Hilary McMillan

Influence of soil and climate on root zone storage capacity

The root zone water storage capacity (Sr) of a catchment is an important variable for the hydrological behaviour of a catchment; it strongly influences the storage, transpiration and runoff generation in an area. However, the root zone storage capacity is largely heterogeneous and not measurable. There are different theories about the variables affecting the root zone storage capacity; among the most debated are soil, vegetation and climate. The effect of vegetation and soil is often accounted for by detailed soil and land use maps. To investigate the effect of climate on the root zone storage capacity, an analogue can be made between the root zone storage capacity of a catchment and the human habit to design and construct reservoirs: both storage capacities help to overcome a dry period of a certain length. Humans often use the mass curve technique to determine the required storage needed to design the reservoir capacity. This mass curve technique can also be used to derive the root zone storage capacity created by vegetation in a certain ecosystem and climate (Gao et al., 2014). Only precipitation and discharge or evaporation data are required for this method. This study tests whether Sr values derived by both the mass curve technique and from soil maps are comparable for a range of catchments in New Zealand. Catchments are selected over a gradient of climates and land use. Special focus lies on how Sr values derived for a larger catchment are representative for smaller nested catchments. The spatial differences are examined between values derived from soil data and from climate and flow data.

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.

Do time‐variable tracers aid the evaluation of hydrological model structure? A multimodel approach

[1] In this paper we explore the use of time-variable tracer data as a complementary tool for model structure evaluation. We augment the modular rainfall-runoff modeling framework FUSE (Framework for Understanding Structural Errors) with the ability to track the age distribution of water in all model stores and fluxes. We therefore gain the novel ability to compare tracer/water age signatures measured in a catchment with those predicted using hydrological models built from components based on four existing popular models. Key modeling decisions available in FUSE are evaluated against streamflow tracer dynamics using weekly observations of tracer concentration which reflect the tracer transit time distribution (TTD). Model structure choice is shown to have a significant effect on simulated water age characteristics, even when simulated flow series are very similar. We show that for a Scottish case study catchment, careful selection of model structure enables good predictions of both streamflow and tracer dynamics. We then use FUSE as a hypothesis testing tool to understand how different model characterization of TTDs and mean transit times affect multicriteria model performance. We demonstrate the importance of time variation in TTDs in simulating water movement along fast flow pathways, and investigate sensitivity of the models to assumptions about our ability to sample fast, near-surface flow.

End-to-end flood risk assessment: A coupled model cascade with uncertainty estimation

[1] This paper presents the case for an ‘End-to-End’ flood inundation modeling strategy: the creation of a coupled system of models to allow continuous simulation methodology to be used to predict the magnitude and simulate the effects of high return period flood events. The framework brings together the best in current thinking on reduced complexity modeling to formulate an efficient, process-based methodology which meets the needs of today’s flood mitigation strategies. The model chain is subject to stochasticity and parameter uncertainty, and integral methods to allow the propagation and quantification of uncertainty are essential in order to produce robust estimates of flood risk. Results from an experimental application are considered in terms of their implications for successful floodplain management, and compared against the deterministic methodology more commonly in use for flood risk assessment applications. The provenance of predictive uncertainty is also considered in order to identify those areas where future effort in terms of data collection or model refinement might best be directed in order to narrow prediction bounds and produce a more precise forecast.

Panta Rhei 2013–2015: global perspectives on hydrology, society and change

ABSTRACT In 2013, the International Association of Hydrological Sciences (IAHS) launched the hydrological decade 2013–2022 with the theme “Panta Rhei: Change in Hydrology and Society”. The decade recognizes the urgency of hydrological research to understand and predict the interactions of society and water, to support sustainable water resource use under changing climatic and environmental conditions. This paper reports on the first Panta Rhei biennium 2013–2015, providing a comprehensive resource that describes the scope and direction of Panta Rhei. We bring together the knowledge of all the Panta Rhei working groups, to summarize the most pressing research questions and how the hydrological community is progressing towards those goals. We draw out interconnections between different strands of research, and reflect on the need to take a global view on hydrology in the current era of human impacts and environmental change. Finally, we look back to the six driving science questions identified at the outset of Panta Rhei, to quantify progress towards those aims. Editor D. Koutsoyiannis; Associate editor not assigned

Uncertainty in hydrological signatures for gauged and ungauged catchments

Reliable information about hydrological behavior is needed for water-resource management and scientific investigations. Hydrological signatures quantify catchment behavior as index values, and can be predicted for ungauged catchments using a regionalization procedure. The prediction reliability is affected by data uncertainties for the gauged catchments used in prediction and by uncertainties in the regionalization procedure. We quantified signature uncertainty stemming from discharge data uncertainty for 43 UK catchments and propagated these uncertainties in signature regionalization, while accounting for regionalization uncertainty with a weighted-pooling-group approach. Discharge uncertainty was estimated using Monte Carlo sampling of multiple feasible rating curves. For each sampled rating curve, a discharge time series was calculated and used in deriving the gauged signature uncertainty distribution. We found that the gauged uncertainty varied with signature type, local measurement conditions and catchment behavior, with the highest uncertainties (median relative uncertainty ±30–40% across all catchments) for signatures measuring high- and low-flow magnitude and dynamics. Our regionalization method allowed assessing the role and relative magnitudes of the gauged and regionalized uncertainty sources in shaping the signature uncertainty distributions predicted for catchments treated as ungauged. We found that 1) if the gauged uncertainties were neglected there was a clear risk of over-conditioning the regionalization inference, e.g. by attributing catchment differences resulting from gauged uncertainty to differences in catchment behavior, and 2) uncertainty in the regionalization results was lower for signatures measuring flow distribution (e.g. mean flow) than flow dynamics (e.g. autocorrelation), and for average flows (and then high flows) compared to low flows. This article is protected by copyright. All rights reserved.

Accelerating advances in continental domain hydrologic modeling

In the past, hydrologic modeling of surface water resources has mainly focused on simulating the hydrologic cycle at local to regional catchment modeling domains. There now exists a level of maturity among the catchment, global water security, and land surface modeling communities such that these communities are converging toward continental domain hydrologic models. This commentary, written from a catchment hydrology community perspective, provides a review of progress in each community toward this achievement, identifies common challenges the communities face, and details immediate and specific areas in which these communities can mutually benefit one another from the convergence of their research perspectives. Those include: (1) creating new incentives and infrastructure to report and share model inputs, outputs, and parameters in data services and open access, machine-independent formats for model replication or reanalysis; (2) ensuring that hydrologic models have: sufficient complexity to represent the dominant physical processes and adequate representation of anthropogenic impacts on the terrestrial water cycle, a process-based approach to model parameter estimation, and appropriate parameterizations to represent large-scale fluxes and scaling behavior; (3) maintaining a balance between model complexity and data availability as well as uncertainties; and (4) quantifying and communicating significant advancements toward these modeling goals.

Use of an entropy‐based metric in multiobjective calibration to improve model performance

Parameter estimation for hydrological models is complicated for many reasons, one of which is the arbitrary emphasis placed, by most traditional measures of fit, on various magnitudes of the model residuals. Recent research has called for the development of robust diagnostic measures that provide insights into which model structural components and/or data may be inadequate. In this regard, the flow duration curve (FDC) represents the historical variability of flow and is considered to be an informative signature of catchment behavior. Here we investigate the potential of using the recently developed conditioned entropy difference metric (CED) in combination with the Kling-Gupta efficiency (KGE). The CED respects the static information contained in the flow frequency distribution (and hence the FDC), but does not explicitly characterize temporal dynamics. The KGE reweights the importance of various hydrograph components (correlation, bias, variability) in a way that has been demonstrated to provide better model calibrations than the commonly used Nash-Sutcliffe efficiency, while being explicitly time sensitive. We employ both measures within a multiobjective calibration framework and achieve better performance over the full range of flows than obtained by single-criteria approaches, or by the common multiobjective approach that uses log-transformed and untransformed data to balance fitting of low and high flow periods. The investigation highlights the potential of CED to complement KGE (and vice versa) during model identification. It is possible that some of the complementarity is due to CED representing more information from moments >2 than KGE or other common metrics. We therefore suggest that an interesting way forward would be to extend KGE to include higher moments, i.e., use different moments as multiple criteria.

How uncertainty analysis of streamflow data can reduce costs and promote robust decisions in water management applications

Streamflow data are used for important environmental and economic decisions, such as specifying and regulating minimum flows, managing water supplies, and planning for flood hazards. Despite significant uncertainty in most flow data, the flow series for these applications are often communicated and used without uncertainty information. In this commentary, we argue that proper analysis of uncertainty in river flow data can reduce costs and promote robust conclusions in water management applications. We substantiate our argument by providing case studies from Norway and New Zealand where streamflow uncertainty analysis has uncovered economic costs in the hydropower industry, improved public acceptance of a controversial water management policy, and tested the accuracy of water quality trends. We discuss the need for practical uncertainty assessment tools that generate multiple flow series realizations rather than simple error bounds. Although examples of such tools are in development, considerable barriers for uncertainty analysis and communication still exist for practitioners, and future research must aim to provide easier access and usability of uncertainty estimates. We conclude that flow uncertainty analysis is critical for good water management decisions.

Robust informational entropy-based descriptors of flow in catchment hydrology

Abstract This paper explores the use of entropy-based measures in catchment hydrology, and provides an importance-weighted numerical descriptor of the flow–duration curve. Although entropy theory is being applied in a wide spectrum of areas (including environmental and water resources), artefacts arising from the discrete, under-sampled and uncertain nature of hydrological data are rarely acknowledged, and have not been adequately explored. Here, we examine challenges to extracting hydrologically meaningful entropy measures from a flow signal; the effect of binning resolution on calculation of entropy is investigated, along with artefacts caused by (1) emphasis of information theoretic measures towards flow ranges having more data (statistically dominant information), and (2) effects of discharge measurement truncation errors. We introduce an importance-weighted entropy-based measure to counter the tendency of common binning approaches to over-emphasise information contained in the low flows which dominate the record. The measure uses a novel binning method, and overcomes artefacts due to data resolution and under-sampling. Our analysis reveals a fundamental problem with the extraction of information at high flows, due to the lack of statistically significant samples in this range. By separating the flow–duration curve into segments, our approach constrains the computed entropy to better respect distributional properties over the data range. When used as an objective function for model calibration, this approach constrains high flow predictions, as well as the commonly used Nash-Sutcliffe efficiency, but provides much better predictions of low flow behaviour. Editor Z.W. Kundzewicz Associate editor Not assigned