a strong relief, the maximal modeled radiation is 25 % too

low on steep, north facing slopes

at the beginning, Coupmodel delivered too high evapotranspiration rates;

the model produced reasonable values after we increased the reference

height of meteorological data from 2 m (default) to 40 m

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Own experiences – plants I (LAI)

Plants I

we calculated the maximal LAI of each of our 1000 forest sites with a

regression model, that uses simple site and vegetation parameters as

input variables; the regression model is based on data from a combined

survey of vegetation and hemispherical photographs on 90 Swiss forest

plots (Powerpoint-presentation is available)

minimal LAI in deciduous forest during winter is roundly 20 % of LAI_max

(literature study)

for deciduous and larch forests, the development of LAI during the year

was derived from phenological data collected by MeteoSchweiz during the

last decades

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Freising, 27.-28. 04. 2010 Workshop water balance models

Own experiences – plants II

Plants II

at the beginning, Coupmodel underestimated the interception rates; the model produced reasonable values after we changed the values of WCB, WC/LAI as well as MaxCover and AreakExp (canopy gaps as a function of LAI)

– the manipulation of WCB and WC/LAI was based on measured interception-time-series of 5 Swiss Level II plots and in the case of MaxCover und AreakExp on vegetation data of 1000 Swiss forest sites (canopy structure and LAI)

with the default value of 20 mm/s for the canopy conductance (gc_max) Coupmodel overestimates the transpiration rates, plausible transpiration values can be obtained with 10 mm/s for deciduous forests, 9 mm/s for mixed forests and 8 mm/s for coniferous forests (literature study)

we fixed the rooting depth in all soils at 150 cm, with exception of soils having a Gr-horizon (gleys) or a R-horizon (bedrock)

– 150 cm seems reasonable after we evaluated the rooting depth and the rooting intensity in roundly 600 Swiss forest soils of our soil database

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Own experiences – soil I (stone content)

Stone content (> 2 mm)

stones have an influence on the water balance of soils

we wish that the plant available water is reduced proportionally to the stone content of the soil

therefore we manipulated the pF-curve by reducing the water contents Theta_s, Theta_r and Theta_pwp proportionally to the stone content but we did not change the shape parameters (alpha, n) of the pF-curve

when the plant available water amount (nWSK) (50 to 15'000 hPa) gets very small (<5Vol%) due to the manipulation of the pF-curve, Coupmodel fails to simulate the water balance correctly (matric potential shows a high zero-bias in the horizon just above the zone with the critical nWSK of <5Vol%)

1976-2006, May-October, daily values

Matric potential 45-70 cm

nWSK > 70 cm = 3 Vol%; Ksat: KA5

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1976-2006, May-October, daily values

Reduction of transpiration AT/PT

nFK > 70 cm = 3 Vol%; Ksat: KA5

Horizon OG UG sand silt clay FE-density Corg Skelett nFK (KA5, ohne Skelett) nFK (KA5, mit Skelett) alpha (KA5) n (KA5)

m m % % % g/cm3 % % (cm3/cm3) (cm3/cm3) kPa-1 -

Ah 0.0 0.3 14 34 52 0.65 9.0 5 0.37 0.35 0.132 5.233

AC 0.3 0.7 22 24 54 0.90 3.2 63 0.25 0.09 0.330 1.352

C 0.7 1.3 26 38 36 1.00 1.0 88 0.22 0.03 0.252 1.530

C 1.3 1.4 26 38 36 1.00 1.0 88 0.22 0.03 0.252 1.530

C 1.4 1.5 26 38 36 1.00 1.0 88 0.22 0.03 0.252 1.530

C 1.5 1.6 26 38 36 1.00 1.0 88 0.22 0.03 0.252 1.530

C 1.6 1.7 26 38 36 1.00 1.0 88 0.22 0.03 0.252 1.530

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Own experiences – soil II (stone content)

Stone content (> 2 mm)

many simulations of stone rich soils showed that the zero-bias of matric potential gets tolerable when nWSK is bigger than 6 Vol% in all layers of the soil profile. As a consequence, the amount of stones, that can be considered for the manipulation of the pF-curve, is calculated with respect to both the minimal tolerable nWSK (e.g. 6 Vol%) and the nWSK of the soil without stones.

1976-2006, May-October

Matric potential 45-70 cm

nWSK > 70 cm = 3 Vol%; Ksat: KA5

1976-2006, May-October

Reduction of transpiration AT/PT

nFK > 70 cm = 6 Vol%; Ksat: KA5

Horizon OG UG sand silt clay FE-density Corg Skelett nFK (KA5, ohne Skelett) nFK (KA5, mit Skelett) alpha (KA5) n (KA5)

m m % % % g/cm3 % % (cm3/cm3) (cm3/cm3) kPa-1 -

Ah 0.0 0.3 14 34 52 0.65 9.0 5 0.37 0.35 0.132 5.233

AC 0.3 0.7 22 24 54 0.90 3.2 63 0.25 0.09 0.330 1.352

C 0.7 1.3 26 38 36 1.00 1.0 88 0.22 0.06 0.252 1.530

C 1.3 1.4 26 38 36 1.00 1.0 88 0.22 0.06 0.252 1.530

C 1.4 1.5 26 38 36 1.00 1.0 88 0.22 0.06 0.252 1.530

C 1.5 1.6 26 38 36 1.00 1.0 88 0.22 0.06 0.252 1.530

C 1.6 1.7 26 38 36 1.00 1.0 88 0.22 0.06 0.252 1.530

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Own experiences – soil III

Organic layer and drought stress

We considered the organic layer in our simulations but we realised, that

there is a big incertitude concerning both Ksat and the Van Genuchten

Parameters in organic layers (Wösten et al., 1999; Hammel and

Kennel, 2001; Schramm et al., 2006).

Attention: if you want to quantify drought stress as AT/PT, you should

use not PT but potWaterUptake in the Coupmodel. Be aware that

frozen soil influences AT/PT.

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Coupmodel - open questions - Ksat

different PTF provide very different values for Ksat especially for loose and porose soil layers (e.g. KA5, 2005 or Balland et al., 2008). In some soils, the value of Ksat has an extremely high impact on the drying of the soil. Which value of Ksat might be reasonable for porose, humus rich topsoils with a density between 0.6 and 0.9 g/cm3?

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Matric potential 0-5 cm

nFK > 70 cm = 6 Vol%

Ksat: KA5 (80 mm/d)

1976-2006, May-October, daily values

Matric potential 0-5 cm

nFK > 70 cm = 6 Vol%

Ksat: 3000 mm/d (Balland et al., 2008: 3075 mm/d)

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Coupmodel - open questions II

We lost a lot of time by searching a reasonable PTF for the Van Genuchten Parameters (Schramm et al., 2006). Can we expect a better PTF from the Multistep Outflow Experiments of Von Wilpert et al.?

Are now better PTF’s available for organic layers than formulated by Wösten et al. (1999) or by Hammel and Kennel (2001)?

How can we model the aeration / air regime of soils with a Darcy based water balance model? What are the consequences on the air regime, when we manipulate the pF-curve due to stones in the soil (reduction of porosity)?

To what extent do stones influence the water conductivity?

Quantification of lateral flow in hydromorphic soils?

Is there any literature available dealing with surface runoff on forest sites?

How can we incorporate relief characteristics (concave, convex) in Darcy based water balance models (loss or supply location)?

Can we use hydromorphic symptoms of the soil in water balance models?