Lachlan Newham

A Bayesian network approach for assessing the sustainability of coastal lakes in New South Wales, Australia

Coastal lakes are ecosystems of significant value generating many ecological, social and economic benefits. Increasing demands resulting from urban development and other human activities within coastal lake catchments have the potential to result in their degradation and can lead to conflicts, for example between lake users and upstream communities. There are many techniques that can be used to integrate the variables involved in such conflicts including system dynamics, meta-modelling, and coupled component models, but many of these techniques are too complex for catchment managers to employ on a routine basis. The overall result is the potential to compromise the sustainability of these important ecosystems. This paper describes research to address this problem. It presents the development of an integrated model framework based on a Bayesian network (Bn). Bns are used to assess the sustainability of eight coastal lake-catchment systems, located on the coast of New South Wales (NSW), Australia. The paper describes the potential advantages in the use of Bns and the methods used to develop their frameworks. A case study application for the Cudgen Lake of northern NSW is presented to illustrate the techniques. The case study includes a description of the relevant management issues being considered, the model framework and the techniques used to derive input data. Results for the case study application and their implications for management are presented and discussed. Finally, the directions for future research and a discussion of the applicability of Bn techniques to support management in similar situations are proffered.

A framework for integrated hydrologic, sediment and nutrient export modelling for catchment-scale management

Abstract Many catchments in Australia have experienced increased sediment and nutrient loadings and concomitant declines in water quality and increases in problematic blue–green algal blooms over the past several decades. This paper describes an integrated hydrologic, sediment and nutrient export modelling framework known as catchment-scale management of diffuse sources (CatchMODS). The modelling framework is designed to simulate and assess catchment-scale land and water management activities designed to reduce nutrient and sediment delivery to receiving waters. The Ben Chifley Dam Catchment in New South Wales, Australia is used as a case study for describing the development of the framework. Improving water quality through reduction of sediment and nutrient loads will reduce the probability of algal bloom occurrence in the dam. The innovation of the system is the integration of otherwise separate modelling approaches to enable biophysical and economic assessment of different management options. The outputs from the research are used to improve and focus on-ground remediation, targeted to specific stream reaches or subcatchment areas, as well as to encourage sustainable management practices more broadly in the catchment. With minimal modification, the methods developed are applicable elsewhere to address water quality decline.

An integrated approach to linking economic valuation and catchment modelling

An increased emphasis on integrated water management at a catchment scale has led to the development of numerous modelling tools. To support efficient decision making and to better target investment in management actions, such modelling tools need to link socioeconomic information with biophysical data. However, there is still limited experience in developing catchment models that consider environmental changes and economic values in a single framework. We describe a model development process where biophysical modelling is integrated with economic information on the non-market environmental costs and benefits of catchment management changes for a study of the George catchment in northeast Tasmania, Australia. An integrated assessment approach and Bayesian network modelling techniques were used to integrate knowledge about hydrological, ecological and economic systems. Rather than coupling existing information and models, synchronous data collection and model development ensured tailored information exchange between the different components. The approach is largely transferable to the development of integrated hydro-economic models in other river catchments. Our experiences highlight the challenges in synchronizing economic and scientific modelling. These include the selection of common attributes and definition of their levels suitable for the catchment modelling and economic valuation. The lessons from the model development process are useful for future studies that aim to integrate scientific and economic knowledge.

A review of nitrogen and phosphorus export to waterways: context for catchment modelling

This paper reviews knowledge of nitrogen and phosphorus generation from land use and export to water- ways, including studies relevant to Australia. It provides a link between current and future modelling requirements, and the context for incorporation of this knowledge into catchment models for use by catchment managers. Selected catchment models used by catchment managers are reviewed, and factors limiting their application are addressed. The review highlights the importance of dissolved N and P for overland flow and groundwater pathways, for sheep, beef and dairy grazing land use. Consequently, the effectiveness of riparian buffers to remove N and P may not be adequate. Consideration of the effects of rainfall and hydrology, dissolved P and N losses from pastures and event- based catchment-scale loads are therefore important factors that should be incorporated into catchment models. The review shows that it is likely that nutrient losses under Australian dairying conditions have many similarities to worldwide studies. Catchment models need to represent the importance of event-based loads, intensively farmed land use, management and forms of nutrients. Otherwise there is a likelihood of either underestimating nutrient losses, or potentially overestimating the effectiveness of riparian buffers.

Review: A review of surface erosion and sediment delivery models for unsealed roads

This paper reviews available models for estimating surface erosion and sediment delivery to streams from unsealed roads. It summarises current progress and identifies directions for ongoing research and model development. The paper provides a framework for assessing road erosion and sediment delivery models and it includes an overview of road erosion and sediment delivery processes and how they are commonly represented in models. Seven road models are reviewed in terms of their representations of erosion and sediment delivery processes, assumptions, application and limitations. While simple models are thought to be more useful and easily applied for land management purposes, more complex models provide a basis for building and consolidating scientific knowledge. This article reveals some of the limitations and needs of existing road erosion models. These include limitations of their ancestor hillslope erosion models, the imbalance between representation of erosion processes versus sediment delivery, a lack of representation of subsurface flow interception and the lack of model testing and uncertainty analysis. One of the most fundamental limitations to developing improved models of road erosion and delivery is access to data of an appropriate standard.

A framework for estimating pollutant export coefficients from long-term in-stream water quality monitoring data

Modeling techniques for estimating pollutant loadings to water bodies range from simple export coefficient and regression models to more complex mechanistic models. All export coefficient models and many complex mechanistic models rely on pollutant export coefficients to estimate pollution sources and transport in large watersheds. Typically, pollutant export coefficients are determined by monitoring small catchments or field plots to isolate individual landuse contributions. However, pollutant export coefficients derived from small catchment and field plot scale studies cannot be confidently used in catchment-scale water quality modeling. The objective of this paper is to present a framework to estimate the export coefficients of pollutants from commonly available in-stream water quality monitoring data. A combination of readily and freely available statistical, spatial and hydrological tools and a multiple regression methodology is proposed to estimate pollutant export coefficients. A case study from the Fuji River catchment, Japan is presented where export coefficients of organic matters and nutrients are estimated. Most of the estimated pollutant export coefficients are significant at @a equal to 0.05 and the landuse categories used in the multiple regression models explained more than 85% variability in loadings. These results are encouraging especially given the pressing need to identify appropriate management practices to improve the water quality within the catchment. It is recommended to investigate further the required number of water quality monitoring stations, sampling frequencies and sampling duration of water quality constituents to enhance the robustness and usefulness of the proposed methodology.

How Can We Make Progress with Decision Support Systems in Landscape and River Basin Management? Lessons Learned from a Comparative Analysis of Four Different Decision Support Systems

This article analyses the benefits and shortcomings of the recently developed decision support systems (DSS) FLUMAGIS, Elbe-DSS, CatchMODS, and MedAction. The analysis elaborates on the following aspects: (i) application area/decision problem, (ii) stakeholder interaction/users involved, (iii) structure of DSS/model structure, (iv) usage of the DSS, and finally (v) most important shortcomings. On the basis of this analysis, we formulate four criteria that we consider essential for the successful use of DSS in landscape and river basin management. The criteria relate to (i) system quality, (ii) user support and user training, (iii) perceived usefulness and (iv) user satisfaction. We can show that the availability of tools and technologies for DSS in landscape and river basin management is good to excellent. However, our investigations indicate that several problems have to be tackled. First of all, data availability and homogenisation, uncertainty analysis and uncertainty propagation and problems with model integration require further attention. Furthermore, the appropriate and methodological stakeholder interaction and the definition of ‘what end-users really need and want’ have been documented as general shortcomings of all four examples of DSS. Thus, we propose an iterative development process that enables social learning of the different groups involved in the development process, because it is easier to design a DSS for a group of stakeholders who actively participate in an iterative process. We also identify two important lines of further development in DSS: the use of interactive visualization tools and the methodology of optimization to inform scenario elaboration and evaluate trade-offs among environmental measures and management alternatives.

Suspended sediment, nitrogen and phosphorus concentrations and exports during storm-events to the Tuross estuary, Australia.

This paper presents a process for estimating pollutant loads from water quality data, to improve catchment-scale modelling in the region for resource management purposes. It describes a program to estimate suspended sediment, total and dissolved nitrogen and phosphorus loads to the Tuross estuary from the Tuross River catchment (1810 km(2)) of coastal southeast Australia. Event-based water quality sampling results obtained during storm events in 2005 are presented. Event 1, during July 2005 was the largest storm event in terms of peak flow for 3.5 years. Other events monitored were also in July, November and December 2005. The early July 2005 event had a flow-weighted mean suspended sediment (SS) concentration during the first 4 days of 63 mg L(-1). Of the events monitored, this was unusual as it was preceded by drought and had the largest SS concentrations (peaking at 180 mg L(-1)) during the rising-stage. In contrast, the November event had a much lower flow-weighted SS mean (28 mg L(-1)), even though peak flow magnitudes were similar. The July and November 2005 events had peak flows of 12,360 and 11,330 ML day(-1). Low-cost rising-stage siphon samplers were used to collect samples during the rapidly rising phase of these events. The use of such samplers and consideration of time-lead/lag flow adjustments, quantified using cross-correlation analysis to account for hysteresis effects, were incorporated into the load estimation techniques. The technique is a potentially useful approach for understanding relationships between water quality concentrations and flow for modelling catchment source strengths and transport processes.

Review: Three complementary methods for sensitivity analysis of a water quality model

In this paper, sensitivity analysis (SA) has been used to assess model sensitivities to input parameter values in a water quality model. The water quality model incorporates a rainfall-runoff sub-model and a sediment load estimation sub-model, and is calibrated against hydrologic and water quality data from the Moruya River catchment in southeast Australia. The tested methods, One-at-A-Time (OAT), Morris Method (MM) and Regional SA (RSA) are found to be complementary, and help to characterise the behaviour of the water quality model. The most important parameters are plant stress threshold (f), coefficient of evapotranspiration (e), catchment moisture threshold (d), in decreasing order, indicating that sediment and nutrient loads are more sensitive to parameters that affect the magnitude of flows than those (vs, @t^q, @t^s) that control the timing and shape of the peak in a time series. But this application shows a need to be flexible in the use of different SA techniques. RSA is more appropriate for complex models where system nonlinearities and parameter interactions are more likely to be important. The RSA suggests that f and vs have strong interactions in the influence on nitrogen estimation. This study is also valuable for future uncertainty analysis, by separating the source of uncertainty of model parameters from the uncertainty in the model inputs.

Sensitivity analysis for assessing the behaviour of a landscape-based sediment source and transport model

Abstract Widespread degradation of aquatic habitat and water quality has occurred since European settlement in Australia. Repairing this degradation is expensive and hence on-ground management needs to be carefully focussed. The Sediment River Network model, SedNet, used to estimate (spatially) the sources and transport of sediment at catchment scales provides a potentially useful tool to assist land managers in focusing this work. The complete model, while broadly applied has not been systematically tested to assess its sensitivity to its various model components. This paper describes sensitivity assessment to improve understanding of the model, with the aim of prioritising data acquisition and improving the structure and parameterisation of the model where necessary. It was found that the SedNet model was most sensitive to perturbations in its hydrologic parameters across a variety of scales and sites. Because of this it is important that ongoing model development activities focus on how to effectively represent hydrologic processes in the model.