The scientific legacy of Harold Edwin Hurst (1880–1978)

ABSTRACT

Emanating from his remarkable characterization of long-term variability in geophysical records in the early 1950s, Hurst’s scientific legacy to hydrology and other disciplines is explored. A statistical explanation of the so-called “Hurst Phenomenon” did not emerge until 1968 when Mandelbrot and co-authors proposed fractional Gaussian noise based on the hypothesis of infinite memory. A vibrant hydrological literature ensued where alternative modelling representations were explored and debated, e.g. ARMA models, the Broken Line model, shifting mean models with no memory, FARIMA models, and Hurst-Kolmogorov dynamics, acknowledging a link with the work of Kolmogorov in 1940. The diffusion of Hurst’s work beyond hydrology is summarized by discipline and citations, showing that he arguably has the largest scientific footprint of any hydrologist in the last century. Its particular relevance to the modelling of long-term climatic variability in the era of climate change is discussed. Links to various long-term modes of variability in the climate system, driven by fluctuations in sea surface temperatures and ocean dynamics, are explored. Several issues related to the Hurst Phenomenon in hydrology remain as a challenge for future research.

Editor M. Acreman; Associate editor A. Carsteanu     

Structural uncertainty assessment in a discharge simulation model

Abstract

A major goal in hydrological modelling is to identify and quantify different sources of uncertainty in the modelling process. This paper analyses the structural uncertainty in a streamflow modelling system by investigating a set of models with increasing model structure complexity. The models are applied to two basins: Kielstau in Germany and XitaoXi in China. The results show that the model structure is an important factor affecting model performance. For the Kielstau basin, influences from drainage and wetland are critical for the local runoff generation, while for the XitaoXi basin accurate distributions of precipitation and evapotranspiration are two of the determining factors for the success of the river flow simulations. The derived model uncertainty bounds exhibit appropriate coverage of observations. Both case studies indicate that simulation uncertainty for the low-flow period contributes more to the overall uncertainty than that for the peak-flow period, although the main hydrological features in these two basins differ greatly.

Citation Zhang, X. Y., Hörmann, G., Gao, J. F. & Fohrer, N. (2011) Structural uncertainty assessment in a discharge simulation model. Hydrol. Sci. J. 56(5), 854–869.     

Incorporating uncertainty in hydrological predictions for gauged and ungauged basins in southern Africa

Abstract

The increasing demand for water in southern Africa necessitates adequate quantification of current freshwater resources. Watershed models are the standard tool used to generate continuous estimates of streamflow and other hydrological variables. However, the accuracy of the results is often not quantified, and model assessment is hindered by a scarcity of historical observations. Quantifying the uncertainty in hydrological estimates would increase the value and credibility of predictions. A model-independent framework aimed at achieving consistency in incorporating and analysing uncertainty within water resources estimation tools in gauged and ungauged basins is presented. Uncertainty estimation in ungauged basins is achieved via two strategies: a local approach for a priori model parameter estimation from physical catchment characteristics, and a regional approach to regionalize signatures of catchment behaviour that can be used to constrain model outputs. We compare these two sources of information in the data-scarce region of South Africa. The results show that both approaches are capable of uncertainty reduction, but that their relative values vary.

Editor D. Koutsoyiannis

Citation Kapangaziwiri, E., Hughes, D.A., and Wagener, T., 2012. Incorporating uncertainty in hydrological predictions for gauged and ungauged basins in southern Africa. Hydrological Sciences Journal, 57 (5), 1000–1019.     

Climate change impacts on groundwater hydrology – where are the main uncertainties and can they be reduced?

ABSTRACT

This paper assesses how various sources of uncertainty propagate through the uncertainty cascade from emission scenarios through climate models and hydrological models to impacts, with a particular focus on groundwater aspects from a number of coordinated studies in Denmark. Our results are similar to those from surface water studies showing that climate model uncertainty dominates the results for projections of climate change impacts on streamflow and groundwater heads. However, we found uncertainties related to geological conceptualization and hydrological model discretization to be dominant for projections of well field capture zones, while the climate model uncertainty here is of minor importance. How to reduce the uncertainties on climate change impact projections related to groundwater is discussed, with an emphasis on the potential for reducing climate model biases through the use of fully coupled climate–hydrology models.

Editor D. Koutsoyiannis; Associate editor not assigned     

Ancient dams,settlement archaeology and Buddhist propagation in central India: the hydrological background

Abstract

A group of ancient dams (c. second—first century BC) was located during an archaeological study of the Sanchi area in central India. Comparison of reservoir volumes with estimated inflows suggests that their design was based on hydrological understanding.     

Seasonal and annual maximum streamflow forecasting using climate information: application to the Three Gorges Dam in the Yangtze River basin,China / Prévision d'écoulements saisonnier et maximum annuel à l'aide d'informations climatiques: application au Barrage des Trois Gorges dans le bassin du Fleuve Yangtze,Chine

Abstract

This paper explores the potential for seasonal prediction of hydrological variables that are potentially useful for reservoir operation of the Three Gorges Dam, China. The seasonal flow of the primary inflow season and the peak annual flow are investigated at Yichang hydrological station, a proxy for inflows to the Three Gorges Dam. Building on literature and diagnostic results, a prediction model is constructed using sea-surface temperatures and upland snow cover available one season ahead of the prediction period. A hierarchical Bayesian approach is used to estimate uncertainty in the parameters of the prediction model and to propagate these uncertainties to the predictand. The results show skill for both the seasonal flow and the peak annual flow. The peak annual flow model is then used to estimate a design flood (50-year flood or 2% exceedence probability) on a year-to-year basis. The results demonstrate the inter-annual variability in flood risk. The predictability of both the seasonal total inflow and the peak annual flow (or a design flood volume) offers potential for adaptive management of the Three Gorges Dam reservoir through modification of the operating policy in accordance with the year-to-year changes in these variables.     

Analyzing hydrologic uncertainty and its impact upon decision making in water resources

Bayesian Inference and Decision Theory tools are applied to the problem of synthetic hydrology when model and parameter uncertainty exist. Issues such as optimal parameter estimation, use of synthetic generation in design problems, and the effects of parameter uncertainty on statistical estimation are discussed and applied to the problem of reservoir slorage-yield analysis.     

The seventh facet of uncertainty: wrong assumptions,unknowns and surprises in the dynamics of human–water systems

ABSTRACT

The scientific literature has focused on uncertainty as randomness, while limited credit has been given to what we call here the “seventh facet of uncertainty”, i.e. lack of knowledge. This paper identifies three types of lack of understanding: (i) known unknowns, which are things we know we don’t know; (ii) unknown unknowns, which are things we don’t know we don’t know; and (iii) wrong assumptions, things we think we know, but we actually don’t know. Here we discuss each of these with reference to the study of the dynamics of human–water systems, which is one of the main topics of Panta Rhei, the current scientific decade of the International Association of Hydrological Sciences (IAHS), focusing on changes in hydrology and society. In the paper, we argue that interdisciplinary studies of socio-hydrological dynamics leading to a better understanding of human–water interactions can help in coping with wrong assumptions and known unknowns. Also, being aware of the existence of unknown unknowns, and their potential capability to generate surprises or black swans, suggests the need to complement top-down approaches, based on quantitative predictions of water-related hazards, with bottom-up approaches, based on societal vulnerabilities and possibilities of failure.

Editor D. Koutsoyiannis; Associate editor S. Weijs     

High-resolution simulation of the spatial pattern of water use in continental China

ABSTRACT

High-resolution data on the spatial pattern of water use are a prerequisite for appropriate and sustainable water management. Based on one well-validated hydrological model, the Distributed Time Variant Gains Model (DTVGM), this paper obtains reliable high-resolution spatial patterns of irrigation, industrial and domestic water use in continental China. During the validation periods, ranges of correlation coefficient (R) and Nash-Sutcliffe efficiency (NSE) coefficient are 0.67–0.96 and 0.51–0.84, respectively, between the observed and simulated streamflow of six hydrological stations, indicating model applicability to simulate the distribution of water use. The simulated water use quantities have relative errors (RE) less than 5% compared with the observed. In addition, the changes in streamflow discharge were also correctly simulated by our model, such as the Zhangjiafen station in the Hai River basin with a dramatic decrease in streamflow, and the Makou station in the Pearl River basin with no significant changes. These changes are combined results of basin available water resources and water use. The obtained high-resolution spatial pattern of water use could decrease uncertainty of hydrological simulation and guide water management efficiently.

Editor M.C. Acreman; Associate editor X. Fang     

换水率和营养水平对太湖流域横山水库硅藻水华的影响

为探讨水文过程对水库硅藻异常增殖的影响,对江苏宜兴横山水库的硅藻生消过程中浮游植物、水质、降水、水位、气温等指标进行观测研究.结果表明,横山水库硅藻年际生物量波动很大,9月出现明显的异常增殖,总生物量达到14.27 mg/L,硅藻的优势属为针杆藻(Synedra)、小环藻(Cyclotella)、曲壳藻(Achnanthes)和直链藻(Melosira),以针杆藻的优势度最高;浮游植物生物量与营养盐浓度关系不明显,与总氮浓度甚至呈负相关,但小环藻生物量与水体溶解性磷浓度呈正相关;水库的换水率与浮游植物生物量、硅藻的异常增殖过程和营养盐浓度水平均密切关联,总氮、溶解性磷浓度与水库换水率呈正相关,而硅藻生物量与水库换水率呈指数负相关.数值拟合分析显示硅藻生物量可以用换水率和磷浓度推算而得.研究表明,对于中营养水平的水库,硅藻生物量变化可能受水文过程与水质条件共同控制,在水库的硅藻水华防控中,既要加强营养盐水平的严格控制,也需考虑水文过程的调控手段.     

E-monitoring the nature of water

ABSTRACT

The critical need for hydrological observations in support of water resources management, particularly during extreme events, has transformed traditional methods of hydrological data management. This transformation has given rise to a framework of e-monitoring the hydrological cycle, the aim of which is to improve understanding of the nature of water. New trends in data science, coupled with increasing technological evolution, make the new generation of data systems more agile and responsive to the needs and expectations for efficient and effective data sharing and service delivery. The WMO Hydrological Observing System was designed around the integration of observations, data exchange, research, data processing, modelling and forecasting, in such a way that societal needs for disaster risk reduction, improved sustainability of environmental resources, climate resilience and economic growth can be effectively met. With its implementation of conceptual functionalities for sustainable data management, the WHOS operational architecture is hydrology’s system for the future.     

A philosophical basis for hydrological uncertainty

ABSTRACT

Uncertainty is an epistemological concept in the sense that any meaningful understanding of uncertainty requires a theory of knowledge. Therefore, uncertainty resulting from scientific endeavors can only be properly understood in the context of a well-defined philosophy of science. Our main message here is that much of the discussion about uncertainty in hydrology has lacked grounding in these foundational concepts, and has resulted in a controversy that is largely the product of logical errors rather than true (axiomatic) disagreement. As an example, we explore the current debate about the appropriate role of probability theory for hydrological uncertainty quantification. Our main messages are: (1) apparent (and/or claimed) limitations of probability theory are not actually consequences of that theory, but rather of deeper underlying epistemological (and ontological) issues; (2) questions about the appropriateness of probability theory are only meaningful if posed as questions about our preferred philosophy of science; and (3) questions about uncertainty may often be better posed as questions about available information and information use efficiency. Our purpose here is to discuss how hydrologists might ask more meaningful questions about uncertainty.     

A stochastic optimization framework for the restoration of an over-exploited aquifer

ABSTRACT

This study investigates the impact of hydraulic conductivity uncertainty on the sustainable management of the aquifer of Lake Karla, Greece, using the stochastic optimization approach. The lack of surface water resources in combination with the sharp increase in irrigation needs in the basin over the last 30 years have led to an unprecedented degradation of the aquifer. In addition, the lack of data regarding hydraulic conductivity in a heterogeneous aquifer leads to hydrogeologic uncertainty. This uncertainty has to be taken into consideration when developing the optimization procedure in order to achieve the aquifer’s sustainable management. Multiple Monte Carlo realizations of this spatially-distributed parameter are generated and groundwater flow is simulated for each one of them. The main goal of the sustainable management of the ‘depleted’ aquifer of Lake Karla is two-fold: to determine the optimum volume of renewable groundwater that can be extracted, while, at the same time, restoring its water table to a historic high level. A stochastic optimization problem is therefore formulated, based on the application of the optimization method for each of the aquifer’s multiple stochastic realizations in a future period. In order to carry out this stochastic optimization procedure, a modelling system consisting of a series of interlinked models was developed. The results show that the proposed stochastic optimization framework can be a very useful tool for estimating the impact of hydraulic conductivity uncertainty on the management strategies of a depleted aquifer restoration. They also prove that the optimization process is affected more by hydraulic conductivity uncertainty than the simulation process.

Editor Z.W. Kundzewicz; Guest editor S. Weijs     

A hydropedological approach to simulate streamflow and soil water contents with SWAT+

Reflecting internal catchment hydrological processes in hydrological models is important for accurate predictions of the impact of climate and land-use change on water resources. Characterizing these processes is however difficult and expensive due to their dynamic nature and spatio-temporal variability. Hydropedology is a relatively new discipline focusing on the synergistic integration of hydrology, soil physics and pedology. Hydropedological interpretations of soils and soil distribution can be used to characterize key hydrological processes, especially in areas with no or limited hydrometric measurements. Here we applied a hydropedological approach to reflect flowpaths through detailed routing in SWAT+ for a 157 ha catchment (Weatherley) in South Africa. We compared the hydropedological approach and a standard (no routing) approach against measured streamflow (two weirs) and soil water contents (13 locations). The catchment was treated as ‘ungauged’ and the model was not calibrated against hydrometric measurements in order to determine the direct contribution of hydropedology on modelling efficiency. Streamflow was predicted well without calibration (NSE > 0.8; R² > 0.82) for both approaches at both weirs. The standard approach yielded slightly better streamflow predictions. The hydropedological approach resulted in considerable improvements in the simulation of soil water contents (R² increased from 0.40 to 0.49 and PBIAS decreased from 40% to 20%). The routing capacity of SWAT+ as employed in the hydropedological approach reduced the underestimation of wetland water regimes drastically and resulted in a more accurate representation of the dominant hydrological processes in this catchment. We concluded that hydropedology can be a valuable source of ‘soft data’ to reflect internal catchment structure and processes and, potentially, for realistic calibrations in other studies, especially those conducted in areas with limited hydrometric measurements.     

Uncertainty,entropy, scaling and hydrological stochastics. 1. Marginal distributional properties of hydrological processes and state scaling / Incertitude,entropie, effet d'échelle et propriétés stochastiques hydrologiques. 1. Propriétés distributionnelles marginales des processus hydrologiques et échelle d'état

Abstract

The well-established physical and mathematical principle of maximum entropy (ME), is used to explain the distributional and autocorrelation properties of hydrological processes, including the scaling behaviour both in state and in time. In this context, maximum entropy is interpreted as maximum uncertainty. The conditions used for the maximization of entropy are as simple as possible, i.e. that hydrological processes are non-negative with specified coefficients of variation (CV) and lag one autocorrelation. In this first part of the study, the marginal distributional properties of hydrological variables and the state scaling behaviour are investigated. Application of the ME principle under these very simple conditions results in the truncated normal distribution for small values of CV and in a nonexponential type (Pareto) distribution for high values of CV. In addition, the normal and the exponential distributions appear as limiting cases of these two distributions. Testing of these theoretical results with numerous hydrological data sets on several scales validates the applicability of the ME principle, thus emphasizing the dominance of uncertainty in hydrological processes. Both theoretical and empirical results show that the state scaling is only an approximation for the high return periods, which is merely valid when processes have high variation on small time scales. In other cases the normal distributional behaviour, which does not have state scaling properties, is a more appropriate approximation. Interestingly however, as discussed in the second part of the study, the normal distribution combined with positive autocorrelation of a process, results in time scaling behaviour due to the ME principle.     

Hydrology and change

Abstract

Since “panta rhei” was pronounced by Heraclitus, hydrology and the objects it studies, such as rivers and lakes, have offered grounds to observe and understand change and flux. Change occurs on all time scales, from minute to geological, but our limited senses and life span, as well as the short time window of instrumental observations, restrict our perception to the most apparent daily to yearly variations. As a result, our typical modelling practices assume that natural changes are just a short-term “noise” superimposed on the daily and annual cycles in a scene that is static and invariant in the long run. According to this perception, only an exceptional and extraordinary forcing can produce a long-term change. The hydrologist H.E. Hurst, studying the long flow records of the Nile and other geophysical time series, was the first to observe a natural behaviour, named after him, related to multi-scale change, as well as its implications in engineering designs. Essentially, this behaviour manifests that long-term changes are much more frequent and intense than commonly perceived and, simultaneously, that the future states are much more uncertain and unpredictable on long time horizons than implied by standard approaches. Surprisingly, however, the implications of multi-scale change have not been assimilated in geophysical sciences. A change of perspective is thus needed, in which change and uncertainty are essential parts.

Editor Z.W. Kundzewicz

Citation Koutsoyiannis, D., 2013. Hydrology and change. Hydrological Sciences Journal, 58 (6), 1177–1197.     

Climate variability,hydrology and water resources: do we communicate in the field? (HAPEX,FIFE, GEWEX,GCIP and what next?)

Abstract

All the field “experiments” indicated in the sub-title above include the hydrological cycle in some or all of its aspects and thus require the use of “hydrological sciences”. Is hydrology actually included in them? This depends on the definition of hydrology used. The paper briefly describes the different definitions of “hydrology” in the context of the scientific objectives and concepts of these experiments and related scientific activities. It further evaluates the role actually assigned to hydrologists in past cross-disciplinary endeavours to conduct “field experiments” and goes on to propose adjustments to this role in the GEWEX Continental-scale International Project (GCIP). Related activities are analysed in some detail in this framework and proposals are presented for increased inter-disciplinary communication.     

Standardized uncertainty analysis for hydrometry: a review of relevant approaches and implementation examples

Abstract

The water-centric community has continuously made efforts to identify, assess and implement rigorous uncertainty analyses for routine hydrological measurements. This paper reviews some of the most relevant efforts and subsequently demonstrates that the Guide to the expression of uncertainty in measurement (GUM) is a good candidate for estimation of uncertainty intervals for hydrometry. The demonstration is made by implementing the GUM to typical hydrometric applications and comparing the analysis results with those obtained using the Monte Carlo method. The results show that hydrological measurements would benefit from the adoption of the GUM as the working standard, because of its soundness, the availability of software for practical implementation and potential for extending the GUM to hydrological/hydraulic numerical simulations.

Editor D. Koutsoyiannis

Citation Muste, M., Lee, K. and Bertrand-Krajewski, J.-L., 2012. Standardized uncertainty analysis for hydrometry: a review of relevant approaches and implementation examples. Hydrological Sciences Journal, 57 (4), 643–667.     

Large-sample hydrology: recent progress,guidelines for new datasets and grand challenges

ABSTRACT

Large-sample hydrology (LSH) relies on data from large sets (tens to thousands) of catchments to go beyond individual case studies and derive robust conclusions on hydrological processes and models. Numerous LSH datasets have recently been released, covering a wide range of regions and relying on increasingly diverse data sources to characterize catchment behaviour. These datasets offer novel opportunities, yet they are also limited by their lack of comparability, uncertainty estimates and characterization of human impacts. This article (i) underscores the key role of LSH datasets in hydrological studies, (ii) provides a review of currently available LSH datasets, (iii) highlights current limitations of LSH datasets and (iv) proposes guidelines and coordinated actions to overcome these limitations. These guidelines and actions aim to standardize and automatize the creation of LSH datasets worldwide, and to enhance the reproducibility and comparability of hydrological studies.     

On the value of isotope-enabled hydrological model calibration

ABSTRACT

Calibration of hydrological models is challenging in high-latitude regions where hydrometric data are minimal. Process-based models are needed to predict future changes in water supply, yet often with high amounts of uncertainty, in part, from poor calibrations. We demonstrate the utility of stable isotopes (¹⁸O, ²H) as data employed for improving the amount and type of information available for model calibration using the isoWATFLOOD^TM model. We show that additional information added to calibration does not hurt model performance and can improve simulation of water volume. Isotope-enabled calibration improves long-term validation over traditional flow-only calibrated models and offers additional feedback on internal flowpaths and hydrological storages that can be useful for informing internal water distribution and model parameterization. The inclusion of isotope data in model calibration reduces the number of realistic parameter combinations, resulting in more constrained model parameter ranges and improved long-term simulation of large-scale water balance.