Barry Croke

Integrated assessment modelling for water resource allocation and management: A generalised conceptual framework

Nodal network approaches are a common framework for considering water allocation in river basins. In this type of model framework, a river basin is represented as a series of nodes, where nodes generally represent key points of extraction or instream use. When considering water allocation, agricultural production and other water use decisions generally interact with the stream system in two ways: they can affect the generation of runoff and thus the volume of water reaching the stream; or, they may involve direct extraction or use of water once it has reached the stream. Models are generally required to consider the influence of these decisions on flows and downstream water availability, as well as the influence of flows on the productive, passive use and environmental values of water. This paper provides a generalised conceptual framework for considering these types of interactions and their representation in integrated water allocation models. Applications of this framework to three very different case studies are outlined.

A catchment moisture deficit module for the IHACRES rainfall-runoff model

Abstract The IHACRES rainfall-runoff model uses a non-linear loss module to calculate the effective rainfall and a linear routing module to convert effective rainfall into streamflow. This paper describes a new version of the non-linear module, developed to aid in estimating flows in ungauged basins and for applications where timeseries estimates of actual evapotranspiration are required. The new module has only 3 parameters and has significantly less correlation between the parameters.

An open software environment for hydrological model assessment and development

The hydromad (Hydrological Model Assessment and Development) package provides a set of functions which work together to construct, manipulate, analyse and compare hydrological models. The class of hydrological models considered are dynamic, spatially-aggregated conceptual or statistical models. The package functions are designed to fit seamlessly into the R system, and builds on its powerful data manipulation and analysis capabilities. The framework used in the package encourages a separation of model components based on Unit Hydrograph theory; many published models are consistent with this and implementations of several are included. For comparative assessment, model performance can be analysed over time and with respect to covariates to reveal systematic biases. Support has been built in for event-based analysis of data and assessment of model performance. Fit statistics can be defined by choices of (1) temporal scale and aggregation function; (2) weighting and transformation; and (3) reference model. One can define new Soil Moisture Accounting models, routing models, calibration methods, objective functions, and evaluation statistics, while retaining as much of the default framework as is useful. And as the package code is available under a free software licence, one always has the freedom to adapt it as required. Use of the software is demonstrated in a case study of the Queanbeyan River catchment in South-East Australia.

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.

Development of a process-based model to predict pathogen budgets for the Sydney drinking water catchment

Over 1.1 billion people in the world lack access to improved drinking water. Diarrheal and other waterborne diseases cause an estimated 2.2 million deaths per year. The Safe Water System (SWS) is a proven household water treatment intervention that reduces diarrheal disease incidence in users in developing countries. Because the SWS recommends the addition of sodium hypochlorite to unfiltered water sources, concerns have been raised about the potential long-term health effects of disinfection by-products to SWS users. This study investigated the production of trihalomethanes (THMs) in water treated with sodium hypochlorite from six sources used for drinking water in western Kenya. The turbidity values of these sources ranged from 4.23 NTU to 305 NTU. THM concentrations were analysed at 1, 8, and 24 hours after addition of sodium hypochlorite. No sample exceeded the World Health Organization (WHO) guideline values for any of the four THMs: chloroform, bromodichloromethane, dibromochloromethane, or bromoform. In addition, no sample exceeded the WHO additive total THM guideline value. These results clearly show that point-of-use chlorination of a variety of realistic source waters used for drinking did not lead to THM concentrations that pose a significant health risk to SWS users.

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.

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.

Flood inundation modelling

This paper reviews state-of-the-art empirical, hydrodynamic and simple conceptual models for determining flood inundation. It explores their advantages and limitations, highlights the most recent advances and discusses future directions. It addresses how uncertainty is analysed in this field with the various approaches and identifies opportunities for handling it better. The aim is to inform scientists new to the field, and help emergency response agencies, water resources managers, insurance companies and other decision makers keep up-to-date with the latest developments. Guidance is provided for selecting the most suitable method/model for solving practical flood related problems, taking into account the specific outputs required for the modelling purpose, the data available and computational demands. Multi-model, multi-discipline approaches are recommended in order to further advance this research field. This paper reviews state-of-the-art flood inundation models.It explores their advantages and limitations.It highlights the most recent advances and discusses future directions.It addresses how uncertainty is analysed and identifies opportunities for handling it better.

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.

Evaluation of streamflow predictions by the IHACRES rainfall-runoff model in two South African catchments

In many South African catchments, water is an increasingly limited and highly fluctuating resource. Accurate prediction of low flows is especially vital if water resource managers are to successfully balance the growing needs of agriculture, industry and rural and urban populations, while maintaining the ecological health of aquatic and riparian ecosystems. Existing hydrological models in use in South Africa suffer from a number of disadvantages. They are complex, over-parameterised, data demanding and expensive to use. IHACRES, a lumped conceptual model requiring minimal input data, is less limited by these problems, and has the potential to advance our understanding of streamflow patterns and predict how these may be altered by land-use change. The purpose of this paper is to evaluate IHACRES performance for two South African catchments: Lambrechtsbos A (a 31 ha research catchment) and Groot-Nylrivier (74 km2). IHACRES predicted streamflow at Lambrechtsbos A with useful accuracy (pre-afforestation period, R2>0.81; bias <26 mm/yr; post-afforestation period, R2=0.81, bias=8.4 mm/yr). With prior knowledge of changes in annual evapotranspiration, predictions of land-use impacts on flow regime may be satisfactorily predicted. Simulations of flows in the Groot-Nylrivier catchment were found to be of useful accuracy for relatively short periods of 2–3 yr, but performance over longer time periods was reduced by poor predictions in certain years. We ascribe this primarily to poor catchment-average rainfall estimation following certain storms in some years. Our simulations highlighted a tendency for IHACRES to underestimate quick flow events, especially at times when the greater part of a catchment is dry. Further model development is required to overcome these problems. IHACRES shows great potential in linking proposed land-use change to altered flow regimes, and efficiently describing the flow characteristics within catchments. However, poor estimation of average rainfall in larger catchments is a limitation that needs to be overcome before long-term flow regimes of non-research catchments may be predicted with confidence.