christian klar and peter neuhaus 19.9.2005 working group ‚agroecosystems‘ designing an...

Christian Klar and Peter Neuhaus 19.9.2005

Working group ‚Agroecosystems‘

Designing an object-oriented architecture for process-based modelling of soil nitrogen fluxes in DANUBIA

Christian Klar and Peter Neuhaus



Outline

Introduction

Model description

Modelling tools

OOP, Java & UML

Process model

Architecture

Computation cycle

Debugging and validation

Easy expandability

Summary

Perspective



Introduction

GLOWA-Danube and DANUBIA

• Integrative and interdisciplinary research program of the BMBF

• GLOWA – Global Change of the Water cycle

• Development of integrative strategies for the sustainable and anticipatory management of water at the regional scale (Upper Danube catchment)

• Development of the integrative, multi-disciplinary decision support system DANUBIA

What is our function/role in GLOWA-Danube?

• Working group ‘Agroecosystems‘ is responsible for the development of the agricultural plant growth and the nitrogen transformation component within GLOWA-Danube

• Implementation of nitrogen transformation processes and plant uptake

Why to develop a new model instead of using an existing one?

• Connection to the complex framework of DANUBIA demands technical adaptations/restrictions

• DANUBIA is implemented in JAVA

• JAVA as programming language still rarely used in ecological modelling



Model description

General information:

• Process description based on CERES approach

• Spatially distributed

• Spatial resolution: 1 km²

• Temporal resolution: daily

Why CERES?

• Suitable process description for the use in DANUBIA

• Established in the modelling society

• Well validated

• Freely available code

Project status:

• Technical development and validation completed

• Validation of model results has just started



OOP, Java and UML

Why to use these modelling tools?

• OOP (Object oriented programming) especially suited for ecological modelling by „breaking systems into intellectually manageable components and combining

them and making explicit the interactions between them“ (Wainwright 2005, 9)

• JAVA is one of the most widespread OOP-languages, industry standard, independent of operating system and comparatively easy to learn

• UML (Unified modelling language) is a graphical meta-modelling language to describe the structure of models and

serves as common interdisciplinary language to describe models and interfaces

enables involved disciplines to jointly model complex processes and interactions in an integrated system (Ludwig et al. 2003)

UML and JAVA are well suited for object-oriented ecological modelling!



OOP, Java and UML

How can ecosystem modelling benefit from Object Oriented Programming?



Architecture

Grid cell, Process pixel

Delegates calculations per layer

Common data object, preparation of data

Interface for processes, defines states

Container for processes

Explicit and restricted data exchange

Processes encapsulate

their own state, process

description, data

Debugging tool



Computation cycle

Datapool

Data import& preparation

Processes

Data computation

DatapoolData export




Process debug proxy:

• facilitates technical debugging and

validation of processes without manipulation of

source code

• acts as an intermediary for any process object

• implements the same interface as the

process object (Process)

• forwards method calls to process object and writes/logs information

about the process state



Easy expandability

Adding a new process:

e.g. modelling of phosphorous conversion or N2O emission

1) Building an interface

only few lines of code

specifies which data can be exchanged with pool

2) Implementing the process logic

implementation of the process algorithms

no side effects with other processes or pool data (encapsulation)

3) Data pool extension

only if new input or output data are needed

4) Process registration

via config-file



Summary

The Process framework serves multiple purposes:

1) Modular structure and encapsulation

- clear organisation of code, separation of scientific content from technical framework

- separation and encapsulation of individual processes

- no uncontrollable side effects2) Data integrity

- explicit and restricted data exchange

- controlled access to and manipulation of shared and global data

3) Debugging and validation

- log and debug output is configurable at runtime

- selection of processes is configurable at runtime

4) Applicability

- easy for new/unexperienced-programmers

- model calculations easily manageable and traceable



Perspective for DANUBIA

Parametrisation, calibration and validation: • On the microscale

• Comparison of modelling results with measurements and validated point models, statistical analysis

Perspective:

• Modelling of nitrogen fluxes between soil-plant system

• Spatially distributed nitrogen fluxes modelling on the mesoscale • Development of a subscale approach with landuse/soil texture classes to

consider landscape heterogeneity

• Development of strategies to validate nitrogen fluxes on a regional scale

• Modelling of nitrogen fluxes under Global Change conditions (long termpredictions)




Sequence diagram:

1) fetch() and compute()are forwarded

2) whenever compute() is called the proxy‘s debug() method is triggered

3) debug() uses introspection to get actual data values from the respective process object at each timestep

4) data values are then logged by DataWriter object

1.

2.3.

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christian klar and peter neuhaus 19.9.2005 working group ‚agroecosystems‘ designing an...

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