Eden Catchment Research Articles

Identifying and testing adaptive management options to increase river catchment system resilience using a Bayesian Network model

AbstractThe cumulative impacts of future climatic and socioeconomic change threaten the ability of freshwater catchments to provide essential ecosystem services. Stakeholders who manage freshwaters require decision-support tools that increase their understanding of catchment system resilience and support the appraisal of adaptive management options to inform decision-making. Our research aims to test the ability of a Bayesian Network model to identify adaptive management scenarios and test their effectiveness across future pathways to 2050. Using the predominantly arable river Eden catchment (320 km2) in eastern Scotland as a case study, we invited stakeholders from multiple sectors to participate in a series of workshops aimed at addressing water quality issues and achieving good ecological status in the catchment both now and in the future. Our participatory methods helped stakeholders overcome multiple layers of complexity and uncertainty associated with future-focused water management. Outputs of a Bayesian Network model simulated both current and future catchment resilience to inform the identification of six management scenarios. The effectiveness of each management scenario was tested using the Bayesian Network model. Two adaptive management scenarios increased catchment resilience and helped achieve good ecological status; a ‘Best Available Technology’ scenario, including aerobic granular sludge treatment, and a management scenario focused on ‘Resource Centre’, including phosphorus recovery from wastewater treatment works and constructed lagoons for crop irrigation. Stakeholders were interested in a 'Nature Based' management scenario including options such as wetland wastewater treatment methods and rural sustainable drainage systems, which improved water quality in the catchment, but had lower certainty in achieving desired outcome. Findings led to a recognition that innovative and collaborative action was required to improve current and future freshwater conditions.

A High‐Performance Coupled Human And Natural Systems (CHANS) Model for Flood Risk Assessment and Reduction

AbstractIn recent years, flood risk in urban areas has been rapidly increasing due to unsustainable urban development, changes of hydrological processes and frequent occurrence of extreme weather events. Flood risk assessment should realistically take into account the complex interactions between human and natural systems to better inform risk management and improve resilience. In this study, we propose a novel Coupled Human And Natural Systems (CHANS) modeling framework to capture the intricate interactive human behaviors and flooding process at a high spatial resolution. The new CHANS modeling framework integrates a high‐performance hydrodynamic model with an agent‐based model to simulate the complex responses of individual households to the evolving flood conditions, leveraging the computing power of graphics processing units (GPUs) to achieve real‐time simulation. The framework is applied to reproduce the 2015 Desmond flood in the 2,500 km2 Eden Catchment in England, demonstrating its ability to predict interactive flood‐human dynamics and assess flood impact at the household‐level. The study also further explores the effectiveness of different flood risk management strategies, including the provision of early warning and distribution of sandbags, in mitigating flood impact. The new CHANS model potentially provides a useful tool for understanding short‐term human behaviors and their impact on flood risk during a flood event, which is important for the development of effective disaster risk management plans.

Antimicrobial resistance in rural rivers: Comparative study of the Coquet (Northumberland) and Eden (Cumbria) River catchments

Many studies have characterised resistomes in river microbial communities. However, few have compared resistomes in parallel rural catchments that have few point-source inputs of antimicrobial genes (ARGs) and organisms (i.e., AMR) – catchments where one can contrast more nebulous drivers of AMR in rural rivers. Here, we used quantitative microbial profiling (QMP) to compare resistomes and microbiomes in two rural river catchments in Northern England, the Coquet and Eden in Northumberland and Cumbria, respectively, with different hydrological and geographical conditions. The Eden has higher flow rates, higher annual surface runoff, and longer periods of soil saturation, whereas the Coquet is drier and has lower flowrates. QMP analysis showed the Eden contained significantly more abundant microbes associated with soil sources, animal faeces, and wastewater than the Coquet, which had microbiomes like less polluted rivers (Wilcoxon test, p < 0.01). The Eden also had greater ARG abundances and resistome diversity (Kruskal Wallis, p < 0.05), and higher levels of potentially clinically relevant ARGs. The Eden catchment had greater and flashier runoff and more extensive agricultural land use in its middle reach, which explains higher levels of AMR in the river. Hydrological and geographic factors drive AMR in rural rivers, which must be considered in environmental monitoring programmes.

Developing a Bayesian network model for understanding river catchment resilience under future change scenarios

Abstract. The resilience of river catchments and the vital socio-ecological services they provide are threatened by the cumulative impacts of future climatic and socio-economic change. Stakeholders who manage freshwaters require tools for increasing their understanding of catchment system resilience when making strategic decisions. However, unravelling causes, effects and interactions in complex catchment systems is challenging, typically leading to different system components being considered in isolation. In this research, we tested a five-stage participatory method for developing a Bayesian network (BN) model to simulate the resilience of the Eden catchment in eastern Scotland to future pressures in a single transdisciplinary holistic framework. The five-stage participatory method involved co-developing a BN model structure by conceptually mapping the catchment system and identifying plausible climatic and socio-economic future scenarios to measure catchment system resilience. Causal relationships between drivers of future change and catchment system nodes were mapped to create the BN model structure. Appropriate baseline data to define and parameterise nodes that represent the catchment system were identified with stakeholders. The BN model measured the impact of diverse future change scenarios to a 2050 time horizon. We applied continuous nodes within the hybrid equation-based BN model to measure the uncertain impacts of both climatic and socio-economic change. The BN model enabled interactions between future change factors and implications for the state of five capitals (natural, social, manufactured, financial and intellectual) in the system to be considered, providing stakeholders with a holistic catchment-scale approach to measure the resilience of multiple capitals and their associated resources. We created a credible, salient and legitimate BN model tool for understanding the cumulative impacts of both climatic and socio-economic factors on catchment resilience based on stakeholder evaluation. BN model outputs facilitated stakeholder recognition of future risks to their primary sector of interest, alongside their interaction with other sectors and the wider system. Participatory modelling methods improved the structure of the BN through collaborative learning with stakeholders while providing stakeholders with a strategic systems-thinking approach for considering river basin catchment resilience

Novel variable reconstruction and friction term discretisation schemes for hydrodynamic modelling of overland flow and surface water flooding

Due to the recent advances in computing and data acquisition technologies, numerical models solving the 2D shallow water equations (SWEs) are now widely used in predicting overland flow and surface water flooding process in natural catchments. In catchment-scale flood modelling, in addition to the calculation of convective terms that are usually achieved through solving local Riemann problems to capture transient flow dynamics, correct discretisation of source terms is also essential to handle complex domain topography and ensure accurate and stable numerical solutions. The external forces induced by gravity and bed friction create the key source terms that drive the change of momentum in the SWEs and affect the stability and accuracy of the adopted numerical scheme, especially for applications involving very shallow water depth (e.g. wet and dry fronts, overland flows). Herein, new schemes are introduced to reconstruct the face values of flow variables and a fully implicit algorithm is improved to discretise the stiff friction terms, in the context of developing a Godunov-type finite volume hydrodynamic model for accurate and stable simulation of overland flow and surface water flooding involving very shallow water depth. Five analytical test cases are considered to validate the resulting models and the numerical results are compared with those produed by two alternative numerical schemes. The performance of the models are further demonstrated by reproducing a flood event in the 2500 km2 Eden Catchment, UK.

Spatial targeting of nature‐based solutions for flood risk management within river catchments

AbstractA wide range of nature‐based solutions for flood hazard management work by storing and slowing flow within catchments, and therefore, there is a need to identify the optimal locations for implementing these solutions. This paper presents a relative scoring‐based mapping of the likely locations that contribute to the flood peak. Targeting flow reduction and attenuating mitigation actions in these locations can be an effective way to reduce flood damages at impact points downstream. The presented tool, SCIMAP‐Flood, uses information on land cover, hydrological connectivity, flood generating rainfall patterns and hydrological travel time distributions to impacted communities to find the potential source areas of flood waters. The importance of each location in the catchment is weighted based on its contribution to the flood hazard at each of the downstream impact points. In the example application, SCIMAP‐Flood is applied at a 5‐m grid resolution for the River Eden catchment, Cumbria, England, to provide sub‐field scale information at the landscape extent. Therefore, the tool can identify sub‐catchments where more detailed work can test different mitigation measures.

Climate change allowances, non‐stationarity and flood frequency analyses

AbstractWhen considering future adaptation to climate change in UK fluvial flood alleviation schemes, the current recommendation by the Environment Agency (England) is to increase peak design flood flows by a preselected percentage. This allowance varies depending on the period for which the estimate is being made, the vulnerability of the development being considered and its location. Recently, questions have been raised as to whether these percentage uplifts should be kept the same, or whether change has already happened within the baseline period and so uplifts should be reduced. A complicating factor is that changes in flood frequency can occur for reasons in addition to climate change, such as land‐use change or natural variability. This article describes current approaches taken by different stakeholders for catchments in England and Wales to account for climate change, and discusses these allowances where there is already an observed presence of trend in flood regimes. Theil–Sen estimators of trend were used in comparing non‐stationary and stationary flood frequency curves with allowances applied, leading to a recommendation of evaluating non‐stationary models at 1990, the end of the reference period. Examples were explored such as the Eden catchment, which was heavily affected by Storm Desmond in December 2015.

How groundwater time series and aquifer property data explain heterogeneity in the Permo-Triassic sandstone aquifers of the Eden Valley, Cumbria, UK

A novel investigation of the impact of meteorological and geological heterogeneity within the Permo-Triassic Sandstone aquifers of the River Eden catchment, Cumbria (UK), is described. Quantifying the impact of heterogeneity on the water cycle is increasingly important to sustainably manage water resources and minimise flood risk. Traditional investigations on heterogeneity at the catchment scale require a considerable amount of data, and this has led to the analysis of available time series to interpret the impact of heterogeneity. The current research integrated groundwater-level and meteorological time series in conjunction with aquifer property data at 11 borehole locations to quantify the impact of heterogeneity and inform the hydrogeological conceptual understanding. The study visually categorised and used seasonal trend decomposition by LOESS (STL) on 11 groundwater and meteorological time series. Decomposition components of the different time series were compared using variance ratios. Though the Eden catchment exhibits highly heterogeneous rainfall distribution, comparative analysis at borehole locations showed that (1) meteorological drivers at borehole locations are broadly homogeneous and (2) the meteorological drivers are not sufficient to generate the variation observed in the groundwater-level time series. Three distinct hydrogeological regimes were identified and shown to coincide with heterogeneous features in the southern Brockram facies, which is the northern silicified region of the Penrith Sandstone and the St Bees Sandstone. The use of STL analysis in combination with detailed aquifer property data is a low-impact insightful investigative tool that helps guide the development of hydrogeological conceptual models.

Science-Narrative Explorations of “Drought Thresholds” in the Maritime Eden Catchment, Scotland: Implications for Local Drought Risk Management

Drought in the United Kingdom is a “hidden” pervasive risk, defined and perceived in different ways by diverse stakeholders and sectors. Scientists and water managers distinguish meteorological, agricultural, hydrological, and socio-economic drought. Historically triggers in drought risk management have been demarcated solely in specialist hydrological science terms using indices and critical thresholds. This paper explores “drought thresholds” as a bridging concept for interdisciplinary science-narrative enquiry. The Eden catchment, Scotland acts as an exemplar, in a maritime country perceived as wet. The research forms part of creative experimentation in science-narrative methods played out in seven United Kingdom case-study catchments on hydro-meteorological gradients in the Drought Risk and You (DRY) project, with the agricultural Eden the most northerly. DRY explored how science and stories might be brought together to support better decision-making in United Kingdom drought risk management. This involved comparing specialist catchment-scale modelling of drought risk with evidence gathered from local narratives of drought perceptions/experiences. We develop the concept of thresholds to include perceptual triggers of drought awareness and impact within and between various sectors in the catchment (agriculture, business, health and wellbeing, public/communities, and natural and built environments). This process involved developing a framework for science-narrative drought “threshold thinking” that utilizes consideration of severity and scale, spatial and temporal aspects, framing in terms of enhancing or reducing factors internal and external to the catchment and new graphical methods. The paper discusses how this extended sense of thresholds might contribute to research and practice, involving different ways of linking drought severity and perception. This has potential to improve assessment of sectoral vulnerabilities, development of adaptive strategies of different stakeholders, and more tailored drought communication and messaging. Our findings indicate that drought risk presents many complexities within the catchment, given its cross-sectoral nature, rich sources of available water, variable prior drought experience among stakeholders, and different quantitative and perceptual impact thresholds across and within sectors. Fuzziness in identification of drought thresholds was multi-faceted for varied reasons. Results suggest that a management paradigm that integrates both traditional and non-traditional “fuzzy” threshold concepts across sectors should be integrated into current and future policy frameworks for drought risk management.

Assessment of the potential impacts of climate change on the hydrology at catchment scale: modelling approach including prediction of future drought events using drought indices

In this study, the Distributed Catchment-Scale Model, DiCaSM, was used to study the impact of climate change on the hydrology of the Eden catchment, north east of Scotland. As a first step, the model was successfully calibrated and validated for a 42 years period. The DiCaSM model was then used to study the impact of climate change on the water availability. Data from the UKCP09 Climate change scenarios for the 2010–2039, 2040–2069 and 2070–2099 periods, considering three gas emission scenarios (low, medium and high), were applied. The results indicated that the greatest decrease in streamflow and groundwater recharge was projected to happen under the high emission scenarios towards the end of the century, i.e. between 2070 and 2099. This would mainly be due to the summers becoming drier. Meanwhile, the projected increase in winter precipitation did not contribute much towards groundwater recharge due the projected increases in evapotranspiration and soil moisture deficit.The following drought indices were calculated and were found to be effective in predicting different types of droughts: the Standardized Precipitation Index, SPI, and the Standardized Precipitation Evaporation Index, SPEI, the Reconnaissance Drought Index, RDI, the modified adjusted RDI, the Soil Moisture Deficit, SMD and the Wetness Index, WI. The findings of the study have broader implications in water resources management considering the future changes in climate.

A full-scale fluvial flood modelling framework based on a high-performance integrated hydrodynamic modelling system (HiPIMS)

Full-scale fluvial flood modelling over large catchments has traditionally been carried out using coupled hydrological and hydraulic/hydrodynamic models. Such a traditional modelling approach is not well suited for the simulation of extreme floods induced by intense rainfall, which is usually featured with highly transient and dynamic rainfall-runoff and flooding process. This work aims to develop and demonstrate a modelling framework to predict the full-scale process of fluvial flooding from the source (rainfall) to impact (inundation) over a large catchment using a single high-performance hydrodynamic model driven by rainfall inputs. The modelling framework is applied to reproduce the flood event caused by the 2015 Storm Desmond in the 2500 km2 Eden Catchment at 5 m resolution. Without intensive model calibration, the predicted results compare well with field observations in terms of inundation extent and gauged water levels across the catchment. Sensitivity tests reveal that high-resolution grid is essential for accurate simulation of fluvial flood events using a 2D hydrodynamic model. Accelerated by multiple modern GPUs, the simulation is more than 2.5 times faster than real time although it involves 100 million computational cells inside the computational domain. This work provides a novel and promising approach to assess and forecast at real time the risk of extreme fluvial floods from intense rainfall.

A multi-scale nested experiment for understanding flood wave generation across four orders of magnitude of catchment area

Abstract Current understanding of flood response is deficient concerning the variation of flood generation at different spatial scales as a function of spatial and temporal variations in storm rainfall. This study therefore investigates the relationship between rainfall spatial variability and flood response through a multi-scale nested experiment. Hydrological data from an extensive network in the Eden catchment, UK, were collected for a range of flood events over varying scales from 1.1 km2 to 2,286 km2. The data were analysed to show the spatial scale dependency of flood peak and lag time. Peak specific discharge for winter events appears to remain constant with area up to 20–30 km2, corresponding to the main upland headwater catchments, thereafter declining as area increases. The flood response to the convective storms depends on the location of the rainfall and the downstream rates of change of runoff and peak discharge can vary significantly from the winter storm relationships. Particularly for large synoptic storms, average scaling laws for peak discharge have been quantified (exponents ranging between 0.75 and 0.86), illustrating the non-linear nature of the cross-scale variations. Such laws provide a means of linking the headwater catchments with the larger scale at which planners and decision-makers operate.

An exploration of individual, social and material factors influencing water pollution mitigation behaviours within the farming community

Diffuse pollution of watercourses from agriculture represents a complex and persistent environmental problem in the UK. This paper provides insights into why UK policy interventions have had limited success to date, drawing on the disciplines of psychology, sociology and behavioural economics to more thoroughly understand farmer attitudes and behaviours towards pollution mitigation. Our analysis is based on eliciting the opinions of commercial farmers through a series of surveys and discussion groups in three catchments: the grassland dominated River Eden catchment; the arable dominated River Wensum catchment and the mixed farming area of the Hampshire River Avon catchment. Results strongly suggest that a fundamental shift in identities, normative behavioural beliefs and social norms is required within the farming community before mitigation behaviours become embedded. Simply offering financial incentives or imposing regulatory penalties is unlikely to achieve the desired results. Double loop learning has the potential to enable farmers to migrate from a productivist to a multifunctional outlook where pollution mitigation becomes internalised within a farm management system. Expert farm advisors will be required to facilitate this process.

Improving bank erosion modelling at catchment scale by incorporating temporal and spatial variability

AbstractBank erosion can contribute a significant portion of the sediment budget within temperate catchments, yet few catchment scale models include an explicit representation of bank erosion processes. Furthermore, representation is often simplistic resulting in an inability to capture realistic spatial and temporal variability in simulated bank erosion. In this study, the sediment component of the catchment scale model SHETRAN is developed to incorporate key factors influencing the spatio‐temporal rate of bank erosion, due to the effects of channel sinuosity and channel bank vegetation. The model is applied to the Eden catchment, north‐west England, and validated using data derived from a GIS methodology. The developed model simulates magnitudes of total catchment annual bank erosion (617–4063 t y‐1) within the range of observed values (211–4426 t yr‐1). In addition, the model provides both greater inter‐annual and spatial variability of bank eroded sediment generation when compared with the basic model, and indicates a potential 61% increase of bank eroded sediment as a result of temporal flood clustering. The approach developed within this study can be used within a number of distributed hydrologic models and has general applicability to temperate catchments, yet further development of model representation of bank erosion processes is required. © 2017 The Authors. Earth Surface Processes and Landforms published by John Wiley &amp; Sons Ltd.

Evaluating the Impacts of Nitrate Vulnerable Zones on the Environment and Farmers’ Practices: A Scottish Case Study

ABSTRACTNitrate vulnerable zones (NVZs) have been established throughout Europe to tackle diffuse pollution. This research investigates the attitudes and practices of farmers in the River Eden catchment, within the Strathmore and Fife NVZ in eastern Scotland, and explores how these changed between 2002 and 2011. Attitudes were investigated using interviews; efficiency of nutrient use was evaluated using farm gate nutrient budgets (NBs). Most of the 16 farmers regard NVZ regulations as burdensome and costly; however, attitudes to NVZs became more positive during the period. NBs demonstrated that arable farms generate the least nitrogen (N) and phosphorus (P) surpluses, dairy the most. N efficiency improved on nine farms and declined on two; P efficiency improved on 12 farms and declined on two. Overall, the 16 farms were using 13% less N and 19% less P in 2011 compared with 2003. Water quality data demonstrate that Nitrate N in the catchment's main rivers dropped between 2004 and 2011 by a mean of 15.5%, whereas mean phosphate P declined very little. Legacy P and Inefficient sewerage treatment facilities may explain the latter finding. Results demonstrate that NVZ regulations, combined with economic pressures, have affected farmers’ attitudes and behaviour, resulting in significant improvements in surface water quality.

Application of data-based mechanistic modelling for flood forecasting at multiple locations in the Eden catchment in the National Flood Forecasting System (England and Wales)

Abstract. The Delft Flood Early Warning System provides a versatile framework for real-time flood forecasting. The UK Environment Agency has adopted the Delft framework to deliver its National Flood Forecasting System. The Delft system incorporates new flood forecasting models very easily using an "open shell" framework. This paper describes how we added the data-based mechanistic modelling approach to the model inventory and presents a case study for the Eden catchment (Cumbria, UK).

Design flood flows with climate change: method and limitations

An extended method is presented for ‘perturbing' design flood flows to account for climate change. Specifically, the method uses climate model output to directly alter parameters in the UK Flood Estimation Handbook rainfall–runoff model. The method is explored using a model of the River Eden catchment in northwest England, which comprises 26 sub-catchment hydrological models, with outflows routed using a hydraulic model. The results show a significant increase in flood flows and water levels by the 2080s, although uncertainties are large. The size of the increases varies depending on the climate change scenario and timing of the event, with the monthly precipitation change factor the single largest determinant of the change in peak flow. The method is reasonably simple to apply and there are benefits of using climate model information, rather than a sensitivity allowance, in terms of geographical interpretation of changes in precipitation and explicit representation of some of the uncertainty related to climate change. However, there are significant limitations to the methodology, in particular the minimal representation of antecedent conditions and more generally due to the ability of climate models to accurately reproduce and simulate extreme precipitation.

Monitoring agricultural diffuse pollution through a dense monitoring network in the River Eden Demonstration Test Catchment, Cumbria, UK

The water quality of our rivers and lakes is a reflection of the landscape over and through which it travels. The UK government, along with all European Union member states, are obliged under the Water Framework Directive (WFD) to aim for good ecological status of fresh water bodies by 2015. In order to evaluate the effectiveness of potential mitigation measures in reducing diffuse water pollution from agriculture at the catchment scale, the Demonstration Test Catchment (DTC) project was developed. The project is jointly funded by Defra, the Environment Agency (EA) and the Welsh Assembly Government (WAG). There are three DTCs across the country: the Eden catchment, Cumbria; the Wensum catchment, Norfolk and the Hampshire Avon catchment. The Eden DTC has established three ∼10 km2 focus catchments, chosen to reflect different farming practices, geologies, elevations and hydrological characteristics. Within each focus catchment, two sub‐catchments have been selected, one control and one mitigated, in which numerous existing and novel mitigation measures will be tested. It is hoped that the mitigation features will be multi‐purpose, having positive effects on pollutant retention, flooding, carbon sequestration, habitat creation and biodiversity. The effectiveness of these measures is assessed through networks of hydro‐meteorological and water‐quality instrumentation, most of which will provide data in near real time, with sub‐hourly time steps.

A method for incorporating climate variability in climate change impact assessments: Sensitivity of river flows in the Eden catchment to precipitation scenarios

Interest in the impacts of climate change is ever increasing. This is particularly true of the water sector where understanding potential changes in the occurrence of both floods and droughts is important for strategic planning. Climate variability has been shown to have a significant impact on UK climate and accounting for this in future climate change projections is essential to fully anticipate potential future impacts. In this paper a new resampling methodology is developed which includes the variability of both baseline and future precipitation. The resampling methodology is applied to 13 CMIP3 climate models for the 2080s, resulting in an ensemble of monthly precipitation change factors. The change factors are applied to the Eden catchment in eastern Scotland with analysis undertaken for the sensitivity of future river flows to the changes in precipitation. Climate variability is shown to influence the magnitude and direction of change of both precipitation and in turn river flow, which are not apparent without the use of the resampling methodology. The transformation of precipitation changes to river flow changes display a degree of non-linearity due to the catchment’s role in buffering the response. The resampling methodology developed in this paper provides a new technique for creating climate change scenarios which incorporate the important issue of climate variability.

Visualization approaches for communicating real‐time flood forecasting level and inundation information

AbstractThe January 2005 flood event in the Eden catchment (UK) has focused considerable research effort towards strengthening and extending operational flood forecasting in the region. The Eden catchment has become a key study site within the remit of phase two of the Flood Risk Management Research Consortium. This paper presents a synthesis of results incorporating model uncertainty analysis, computationally efficient real‐time data assimilation/forecasting algorithms, two‐dimensional (2D) inundation modelling, and data visualization for decision support. The emphasis here is on methods of presenting information from a new generation of probabilistic flood forecasting models. Using Environment Agency rain and river‐level gauge data, a data‐based mechanistic model is identified and incorporated into a modified Kalman Filter (KF) data assimilation algorithm designed for real‐time flood forecasting applications. The KF process generates forecasts within a probabilistic framework. A simulation of the 6‐h ahead forecast for river levels at Sheepmount (Carlisle) covering the January 2005 flood event is presented together with methods of visualizing the associated uncertainty. These methods are then coupled to the 2D hydrodynamic LISFLOOD‐FP model to produce real‐time flood inundation maps. The value of incorporating probabilistic information is emphasized.