Matthew R. Hipsey

Panta Rhei-Everything Flows: Change in hydrology and society-The IAHS Scientific Decade 2013-2022

Abstract The new Scientific Decade 2013–2022 of IAHS, entitled “Panta Rhei—Everything Flows”, is dedicated to research activities on change in hydrology and society. The purpose of Panta Rhei is to reach an improved interpretation of the processes governing the water cycle by focusing on their changing dynamics in connection with rapidly changing human systems. The practical aim is to improve our capability to make predictions of water resources dynamics to support sustainable societal development in a changing environment. The concept implies a focus on hydrological systems as a changing interface between environment and society, whose dynamics are essential to determine water security, human safety and development, and to set priorities for environmental management. The Scientific Decade 2013–2022 will devise innovative theoretical blueprints for the representation of processes including change and will focus on advanced monitoring and data analysis techniques. Interdisciplinarity will be sought by increased efforts to connect with the socio-economic sciences and geosciences in general. This paper presents a summary of the Science Plan of Panta Rhei, its targets, research questions and expected outcomes. Editor Z.W. Kundzewicz Citation Montanari, A., Young, G., Savenije, H.H.G., Hughes, D., Wagener, T., Ren, L.L., Koutsoyiannis, D., Cudennec, C., Toth, E., Grimaldi, S., Blöschl, G., Sivapalan, M., Beven, K., Gupta, H., Hipsey, M., Schaefli, B., Arheimer, B., Boegh, E., Schymanski, S.J., Di Baldassarre, G., Yu, B., Hubert, P., Huang, Y., Schumann, A., Post, D., Srinivasan, V., Harman, C., Thompson, S., Rogger, M., Viglione, A., McMillan, H., Characklis, G., Pang, Z., and Belyaev, V., 2013. “Panta Rhei—Everything Flows”: Change in hydrology and society—The IAHS Scientific Decade 2013–2022. Hydrological Sciences Journal. 58 (6) 1256–1275.

Challenges and Opportunities for Integrating Lake Ecosystem Modelling Approaches

A large number and wide variety of lake ecosystem models have been developed and published during the past four decades. We identify two challenges for making further progress in this field. One such challenge is to avoid developing more models largely following the concept of others (‘reinventing the wheel’). The other challenge is to avoid focusing on only one type of model, while ignoring new and diverse approaches that have become available (‘having tunnel vision’). In this paper, we aim at improving the awareness of existing models and knowledge of concurrent approaches in lake ecosystem modelling, without covering all possible model tools and avenues. First, we present a broad variety of modelling approaches. To illustrate these approaches, we give brief descriptions of rather arbitrarily selected sets of specific models. We deal with static models (steady state and regression models), complex dynamic models (CAEDYM, CE-QUAL-W2, Delft 3D-ECO, LakeMab, LakeWeb, MyLake, PCLake, PROTECH, SALMO), structurally dynamic models and minimal dynamic models. We also discuss a group of approaches that could all be classified as individual based: super-individual models (Piscator, Charisma), physiologically structured models, stage-structured models and trait-based models. We briefly mention genetic algorithms, neural networks, Kalman filters and fuzzy logic. Thereafter, we zoom in, as an in-depth example, on the multi-decadal development and application of the lake ecosystem model PCLake and related models (PCLake Metamodel, Lake Shira Model, IPH-TRIM3D-PCLake). In the discussion, we argue that while the historical development of each approach and model is understandable given its ‘leading principle’, there are many opportunities for combining approaches. We take the point of view that a single ‘right’ approach does not exist and should not be strived for. Instead, multiple modelling approaches, applied concurrently to a given problem, can help develop an integrative view on the functioning of lake ecosystems. We end with a set of specific recommendations that may be of help in the further development of lake ecosystem models.

Sensitivity analysis for complex ecological models - A new approach

A strategy for global sensitivity analysis of a multi-parameter ecological model was developed and used for the hydrodynamic-ecological model (DYRESM-CAEDYM, DYnamic REservoir Simulation Model-Computational Aquatic Ecosystem Dynamics Model) applied to Lake Kinneret (Israel). Two different methods of sensitivity analysis, RPART (Recursive Partitioning And Regression Trees) and GLM (General Linear Model) were applied in order to screen a subset of significant parameters. All the parameters which were found significant by at least one of these methods were entered as input to a GBM (Generalized Boosted Modeling) analysis in order to provide a quantitative measure of the sensitivity of the model variables to these parameters. Although the GBM is a general and powerful machine learning algorithm, it has substantial computational costs in both storage requirements and CPU time. Employing the screening stage reduces this cost. The results of the analysis highlighted the role of particulate organic material in the lake ecosystem and its impact on the over all lake nutrient budget. The GBM analysis established, for example, that parameters such as particulate organic material diameter and density were particularly important to the model outcomes. The results were further explored by lumping together output variables that are associated with sub-components of the ecosystem. The variable lumping approach suggested that the phytoplankton group is most sensitive to parameters associated with the dominant phytoplankton group, dinoflagellates, and with nanoplankton (Chlorophyta), supporting the view of Lake Kinneret as a bottom-up system. The study demonstrates the effectiveness of such procedures for extracting useful information for model calibration and guiding further data collection.

A community-based framework for aquatic ecosystem models

Here, we communicate a point of departure in the development of aquatic ecosystem models, namely a new community-based framework, which supports an enhanced and transparent union between the collective expertise that exists in the communities of traditional ecologists and model developers. Through a literature survey, we document the growing importance of numerical aquatic ecosystem models while also noting the difficulties, up until now, of the aquatic scientific community to make significant advances in these models during the past two decades. Through a common forum for aquatic ecosystem modellers we aim to (i) advance collaboration within the aquatic ecosystem modelling community, (ii) enable increased use of models for research, policy and ecosystem-based management, (iii) facilitate a collective framework using common (standardised) code to ensure that model development is incremental, (iv) increase the transparency of model structure, assumptions and techniques, (v) achieve a greater understanding of aquatic ecosystem functioning, (vi) increase the reliability of predictions by aquatic ecosystem models, (vii) stimulate model inter-comparisons including differing model approaches, and (viii) avoid ‘re-inventing the wheel’, thus accelerating improvements to aquatic ecosystem models. We intend to achieve this as a community that fosters interactions amongst ecologists and model developers. Further, we outline scientific topics recently articulated by the scientific community, which lend themselves well to being addressed by integrative modelling approaches and serve to motivate the progress and implementation of an open source model framework.

The Impact of Extreme Low Flows on the Water Quality of the Lower Murray River and Lakes (South Australia)

The impact of extreme low flows on the water quality of the Lower Murray River and Lower Lakes (Alexandrina and Albert) in South Australia was assessed by comparing water quality from five sites during an extreme low flow period (March 2007–November 2009) and a preceding reference period (March 2003–November 2005). Significant increases in salinity, total nitrogen, total phosphorus, chlorophyll a and turbidity were observed in the Lower Lakes during the low flow period. Consequently, water quality guidelines for the protection of aquatic ecosystems were greatly exceeded. Principal Component Analysis, empirical and mass balance model calculations suggested these changes could be attributed primarily to the lack of flushing resulting in concentration of dissolved and suspended material in the lakes, and increased sediment resuspension as the lakes became shallower. The river sites also showed significant but more minor salinity increases during the extreme low flow period, but nutrient and turbidity concentrations decreased. The most plausible reasons for these changes were decreased catchment inputs and increased influence of saline groundwater inputs. The results highlight the vulnerability of arid and semi-arid lake systems to reduced flow conditions as a result of climatic changes and/or water management decisions.

A model of the socio‐hydrologic dynamics in a semiarid catchment: Isolating feedbacks in the coupled human‐hydrology system

The challenge of sustainable freshwater management requires identification and characterization of the underlying components and dynamic interactions within the coupled human-hydrology system. This paper builds a model that captures the dynamic water balance evolution and coupled human response within the Lake Toolibin catchment in West Australias wheatbelt region. Two subcatchments in different parts of the landscape were selected to examine the key emergent properties of the coupled socio-hydrology system over a 100 year period, by analyzing the two-way feedbacks of land use management (human system feedback) and land degradation (natural system feedback). Using a relatively simple parameterization of community sensitivity to land degradation within the model, we identified positive and negative feedbacks, the presence of threshold behavior, time scale differences between fast and slow moving variables, differences in time lags resulting from disparate resistance levels of the natural system, and the degree of adaptive learning inherent in the human system. Specifically, the valley floor subcatchment transitioned through four phases—expansion, contraction, recession, and recovery—demonstrating a threshold shift in the human feedback after 60 years, while the upslope subcatchment appears to still be in the contraction phase, with no sign of reaching a threshold shift in 100 years. These results demonstrate that the model is capable of isolating the two-way feedbacks of the coupled system and has implications for resilience theory, suggesting that greater resistance in the underlying natural system counteracts the onset of a negative feedback loop and instigation of adaptive behaviors in the human system.

Predicting the resilience and recovery of aquatic systems: A framework for model evolution within environmental observatories

Maintaining the health of aquatic systems is an essential component of sustainable catchment management, however, degradation of water quality and aquatic habitat continues to challenge scientists and policy-makers. To support management and restoration efforts aquatic system models are required that are able to capture the often complex trajectories that these systems display in response to multiple stressors. This paper explores the abilities and limitations of current model approaches in meeting this challenge, and outlines a strategy based on integration of flexible model libraries and data from observation networks, within a learning framework, as a means to improve the accuracy and scope of model predictions. The framework is comprised of a data assimilation component that utilizes diverse data streams from sensor networks, and a second component whereby model structural evolution can occur once the model is assessed against theoretically relevant metrics of system function. Given the scale and transdisciplinary nature of the prediction challenge, network science initiatives are identified as a means to develop and integrate diverse model libraries and workflows, and to obtain consensus on diagnostic approaches to model assessment that can guide model adaptation. We outline how such a framework can help us explore the theory of how aquatic systems respond to change by bridging bottom-up and top-down lines of enquiry, and, in doing so, also advance the role of prediction in aquatic ecosystem management.

Linking Eco-Energetics and Eco-Hydrology to Select Sites for the Assisted Colonization of Australia’s Rarest Reptile

Assisted colonization—the deliberate translocation of species from unsuitable to suitable regions—is a controversial management tool that aims to prevent the extinction of populations that are unable to migrate in response to climate change or to survive in situ. The identification of suitable translocation sites is therefore a pressing issue. Correlative species distribution models, which are based on occurrence data, are of limited use for site selection for species with historically restricted distributions. In contrast, mechanistic species distribution models hold considerable promise in selecting translocation sites. Here we integrate ecoenergetic and hydrological models to assess the longer-term suitability of the current habitat of one of the world’s rarest chelonians, the Critically Endangered Western Swamp Tortoise (Psuedemydura umbrina). Our coupled model allows us to understand the interaction between thermal and hydric constraints on the foraging window of tortoises, based on hydrological projections of its current habitat. The process can then be repeated across a range of future climates to identify regions that would fall within the tortoise’s thermodynamic niche. The predictions indicate that climate change will result in reduced hydroperiods for the tortoises. However, under some climate change scenarios, habitat suitability may remain stable or even improve due to increases in the heat budget. We discuss how our predictions can be integrated with energy budget models that can capture the consequences of these biophysical constraints on growth, reproduction and body condition.

Sediment diagenesis models

A range of sediment diagenesis modelling approaches have been developed over the last two decades, however, the diversity makes it difficult to identify the best approach for a particular aquatic system. This study summarised and categorised the variables, parameterisations and applications of 83 models published since 1996. The choice of variables and processes used was found to be largely arbitrary. Models have been applied to a range of environments, however, there was no corresponding difference in approach or complexity. The major challenges and opportunities for the development of the models include: aligning conceptual models of organic matter transformations with measurable parameters; gathering accurate data for model input and validation, including datasets that capture a range of time-scales; coupling sediment models with ecological and spatially-resolved hydrodynamic models; and making the models more accessible for water quality and biogeochemical modelling studies by developing a consistent notation through community modelling initiatives. 83 sediment diagenesis model studies were reviewed.The conceptual model of organic matter oxidation is compared to other models and input data.Future directions include 3D hydro models, resuspension and time-resolved datasetsThe models can be improved through consistent reporting and community-based modelling.

The nearshore shunt and the decline of the phytoplankton spring bloom in the Laurentian Great Lakes: insights from a three-dimensional lake model

Dreissenid mussels have been hypothesized to cause selective decreases of phytoplankton in nearshore areas (nearshore shunt hypothesis) as well as the near-complete loss of the offshore phytoplankton spring bloom in some Laurentian Great Lakes. To evaluate whether mussels can reasonably be expected to mediate such changes, we extended the three-dimensional hydrodynamic-ecological model (ELCOM-CAEDYM) to include mussels as a state variable and applied it to Lake Erie (USA-Canada). Mussel-mediated decreases in mean phytoplankton biomass were highly sensitive to the assigned mussel population size in each basin. In the relatively deep east basin, mussels were predicted to decrease phytoplankton in both nearshore and offshore zones, even during periods of thermal stratification but especially during the spring phytoplankton maximum. Spatially, impacts were associated with mussel distributions but could be strong even in areas without high mussel biomass, consistent with advection from areas of higher mussel biomass. The results supported the nearshore shunt hypothesis that mussel impacts on phytoplankton should be greater in nearshore than offshore waters and also supported suggestions about the emerging importance of deep water offshore mussels. The results of this study provide an important insight into ecological role of mussels in lowering plankton productivity in some world’s largest lakes.