Name
Title | ||
|---|---|---|
A software framework for construction of process-based stochastic spatio-temporal models and data assimilation |
Abstract | ||
|---|---|---|
Process-based spatio-temporal models simulate changes over time using equations that represent real world processes. They are widely applied in geography and earth science. Software implementation of the model itself and integrating model results with observations through data assimilation are two important steps in the model development cycle. Unlike most software frameworks that provide tools for either implementation of the model or data assimilation, this paper describes a software framework that integrates both steps. The software framework includes generic operations on 2D map and 3D block data that can be combined in a Python script using a framework for time iterations and Monte Carlo simulation. In addition, the framework contains components for data assimilation with the Ensemble Kalman Filter and the Particle filter. Two case studies of distributed hydrological models show how the framework integrates model construction and data assimilation. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1016/j.envsoft.2009.10.004 | Environmental Modelling and Software |
Keywords | Field | DocType |
ensemble kalman filter,spatio-temporal model,software implementation,process-based spatio-temporal model,model development cycle,snow,hydrological model,calibration,environmental model,pcraster,data assimilation,software framework,time iteration,particle filter,block data,hydrology,process-based stochastic spatio-temporal model,python,model construction,model result,monte carlo simulation | Data mining,Monte Carlo method,Computer science,Particle filter,Block (data storage),Temporal models,Data assimilation,Ensemble Kalman filter,Python (programming language),Software framework | Journal |
Volume | Issue | ISSN |
25 | 4 | Environmental Modelling and Software |
Citations | PageRank | References |
20 | 1.58 | 10 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Derek Karssenberg | 1 | 112 | 16.11 |
| Oliver Schmitz | 2 | 36 | 4.45 |
| Peter Salamon | 3 | 41 | 5.70 |
| Kor De Jong | 4 | 119 | 14.08 |
| Marc F. P. Bierkens | 5 | 22 | 2.05 |