Wendy Merritt

A review of erosion and sediment transport models

Abstract Information on sediment and nutrient export from catchments and about related erosive processes is required by catchment managers and decision-makers. Many models exist for the consideration of these processes. However, these models differ greatly in terms of their complexity, their inputs and requirements, the processes they represent and the manner in which these processes are represented, the scale of their intended use and the types of output information they provide. This paper reviews several different erosion and sediment and sediment-associated nutrient transport models with regard to these factors. The review of models is limited to those models with explicit considerations of either the sediment generation or transport process.

Using Bayesian Networks to complement conventional analyses to explore landholder management of native vegetation

Influencing the management of private landholders is a key element of improving the condition of Australias natural resources. Despite substantial investment by governments, effecting behavioural change on a scale likely to stem biodiversity losses has proven difficult. Understanding landholder decision-making is now acknowledged as fundamental to achieving better policy outcomes. There is a large body of research examining landholder adoption of conservation practices. Social researchers are able to employ a suite of conventional techniques to analyse their survey data and assist in identifying significant and causal relationships between variables. However, these techniques can be limited by the type of data available, the breadth of issues that can be represented and the extent that causality can be explored. In this paper we discuss the findings of a unique study exploring the benefits of combining Bayesian Networks (BNs) with conventional statistical analysis to examine landholder adoption. Our research examined the landholder fencing of native bushland in the Wimmera region in south east Australia. Findings from this study suggest that BNs provided enhanced understanding of the presence and strength of causal relationships. There was also the additional benefit that a BN could be quickly developed and that this process helped the research team clarify and understand relationships between variables. However, a key finding was that the interpretation of the results of the BNs was complemented by the conventional data analysis and expert review. An additional benefit of the BNs is their capacity to present key findings in a format that is more easily interpreted by researchers and enables researchers to more easily communicate their findings to natural resource practitioners and policy makers.

CATCHCROP: modeling crop yield and water demand for integrated catchment assessment in Northern Thailand

Abstract As part of an Integrated Water Resource Assessment and Management project (IWRAM) in Northern Thailand, a Decision Support System is being constructed in order to provide guidelines for crop diversification and water allocation. The IWRAM software integrates a crop model with hydrological and economic models. Presented here is the integrated crop model, called CATCHCROP, which is capable of simulating yield response to water deficit and fertility depletion. External and internal constraints have largely influenced the model construction. Paucity of observed data and its reliability required the use of conceptual and recognized algorithms. Linkages with the economic and hydrological models led to the choice of a 10-days time step. The stand-alone version of the model has been tested against available data sets coming from two small catchments. First results are fairly satisfactory but it is acknowledged that this kind of integrated model should not be used at the farm plot level to assess cropping practices.

Potential impacts of climate change on water availability for crops in the Okanagan Basin, British Columbia

Crop water demand in the Okanagan Basin was determined for 1961 to 1990, 2010 to 2039, 2040 to 2069, and 2070 to 2099. Daily station temperature data were spatially interpolated to a 1 × 1 km grid and adjusted for elevation. Daily precipitation data were estimated across four climatic regions. Output from three global climate models (GCM), CGCM2, CSIROMk2 and HadCM3 was used to create future daily climate. Daily potential evapo-transpiration (grass reference) was estimated from an empirical relationship between Bellani- plate atmometer readings, temperature and extra-terrestrial solar radiation, and then modified by crop coefficients for all crops except pasture. Depending on GCM, projected water demand increased by 12–20% (2010 to 2039), 24–38% (2040 to 2069) and 40–61% (2070 to 2099). Possible elevated CO2 effects on stomatal conductance, which may reduce water demand, were not accounted for. Comparisons with modeled Okanagan Lake inflows indicated that, on average, high water demand and low supply scen...

Sensitivity testing of a model for exploring water resources utilisation and management options

This paper investigates the model sensitivities to input parameter values in a Biophysical Toolbox for integrated catchment assessment and management of land and water resources. The toolbox was developed for application in the highland regions of northern Thailand. It incorporates the IHACRES rainfall-runoff model, a crop model (CATCHCROP), and an erosion model (a Universal Soil Loss Equation [USLE], modified for application to northern Thailand). In developing the individual models in the Biophysical Toolbox, emphasis was placed on limiting model complexity. The toolbox was developed and tested using data from the Mae Chaem catchment in northern Thailand. Due to the short duration and sparse distribution of the available data, the complexity of the model structure is constrained to consider only the key processes of interest. Despite the relative simplicity of the individual models, linkages between the models encompassed in the Biophysical Toolbox increase the complexity of the modelling system. This paper explores sensitivities in the Biophysical Toolbox to the parameters of CATCHCROP as this component has the greatest potential for propagating errors though the Toolbox. A simple sensitivity analysis was undertaken, whereby parameter values were perturbed to ascertain the effect of these perturbations on output indicators. The hydrologic component showed strong non-linearity to the infiltration parameters of the CATCHCROP model, although this did not greatly impact estimates of total annual discharge. Additionally, a number of CATCHCROP parameters did not greatly impact some output indicators of the toolbox. While the CATCHCROP model is relatively parsimonious when compared with many crop models, there are still 19 model parameters that must be determined from the field or prescribed from the literature. There is potential for the model to be further simplified although more extensive model testing is required to ensure that such simplifications would not adversely impact on the utility of the toolbox.

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.

Modeling livelihood indicators and household resilience using Bayesian networks

The Bayesian network (BN) approach has garnered popularity in the field of environmental modeling because it is well-suited to representing relationships between the biophysical and societal factors critical to the success of natural resource management programs. BNs can be highly useful for structuring, clarifying, and communicating model results to stakeholders. This chapter introduces the BN methodology and its previous application to livelihood issues. The process used to construct a BN model relating the stocks of the livelihood capitals (e.g., social capital) held by households to their capacity to survive consecutive droughts (resilience) is described, followed by a demonstration of the model behavior and performance.

Exploring Implications of Climate, Land Use, and Policy Intervention Scenarios on Water Resources, Livelihoods, and Resilience

Abstract Integrated modeling methodologies have a greater potential than purely disciplinary approaches to support comprehensive assessment of social, economic, and biophysical aspects of complex natural resource management such as the Indian governments’ Integrated Watershed Management Program (IWMP). Climate and recharge estimates drive predictions assessment of the availability of surface and groundwater resources as impacted by IWMP, climate, and land use (i.e., water extractions). Water availability, land use mix, and crop productivity influence access to the available water resources, their usage, and, consequently, the decisions and resilience of households. This chapter draws together the science described in earlier chapters to allow scenario analysis of the likely impacts of selected climate, land use, IWMP, and other policy interventions on surface and groundwater resources, agricultural productivity, people’s livelihoods, and resilience. A brief recap of the biophysical and socioeconomic models is also provided, and their linkage within an integrated model is outlined. Examples of biophysical scenarios and social policy scenarios are used to demonstrate the value of the integrated and disciplinary models for assessing IWMP and other impacts on water resources and resilience.

Analytical Framework, Study Design, and Methodology

Abstract As most of the chapters in this book are based on research that has adopted a clear analytical framework and scientific approach for assessing watershed impacts, it is necessary to discuss the aims of the research and the adopted framework and approach before we go into these chapters. The purpose of the research is to provide design inputs for sustainable watershed interventions that enhance livelihoods outcomes. The multidisciplinary nature and integrated approach adopted in the research has used various methods and tools cutting across hydrological, biophysical, and socioeconomic methodologies. While the specific details of methodologies used are discussed in their respective chapters, this chapter provides the overall framework for hydrogeology modeling, biophysical modeling, and socioeconomic “sustainable livelihoods.” This framework would be based on the review of existing literature and its appropriateness for sample sites. The chapter also provides the framework for the Bayesian network used for integrating the hydrogeological, biophysical, and livelihood aspects. Also, details like the sampling design, profile of sample sites, etc., will be presented in this chapter.