Predicting diffuse microbial pollution risk across catchments: The performance of SCIMAP and recommendations for future development

Microbial pollution of surface waters in agricultural catchments can be a consequence of poor farm management practices, such as excessive stocking of livestock on vulnerable land or inappropriate handling of manures and slurries. Catchment interventions such as fencing of watercourses, streamside buffer strips and constructed wetlands have the potential to reduce faecal pollution of watercourses. However these interventions are expensive and occupy valuable productive land. There is, therefore, a requirement for tools to assist in the spatial targeting of such interventions to areas where they will have the biggest impact on water quality improvements whist occupying the minimal amount of productive land. SCIMAP is a risk-based model that has been developed for this purpose but with a focus on diffuse sediment and nutrient pollution. In this study we investigated the performance of SCIMAP in predicting microbial pollution of watercourses and assessed modelled outputs of E. coli, a common faecal indicator organism (FIO), against observed water quality information. SCIMAP was applied to two river catchments in the UK. SCIMAP uses land cover risk weightings, which are routed through the landscape based on hydrological connectivity to generate catchment scale maps of relative in-stream pollution risk. Assessment of the model's performance and derivation of optimum land cover risk weightings was achieved using a Monte-Carlo sampling approach. Performance of the SCIMAP framework for informing on FIO risk was variable with better performance in the Yealm catchment (rs = 0.88; p 0.05). Across both catchments much uncertainty was associated with the application of optimum risk weightings attributed to different land use classes. Overall, SCIMAP showed potential as a useful tool in the spatial targeting of FIO diffuse pollution management strategies; however, improvements are required to transition the existing SCIMAP framework to a robust FIO risk-mapping tool

Impact of land cover, rainfall and topography on flood risk in West Java

Flooding represents around 32% of total disasters in Indonesia and disproportionately affects the poorest of communities. The objective of this study was to determine significant statistical differences, in terms of river catchment characteristics, between regions in West Java that reported suffering from flood disasters and those that did not. Catchment characteristics considered included various statistical measures of topography, land-use, soil-type, meteorology and river flow rates. West Java comprises 154 level 9 HydroSHEDS sub-basin regions. We split these regions into those where flood disasters were reported and those where they were not, for the period of 2009 to 2013. Rainfall statistics were derived using the CHIRPS gridded precipitation data package. Statistical estimates of river flow rates, applicable to ungauged catchments, were derived from regionalisation relationships obtained by stepwise linear regression with river flow data from 70 West Javanese gauging stations. We used Kolmogorov–Smirnov tests to identify catchment characteristics that exhibit significant statistical differences between the two sets of regions. Median annual maximum river flow rate (AMRFR) was found to be positively correlated with plantation cover. Reducing plantation land cover from 20 to 10% was found to lead to a modelled 38% reduction in median AMRFR. AMRFR with return periods greater than 10 years were found to be negatively correlated with wetland farming land cover, suggesting that rice paddies play an important role in attenuating extreme river flow events. Nevertheless, the Kolmogorov–Smirnov tests revealed that built land cover is the most important factor defining whether or not an area is likely to report flood disasters in West Java. This is presumably because the more built land cover, the more people available to experience and report flood disasters. Our findings also suggest that more research is needed to understand the important role of plantation cover in aggravating median annual maximum river flow rates and wetland farming cover in mitigating extreme river flow events

Predicting microbial water quality with models: Over-arching questions for managing risk in agricultural catchments

The application of models to predict concentrations of faecal indicator organisms (FIOs) in environmental systems plays an important role for guiding decision-making associated with the management of microbial water quality. In recent years there has been an increasing demand by policy-makers for models to help inform FIO dynamics in order to prioritise efforts for environmental and human-health protection. However, given the limited evidence-base on which FIO models are built relative to other agricultural pollutants (e.g. nutrients) it is imperative that the end-user expectations of FIO models are appropriately managed. In response, this commentary highlights four over-arching questions associated with: (i) model purpose; (ii) modelling approach; (iii) data availability; and (iv) model application, that must be considered as part of good practice prior to the deployment of any modelling approach to predict FIO behaviour in catchment systems. A series of short and longer-term research priorities are proposed in response to these questions in order to promote better model deployment in the field of catchment microbial dynamics

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

A 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

Transmission loss estimation for ephemeral sand rivers in Southern Africa

Ephemeral sand rivers represent an important water resource in Southern Africa. These rivers only flow for a few days in a year. However, much of this water infiltrates the underlying river bed sediments where it is protected from evaporation and utilized by farmers throughout the dry season. Despite their importance, little is known about how much recoverable water is annually stored within the sand. A particular difficulty concerns obtaining reliable estimates of transmission losses (the amount of water that infiltrates the river bed). The objective of this article was to develop an improved methodology for quantifying transmission loss from ephemeral sand rivers by calibrating a lumped rainfall-runoff model to observed river flow data. Fifteen years of daily river flow data were obtained from four sand rivers in Botswana, namely, Shahshe, Ntshe, Tati and Metsimotlhabe. These data were supplemented with meteorological data from AgMERRA (Ruane et al., 2015) and precipitation data from CHIRPS (Funk et al., 2015). Our simplified rainfall runoff model had four unknown parameters including a river bed infiltration factor, a surface storage capacity, a river bed storage capacity and an average river channel width. Posteriori parameter distributions were derived using a GLUE (Beven and Binley, 1992) methodology. Our study confirms that upper and lower bounds for transmission loss can be obtained by calibrating a lumped 1rainfall runoff model to a single set of river flow gauging data. Transmission loss was found to represent between 55% and 85% of the total surface runoff at these locations

High resolution characterisation of E. coli proliferation profiles in livestock faeces

Agricultural intensification can lead to high volumes of livestock faeces being applied to land, either as solid or liquid manures or via direct defecation, and can result in reservoirs of faecal indicator organisms (FIOs) persisting within farmland. Understanding the survival of FIOs, e.g. E. coli, in agricultural environments, and in particular within different livestock faeces, is key to developing catchment management practices for the protection of ecosystem services provided by clean water. Frequently, controlled laboratory studies, under constant temperature regimes, are used to determine the impact of environmental factors on E. coli persistence in livestock faeces; however, such studies oversimplify the diurnal variations and interactions of real world conditions. The aim of this study was to investigate the survival of E. coli using a controlled environment facility, which simulated diurnal variation of temperatures typically experienced during a British spring and summer. The approach provided a comparison of E. coli persistence profiles within faeces of sheep, beef cattle and dairy cattle to allow novel interpretations of E. coli regrowth patterns in contrasting livestock faeces in the period immediately post-defecation. Thus, the coupling of a tightly controlled environment facility with high resolution monitoring enabled the development of a new non-linear, asymptotic description of E. coli proliferation in livestock faeces, with increased potential for E. coli growth observed during warmer temperatures for all livestock types. While this study focused on temperatures typical of the UK, the occurrence of a phase of E. coli regrowth has implications for microbial water quality management worldwide

A new framework for integrated, holistic, and transparent evaluation of inter-basin water transfer schemes

Water shortages are forecast to affect 50% of the world's population by 2030, impacting developing nations most acutely. To increase water security there has been a significant increase in Inter-basin Water Transfer (IBWT) schemes, engineering mega-projects that redistribute water from one basin to another. However, the implementation of these schemes is often contested, and evaluation of their complex impacts inadequate, or hidden from full public scrutiny. There is an urgent need to develop more integrated, holistic, and transparent ways of evaluating the multiple interlinking impacts of IBWT schemes of this scale. In this paper, we address this gap by outlining an experimental methodology to evaluate IBWT schemes using a multidisciplinary and transparent methodology which utilises publicly available data. We illustrate the method using a case study from the Inter-Linking Rivers Project in Northern India, comparing the results of the experimental approach against the official analysis of the proposed scheme produced by the State Government of Jharkhand. The results demonstrate that the proposed experimental method allows more detailed evaluation of spatial and temporal variability in water availability and demand, as well as holistic evaluation of the functioning of the proposed scheme under different future scenarios. Based on these results we propose a flexible framework for future evaluation of proposed water transfer schemes which embeds the principles of integrated assessment, transparency, and sound science which can be adapted to other IBWT projects across the world

Catchment scale flood management using SCIMAP-Flood: Spatial targeting of flood hazard reduction measures in the East Rapti catchment, Nepal

International audiencePractical approaches for managing flood hazards are moving from mitigation solely at the point of the impact, and towards an integrated catchment management approach which considers the source areas, flow pathways of flood waters and the impacted communities. However, there is uncertainty associated with providing catchment scale solutions which is primarily a function of spatial and temporal variability in patterns of rainfall, land cover, and hydrological connectivity across a catchment. These factors mean that flood waters are not produced in a homogenous way from one event to the next, resulting in a distribution of travel times to points of impact, such as towns and key infrastructure. There must also be careful consideration of the potential for a reduction in the flood hazard in one sub-catchment to increase the hazard elsewhere due to tributary timing and synchronisation

Catchment scale flood management using SCIMAP-Flood: Spatial targeting of flood hazard reduction measures in the East Rapti catchment, Nepal

International audiencePractical approaches for managing flood hazards are moving from mitigation solely at the point of the impact, and towards an integrated catchment management approach which considers the source areas, flow pathways of flood waters and the impacted communities. However, there is uncertainty associated with providing catchment scale solutions which is primarily a function of spatial and temporal variability in patterns of rainfall, land cover, and hydrological connectivity across a catchment. These factors mean that flood waters are not produced in a homogenous way from one event to the next, resulting in a distribution of travel times to points of impact, such as towns and key infrastructure. There must also be careful consideration of the potential for a reduction in the flood hazard in one sub-catchment to increase the hazard elsewhere due to tributary timing and synchronisation

A catchment-scale model to predict spatial and temporal burden of E . coli on pasture from grazing livestock

Effective management of diffuse microbial water pollution from agriculture requires a fundamental understanding of how spatial patterns of microbial pollutants, e.g. E. coli, vary over time at the landscape scale. The aim of this study was to apply the Visualising Pathogen & Environmental Risk (ViPER) model, developed to predict E. coli burden on agricultural land, in a spatially distributed manner to two contrasting catchments in order to map and understand changes in E. coli burden contributed to land from grazing livestock. The model was applied to the River Ayr and Lunan Water catchments, with significant correlations observed between area of improved grassland and the maximum total E. coli per 1 km2 grid cell (Ayr: r = 0.57; p < 0.001, Lunan: r = 0.32; p < 0.001). There was a significant difference in the predicted maximum E. coli burden between seasons in both catchments, with summer and autumn predicted to accrue higher E. coli contributions relative to spring and winter (P < 0.001), driven largely by livestock presence. The ViPER model thus describes, at the landscape scale, spatial nuances in the vulnerability of E. coli loading to land as driven by stocking density and livestock grazing regimes. Resulting risk maps therefore provide the underpinning evidence to inform spatially-targeted decision-making with respect to managing sources of E. coli in agricultural environments