An open and extensible framework for spatially explicit land use change modelling in R: the lulccR package (0.1.0)

Land use change has important consequences for biodiversity and the sustainability of ecosystem services, as well as for global environmental change. Spatially explicit land use change models improve our understanding of the processes driving change and make predictions about the quantity and location of future and past change. Here we present the lulccR package, an object-oriented framework for land use change modelling written in the R programming language. The contribution of the work is to resolve the following limitations associated with the current land use change modelling paradigm: (1) the source code for model implementations is frequently unavailable, severely compromising the reproducibility of scientific results and making it impossible for members of the community to improve or adapt models for their own purposes; (2) ensemble experiments to capture model structural uncertainty are difficult because of fundamental differences between implementations of different models; (3) different aspects of the modelling procedure must be performed in different environments because existing applications usually only perform the spatial allocation of change. The package includes a stochastic ordered allocation procedure as well as an implementation of the widely used CLUE-S algorithm. We demonstrate its functionality by simulating land use change at the Plum Island Ecosystems site, using a dataset included with the package. It is envisaged that lulccR will enable future model development and comparison within an open environment

Hydrological Models as Web Services: An Implementation using OGC Standards

<p>Presentation for the HIC 2012 - 10th International Conference on Hydroinformatics. "Understanding Changing Climate and Environment and Finding Solutions" Hamburg, Germany July 14-18, 2012</p> <p> </p

Data Mining of Hydrological Model Performance

Multi-objective criteria have long been used to infer hydrological simulations and fit the natural world. On the other hand, modelling frameworks are also becoming more and more popular as identification of the processes occurring in a catchment is still a very uncertain matter. In theory, multi-objective criteria and multi-model frameworks should be used in combination so that the ’representation’ of the catchment is fitted to the observations, not only the simulated results. In practise those approaches are highly computationally demanding. The modeller is often obliged to find a compromise reducing either the number of objective functions or model structures taken into consideration. This compromise is becoming obsolete using parallel computing. In the present study we investigate the extend to which model selection algorithms and regionalisation techniques can be improved by such facilities and highlight the challenges that still need to be addressed. The model simulations are obtained using an ensemble of conceptual lumped models (FUSE by Clark et al. 2008), but techniques and suggestions are of general use and applicable to any modelling frameworks. In particular we developed a novel model selection algorithm tuned to drastically reduce the subjectivity in the analysis. The procedure was automated and coupled with redundancy reduction techniques such as PCA and Cluster Analysis. Results show that the actual model ’representation’ has the shape of a set of complementing model structures. It is also possible to capture intra-annum dynamics of the response as the algorithm recognises subtle variations in the selected model structures in different seasons. Similar variations can be found analysing different catchments. This suggests the same methodology would be suitable for analysing spatial patterns in the distribution of suitable model structures and maybe long term dynamics in relation with expedited climate modifications. Although the mentioned methodology has proven to be successful with regards to the case study, some limitations are worth noting. If this is going to be applied to the more general case of ’models of everywhere’, for instance, there could be dominant processes not described in the FUSE framework. Further studies could therefore extend the current framework to include routines able to simulate missing processes

Water for cities: The impact of climate change and demographic growth in the tropical Andes

[1] Globally, water resources for cities are under increasing stress. Two main stressors are climate change and population growth, but evaluating their relative impact is difficult, especially because of the complex topology of water supply. This is especially true in the tropical Andes, which is a region with strong climatic gradients and topographical limits to water resources. This paper presents an evaluation of both stressors on water resources in a geospatial framework to identify gradients in water availability that may lead to conflicts over water use. We focus on four major cities in, or receiving water from, the tropical Andes. A multimodel data set of 19 climate models is used as input for a regional water balance model. Per capita water availability is evaluated along topographic gradients for the present and for future scenarios of population growth and climate change. In all cases, the median projection of climate change suggests a relatively limited impact on water availability, but uncertainties are large. Despite these uncertainties, we find that the expected demographic changes are very likely to outpace the impact of climate change on water availability and should therefore be the priority for local policy making. However, distinctive geospatial patterns characterize the supply systems of the studied cities, highlighting the need to analyze the topology of water supply within an ecosystem services context. Our approach is flexible enough to be extended to other regions, stressors and water resources topologies. Citation: Buytaert, W., and B. De Bièvre (2012), Water for cities: The impact of climate change and demographic growth in th

An open and extensible framework for spatially explicit land use change modelling: the lulcc R package

We present the lulcc software package, an object-oriented framework for land use change modelling written in the R programming language. The contribution of the work is to resolve the following limitations associated with the current land use change modelling paradigm: (1) the source code for model implementations is frequently unavailable, severely compromising the reproducibility of scientific results and making it impossible for members of the community to improve or adapt models for their own purposes; (2) ensemble experiments to capture model structural uncertainty are difficult because of fundamental differences between implementations of alternative models; and (3) additional software is required because existing applications frequently perform only the spatial allocation of change. The package includes a stochastic ordered allocation procedure as well as an implementation of the CLUE-S algorithm. We demonstrate its functionality by simulating land use change at the Plum Island Ecosystems site, using a data set included with the package. It is envisaged that lulcc will enable future model development and comparison within an open environment

Participatory monitoring of the impact of watershed interventions in the tropical Andes

This chapter documents the motivations and methods of the Regional Initiative for Hydrological Monitoring of Andean Ecosystems (iMHEA). First, it introduces the context that led to the formation of a diverse consortium of institutions with a joint interest in Andean ecosystems and water. The methodological approach adopted by the monitoring network is then presented in detail. Lastly, this chapter shows preliminary main results, the most relevant milestones and breakthroughs, and the major remaining challenges and perspectives in the scientific, technological and social domains. The objective of the monitoring, as promoted by iMHEA, is to generate standardized data that can be used to increase the knowledge about hydrological ecosystem services in Andean watersheds and the impacts of watershed interventions. The correct use of the generated knowledge, from community level to national governance entities, proves crucial to increase catchment intervention efficiency and improve decision-making on water resources management in data-scarce regions, with potential application to other regions of the world

User-driven design of decision support systems for polycentric environmental resources management

Open and decentralized technologies such as the Internet provide increasing opportunities to create knowledge and deliver computer-based decision support for multiple types of users across scales. However, environmental decision support systems/tools (henceforth EDSS) are often strongly science-driven and assuming single types of decision makers, and hence poorly suited for more decentralized and polycentric decision making contexts. In such contexts, EDSS need to be tailored to meet diverse user requirements to ensure that it provides useful (relevant), usable (intuitive), and exchangeable (institutionally unobstructed) information for decision support for different types of actors. To address these issues, we present a participatory framework for designing EDSS that emphasizes a more complete understanding of the decision making structures and iterative design of the user interface. We illustrate the application of the framework through a case study within the context of water-stressed upstream/downstream communities in Lima, Peru