Abstract

The CoupModel has been developed to represent a platform with a number of models that could be linked together for the specific application of the user. A review of its model development, calibration procedures and previous applications are made here. For each application the user of the model can select different module and how they should be linked. In the next step appropriate input to run the model has to be specified based on the choice of modules. The modules include water, heat, tracers, chloride, nitrogen and carbon of any terrestrial ecosystem including soil, plant and atmosphere components. The spatial distribution is lumped or distributed to any used defined scale. Temporal resolution is from minutes to some 100-years. The platform allows the user to specify inputs as (1) forcing time series, (2) simple predefined patterns of variation by parameter functions or (3) dynamic parameters that could change value at specified dates during the simulation. Output variables from simulations can be compared with any independent measurement either as time series or as a single value. The performance is expressed as conventional statistical indicator or as log likelihood sums. Simulations are made as single runs to represent a unique input or as a multiple series of simulations based on random or systematic sampling of parameter values. Parameters can also represent an object that is a collection of different parameters to represent one certain system (for instance a soil profile). Two possible approaches: Bayesian or generalized likelihood uncertainty estimation (GLUE) may be used for calibration. The former is using a Markov chain Monte Carlo (MCMC) method to sample among parameter values based on predefined error parameters for estimation of log likelihoods.

Keywords: Richards Equation, Fourier equation, soil frost, snow, greenhouse gas emissions, soil carbon sequestration, climate change, water use efficiency, light use efficiency, nitrogen use efficiency, ecosystem

Background

The CoupModel represents a platform of various modules (Jansson & Moon, 2001) that have been developed and modified since 1979 when the SOIL model was first published (Jansson & Halldin, 1979) with a basic description of how to simulate water and heat fluxes in a soil profile. The model has a strong focus on soil physics and presented a coupling between the Richards equation for the water flow with the corresponding Fourier equation for heat flows in a 1D domain. A major focus was to describe the hydrological processes during the course of a year with daily resolution within the boreal region. The model was later modified to include the turnover of nitrogen processes in soils and the SOILN was presented (Johnsson et al, 1987) with a direct coupling to the SOIL model. In its infanty the SOIL model was mainly used for forest ecosystem within the Boreal region (Jansson, 1987; Jansson et al, 1999 and Gustafsson et al, 2004) but was later applied to any type of terrestrial system including semi-arid regions (RockStröm et al, 1998) and regions with permafrost conditions (Hollesen et al, 2011). Various options for understanding and simulating macropore flows during unfrozen (Eckersten & Jansson, 1991) and frozen conditions (Stähli et al, 1996) have been implemented as options of the model. Most of the application was made by simulation of one single profile but various methods have been used to represent the connection of water flows from one position to another within the area as first presented by Espeby (1982) and later on was further developed to test the role of soil freezing on generation of runoff to a stream (Stähli et al, 2001).

The plant components were assumed to be governed by forcing inputs to the model but was further developed to include a dynamic plant representing both carbon and nitrogen processes (Eckersten & Jansson, 1991; Blombäck et al, 1995; Eckersten et al, 1995 and Eckersten et al, 1998). More recent developments have been made to includ various options of the plant growth with connection to a wide range of limiting factors for plant development (Karlberg et al, 2006, Zhang et al, 2007 and Wu et al, 2011a). Attention has been made on simulation of carbon sequestration in forest ecosystem (Svensson et al, 2008b) and in that case also simulation of climate impacts (Jansson et al, 1998). In addition more components have been added by including a detailed model for the denitrification as first presented by Norman et al (2008). Model improvement was carried out by adopting a detailed submodel of microbiological production of gaseous N from the PnET-N-DNDC model (Li et al., 2000). A submodel to follow trace elements within the soil-plant-atmosphere system (Gärdenäs et al, 2009) is also implemented as part of the platform. A submodel for how to simulate the spread of de-icing salt in the roadside environment has also been developed (Lundmark & Jansson, 2008). Other applications have been focusing on understanding detailed physical processes for common an artificial surface like asphalt (Jansson et al, 2006)

The CoupModel software (KTH, 2011) has been continuously improved and modified during the last 10 years but also prior that the previous SOIL and SOILN models have been distributed free of charge. A detailed technical description was first published by Jansson & Karlberg (2004) and later on it was also published as a translation to Chinese (Jansson & Karlberg, 2009). Today it is published online as a pdf document (Jansson & Karlberg, 2010) and as complete help library on the internet. The model has o a user-group that is administrated from KTH as an interactive forum for the users. Also informal courses and tutorials are available from KTH.

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