Experiences in an integrated assessment of water allocation issues in the Namoi river catchment, Australia

The Namoi river catchment in northern NSW is an important irrigation region. However water resources in this region are increasingly stressed. Both surface and groundwater supplies are overallocated in many areas of the catchment. Management options to reduce allocations in line with available supply and environmental requirements are expected to have long term social, economic and environmental implications. This paper looks at an integrated assessment model which has been developed to assess long term outcomes of management options for water allocation in the catchment. The development of this tool has been undertaken using an iterative approach with key stakeholders. Feedback on the model and preferred future directions of development arising from discussions with relevant stakeholder groups are discussed. A key aspect of the model framework is that it has been developed to be general enough for reapplication to water allocation issues in other catchments Lessons are drawn from this experience in framework development for the field of integrated assessment

Towards Best Practice Framing of Uncertainty in Scientific Publications: A Review of Water Resources Research Abstracts

Uncertainty is recognized as a key issue in water resources research, amongst other sciences. Discussions of uncertainty typically focus on tools and techniques applied within an analysis, e.g. uncertainty quantification and model validation. But uncertainty is also addressed outside the analysis, in writing scientific publications. The language that authors use conveys their perspective of the role of uncertainty when interpreting a claim —what we call here “framing” the uncertainty. This article promotes awareness of uncertainty framing in four ways. 1) It proposes a typology of eighteen uncertainty frames, addressing five questions about uncertainty. 2) It describes the context in which uncertainty framing occurs. This is an interdisciplinary topic, involving philosophy of science, science studies, linguistics, rhetoric, and argumentation. 3) We analyze the use of uncertainty frames in a sample of 177 abstracts from the Water Resources Research journal in 2015. This helped develop and tentatively verify the typology, and provides a snapshot of current practice. 4) Provocative recommendations promote adjustments for a more influential, dynamic science. Current practice in uncertainty framing might be described as carefully-considered incremental science. In addition to uncertainty quantification and degree of belief (present in ~5% of abstracts), uncertainty is addressed by a combination of limiting scope, deferring to further work (~25%) and indicating evidence is sufficient (~40%) – or uncertainty is completely ignored (~8%). There is a need for public debate within our discipline to decide in what context different uncertainty frames are appropriate. Uncertainty framing cannot remain a hidden practice evaluated only by lone reviewers

IWRAM: An integrated toolbox for considering impacts of development and land use change in Northern Thailand

The IWRAM Decision Support System was developed to consider economic, environmental, and sociocultural trade-offs involved with resource competition and development in the Mae Chaem catchment in Northern Thailand. IWRAM contains two modelling toolboxes utilising a nodal network structure for catchment analysis: a Biophysical Toolbox, for considering the biophysical (erosion, streamflow, crop) implications of 'painted on' land use scenarios; and, an Integrated Modelling Toolbox, which links models of household decision making with the biophysical toolbox to allow for consideration of socioeconomic and environmental trade-offs of many development and policy scenarios. This paper describes the Integrated Modelling Toolbox within the IWRAM system. Links between household decision models, a socioeconomic impacts model and the biophysical toolbox are described and results for a number of forest encroachment scenarios are demonstrated using key indicators of social, economic and environmental performance. The potential for reapplication of the modelling framework to a large number of catchment situations is also discussed. (Résumé d'auteur

Participatory natural resource management: a comparison of four case studies

This paper presents an overview of four recent participatory resource management projects carried out on three continents. The aim is to elicit from these case studies a description of participatory process structures as well as an analysis of the driving forces behind the selection of stakeholders and their involvement in management projects. The case studies represent four different process structures set up to achieve two categories of process goal. They also suggest four main drivers in the design of such structures: process goals, existing power structures, process direction and stakeholder numbers. The concept of scale of action mismatch is introduced as directly affecting two out of four studies. Such mismatches reduce the chance of achieving the participation goals (e.g. greater equity and effectiveness) of the stakeholder involvement. The consequential need for greater institutional safeguards for participation is discussed

Sensitivity analysis: A discipline coming of age

Sensitivity analysis (SA) as a ‘formal’ and ‘standard’ component of scientific development and policy support is relatively young. Many researchers and practitioners from a wide range of disciplines have contributed to SA over the last three decades, and the SAMO (sensitivity analysis of model output) conferences, since 1995, have been the primary driver of breeding a community culture in this heterogeneous population. Now, SA is evolving into a mature and independent field of science, indeed a discipline with emerging applications extending well into new areas such as data science and machine learning. At this growth stage, the present editorial leads a special issue consisting of one Position Paper on “The future of sensitivity analysis” and 11 research papers on “Sensitivity analysis for environmental modelling” published in Environmental Modelling & Software in 2020–21.publishedVersio

A review of surrogate models and their application to groundwater modeling

The spatially and temporally variable parameters and inputs to complex groundwater models typically result in long runtimes which hinder comprehensive calibration, sensitivity, and uncertainty analysis. Surrogate modeling aims to provide a simpler, and hence faster, model which emulates the specified output of a more complex model in function of its inputs and parameters. In this review paper, we summarize surrogate modeling techniques in three categories: data-driven, projection, and hierarchical-based approaches. Data-driven surrogates approximate a groundwater model through an empirical model that captures the input-output mapping of the original model. Projection-based models reduce the dimensionality of the parameter space by projecting the governing equations onto a basis of orthonormal vectors. In hierarchical or multifidelity methods the surrogate is created by simplifying the representation of the physical system, such as by ignoring certain processes, or reducing the numerical resolution. In discussing the application to groundwater modeling of these methods, we note several imbalances in the existing literature: a large body of work on data-driven approaches seemingly ignores major drawbacks to the methods; only a fraction of the literature focuses on creating surrogates to reproduce outputs of fully distributed groundwater models, despite these being ubiquitous in practice; and a number of the more advanced surrogate modeling methods are yet to be fully applied in a groundwater modeling context

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

This paper investigates the sensitivities of model outputs to model parameter values within a Biophysical Toolbox developed as part of a Decision Support System (DSS) for integrated catchment assessment and management of land and water resources in the highland regions of northern Thailand. The toolbox contains a hydrological module based upon the IHACRES rainfall-runoff model, a crop model (CATCHCROP), and an erosion model (USLE) modified to suit conditions in northern Thailand. Emphasis in the development of the individual models within the Biophysical Toolbox was placed upon limiting model complexity. Limited data availability commonly restricts the complexity of the model structure that can justifiably be used to model natural systems. The challenge under conditions with limited data is then to strike a balance in the model(s) between statistical rigour and model complexity. Once encompassed within the Biophysical Toolbox, linkages between the models increase the complexity of the system, despite the relative simplicity of the individual models. Consequently, the impacts of outputs from individual models on the outputs of other models deserve considerable attention. Understanding model sensitivity is of particular importance where there is a lack of data with which to support or adequately verify model behaviour. Sensitivity analysis potentially allows the identification of model components that require attention in terms of improved parameter estimation or improvement in model structure. Preliminary testing of the individual models within the Biophysical Toolbox has been reported previously within the literature and the Biophysical Toolbox as a whole has been described. This paper explores sensitivities within the Biophysical Toolbox, targeting in particular the identification of components of the toolbox in which sensitivities are propagated throughout the model

Design of water quality monitoring programs and automatic sampling techniques

An important means of characterising the health of streams is through the measurement of the sediment and nutrient fluxes that they transport. Cost effective and targeted water quality monitoring programs are required to properly quantify both the total loads and temporal distribution of these fluxes at catchment scales. Careful analysis of data from such programs ensures ameliorative efforts to reduce the biological, chemical and physical impacts of high loads are targeted to have the best effect. This paper reports on the development of a monitoring program in tributaries of the upper Murrumbidgee River. The aim of the program is to provide data for the modelling of both nutrient and sediment loads transported from upland catchments. The objective of the modelling is to spatially identify sediment transport and storage dynamics together with source strength variations in upland catchments. A brief review of design considerations for water quality programs is made with reference to the Murrumbidgee case study. The tools, techniques and sites of an alternative monitoring program in tributaries of the upper Murrumbidgee River are detailed. Included in the paper are modifications to the design of Graczyk et al. (2000) for an inexpensive, rising-stage water quality sampler, suitable for Australian conditions and currently in use. The research demonstrates that water quality data can be collected simply and cost effectively if programs are appropriately designed