A.J. Jakeman

Australian National University | ANU · Fenner School of Environment & Society

Evolutionary mechanisms enabled humans to profoundly transform Earth systems. Because the resulting Anthropocene systems are highly interdependent and dynamically evolving, often with accelerating rates of cultural and technological evolution, the ensuing family of societal challenges must be framed and addressed in a holistic fashion. An agile, ev...

Artificial intelligence is rapidly being integrated into Earth science, but how Earth science may benefit artificial intelligence has been overlooked. We call for mutual balancing between the two disciplines and improving cross-disciplinary collaboration. The increasing adoption of artificial intelligence (AI) in various fields of Earth science (ES...

Choices made in modeling matter and demand more explication since they determine how much we can trust modeling insights and predictions within their social, political and ethical contexts. Good Modeling Practice (GMP) is a key research area for strengthening and maturing the modeling field and community, through identifying, formulating and sharin...

In global sensitivity analysis (GSA) of a model, a proper convergence analysis of metrics is essential for ensuring a level of confidence or trustworthiness in sensitivity results obtained, yet is somewhat deficient in practice. The level of confidence in sensitivity measures, particularly in relation to their influence and support for decisions fr...

The notion of convergent and transdisciplinary integration, which is about braiding together different knowledge systems, is becoming the mantra of numerous initiatives aimed at tackling pressing water challenges. Yet, the transition from rhetoric to actual implementation is impeded by incongruence in semantics, methodologies, and discourse among d...

A strong and close connection between science and practice in socio-environmental systems (SES) research and modelling is warranted to face complex and interdisciplinary socio-environmental challenges around issues such as sustainability and climate change. However, significant gaps and inadequate knowledge flow between the scientific and practical...

As hydrological systems are pushed outside the envelope of historical experience, the ability of current hydrological models to serve as a basis for credible prediction and decision making is increasingly challenged. Conceptual models are the most common type of surface water hydrological model used for decision support due to reasonable performanc...

Recent years have witnessed a significant increase in the availability and number of geographic simulation models across various domains, leading to challenges in evaluating their relative value. Traditional model evaluations typically compare simulation results with measured data or other models. This report presents the application of the newly “...

Vegetation in semi-arid wetlands often serve as a critical habitat and refuge for a wide range of species. In many wetlands, on-ground monitoring of vegetation is either not comprehensive or unavailable, which impedes our understanding of the system. However, basic data on climate and hydrological variables, as well as remote sensing data, can ofte...

Factor Fixing (FF) is a common method for reducing the number of model parameters to lower computational cost. FF typically starts with distinguishing the insensitive parameters from the sensitive and pursues uncertainty quantification (UQ) on the resulting reduced‐order model, fixing each insensitive parameter at a fixed value. There is a need, ho...

Earth system modelling (ESM) is essential for understanding past, present and future Earth processes. Deep learning (DL), with the data-driven strength of neural networks, has promise for improving ESM by exploiting information from Big Data. Yet existing hybrid ESMs largely have deep neural networks incorporated only during the initial stage of mo...

Models play a pivotal role in advancing our understanding of Earth's physical nature and environmental systems, aiding in their efficient planning and management. The accuracy and reliability of these models heavily rely on data, which are generally partitioned into subsets for model development and evaluation. Surprisingly, how this partitioning i...

The Millennium drought which occurred around 1997–2009 throughout southeastern Australia has led to recorded low groundwater levels causing considerable economical losses. Improving the drought resilience of at-risk groundwater systems has been recognized as a priority for sustainable water resources management in the region. This study introduces...

Models of socio-environmental or social-ecological systems (SES) commonly address problems requiring interdisciplinary scientific expertise and input from a heterogeneous group of stakeholders. In SES modelling multiple interactions occur on different scales among various phenomena. These scale phenomena include the technical, such as system variab...

Analyzing land use/ land cover change is a fundamental tool for evaluating the environmental consequences of human activities. This research was conducted to detect and predict the likely land use changes in the Gorgan‐rud River Basin, Iran, and to estimate the past and future population growth as a driving force in land use change and degradation....

Study region Australia Study focus Our incomplete knowledge of groundwater systems and processes imposes barriers in attempting to manage groundwater sustainably. Challenges also arise through complex institutional arrangements and decision-making processes, and the difficulty in involving stakeholders. In some areas, these difficulties have led t...

Geographic simulation models can be used to explore and better understand the geographical environment. Recent advances in geographic and socio-environmental research have led to a dramatic increase in the number of models used for this purpose. Some model repositories provide opportunities for users to explore and apply models, but few provide a g...

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...

Small hydropower (SHP) possesses significant economic, technical, and environmental advantages, and accounts for a large proportion of hydropower development in China. However, the concentrated, cascaded, and diversion-type development of SHP has resulted in long-distance dewatering of river sections, and inter-basin water transfers have led to sev...

Abstract submission is now open for the 10th International Conference on Sensitivity Analysis of Model Output (SAMO). The conference will be held at Florida State University, Tallahassee, Florida. The dates of the conference are March 14 -16, 2022, at the Florida State Conference Center. See: https://samo2022.math.fsu.edu/

Integrated Assessment Models (IAMs) were initially developed to inform decision processes relating to climate change and then extended to other natural resource management decisions, including issues around integrated water resources management. Despite their intention to support long-term planning decisions, model uptake has generally been limited...

Active Subspaces is a recently developed concept that identifies essential directions of the response surface of a model, providing sensitivity metrics known as activity scores. We compare activity scoring with the Sobol' and the Morris global methods using a series of well-known benchmark test functions with exactly computable sensitivities. In th...

A computationally efficient and robust sampling scheme can support a sensitivity analysis of models to discover their behaviour through Quasi Monte Carlo approximation. This is especially useful for complex models, as often occur in environmental domains when model runtime can be prohibitive. The Sobol' sequence is one of the most used quasi-random...

Although it is widely acknowledged as a fundamental principle that models be fit-for-purpose, there remains lack of clarity on what this notion actually means and therefore how it is achieved. We contend that fitness-for-purpose must go beyond the functional use of the model to include its management, problem and project contexts. Accordingly, we p...

Despite widespread use of factor fixing in environmental modeling, its effect on model predictions has received little attention and is instead commonly presumed to be negligible. We propose a proof-of-concept adaptive method for systematically investigating the impact of factor fixing. The method uses Global Sensitivity Analysis methods to identif...

Highlights • Advances of science and policy has deep but informal roots in sensitivity analysis. • Modern sensitivity analysis is now evolving into a formal and independent discipline. • New areas such data science and machine learning benefit from sensitivity analysis. • Challenges, methodological progress, and outlook are outlined in this specia...

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...

The Millennium drought occurred around 1997–2009 throughout southeastern Australia has led to recorded low groundwater levels causing considerable economical losses. Improving the drought resilience of at-risk groundwater systems has been recognized as a priority for sustainable water resources management in the region. This study introduces the st...

This study aims to present a process for hydrological model exploration for selecting an appropriate model compatible with the modeling objectives. The process consists of three stages: (1) initial choice based on the modeling objectives; (2) model selection based on intercomparison among underlying conceptualizations of the models; and (3) final m...

The pathways taken throughout any model-based process are undoubtedly influenced by the modeling team involved and the decision choices they make. For interconnected socioenvironmental systems (SES), such teams are increasingly interdisciplinary to enable a more expansive and holistic treatment that captures the purpose, the relevant disciplines an...

Sustainable groundwater management is becoming increasingly important due to intensifying water deficits around the world, which highlights the necessities and challenges to explore the dynamics of groundwater at the catchment-scale. In this paper, a tracer-aided approach has been developed and applied to quantify the relationships between groundwa...

This paper introduces an alternative way of randomizing Sobol0 sequences, called the Column Shift method, for reconstructing replicates to improve estimation of the uncertainty in sensitivity indices. The Column Shift method provides reliable results when applied to variance-based sensitivity analysis of the V function, with much higher accuracy th...

Recent literature on model evaluation has highlighted the need, particularly in an interdisciplinary problem and team setting, to go beyond the evaluation of results and outputs of a problem-solving pathway (process), and monitor and evaluate the pathway itself to improve ongoing activities undertaken by the research team that best achieve the desi...

Diagnostic testing is an oft-recommended use of sensitivity analysis to assess correctness or plausibility of model behavior. In this paper we demonstrate the use of sensitivity analysis as a complementary first-pass software test for the validation of model behavior. Typical testing processes rely on comparing model outputs to results known to be...

System-of-systems approaches for integrated assessments have become prevalent in recent years. Such approaches integrate a variety of models from different disciplines and modeling paradigms to represent a socioenvironmental (or social-ecological) system aiming to holistically inform policy and decision-making processes. Central to the system-of-sy...

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...

In this synthesis, we assess present research and anticipate future development needs in modeling water quality in watersheds. We first discuss areas of potential improvement in the representation of freshwater systems pertaining to water quality, including representation of environmental interfaces, in-stream water quality and process interactions...

Sensitivity analysis (SA) has been used to evaluate the behavior and quality of environmental models by estimating the contributions of potential uncertainty sources to quantities of interest (QoI) in the model output. Although there is an increasing literature on applying SA in environmental modeling, a pragmatic and specific framework for spatial...

Integrated geographic modelling and simulation is a computational means to improve understanding of the environment. With the development of Service Oriented Architecture (SOA) and web technologies, it is possible to conduct open, extensible integrated geographic modelling across a network in which resources can be accessed and integrated, and furt...

Forest management activities have the potential to significantly modify large wood loads in riparian areas, and thus the availability of material for recruitment into the stream channel, hence it is important that forest management practices take account of the role wood supplied from riparian areas play in the development of channel structure and...

Groundwater is experiencing a higher risk of aquifer depletion due to longer drought duration and increasing water demand induced by climate change. The climate impacts on groundwater can be propagated to changes in groundwater discharge to rivers, which will deeply alter the connection between groundwater and surface water and reshape the fundamen...

Exploratory analysis, while useful in assessing the implications of model assumptions under large uncertainty, is considered at best a semi-structured activity. There is no algorithmic way for performing exploratory analysis and the existing canonical techniques have their own limitations. To overcome this, we advocate a bricolage-style exploratory...

Although the Dublin principles of Integrated Water Resource Management (IWRM) are well-established, the third principle on gender is commonly missing in practice. We use gender mainstreaming to identify examples where gender-specific perspectives might influence water resource management modelling choices. We show how gender considerations could le...

This paper presents a component-based integrated environmental model developed through participatory processes to explore sustainable water management options. Possible futures with improved farm profitability and ecological outcomes relative to modelled baselines were identified through exploratory modelling. The integrated model and the results p...

In a native forest on the south coast of New South Wales, Australia, five channels were instrumented with rain gauges and weirs to monitor rainfall, streamflow, turbidity, and suspended sediment yield over a seven and a half year period. After a five year calibration period, four of the catchments were harvested, while one remained as a control. In...

Diffuse recharge is vital in determining the availability of renewable groundwater. Estimating diffuse recharge, however, is a great challenge plagued with uncertainty due to limitations in direct observation and process understanding. Hydrological model is functional for diffuse recharge estimation at catchment scale. It can be used independently...

The pathway of a modelling project is commonly described as an adaptively adjusted chain of steps at which various decisions are made. Communication and documentation about these decisions are crucial to enabling reflection and adapting the pathway to changing circumstances, such that well-informed planning is required. Project decision making, how...

Modeling is essential to characterize and explore complex societal and environmental issues in systematic and collaborative ways. Socio-environmental systems (SES) modeling integrates knowledge and perspectives into conceptual and computational tools that explicitly recognize how human decisions affect the environment. Depending on the modeling pur...

Uncertainty communication is too frequently approached as a linear task from "experts" to their audience, though admittedly sometimes with feedback and dialogue. From a system-wide perspective, uncertainty is managed and communicated in many ways by many people and groups both within organisations and in society generally. In the water sector, the...

Presentation given at MODSIM 2019, (Canberra, Dec 2 - 6) on the value of conceptual testing processes to provide quick and early indication of possible issues during model development.

The Beijing-Tianjin-Hebei (Jingjinji) region is the most densely populated region in China and suffers from severe water resource shortage, with considerable water-related issues emerging under a changing context such as construction of water diversion projects (WDP), regional synergistic development, and climate change. To this end, this paper dev...

Uncertainty and sensitivity analysis (UA/SA) aid in assessing whether model complexity is warranted and under what conditions. To support these analyses a variety of software tools have been developed to provide UA/SA methods and approaches in a more accessible manner. This paper applies a hybrid bibliometric approach using 11 625 publications sour...

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...

Identifiability is a fundamental concept in parameter estimation, and therefore key to the large majority of environmental modeling applications. Parameter identifiability analysis assesses whether it is theoretically possible to estimate unique parameter values from data, given the quantities measured, conditions present in the forcing data, model...

Similar to any modelling technique, system dynamics (SD) modelling should start with the essential step of scop-ing and identifying the problem of interest before further analysis and modelling. In practice, this first step is a challenging task, especially when wicked issues such as water management are being addressed. There is still a vital need...

Environmental modelling is transitioning from the traditional paradigm that focuses on the model and its quantitative performance to a more holistic paradigm that recognises successful model-based outcomes are closely tied to undertaking modelling as a social process, not just as a technical procedure. This paper redefines evaluation as a multi-dim...

خروجی مدل‌های گردش عمومی جو به دلیل تفکیک مکانی درشت آنها، در مقیاس منطقه‌ای و محلی قابل کاربرد نیستند و لازم است در سطح کوچک‌تر ریزمقیاس گردند. در این پژوهش عملکرد مدل SDSM برای ریزمقیاس‌نمایی متغیرهای بارش، دمای حداقل، و دمای حداکثر در حوضه رودخانه گرگانرود مورد بررسی قرار گرفت و به‌منظور انتخاب متغیرهای پیش‌بینی‌کننده، روش غربال‌گری کمّی به‌کار...

The effectiveness of Integrated Water Resource Management (IWRM) modeling hinges on the quality of practices employed through the process, starting from early problem definition all the way through to using the model in a way that serves its intended purpose. The adoption and implementation of effective modeling practices need to be guided by a pra...

The simple conceptual flood inundation model TVD (Teng-Vaze-Dutta) is more computationally efficient and cost-effective than traditional hydrodynamic models. It is especially useful for applications that do not require velocity output and have low demands on flood dynamic representation. In this study, we have addressed the main inherent limitation...

Catchment-scale water quality models have become important tools for water quality management, planning and reporting worldwide. In this review, we synthesise recent developments in water quality modelling, focusing on catchment-scale models of freshwater, non-urban systems and their ability to support catchment management. We explore 10 key attrib...

Hydrologic models are essential tools for understanding hydrologic processes, such as precipitation, which is a fundamental component of the water cycle. For an improved understanding and the evaluation of different precipitation datasets, especially their applicability for hydrologic modelling, three kinds of precipitation products, CMADS, TMPA-3B...

Many of the world's greatest challenges are complex socio-environmental problems, often framed in terms of integrated assessment, resilience or sustainability. To resolve any of these challenges, it is essential to elicit and integrate knowledge across a range of systems, informing the design of solutions that take into account the complex and unce...

China is anticipated to face reductions in crop yield due to climate change. Combining a process-based agricultural model (APSIM) with a simplified empirical model, we investigate the association between wheat productivity and climate variables in the North China Plain (NCP) over the period 1960–2010. The results show that the spatial distribution...

General software development best practices that are compatible with, and beneficial to, the model development process. Presented at iEMSs 2018 (Fort Collins, Colorado)

Management of water resources requires understanding of the hydrology and hydrogeology, as well as the policy and human drivers and their impacts. This understanding requires relevant inputs from a wide range of disciplines, which will vary depending on the specific case study. One approach to gain understanding of the impact of climate and society...

Integrated models are often made up of smaller component models, each representing a particular domain that are coupled together. Such models are software for a scientific purpose, and so similarities between model and software development exist. These models tend to be developed by researchers who take on a dual-role of scientist and software deve...

Best practice modelling reduces model uncertainties and quantitatively and qualitatively documents any uncertainties and assumptions for user transparency. Conversely, poor modelling practices contribute to uncertainties and increase user distrust in the value of modelling. This discussion paper synthesises existing knowledge and experience on good...