Baihua Fu

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.

Modelling erosion and sediment delivery from unsealed roads in southeast Australia

Unsealed roads and tracks are potentially significant sources of diffuse pollutants, particularly sediment. This paper describes the application and development of a road erosion and sediment transport model in the Moruya-Deua and Tuross River catchments of southeast Australia. An empirical model based on the Washington Road Surface Erosion Model (WARSEM) is applied using typically widely available spatial data sets and field-collected data. The results suggest that approximately 21kt and 35kt of sediment respectively are produced annually from road erosion in the Moruya-Deua and Tuross River catchments, but that less than 10% of the sediment is delivered to streams. Surprisingly, about half of the delivered sediment is derived from only 4% of the total road network. Testing of the model shows that the model outputs are likely to overestimate road erosion rates. To address this problem, catchment-specific testing of the factors of the model and improving knowledge of the processes of road to stream sediment transport are required.

Assessing certainty and uncertainty in riparian habitat suitability models by identifying parameters with extreme outputs

The aim of this paper is to introduce a computationally efficient uncertainty assessment approach using an index-based habitat suitability model. The approach focuses on uncertainty in ecological knowledge regarding parameters of index curves and weights. A case study determines which of two 15-year periods has more suitable surface water and groundwater regimes for riparian vegetation. The uncertainty assessment consists of defining constraints on index curves and weights. Linear programming is used to identify parameters that yield two extreme outputs: maximising and minimising differences between the two periods. Because they are extremes, if both outputs agree on which period is better (e.g. maximum and minimum differences are both positive), then all other models will also agree. Identifying models with extreme outputs prompts learning about the boundaries of our knowledge and identifies patterns about what is considered certain. It helps build an understanding of what is already known despite the high uncertainty.

Methods for Exploring Uncertainty in Groundwater Management Predictions

Models of groundwater systems help to integrate knowledge about the natural and human system covering different spatial and temporal scales, often from multiple disciplines, in order to address a range of issues of concern to various stakeholders. A model is simply a tool to express what we think we know. Uncertainty, due to lack of knowledge or natural variability, means that there are always alternative models that may need to be considered. This chapter provides an overview of uncertainty in models and in the definition of a problem to model, highlights approaches to communicating and using predictions of uncertain outcomes and summarises commonly used methods to explore uncertainty in groundwater management predictions. It is intended to raise awareness of how alternative models and hence uncertainty can be explored in order to facilitate the integration of these techniques with groundwater management.

An iterative method for discovering feasible management interventions and targets conjointly using uncertainty visualizations

This paper presents a generic method, referred to as Iterative Discovery, to guide deliberation with analysis where the aim is to plan refinements to management interventions with difficult-to-define objectives, often due to system uncertainties and diverse stakeholder positions. The method can be initiated by evaluating a scenario describing the current-best intervention. This provides the starting point for three evaluation cycles, focusing on model assumptions, alternative interventions and management targets. The outcome of this method is a list of management targets that can and cannot be achieved, the potential interventions that correspond to these targets, and the assumptions and uncertainties associated with these interventions. It was applied to a case study for environmental flow management in the Macquarie Marshes, Australia. We identified feasible management targets based on ecological outcomes in flood suitability across different locations, climate conditions and species, and the suitable environmental flow volumes that correspond to these targets. Display Omitted We present an Iterative Discovery method for finding targets and interventions.Application of the method is demonstrated in an environmental flow case study.Visualization is used to explore uncertainties.The method derives from systems thinking, aids capacity building.

A weight-of-evidence approach to integrate suspended sediment source information

Sediment monitoring, tracing and modelling are widely used to identify suspended sediment sources. Although each method has inherent limitations and uncertainties, their integration provides opportunities to form collective knowledge and encourages robust management strategies. This paper presents a Weight-of-Evidence approach to integrate multiple Lines-of-Evidence for identifying suspended sediment sources. Three sources of evidence were used: i) stream flow and suspended sediment monitoring at river gauges; ii) geochemical sediment tracing at river junctions; and iii) catchment-scale suspended sediment modelling of hillslope, gully, streambank and unsealed road erosion. We applied this approach on two data-poor catchments in Australia. Some reaches were consistently identified as major sources of sediment from all Lines-of-Evidence. However, inconsistencies between the types of evidence in other areas highlighted the high uncertainty in identifying suspended sediment sources in these areas and the need for further investigation. The integration framework maximised the use of scarce information, enabled explicit consideration of uncertainties for catchment management and identified where future monitoring and research should be targeted.

Groundwater Dependent Ecosystems: Classification, Identification Techniques and Threats

This chapter begins by briefly discussing the three major classes of groundwater dependent ecosystems (GDEs), namely: (I) GDEs that reside within groundwater (e.g. karsts; stygofauna); (II) GDEs requiring the surface expression of groundwater (e.g. springs; wetlands); and (III) GDEs dependent upon sub-surface availability of groundwater within the rooting depth of vegetation (e.g. woodlands; riparian forests). We then discuss a range of techniques available for identifying the location of GDEs in a landscape, with a primary focus of class III GDEs and a secondary focus of class II GDEs. These techniques include inferential methodologies, using hydrological, geochemical and geomorphological indicators, biotic assemblages, historical documentation, and remote sensing methodologies. Techniques available to quantify groundwater use by GDEs are briefly described, including application of simple modelling tools, remote sensing methods and complex modelling applications. This chapter also outlines the contemporary threats to the persistence of GDEs across the world. This involves a description of the “natural” hydrological attributes relevant to GDEs and the processes that lead to disturbances to natural hydrological attributes as a result of human activities (e.g. groundwater extraction). Two cases studies, (1) Class III: terrestrial vegetation and (2) Class II: springs, are discussed in relation to these issues.

Uncertainty in Environmental Water Quality Modelling: Where Do We Stand?

The physical and biochemical processes that underpin the generation and transport of water quality constituents are extremely complex, as are the social and institutional processes that determine how human activities impact the landscape. Any models attempting to represent these processes will therefore be fraught with huge overall uncertainty. It is incumbent on developers and users of water quality models to manage the sources of uncertainties and reduce the critical ones that affect the clarification of decisions. This paper documents ten sources of uncertainties and suggests nine ways in which uncertainty in a model might be handled. Model conceptualisation is a major source of uncertainty that is all too often not reported nor justified. Commonly used process-based models are often non-identifiable, thus issues concerning the selection of scales and detail of model representation need more rigorous treatment. While parameter fixing is often undertaken to address over-parameterisation, seldom do we see the increasing use of sensitivity and uncertainty analyses leading to model structure improvements. Formal methods of uncertainty analysis are hindered by the many required assumptions. One way around this is to utilise exploratory modelling to identify conditions and assumptions under which certain objectives are met and not met. Methods of robust decision and risk analysis also have much to offer in this respect. Another known source of uncertainty is errors in the data. The paper advocates more attention to understanding one’s data and the signals therein before embarking on any modelling. It also proposes complementary uses of empirical modelling when warranted by the problem context.

Realizing modelling outcomes: A synthesis of success factors and their use in a retrospective analysis of 15 Australian water resource projects

Abstract We review several papers that have afforded insights into determinants of positive outcomes (e.g. the adoption of tools, improved learning and/or collaboration) from modelling projects. From a subsequent internet search in the environmental domain we identified 33 such factors that are then invoked in a transferable survey-based method to facilitate structured reflections by model developers on 15 projects. Four factors were considered most necessary to realize overall success for any modelling project. Three factors related to aspects of stakeholder engagement in the modelling process; the other to critical thinking around problem framing and the role(s) of models. The latter factor was considered reasonably well-achieved across the projects. Harder to control were the stakeholder engagement factors which, along with project management considerations, can constrain or enable achievement of other factors. The paper provides further evidence of the critical need to consider non-technical aspects in the design and implementation of modelling projects.

Integrated Approaches Within Water Resource Planning and Management in Australia—Theory and Application

This chapter overviews the dimensions and challenges in integrative approaches in water resource decision making. Integrative research is central to tackling real-world, complex science and social-political problems, where acceptable solutions often cross disciplinary boundaries. Recent literature on integration theory and the dimensions and challenges of integration are reviewed. Literature on translating integrated approaches from theory to practice is synthesized. We then use three case studies, all from the Murray-Darling Basin, to demonstrate different approaches to integration, where each example sought to achieve a different purpose and had different scales of application. We conclude the chapter with some lessons learned and some needs to consider for future integrative research projects.