Model (version-zalf)

Transcription

1 Designing User Interface for Biome-BGC BGC Model (version-zalf) H.M. Mehedi Hasan This project was funded by: Investition in Ihre Zukunft Gefördert durch das Ministerium für Arbeit, Soziales, Frauen und Familie aus Mitteln des Europäischen Sozialfonds und des Landes Brandenburg.

2 Content - A quick introduction to Biome-BGC Model (and its ZALF version) Rationale of developing a User Interface for the model Overview of the Design (of User Interface) Screenshots of User Interface Concluding Remarks

3 Introduction Biome BGC Biome-BGC is a simulation program It predicts water, carbon, nitrogen, and energy fluxes and storage for the vegetation and soil components of terrestrial ecosystems. The model includes processes concerning new leaf growth and old leaf litterfall, sunlight interception by leaves and penetration to the ground, precipitation routing to leaves and soil, snow accumulation and melting, drainage and runoff of soil water, evaporation of water from soil and wet leaves, transpiration of soil water through leaf stomata, photosynthetic fixation of carbon from CO2 in the air, uptake of nitrogen from the soil, distribution of carbon and nitrogen to growing plant parts, decomposition of fresh plant litter and old soil organic matter, plant mortality, and fire

4 Introduction Biome BGC The model is useful for: establishing the amount and distribution of carbon storage by plants; predicting the behavior of different ecosystems in case of changes of CO2 concentration in the air; exploring the controls of water stress and drought on plant carbon balance; exploring the inter-annual variability of climate on growing season; furnishing important parameters useful to manage the ecosystems and in particular forest

5 Introduction ZALF version ZALF version Inclusion of forest management module for multiple tree species and/or canopy layers, multi-layers in soil module for water, carbon, and temperature, a root growth, and a new phenology module

6 Introduction ZALF version

7 Rationale of User Interface Large Input set (11 input files) Large Output set 800+ output variable 13 output file Switching among different programs Text editor Console application Statistical Tools Hard to modify and hard to keep track among different versions of input / output file set. Increased Risk and demand high time and effort

8 Goals The goal of this project is to develop an interactive user interface intended to Hide the complexity of data handling Output visualization Automated parameter optimization

9 Methodology Planning System Analysis Process Analysis Data requirement Analysis System Design and Development Class Diagram Development Deployment

10 Planning Time Schedule Phase Topic Duration Status I Interface Design 4 Months Completed II Output Visualization 3 Months Completed Developing effective strategies for automated III model calibration 5 Months In progress

11 Planning Selection of tools Language: Python 3.33 Interface Design Tool PyQt4 Data visualization MatPlotLib, NumPy

12 Software Architecture A Black Box approach - User Interface does not know what is happening inside model - User Interface is connected to only input/output port of the model

13 Software Architecture Multi-Layered - Multiple functional layers - Communication through private channel - Layer detail is hidden inside the layer - Changed in one layer does not affect other

14 System Analysis Process Analysis - Create Parameter files - Run Model -Visualize Output - Comparison with measured field data - Change parameter and loop from beginning Modification of Parameter Files Start Create Parameter Files Model Settings, Mapping Input and Output Run Model Read and Visualize Output t Measured ddt Data Visual Comparison Store Parameter Files End

15 System Analysis Data Requirement Analysis Input Files

16 System Analysis Data Requirement Analysis Output Files output variable in four temporal dimension - Output variable are categorize by belongingness to site or vegetation and layer - Output are produced by temporal and site/vegetation

17 System Design Entities and Their Relationship (E-R Diagram)

18 System Design Class Diagram (Model Input)

19 System Design Class Diagram (Reading Data and Visualization)

20 System Design User Interface Classes

21 System Design User Interface Design -.ui file are important for incorporating future changes - 13 forms 13.ui files - 26 classes for user interface

22 Outcome/Result Outcome of this project is a small software The software creates input (parameter) files The model is run within the interface Visualization is comprehensive Changing Parameters is now easier Maintenance of proper versioning of input/output files is Maintenance of proper versioning of input/output files is possible and easier

23 Outcome Initial Setting - Form

24 Outcome Initial Setting - Form

25 Outcome Initial Setting - Form

26 Outcome Initial Setting - Form

27 Outcome Initial Setting - Form

28 Outcome GIS Parameter - Form

29 Outcome Vegetation Parameter - Form

30 Outcome Soil Parameter - Form

31 Outcome Ecophysiological Parameter - Form

32 Outcome Model Run - Form

33 Outcome Model Run - Form

34 Outcome Model Run - Form

35 Outcome Model Run - Form

36 Outcome Model Run - Form

37 Outcome Model Run - Form

38 Outcome Model Run - Form

39 Outcome Read Output - Form

40 Outcome Graph Design - Form

41 Outcome Graph Design - Form

42 Discussion Design is always important to achieve high performance (less execution time) The layer orientation and object oriented design provides flexibility (Adaptability) to change User friendliness is the core for interface design And a remarks: Python is a powerful and flexible language; ultimate flexibility also cause high risk. Python is very good for scripting but its OOP implementation is not that much strong.

43 Challenges Limited Time Poor documentation ti Bottlenecks: - communication between interface and simulation program is primitive -No database

44 Conclusion A careful design is very important to obtain high performance and flexibility The interface would be very useful for model users. It would ultimately reduce the time required for manual parameter optimization.

45 Thank You