2. Interface to use SIMPLACE from R- Package simplace is an interface to the crop modelling framwork SIMPLACE (www.simplace.net). It provides high level functions to run simulations and transform the output into R objects.
3. rGeoJAGS- An R interface for use of the GeoJAGS module within JAGS Bayesian analysis software. This extends JAGS through the inclusion of families of Gaussian Markov Random Field models. Functions to format spatial data for analysis within BUGS are also included
4. Analysis of phenological digital imagery- The package phenopix provides functions to process digital images of a vegetation cover, depict greennes index trajectories and extract relevant phenological stages.
6. Low Flow Analysis- The project offers tools for analysing daily stream flow data focusing on low-flows as descriped in the "Manual on Low-flow Estimation and Prediction", Operational
Hydrology Report No. 50, Koblenz 2009
10. Fish Migration Monitoring (stacomiR)- stacomiR stands for migratory control stations. It enables to read informations in a database dedicated to the monitoring of fish migrations.It allows to build overviews of fish migrations and create charts with data.
Development Status : 5 - Production/Stable [Filter]
11. Flow and Load Duration Curves for TMDL- This project assists in creation of professionally looking Flow and Load Duration Curve plots.
Code moved to https://github.com/mlt/miscelrneous/tree/master/pkg/tmdl
13. EcoHydrology- A package containing a library of principle/fundamental equations used in the interdisciplinary field studying the complex interactions between hydrology and ecology (commonly referred to as Eco-Hydrology).
15. Early Warning Signals Toolbox- The Early-Warning-Signals Toolbox provides to the general practitioner available methods for estimating statistical changes in timeseries that can be used for the in-time identification of critical transitions.
19. general multiple-table data management- Our objective is to develop classes of objects that (1) make handling multiple-table data sets easier and (2) seamlessly integrate with existing R plotting and model-fitting functions; our philosophy is to keep data management and data analysis separate.