Holger Robert Maier

University of Adelaide · School of Civil, Environmental & Mining Engineering

Models and data play an important role in informing decision-making in environmental systems, providing different and complementary information. Multiple frameworks have been developed to address model limitations and there is a large body of research focused on improving the quality of data. However, when models and data disagree the focus is usua...

Achieving a thorough understanding of the determinants of household water consumption is crucial to support demand management strategies. Yet, existing research on household water consumption determinants is often limited to specific case studies, with findings that are difficult to generalize and not conclusive. Here, we first contribute an update...

Pluvial flooding causes significant damage in urban areas worldwide. The most common approaches to mitigating these impacts at regional scales include structural measures such as dams, levees and floodways. More recently, the use of nature-based solutions (NBS) is receiving increasing attention, as such approaches are more adaptive than structural...

Multi‐objective evolutionary algorithms (MOEAs) have been applied to water distribution system (WDS) optimization problems for over two decades. The selection strategy is a key component of an MOEA that determines the composition of a population, and thereby the evolutionary search process, which imitates natural selection by granting fitter indivi...

Stormwater systems will likely require major upgrades due to increases in peak flows caused by the combined effects of urbanization, densification (urban infill) and climate change. Recently, the real-time control (RTC) of storages has been considered as a means to reduce peak flows and potentially avoid major infrastructure upgrades. This paper in...

Data-driven hydrological models are widely used for many practical purposes. However, the reliability of such models depend heavily on the strategy used to partition available observations into model calibration and evaluation subsets. Unfortunately, available data splitting methods are poor at ensuring consistency of statistical properties between...

Wildfires elicit a diversity of hydrological changes, impacting processes that drive both water quantity and quality. As wildfires increase in frequency and severity, there is a need to assess the implications for the hydrological response. Wildfire‐related hydrological changes operate at three distinct timescales: the immediate fire aftermath, the...

Because physics‐based models of dynamical systems are constrained to obey conservation laws, they must typically be fed long sequences of temporally consecutive (TC) data during model calibration and evaluation. When memory time scales are long (as in many physical systems), this requirement makes it difficult to ensure distributional similarity wh...

The rising frequency of heat-related hazards as a result of climate change will increasingly affect heat-sensitive infrastructure assets. Recent studies quantify the heat-related risk to infrastructure, with some exploration of individual mitigation strategies, however missing in literature is an infrastructure sector-transferable and comprehensive...

Achieving a thorough understanding of the determinants of household water consumption is crucial to support demand management strategies. Yet, existing research on household water consumption determinants is often limited to specific case studies, with findings that are difficult to generalize and not conclusive. Here, we contribute a framework for...

The impact of urban flooding is increasing due to the effects of increasing urbanisation and climate change. The use of storages is a relatively well-established approach to reduce peak flows and therefore reduce the need for costly upgrades to stormwater conveyance infrastructure. Recently, real-time control (RTC) has been considered as a means of...

Urban sewer networks (SNs) are increasingly facing water quality issues as a result of many challenges, such as population growth, urbanization and climate change. A promising way to addressing these issues is by developing and using water quality models. Many of these models have been developed in recent years to facilitate the management of SNs....

To aid decision making about environmental systems under deep uncertainty, robustness metrics are commonly used to represent system performance over a number of scenarios. However, there are many robustness metrics and many ways of generating scenarios, making it difficult to know which to choose in order to quantify system robustness and to make r...

Scenario-neutral climate impact assessments are being used increasingly to assess water resource system responses to possible climate changes. The purpose of such assessments is to identify system sensitivity to a range of plausible climate conditions, often including an evaluation of the joint effect of multiple climate stressors. Given the large...

Effective implementation of a scenario-neutral climate impact assessment relies on the integration of many modelling components at multiple stages: from the generation of appropriate climate boundary conditions that can be used to rigorously ‘stress-test’ a system, to the simulation, visualisation and interpretation of resulting system performance....

Sensitivity analysis (SA) is en route to becoming an integral part of mathematical modeling. The tremendous potential benefits of SA are, however, yet to be fully realized, both for advancing mechanistic and data-driven modeling of human and natural systems, and in support of decision making. In this perspective paper, a multidisciplinary group of...

Multiple plausible future scenarios are being used increasingly in preference to a single deterministic or probabilistic prediction of the future in the long‐term planning of water resources systems. These scenarios enable the determination of the robustness of a system—the consideration of performance across a range of plausible futures—and allow...

This paper presents a hybrid automatic calibration method for transition potential based Cellular Automata land-use models by integrating two calibration methods, process-specific and optimisation-based, into a single hybrid approach, combining the advantages of these two methods. The hybrid approach features the detailed exploration of a large pop...

This paper provides a review of the changing nature of the water–energy nexus in urban water supply systems (UWSSs) due to the primary long-term drivers of climate change, population growth and technological development from the ‘energy for water’ perspective. We identify both the physical changes in UWSSs, as well as the changes in the attributes...

Multiobjective evolutionary algorithms (MOEAs) have been used extensively to solve water resources problems. Their success is dependent on how well the operators that control an algorithm's search behavior are able to identify near‐optimal solutions. As commonly used MOEAs contain a relatively small number of operators (generally between 2 and 7),...

Conceptual rainfall‐runoff (CRR) models are widely used for runoff simulation and for prediction under a changing climate. The models are often calibrated with only a portion of all available data at a location and then evaluated independently with another part of the data for reliability assessment. Previous studies report a persistent decrease in...

Deep uncertainty in future climate, socio-economic and technological conditions poses a great challenge to medium-long term decision making. Recently, several approaches have been proposed to identify solutions that are robust with respect to a large ensemble of deeply uncertain future scenarios. In this paper, we introduce ROSS (Robust Optimal Sce...

Disaster risk is a complex, uncertain and evolving threat to society which changes based on broad drivers of hazard, exposure and vulnerability such as population, economic and climatic change, along with new technologies and social preferences. It also evolves as a function of decisions of public policy and public/private investment which alters f...

Urban water systems are being stressed due to the effects of urbanization and climate change. Although household rainwater tanks are primarily used for water supply purposes, they also have the potential to provide flood benefits. However, this potential is limited for critical storms, as they become ineffective once their capacity is exceeded. Thi...

Knowledge on the determinants and patterns of water demand for different consumers supports the design of customized demand management strategies. Smart meters coupled with big data analytics tools create a unique opportunity to support such strategies. Yet, at present, the information content of smart meter data is not fully mined and usually need...

Existing water resources are under stress due to increasing demands associated with population and economic growth as well as the effects of climate change which can reduce available supply and increase demand. Alternative sources such as stormwater harvesting and treated wastewater are being considered in many cities to supplement existing water s...

Scenario-neutral approaches are used increasingly as a means of stress-testing climate-sensitive systems to a range of plausible future climate conditions. To ensure that these stress-tests are able to explore system vulnerability, it is necessary to generate hydrometeorological time series that represent all aspects of plausible future change (e.g...

Disaster risk is a combination of natural hazards, along with society's exposure and vulnerability to them. Therefore, to ensure effective, long-term disaster risk reduction we must consider the dynamics of each of these components and how they change over extended periods due to population, economic and climatic drivers, as well as policy and indi...

Small Mediterranean islands are remote, off-grid communities characterized by carbon intensive electricity systems coupled with high energy consuming desalination technologies to produce potable water. The aim of this study is to propose a novel dynamic, multi-objective optimization approach for improving the sustainability of small islands through...

https://figshare.com/articles/neural-network-add-in-1-5-4-setup_exe/7460756 And a good news that the new version of this add-in is coming in winter.

Environmental models are used extensively to evaluate the effectiveness of a range of design, planning, operational, management and policy options. However, the number of options that can be evaluated manually is generally limited, making it difficult to identify the most suitable options to consider in decision-making processes. By linking environ...

Data are essential in all areas of geophysics. They are used to better understand and manage systems, either directly or via models. Given the complexity and spatiotemporal variability of geophysical systems (e.g., precipitation), a lack of sufficient data is a perennial problem, which is exacerbated by various drivers, such as climate change and u...

Globally, urban infill is stressing existing stormwater systems, necessitating costly infrastructure upgrades. Although household rainwater tanks provide significant distributed storage, they have virtually no impact on reducing peak flows for rare, long duration events. This study introduces an innovative “smart systems” approach to operating tank...

Pipe breaks have significant impacts on the hydraulic and water quality performance of water distribution systems (WDSs). Therefore, it is important to evaluate these impacts for developing effective strategies to ultimately minimize the consequences of these events. However, there has been surprisingly limited research focusing on impact evaluatio...

Although formal simulation-optimization approaches have been shown to be able to identify near-optimal outcomes for a range of stormwater management problems, stakeholder acceptance of these solutions can be problematic, especially if there is a lack of familiarity with the optimization processes and simulation model used to arrive at these solutio...

Leakage or pipe burst detection, often carried out by using the pressure sensor systems (PSSs) within a water distribution network (WDN), is critical to enable such networks to operate in a safe manner. The majority of previous studies have focused on either the advancement of detection equipment or the development of detection algorithms (leakage...

Land-use change models generally include neighbourhood rules to capture the spatial dynamics between different land-uses that drive land-use changes, introducing many parameters that require calibration. We present a process-specific semi-automatic method for calibrating neighbourhood rules that utilises discursive knowledge and empirical analysis...

Salinity modelling in river systems is complicated by a number of processes, including in-stream salt transport and various mechanisms of saline accession that vary dynamically as a function of water level and flow, often at different temporal scales. Traditionally, salinity models in rivers have either been process- or data-driven. The primary pro...

Exploratory scenarios (i.e. scenarios that question what could happen) have been widely applied to a vast array of complex and uncertain socio-environmental system problems. Despite this fact, they have also been criticised by policy makers for not being relevant to policy processes and assessment. This paper proposes a generic approach to enhance...

Modelling of land-use change plays an important role in many areas of environmental planning. However, land-use change models remain challenging to calibrate, as they contain many sensitive parameters, making the calibration process time-consuming. We present a multi-objective optimisation framework for automatic calibration of Cellular Automata la...

Monthly to seasonal streamflow forecasts provide useful information for a range of water resource management and planning applications. This work focuses on improving such forecasts by considering the following two aspects: (1) state updating to force the models to match observations from the start of the forecast period, and (2) selection of a sho...

Hydrological models are used for a wide variety of engineering purposes, including streamflow forecasting and flood-risk estimation. To develop such models, it is common to allocate the available data to calibration and evaluation data subsets. Surprisingly, the issue of how this allocation can affect model evaluation performance has been largely i...

Robustness is being used increasingly for decision analysis in relation to deep uncertainty and many metrics have been proposed for its quantification. Recent studies have shown that the application of different robustness metrics can result in different rankings of decision alternatives, but there has been little discussion of what potential cause...

In this paper, an optimization framework for complex environmental management problems involving multiple stakeholders is developed and illustrated. In the framework, problems are represented as a series of smaller, interconnected optimization problems, reflecting individual stakeholders’ interests. The framework uses interactive visual analytics t...

A generic simulation-optimization framework for optimal irrigation and fertilizer scheduling is developed, where the problem is represented in the form of decision-tree graphs, ant colony optimization (ACO) is used as the optimization engine and a process-based crop growth model is applied to evaluate the objective function. Dynamic decision variab...

Natural hazard risk is largely projected to increase in the future, placing growing responsibility on decision makers to proactively reduce risk. Consequently, decision support systems (DSSs) for natural hazard risk reduction (NHRR) are becoming increasingly important. In order to provide directions for future research in this growing area, a compr...

Salinity modelling in river systems is complicated by a number of processes, including in-stream salt transport and various mechanisms of saline accession that vary dynamically as a function of water level and flow, often at different temporal scales. Traditionally, salinity models in rivers have either been process- or data-driven. The primary pro...

A general framework for the identification of optimal strategies for mitigating the impact of regional shocks to the global food production network is introduced. The framework utilises multi-objective ant colony optimisation (ACO) as the optimisation engine and is applicable to production-, demand-, storage- and distribution-focussed mitigation op...

Integrated urban water management (IUWM) considering alternative water supply options is attracting increasing attention from water resources managers due to its efficiency and flexibility in addressing water scarcity problems. Adelaide, the capital of South Australia, is an example of a city where water supply security has come under increasing pr...

Scenario-neutral approaches are being used increasingly for assessing the potential impact of climate change on water resource systems, as these approaches allow the performance of these systems to be evaluated independently of climate change projections. However, practical implementations of these approaches are still scarce, with a key limitation...

Sub-seasonal streamflow forecasts provide useful information for a range of water resource management and planning applications. This work has focused on improving forecasts for one such application: the management of water available in an open channel drainage network to maximise environmental and social outcomes in a region in southern Australia....

Water resources planning and design problems, such as the sequencing of water supply infrastructure, are often complicated by deep uncertainty, including changes in population dynamics and the impact of climate change. To handle such uncertainties, robustness can be used to assess system performance, but its calculation typically involves many scen...

Validation is a critical component of any modelling process. In artificial neural network (ANN) modelling, validation generally consists of the assessment of model predictive performance on an independent validation set (predictive validity). However, this ignores other aspects of model validation considered to be good practice in other areas of en...

Assessing the factors that have an impact on potential evapotranspiration (PET) sensitivity to changes in different climate variables is critical to understanding the possible implications of climatic changes on the catchment water balance. Using a global sensitivity analysis, this study assessed the implications of baseline climate conditions on t...

Evolutionary algorithms and other metaheuristics have been employed widely to solve optimization problems in many different fields over the past few decades. Their performance in finding optimal solutions often depends heavily on the parameterization of the algorithm’s search operators, which affect an algorithm’s balance between search diversifica...