Combining diverse data sources for CEDSS, an agent-based model of domestic energy demand

CEDSS (Community Energy Demand Social Simulator) is an empirical agent-based model designed and built as part of a multi-method social science project investigating the determinants of domestic energy demand. Ideally, empirical modellers, within and beyond social simulation, would prefer to work from an integrated dataset, gatheredfor the purposes of developing the model. In practice, many have to work with less than ideal data, often including processed data from multiple sources external to the project. Moreover, what data will be required may not be clear at the start of the project. This paper describes the approach to dealing with these factors taken in developing CEDSS, and presents the completed model together with an outline of the calibration and validation procedure used. The discussion section draws together the most distinctive features of empirical data collection, processing and use for and in CEDSS, and argues that the approach taken is sufficiently robust to underpin the model’s purpose – to generate scenarios of domestic energy demand to 2049

A Manifesto for the Equifinality Thesis.

This essay discusses some of the issues involved in the identification and predictions of hydrological models given some calibration data. The reasons for the incompleteness of traditional calibration methods are discussed. The argument is made that the potential for multiple acceptable models as representations of hydrological and other environmental systems (the equifinality thesis) should be given more serious consideration than hitherto. It proposes some techniques for an extended GLUE methodology to make it more rigorous and outlines some of the research issues still to be resolved

Conceptual modelling to assess how the interplay of hydrological connectivity, catchment storage and tracer dynamics controls nonstationary water age estimates

Acknowledgements We would like to gratefully acknowledge the data provided by SEPA, Iain Malcolm. Mark Speed, Susan Waldron and many MSS staff helped with sample collection and lab analysis. We thank the European Research Council (project GA 335910 VEWA) for funding and are grateful for the constructive comments provided by three anonymous reviewers.Peer reviewedPostprin

Application of HYDRUS (2D/3D) for Predicting the Influence of Subsurface Drainage on Soil Water Dynamics in a Rainfed-Canola Cropping System

The HYDRUS (2D/3D) model was applied to investigate the probable effects of different subsurface drainage systems on the soil water dynamics under a rainfed-canola cropping system in paddy fields. Field experiments were conducted during two rainfed-canola growing seasons on the subsurface-drained paddy fields of the Sari Agricultural Sciences and Natural Resources University, Mazandaran Province, northern Iran. A drainage pilot consisting of subsurface drainage systems with different drain depths and spacings was designed. Canola was cultivated as the second crop after the rice harvest. Measurements of the groundwater table depth and drain discharge were taken during the growing seasons. The performance of the HYDRUS-2D model during the calibration and validation phases was evaluated using the model efficiency (EF), root mean square error (RMSE), normalized root mean square error (NRMSE) and mean bias error (MBE) measures. Based on the criteria indices (MBE = 0.01–0.17 cm, RMSE = 0.05–1.02 and EF = 0.84–0.96 for drainage fluxes, and MBE = 0.01–0.63, RMSE = 0.34–5.54 and EF = 0.89–0.99 for groundwater table depths), the model was capable of predicting drainage fluxes as well as groundwater table depths. The simulation results demonstrated that HYDRUS (2D/3D) is a powerful tool for proposing optimal scenario to achieve sustainable shallow aquifers in subsurface-drained paddy fields during winter cropping. Copyright © 2017 John Wiley & Sons, Ltd

Uncertainty propagation and speculation in projective forecasts of environmental change: a lake-eutrophication example

The issue of whether models developed for current conditions can yield correct predictions when used under changed control, as is often the case in environmental management, is discussed. Two models of different complexity are compared on the basis of performance criteria, but it appears that good performance at the calibration stage does not guarantee correctly predicted behavior. A requirement for the detection of such a failure of the model is that the prediction uncertainty range is known. Two techniques to calculate uncertainty propagation are presented and compared: a stochastic first-order error propagation based on the extended Kalman filter (EKF), and a newly developed and robust Monte Carlo set-membership procedure (MCSM). The procedures are applied to a case study of water quality, generating a projective forecast of the algal dynamics in a lake (Lake Veluwe) in response to management actions that force the system into a different mode of behavior. It is found that the forecast from the more complex model falls within the prediction uncertainty range, but its informative value is low due to large uncertainty bounds. As a substitute for time-consuming revisions of the model, educated speculation about parameter shifts is offered as an alternative approach to account for expected but unmodelled changes in the system

Modelling nitrous oxide emissions from mown-grass and grain-cropping systems : Testing and sensitivity analysis of DailyDayCent using high frequency measurements

The lead author, Nimai Senapati (Post doc), was funded by the European community’s Seventh Framework programme (FP2012-2015) under grant agreement no. 262060 (ExpeER). The research leading to these results has received funding principally from the ANR (ANR-11-INBS-0001), AllEnvi, CNRS-INSU. We would like to thank the National Research Infrastructure ‘Agro-écosystèmes, Cycles Biogéochimique et Biodiversité (SOERE-ACBB http://www.soere-acbb.com/fr/) for their support in field experiment. We are deeply indebted to Christophe deBerranger, Xavier Charrier for their substantial technical assistance and Patricia Laville for her valuables suggestion regarding N2O flux estimation.Peer reviewedPostprin

Spatial aggregation of time-variant stream water ages in urbanizing catchments

Date of Acceptance: 25/03/2015 Acknowledgements The help of Clara F. Soulsby with the sampling is gratefully acknowledged.Peer reviewedPostprin