Journal Articles

Ockelford, A, Wohl, E, Ruiz‐Villanueva, V, Comiti, F, Piégay, H, Darby, S, Parsons, D, Yochum, SE, Wolstenholme, J, White, D, Uno, H, Triantafillou, S, Stroth, T, Smrdel, T, Scott, DN, Scamardo, JE, Rees, J, Rathburn, S, Morrison, RR, Milan, D, Marshall, A, Lininger, KB, Kemper, JT, Karpack, M, Johaneman, T, Iskin, E, Hoyo, JGD, Hortobágyi, B, Hinshaw, S, Heath, J, Emmanuel, T, Dunn, S, Christensen, N, Beeby, J, Ash, J, Ader, E, Aarnink, J (2024) Working with wood in rivers in the Western United States, River Research and Applications, 40(8), pp.1626-1641, ISSN: 1535-1459. DOI: 10.1002/rra.4331.

Jones, L, Parsons, K, Halstead, F, Wolstenholme, J (2023) Reimaging activism to save the planet: using transdisciplinary and participatory methodologies to support collective youth action, Children & Society, 38(3), pp.823-838, ISSN: 0951-0605. DOI: 10.1111/chso.12819.

Wolstenholme, JM, Smith, MW, Baird, AJ, Sim, TG (2020) A new approach for measuring surface hydrological connectivity, Hydrological Processes, 34(3), pp.538-552, ISSN: 0885-6087. DOI: 10.1002/hyp.13602.

Datasets

Ockelford, A, Wohl, E, Ruiz‐Villanueva, V, Comiti, F, Piégay, H, Stephen, D, Parsons, D, Yochum, SE, Wolstenholme, J, White, D, Uno, H, Triantafillou, S, Stroth, T, Smrdel, T, Scott, DN, Scamardo, JE, Rees, J, Rathburn, S, Morrison, RR, Milan, D, Marshall, A, Lininger, KB, Kemper, JT, Karpack, M, Johaneman, T, Iskin, E, Hoyo, JGD, Hortobágyi, B, Hinshaw, S, Heath, J, Emmanuel, T, Dunn, S, Christensen, N, Beeby, J, Ash, J, Ader, E, Aarnink, J (2024) Supplementary information for Working with wood in rivers in the Western United States, DOI: 10.17028/rd.lboro.27719772.

Other

Wolstenholme, JM, Skinner, CJ, Milan, DJ, Thomas, RE, Parsons, DR (2024) Supplementary material to "Localised geomorphic response to channel-spanning leaky wooden dams". DOI: 10.5194/egusphere-2024-3001-supplement.

Tomsett, C, Leyland, J, Darby, S, Gernon, T, Parsons, D, Hincks, T, Wolstenholme, J (2024) Vertical Mixing of Suspended Sediment in Big Rivers using ADCP data and Machine Learning, Sediment is an intrinsic component of the fluvial network, supplying material for floodplains and coastal landforms which provide resilience during flooding and storms. As a result, an understanding of the fluvial processes that control how much sediment moves through our river systems, and how this varies across the globe, is of fundamental importance.For the purpose of estimating sediment delivery through the fluvial network, it is often assumed that rivers are well mixed through their vertical extent. However, empirical data reveals that there is frequently large variability in the concentration of sediment through the water column. Better understanding this variability is of interest to the geomorphological community to help explain variations in sediment transport and improve estimates of sediment flux.In this research, we utilise a collection of Acoustic Doppler Current Profiler (ADCP) data from large rivers across the globe to investigate variations in the vertical distribution of suspended sediment. Calibrations of ADCP backscatter to Suspended Sediment Concentration (SSC) from the wider literature are used, alongside median grainsize and acoustic frequency, to create a Machine Learning (ML) model from which SSC from uncalibrated ADCPs can be estimated. This new ML model is subsequently implemented to explore the variations in the vertical mixing of suspended sediment both temporally and spatially. This variability is explored to identify the importance of catchment characteristics in determining variations in suspended sediment concentration within the water column. Comparison of multiple river systems and their catchment characteristics, both between sites and through time, enables the identification of key attributes which exert a greater control on this variation through the water column. Subsequently, this leads to an improved understanding of sediment flux through the river system, whereby knowing the variation in sediment concentration within the water column can help to better calibrate current methods of estimating flux.. DOI: 10.5194/egusphere-egu24-9717.

Wolstenholme, J, Skinner, C, Milan, D, Thomas, R, Parsons, D (2024) Basin-scale hydrological response to leaky wooden dam installation, Leaky wooden dams are commonly incorporated into rivers as part of restoration efforts to increase channel roughness and force geomorphic complexity, slowing the flow in the headwaters and aiming to desynchronise flows to reduce downstream flood risk. These structures are (dis)connectivity agents, working to decrease longitudinal connectivity whilst simultaneously increasing floodplain connectivity and encouraging water storage.Most numerical modelling of leaky wooden dams at the basin scale does not consider sediment transport at spatial resolutions fine enough to appropriately represent the dams as individual features. Due to the paucity of both spatially- and temporally-distributed sediment transport data, there is also a high level of uncertainty regarding the influence of leaky wooden dams on basin hydrology over time, yet it is important that we consider the geomorphological influence of these structures and how their evolution influences flood hazard, particularly given that extreme storms are becoming increasingly common.This study implements a heuristic behavioural approach within the landscape evolution model CAESAR-Lisflood to assess the broad influence of leaky wooden dams on a 32 km2 prototype catchment with a mixture of first, second and third order streams. A 20-year spatially-distributed modelled rainfall time series capable of representing convective storms (2020–2040 obtained from the 2018 UK Climate Projections) was used to drive the hydrology across a suite of simulations where leaky wooden dam location in the river network was systematically varied.Installing leaky wooden dams only on first order streams desynchronised flow and reduced downstream flood peaks by up to 50% whilst retaining the greatest volume of water in the catchment when compared to other stream order combinations. Conversely, installing leaky wooden dams on only third order streams increased peak discharge by over 10% for 22% of storm events owing to the presence of fewer structures and therefore reduced opportunity for desynchronisation of peak flows from the various sub-catchments. Most importantly we detail how storm sequencing, and the capacity of the active channel, plays an important role in exacerbating flood risk, with frequent, yet relatively minor, storms increasing peak discharge despite the presence of leaky wooden dams. As such where leaky dam interventions are installed plays a critical role in their efficacy in mitigating flood peaks and should be given more consideration by practitioners.. DOI: 10.5194/egusphere-egu24-8881.

Wolstenholme, J (2022) Catchment-scale geomorphological modelling of leaky dams using CAESAR-Lisflood, <p><strong>Title: Catchment-scale geomorphological modelling of leaky dams using CAESAR-Lisflood</strong></p><p> </p><p>Joshua Wolstenholme              j.wolstenholme-2018@hull.ac.uk          1</p><p>David Milan      d.milan@hull.ac.uk      1</p><p>Christopher Skinner    chris.skinner@environment-agency.gov.uk 2</p><p>Daniel Parsons              d.parsons@hull.ac.uk               1</p><p> </p><p>Affiliations:</p><ul><li>University of Hull, Energy and Environment Institute, United Kingdom of Great Britain – England, Scotland, Wales (j.wolstenholme-2018@hull.ac.uk)</li> <li>Environment Agency, Flood Hydrology Improvements, United Kingdom of Great Britain – England, Scotland, Wales</li> </ul><p> </p><p>The introduction of large wood to fluvial systems is becoming increasingly popular as a method of natural flood management commonly referred to as leaky dams. These are often installed as semi-permanent features through live felling and anchoring in-situ. Currently, most natural flood management modelling is hydrological and focuses on flood risk without accounting for geomorphology of these ‘fixed’ features. We argue that the long-term effectiveness of NFM interventions require and understanding of the nested hydrogeomorphological processes at work within river catchments, particularly those related to bed scour, sediment transport and deposition, and the associated feedbacks following implementation of leaky dams. Leaky dams that are designed to attenuate the hydrograph and ‘slow-the-flow’, may cause sediment storage as well as scour, potentially impeding the effectiveness of a leaky dam to reduce flood risk after a single storm event. Using the new ‘Working with Natural Processes’ toolbox developed for CAESAR-Lisflood, the influence of different storm scenarios on a series of leaky dams in a hypothetical catchment based on a site in North Yorkshire is assessed. The effectiveness of the model at representing the influence of the dams on hydrogeomorphology is also assessed.</p>. DOI: 10.5194/egusphere-egu22-5730.

Parsons, K and Wolstenholme, J (2021) Mapping hedgerow gaps and fostering positive environmental behaviours through a combination of citizen scientists and artificial intelligence, <p>To meet CO<sub>2</sub> reduction targets, the UK aims to plant c1.5 billion trees by 2050. Gaps within thousands of miles of hedgerows across the country are potentially suitable planting sites, but the extent of gaps and suitability for replanting are currently unknown. Maximising the potential growth of hedgerows however appears to receive relatively little attention compared with wide area tree planting. Hedgerow gaps present the opportunity for tree planting, contributing towards the annual tree-planting goals and net-zero CO2 plan as part of Defra’s 25-year objectives (HM Government, 2018), without requiring extensive land change.</p><p>Our ambitions of fostering a greener society and meeting net zero goals is heavily reliant on ensuring that children and youth are engaged with environmental concerns and have the right skills and knowledge for future careers. This project has been engaging with youth organisations to enhance their environmental and digital knowledge, whilst combining their input with state-of-the-art artificial-intelligence approaches. The open dataset created with public contributions will inform planting decisions whilst educating young people and citizens. The aligned education programme will provide resources detailing how new planting will drawdown CO<sub>2</sub>, reduce flood risk and increase biodiversity availability, ultimately fostering the participants as agents of change in addressing the climate crisis. </p><p>Citizens will be trained in hedgerow surveying techniques, with focus on both remote sensing/geographic information systems applications (GIS) and field surveying - enabling contributions from home (during COVID) as well as encouraging outdoor activity and learning. Through a series of surveys and tasks, citizens are able to utilise a smartphone device (or similar) to contribute new data into an open survey on hedgerow characteristics, simple field experimental measurements and images/videos, all whilst utilising the GPS built into the device. The objectives of the project are two-fold: first, data collected by citizens will be used to refine an existing deep learning model trained to identify hedgerow gaps from high-resolution earth observation imagery. Second, to encourage citizens to learn about and take ownership of their local environment, contributing to the fostering of a nation of climate champions.</p>. DOI: 10.5194/egusphere-egu21-9453.

Wolstenholme, J and Skinner, C (2021) The 360 Lab, <p>Flooding is a major risk to lives and properties globally and this risk is increasing because of several factors, not least the increase of sea level and changes to patterns of precipitation due to climate change. Whilst flood management interventions can reduce the risk and the impact of flooding, it is not possible, and never will be possible, to stop flooding completely and this necessitates a public that is informed and equipped to take actions to increase their personal resilience.</p><p>Successful learning in Geosciences requires 3D thinking yet many of the tools used by educators are 2D visualisations, relying on the student’s individual ability and imagination. There has been an increasing use of interactive 3D visualisations, particularly of geological outcrops, yet the methods used to produce these either rely on expensive equipment or processing using high-specification machines. The 360 Lab uses new functionality offered by state-of-the-art tablets to rapidly capture high-resolution 3D scenes of flood management interventions, for example, woody dams.</p><p>The 3D scenes were used to create interactive models of the flood management features, allowing people to get, virtually, ‘hands-on’ and explore them. The 3D models are fully compatible with virtual reality headsets. Guided tours of schemes have been developed to be used by schools, showing how features are installed and providing a focus to discuss how they work and how effective they might be.  This overcomes challenges to accessing such locations, including location, budget, accessibility, and Covid-19 related restrictions. Future developments include using the rapid scans to create 3D printed models of features for face-to-face learning and scaled experiments.</p>. DOI: 10.5194/egusphere-egu21-10189.

Wolstenholme, J, Skinner, C, Milan, D, Parsons, D (2021) Geomorphological numerical modelling of woody dams in CAESAR-Lisflood, <p>Natural flood management (NFM) promotes the sustainable enhancement of natural fluvial processes to reduce flooding (SEPA, 2015; Wilkinson et al, 2019), and is increasingly popular for use by community groups, contractors and governments (Kay et al, 2019). Reintroduction of wood to a river channel is a popular form of NFM often achieved through seeding natural logjams, or with an emphasis on engineering through installing woody dams (WDs). WDs are currently installed or being installed in catchments in an effort to reduce flood risk, through hydrograph attenuation, increase biodiversity and improve geomorphic heterogeneity (Wenzel et al, 2014; Burgess-Gamble et al, 2017; Grabowski et al, 2019). A further objective is to emulate the effect of natural wood found in river channels by partially, or completely, blocking the channel to accelerate the recruitment of natural wood as part of the natural wood cycle (Addy & Wilkinson, 2016).</p><p>There is a growing body of evidence supporting the benefits of NFM, however, the hydrogeomorphic effects of WDs are less well understood (Dadson et al, 2017). There is little scientific underpinning concerning the long-term impact of these features upon hydrogeomorphology at reach and catchment-scales. Very few numerically based studies consider the influence of sediment transport on WDs, and how changes in local bed morphology influence their effectiveness. Most NFM research to date has focused upon modelling the effectiveness of local NFM measures in small catchments (<10 km<sup>2</sup>) (Dadson et al, 2017), with less work evident at larger spatial and temporal scales (Kay et al, 2019; Wilkinson et al, 2019).</p><p>There is a need for a verified tool that is able to represent WDs accounting for geomorphic processes and interactions between the dams and morphodynamics, different design specifications of dams, and changing efficacy due to geomorphic evolution. We present the new CAESAR-Lisflood (Coulthard et al, 2013) “Working with Natural Processes” toolkit, capable of representing WDs across a digital experimental environment. Global sensitivity testing was conducted using the Morris method (Morris, 1991) to assess the sensitivity of five aspects of the toolkit, and their potentially influences on geomorphology and flood risk reduction.</p>. DOI: 10.5194/egusphere-egu21-9636.