A sub-field scale critical source area index for legacy phosphorus management using high resolution data

AbstractDiffuse phosphorus (P) mitigation in agricultural catchments should be targeted at critical source areas (CSAs) that consider source and transport factors. However, development of CSA identification needs to consider the mobilisation potential of legacy soil P sources at the field scale, and the control of (micro)topography on runoff generation and hydrological connectivity at the sub-field scale. To address these limitations, a ‘next generation’ sub-field scale CSA index is presented, which predicts the risk of dissolved P losses in runoff from legacy soil P. The GIS-based CSA Index integrates two factors; mobile soil P concentrations (water extractable P; WEP) and a hydrologically sensitive area (HSA) index. The HSA Index identifies runoff-generating-areas using high resolution LiDAR Digital Elevation Models (DEMs), a soil topographic index (STI) and information on flow sinks and effects on hydrological connectivity. The CSA Index was developed using four intensively monitored agricultural catchments (7.5–11km2) in Ireland with contrasting agri-environmental conditions. Field scale soil WEP concentrations were estimated using catchment and land use specific relationships with Morgan P concentrations. In-stream total reactive P (TRP) concentrations and discharge were measured sub-hourly at catchment outlet bankside analysers and gauging stations during winter closed periods for fertiliser spreading in 2009–14, and hydrograph/loadograph separation methods were used to estimate TRP loads and proportions from quickflow (surface runoff). A strong relationship between TRP concentrations in quickflow and soil WEP concentrations (r2=0.73) was used to predict dissolved P concentrations in runoff at the field scale, which were then multiplied by the HSA Index to generate sub-field scale CSA Index maps. Evaluation of the tool showed a very strong relationship between the total CSA Index value within the HSA and the total TRP load in quickflow (r2=0.86). Using a CSA Index threshold value of ≥0.5, the CSA approach identified 1.1–5.6% of catchment areas at highest risk of legacy soil P transfers, compared with 4.0–26.5% of catchment areas based on an existing approach that uses above agronomic optimum soil P status. The tool could be used to aid cost-effective targeting of sub-field scale mitigation measures and best management practices at delivery points of CSA pathways to reduce dissolved P losses from legacy P stores and support sustainable agricultural production

Development of watershed-based modeling approach to pollution source identification

Identification of unknown pollution sources is essential to environmental protection and emergency response. A review of recent publications in source identification revealed that there are very limited numbers of research in modeling methods for rivers. What’s more, the majority of these attempts were to find the source strength and release time, while only a few of them discussed how to identify source locations. Comparisons of these works indicated that a combination of biological, mathematical and geographical method could effectively identify unknown source area(s), which was a more practical trial in a watershed. This thesis presents a watershed-based modeling approach to identification of critical source area. The new approach involves (1) identification of pollution source in rivers using a moment-based method and (2) identification of critical source area in a watershed using a hydrograph-based method and high-resolution radar rainfall data. In terms of the moment-based method, the first two moment equations are derived through the Laplace transform of the Variable Residence Time (VART) model. The first moment is used to determine the source location, while the second moment can be employed to estimate the total mass of released pollutant. The two moment equations are tested using conservative tracer injection data collected from 23 reaches of five rivers in Louisiana, USA, ranging from about 3km to 300 km. Results showed that the first moment equation is able to predict the pollution source location with a percent error of less than 18% in general. The predicted total mass has a larger percent error, but a correction could be added to reduce the error significantly. Additionally, the moment-based method can be applied to identify the source location of reactive pollutants, provided that the special and temporal concentrations are recorded in downstream stations. In terms of the hydrograph-based method, observed hydrographs corresponding to pollution events can be utilized to identify the critical source area in a watershed. The time of concentration could provide a unique fingerprint for each subbasin in the watershed. The observation of abnormally high bacterial levels along with high resolution radar rainfall data can be used to match the most possible storm events and thus the critical source area

Development and testing of a risk indexing framework to determine field-scale critical source areas of faecal bacteria on grassland.

This paper draws on lessons from a UK case study in the management of diffuse microbial pollution from grassland farm systems in the Taw catchment, south west England. We report on the development and preliminary testing of a field-scale faecal indicator organism risk indexing tool (FIORIT). This tool aims to prioritise those fields most vulnerable in terms of their risk of contributing FIOs to water. FIORIT risk indices were related to recorded microbial water quality parameters (faecal coliforms [FC] and intestinal enterococci [IE]) to provide a concurrent on-farm evaluation of the tool. There was a significant upward trend in Log[FC] and Log[IE] values with FIORIT risk score classification (r2 =0.87 and 0.70, respectively and P<0.01 for both FIOs). The FIORIT was then applied to 162 representative grassland fields through different seasons for ten farms in the case study catchment to determine the distribution of on-farm spatial and temporal risk. The high risk fields made up only a small proportion (1%, 2%, 2% and 3% for winter, spring, summer and autumn, respectively) of the total number of fields assessed (and less than 10% of the total area), but the likelihood of the hydrological connection of high FIO source areas to receiving watercourses makes them a priority for mitigation efforts. The FIORIT provides a preliminary and evolving mechanism through which we can combine risk assessment with risk communication to end-users and provides a framework for prioritising future empirical research. Continued testing of FIORIT across different geographical areas under both low and high flow conditions is now needed to initiate its long term development into a robust indexing tool

Developing a multi-pollutant conceptual framework for the selection and targeting of interventions in water industry catchment management schemes

In recent years water companies have started to adopt catchment management to reduce diffuse pollution in drinking water supply areas. The heterogeneity of catchments and the range of pollutants that must be removed to meet the EU Drinking Water Directive (98/83/EC) limits make it difficult to prioritise areas of a catchment for intervention. Thus conceptual frameworks are required that can disaggregate the components of pollutant risk and help water companies make decisions about where to target interventions in their catchments to maximum effect. This paper demonstrates the concept of generalising pollutants in the same framework by reviewing key pollutant processes within a source-mobilisation-delivery context. From this, criteria are developed (with input from water industry professionals involved in catchment management) which highlights the need for a new water industry specific conceptual framework. The new CaRPoW (Catchment Risk to Potable Water) framework uses the Source-Mobilisation-Delivery concept as modular components of risk that work at two scales, source and mobilisation at the field scale and delivery at the catchment scale. Disaggregating pollutant processes permits the main components of risk to be ascertained so that appropriate interventions can be selected. The generic structure also allows for the outputs from different pollutants to be compared so that potential multiple benefits can be identified. CaRPow provides a transferable framework that can be used by water companies to cost-effectively target interventions under current conditions or under scenarios of land use or climate change

Modeling Cost Effectiveness of Green Infrastructure at Stormwater Runoff Critical Points in Maunalua Bay Watershed, Oʻahu

Like many urbanized areas, the watersheds surrounding Maunalua Bay are highly developed with impervious surfaces and channelized waterways. This can cause issues with stormwater. Stormwater is water that flows over impermeable surfaces (roads, roofs, etc.) after heavy rain events. Stormwater can pick up pollutants as is flows down slope, negatively impacting the health of water bodies. It can also cause flood events impacting infrastructure and lives Green Infrastructure (G.I.) techniques can be implemented to improve conventional infrastructure and stormwater management. Green infrastructure is an approach to stormwater management that tries to mimic the natural water cycle. Most green infrastructure traps and treats water from a storm event and then slowly releases it back into the environment allowing for more control on the quantity of water being released. We created a map that identifies areas in Maunalua that have the highest potential for stormwater mitigation via G.I. Using existing maps on land cover, slope , soil permeability and storm drain density, we created a model that ranks each map attribute in terms of stormwater risk. This map can assist regional stakeholders in prioritizing and evaluating the costs and benefits of adopting G.I. techniques.Our model identified two stormwater "hotspots" within the Kamilo Iki watershed. One "hotspot" validated the model with existing green infrastructure already present. The other "hotspot" lacked green infrastructure. Using the EPA stormwater calculator we identified the most cost effective green infrastructure for a residential neighborhood.Malama Maunalu

Using datasets from the Internet for hydrological modeling: an example from the Kntnk Menderes Basin, Turkey

River basin development / Water resources / Data collection / Models / Hydrology / Land classification / Water management / Water scarcity / Water allocation / Stream flow / Water demand / Turkey / Kntnk Menderes Basin

Improving the identification of hydrologically sensitive areas using LiDAR DEMs for the delineation and mitigation of critical source areas of diffuse pollution

AbstractIdentifying critical source areas (CSAs) of diffuse pollution in agricultural catchments requires the accurate identification of hydrologically sensitive areas (HSAs) at highest propensity for generating surface runoff and transporting pollutants. A new GIS-based HSA Index is presented that improves the identification of HSAs at the sub-field scale by accounting for microtopographic controls. The Index is based on high resolution LiDAR data and a soil topographic index (STI) and also considers the hydrological disconnection of overland flow via topographic impediment from flow sinks. The HSA Index was applied to four intensive agricultural catchments (~7.5–12km2) with contrasting topography and soil types, and validated using rainfall-quickflow measurements during saturated winter storm events in 2009–2014. Total flow sink volume capacities ranged from 8298 to 59,584m3 and caused 8.5–24.2% of overland-flow-generating-areas and 16.8–33.4% of catchment areas to become hydrologically disconnected from the open drainage channel network. HSA maps identified ‘breakthrough points’ and ‘delivery points’ along surface runoff pathways as vulnerable points where diffuse pollutants could be transported between fields or delivered to the open drainage network, respectively. Using these as proposed locations for targeting mitigation measures such as riparian buffer strips reduced potential costs compared to blanket implementation within an example agri-environment scheme by 66% and 91% over 1 and 5years respectively, which included LiDAR DEM acquisition costs. The HSA Index can be used as a hydrologically realistic transport component within a fully evolved sub-field scale CSA model, and can also be used to guide the implementation of ‘treatment-train’ mitigation strategies concurrent with sustainable agricultural intensification

Ireland’s Rural Environment: Research Highlights from Johnstown Castle

ReportThis booklet gives a flavour of the current research in Teagasc Johnstown Castle Research Centre and introduces you to the staff involved. It covers the areas of Nutrient Efficiency, Gaseous emissions, Agricultural Ecology, Soils and Water quality

Simulation of Reservoir Siltation with a Process-based Soil Loss and Deposition Model

Soil erosion on arable land is the key driver of reservoir siltation in the German loess belt. In this regard, the Baderitz Reservoir suffers from deleterious sediment inputs and resulting siltation processes. In order to estimate the reservoir lifespan, the event-based soil erosion and deposition model EROSION 3D was applied. Simulations of sediment input and sediment deposition processes within the reservoir were realized using a typical crop rotation and a normal heavy rainfall year of the region. Model parameterization was enabled by existing data based on a large number of artificial rainfall simulations. Yearly soil losses of approximately 12 t/ha correspond to sediment inputs of nearly 8800 t. The mean annual increase of the reservoir bottom of 9 cm causes a 13% loss of reservoir storage in only 10 years. The model results are plausible and could be used for planning and dimensioning of mitigation measures