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Lindsay Beevers   Dr.  Institute, Department or Faculty Head 
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Lindsay Beevers published an article in February 2019.
Top co-authors See all
I. Popescu

35 shared publications

IHE Delft Institute for Water Education, Delft, The Netherlands

Gabriela M. Medero

28 shared publications

Heriot-Watt University, School of Energy, Geoscience, Infrastructure and Society, EH14 4AS Edinburgh, UK

Alan Cuthbertson

23 shared publications

Heriot Watt University

Quan Pan

6 shared publications

UNESCO-IHE, Institute for Water Education, P.O. Box 3015, 2601 DA Delft, Netherlands

Lila Collet

4 shared publications

National Research Institute of Science and Technology for Environment and Agriculture (IRSTEA), 1 Rue Pierre-Gilles de Gennes, 92160 Antony, Île-de-France, France

37
Publications
8
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127
Citations
Publication Record
Distribution of Articles published per year 
(2007 - 2019)
Total number of journals
published in
 
25
 
Publications See all
Article 0 Reads 0 Citations Are We Doing ‘Systems’ Research? An Assessment of Methods for Climate Change Adaptation to Hydrohazards in a Complex Wor... Melissa Bedinger, Lindsay Beevers, Lila Collet, Annie Visser Published: 22 February 2019
Sustainability, doi: 10.3390/su11041163
DOI See at publisher website ABS Show/hide abstract
Climate change is a product of the Anthropocene, and the human–nature system in which we live. Effective climate change adaptation requires that we acknowledge this complexity. Theoretical literature on sustainability transitions has highlighted this and called for deeper acknowledgment of systems complexity in our research practices. Are we heeding these calls for ‘systems’ research? We used hydrohazards (floods and droughts) as an example research area to explore this question. We first distilled existing challenges for complex human–nature systems into six central concepts: Uncertainty, multiple spatial scales, multiple time scales, multimethod approaches, human–nature dimensions, and interactions. We then performed a systematic assessment of 737 articles to examine patterns in what methods are used and how these cover the complexity concepts. In general, results showed that many papers do not reference any of the complexity concepts, and no existing approach addresses all six. We used the detailed results to guide advancement from theoretical calls for action to specific next steps. Future research priorities include the development of methods for consideration of multiple hazards; for the study of interactions, particularly in linking the short- to medium-term time scales; to reduce data-intensivity; and to better integrate bottom–up and top–down approaches in a way that connects local context with higher-level decision-making. Overall this paper serves to build a shared conceptualisation of human–nature system complexity, map current practice, and navigate a complexity-smart trajectory for future research.
PREPRINT 0 Reads 0 Citations The Impact of Climate Change on Hydroecological Response in Chalk Streams Annie Visser, Lindsay Beevers, Sandhya Patidar Published: 24 December 2018
doi: 10.20944/preprints201812.0266.v1
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Climate change represents a major threat to lotic freshwater ecosystems and their ability to support the provision of ecosystem services. England’s chalk streams are in a poor state of health, with significant concerns regarding their resilience, the ability to adapt, under a changing climate. This paper aims to quantify the effect of climate change on hydroecological response, the health of the river, for the River Nar, a SSSI in the south-east of England. To this end, we apply a coupled hydrological and hydroecological modelling framework, with the UKCP09 probabilistic climate projections serving as input (A1B high emissions scenario). Results show that, from 2021 to the end of the century, hydroecological response becomes more heterogeneous. Despite the limited range of the functional feeding groups on the baseline, the River Nar has been able to adapt to extreme events due to inter-annual variation. In the future, this variation is greatly reduced, raising real concerns over the resilience of the river ecosystem under climate change. These new insights into the health of the River Nar, and chalk streams more generally, highlights the necessity of further study and the real need to for changed river management practices.
Article 0 Reads 0 Citations Replication of ecologically relevant hydrological indicators following a covariance approach to hydrological model param... Annie Visser, Lindsay Beevers, Sandhya Patidar Published: 19 November 2018
Hydrology and Earth System Sciences Discussions, doi: 10.5194/hess-2018-536
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Hydrological models can be used to assess the impact of hydrologic alteration on the river ecosystem. However, there are considerable limitations and uncertainties associated with the replication of the required, ecologically relevant hydrological indicators. Vogel and Sankarasubramanian's covariance approach to model parameterisation represents a shift away from the traditional calibration-validation goodness-of-fit paradigm. Using the covariance structures of the observed input and simulated output time-series, the region of parameter space which best captures (replicates) the characteristics of a hydrological indicator may be identified. Through a case study, a modified covariance approach is applied with a view to replicating a suite of seven ecologically relevant hydrological indicators. Model performance and consistency are assessed relative to four comparative studies. The ability of the approach to address the limitations associated with traditional calibration-validation is further considered. Benefits of the approach include an overall reduction in model uncertainty whilst also reducing overall time-demands. Difficulties in the replication of complex indicators, such as rate of change, are in line with prior work. Nonetheless, the study illustrates that consistency in the replication of hydrological indicators is achievable; additionally, the replication of magnitude indices is markedly improved upon.
Article 0 Reads 1 Citation Future hot-spots for hydro-hazards in Great Britain: a probabilistic assessment Lila Collet, Shaun Harrigan, Christel Prudhomme, Giuseppe Fo... Published: 19 October 2018
Hydrology and Earth System Sciences, doi: 10.5194/hess-22-5387-2018
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In an increasing hydro-climatic risk context as a result of climate change, this work aims to identify future hydro-hazard hot-spots as a result of climate change across Great Britain. First, flood and drought hazards were defined and selected in a consistent and parallel approach with a threshold method. Then, a nation-wide systematic and robust statistical framework was developed to quantify changes in frequency, magnitude, and duration, and assess time of year for both droughts and floods, and the uncertainty associated with climate model projections. This approach was applied to a spatially coherent statistical database of daily river flows (Future Flows Hydrology) across Great Britain to assess changes between the baseline (1961–1990) and the 2080s (2069–2098). The results showed that hydro-hazard hot-spots are likely to develop along the western coast of England and Wales and across north-eastern Scotland, mainly during the winter (floods) and autumn (droughts) seasons, with a higher increase in drought hazard in terms of magnitude and duration. These results suggest a need for adapting water management policies in light of climate change impact, not only on the magnitude, but also on the timing of hydro-hazard events, and future policy should account for both extremes together, alongside their potential future evolution.
Article 0 Reads 0 Citations A Framework for Assessing Instream Supporting Ecosystem Services Based on Hydroecological Modelling Sikhululekile Ncube, Annie Visser, Lindsay Beevers Published: 14 September 2018
Water, doi: 10.3390/w10091247
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River systems provide diverse ecosystem services (ES), such as flood regulation (regulating), fresh water (provisioning), nutrient cycling (supporting), and recreation (cultural), among others. The construction of infrastructure (e.g., for hydropower, irrigation) enhances the delivery of tangible ES for example food or energy (generally provisioning) to meet human needs. However, the resulting change to river flows threatens both the ecological health of a river and its ability to provide intangible but vital ES, for example those which support the delivery of other services. Understanding these supporting ES processes in river systems is essential to fully recognise the impact of water resources development on ES delivery. Whilst approaches for assessing instream supporting ES are under development, to date few provide quantitative methods for assessing delivery. Thus, this paper sets out a framework for the assessment of instream supporting ES using hydroecological modelling. It links supporting ES delivery to fluvial hydrological indicators through the use of ecologically relevant hydrological indices and macroinvertebrate flow preferences. The proposed framework is demonstrated on the Beas River basin (Western Himalayas, India), and is flexible enough to be transferred to a basin-wide model, thereby allowing ES relationships to be accounted for in basin-wide water resources planning.
Article 0 Reads 1 Citation Complexity in hydroecological modelling: A comparison of stepwise selection and information theory Annie Gallagher Visser, Lindsay Beevers, Sandhya Patidar Published: 25 July 2018
River Research and Applications, doi: 10.1002/rra.3328
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Understanding of the hydroecological relationship is vital to maintaining the health of the river and thus its ecosystem. Stepwise selection is widely used to develop numerical models which represent these processes. Increasingly, however, there are questions over the suitability of the approach, and coupled with the increasing complexity of hydroecological modelling, there is a real need to consider alternative approaches. In this study, stepwise selection and information theory are employed to develop models which represent two realizations of the system which recognizes increasing complexity. The two approaches are assessed in terms of model structure, modelling error, and model (statistical) uncertainty. The results appear initially inconclusive, with the information theory approach leading to a reduction in modelling error but greater uncertainty. A Monte Carlo approach, used to explore this uncertainty, revealed modelling errors to be only slightly more distributed for the information theory approach. Consideration of the philosophical underpinnings of the two approaches provides greater clarity. Statistical uncertainty, as measured by information theory, will always be greater due to its consideration of two sources, parameter and model selection. Consequently, by encompassing greater information, the measure of statistical uncertainty is more realistic, making an information theory approach more reflective of the complexity in real‐world applications.
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