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

On the use of semi-distributed and fully-distributed urban stormwater models

Urban stormwater models comprise four main components: rainfall, rainfall-runoff, overland flow and sewer flow modules. They can be considered semi-distributed (SD) or fully distributed (FD) according to the rainfall-runoff module definition. SD models are based on sub-catchments units through which rainfall is applied to the model and at which runoff volumes are estimated. In FD models, the runoff volumes are estimated and applied directly on every element of a twodimensional (2D) model of the surface. This poster presents a comparison of SD and FD models based on two case studies: Zona Central catchment at Coimbra, Portugal, and Cranbrook catchment at London, UK. SD and FD modelling results are compared against water depth and flow records in sewers, and photographic records of a flood event. In general, FD models are theoretically more realistic and physically-based, but the results of this study suggest that the implementation of these models requires higher resolution (more detailed) elevation, land use and sewer network data than is normally used in the implementation of SD models. Failing to use higher resolution data for the implementation of FD models could result in poor-performing models. In cases when high resolution data are not available, the use of SD models could be a better choice

Integrating green and blue spaces into our cities: Making it happen

Urban blue-green infrastructure (BGI) is a network of nature-based features situated in built-up areas that form part of the urban landscape. These features are either based on vegetation (green), water (blue), or both. Green roofs and walls, grassed areas, rain gardens, swales (shallow channels, or drains), trees, parks, rivers and ponds are all examples of this type of architecture. Blue-green infrastructure is important as a climate change mitigation and adaptation measure, and has a host of wider benefits to people and wildlife. This briefing note summarises the benefits that blue-green infrastructure brings to people, recent trends in the use of blue or green features in urban settings, and the perceived barriers to greater uptake in the UK and how these might be overcome. This paper also explores how thinking about the way these features fit within a wider system of natural and human factors, so-called systems thinking, can help improve the evaluation of blue-green assets from a range of different perspectives

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

Integration of Lightwave Guides in UV-Microstructured Glass

[no abstract available

The use of semi-structured interviews for the characterisation of farmer irrigation practices

For the development of sustainable and realistic water security, generating information on the behaviours, characteristics, and drivers of users, as well as on the resource itself, is essential. In this paper we present a methodology for collecting qualitative and quantitative data on water use practices through semi-structured interviews. This approach facilitates the collection of detailed information on actors' decisions in a convenient and cost-effective manner. Semi-structured interviews are organised around a topic guide, which helps lead the conversation in a standardised way while allowing sufficient opportunity for relevant issues to emerge. In addition, they can be used to obtain certain types of quantitative data. While not as accurate as direct measurements, they can provide useful information on local practices and users' insights. We present an application of the methodology on farmer water use in two districts in the state of Uttar Pradesh in northern India. By means of 100 farmer interviews, information was collected on various aspects of irrigation practices, including irrigation water volumes, irrigation cost, water source, and their spatial variability. Statistical analyses of the information, along with data visualisation, are also presented, indicating a significant variation in irrigation practices both within and between districts. Our application shows that semi-structured interviews are an effective and efficient method of collecting both qualitative and quantitative information for the assessment of drivers, behaviours, and their outcomes in a data-scarce region. The collection of this type of data could significantly improve insights on water resources, leading to more realistic management options and increased water security in the future

Effects of winter and summer-time irrigation over Gangetic Plain on the mean and intra-seasonal variability of Indian summer monsoon

The decreasing trend in rainfall in the last few decades over the Indo-Gangetic Plains of northern India as observed in ground-based observations puts increasing stress on groundwater because irrigation uses up to 70% of freshwater resources. In this work, we have analyzed the effects of extensive irrigation over the Gangetic Plains on the seasonal mean and intra-seasonal variability of the Indian summer monsoon, using a general circulation model and a very high-resolution soil moisture dataset created using extensive field observations in a state-of-the-art hydrological model. We find that the winter-time (November–March) irrigation has a positive feedback on the Indian summer monsoon through large scale circulation changes. These changes are analogous to a positive North Atlantic Oscillation (NAO) phase during winter months. The effects of the positive NAO phase persist from winter to spring through widespread changes in surface conditions over western and central Asia, which makes the pre-monsoon conditions suitable for a subsequent good monsoon over India. Winter-time irrigation also resulted in a reduction of low frequency intra-seasonal variability over the Indian region during the monsoon season. However, when irrigation is practiced throughout the year, a decrease in June–September precipitation over the Gangetic Plains, significant at 95% level, is noted as compared to the no-irrigation scenario. This decrease is attributed to the increase in local soil moisture due to irrigation, which results in a southward shift of the moisture convergence zone during the active phase of monsoon, decreasing its mean and intraseasonal variability. Interestingly, these changes show a remarkable similarity to the long-term trend in observed rainfall spatial pattern and low-frequency variability. Our results suggest that with a decline in the mean summer precipitation and stressed groundwater resources in the Gangetic Plains, the water crisis could exacerbate, with irrigation having a weakening effect on the regional monsoon

A method for adjusting design storm peakedness to reduce bias in hydraulic simulations

In the UK, decision makers use hydraulic model outputs to inform funding, connection consent, adoption of new drainage networks and planning application decisions. Current practice requires the application of design storms to calculate sewer catchment performance metrics such as flood volume, discharge rate and flood count. With flooding incidents occurring more frequently than their designs specify, hydraulic modelling outputs required by practice are questionable. The main focus of this paper is the peakedness factor (ratio of maximum to average rainfall intensity) of design storms, adjudging that this is a key contributor to model bias. Hydraulic models of two UK sewer catchments were simulated under historical storms, design storms and design storms with modified peakedness to test bias in modelling outputs and the effectiveness of peakedness modification in reducing bias. Sustainable drainage systems (Suds) were implemented at catchment scale and the betterment achieved in the modelling outputs was tested. The proposed design storm modification reduced the bias that occurs when driving hydraulic models using design storms in comparison with historical storms. It is concluded that Suds benefits are underestimated when using design rainfall because the synthetic rainfall shape prevents infiltration. Thus, Suds interventions cannot accurately be evaluated by design storms, modified or otherwise

Urban stormwater modelling with MOHID

MOHID is a platform that includes a set of numerical models to simulate the water cycle in an integrated approach. It is an open source project that has been developed and applied to a wide range of studies since 1985. To increase its applicability for urban storm water modelling, the main module of the platform MOHID Land is now integrated with SWMM model via OpenMI. This poster evaluates the performance of MOHID in urban storm water modelling, by comparing results of the test cases presented by S. Néelz and G. Pender (2013) and of a real case study with InfoWorks ICM vs. 5.5. Moreover, it is discussed the advantage of covering the entire water cycle in MOHID platform, making it applicable for a wide range of cases