Ross Woods

A decade of Predictions in Ungauged Basins (PUB)—a review

Abstract The Prediction in Ungauged Basins (PUB) initiative of the International Association of Hydrological Sciences (IAHS), launched in 2003 and concluded by the PUB Symposium 2012 held in Delft (23–25 October 2012), set out to shift the scientific culture of hydrology towards improved scientific understanding of hydrological processes, as well as associated uncertainties and the development of models with increasing realism and predictive power. This paper reviews the work that has been done under the six science themes of the PUB Decade and outlines the challenges ahead for the hydrological sciences community. Editor D. Koutsoyiannis Citation Hrachowitz, M., Savenije, H.H.G., Blöschl, G., McDonnell, J.J., Sivapalan, M., Pomeroy, J.W., Arheimer, B., Blume, T., Clark, M.P., Ehret, U., Fenicia, F., Freer, J.E., Gelfan, A., Gupta, H.V., Hughes, D.A., Hut, R.W., Montanari, A., Pande, S., Tetzlaff, D., Troch, P.A., Uhlenbrook, S., Wagener, T., Winsemius, H.C., Woods, R.A., Zehe, E., and Cudennec, C., 2013. A decade of Predictions in Ungauged Basins (PUB)—a review. Hydrological Sciences Journal, 58 (6), 1198–1255.

A unified approach for process-based hydrologic modeling: 1. Modeling concept

This work advances a unified approach to process-based hydrologic modeling to enable controlled and systematic evaluation of multiple model representations (hypotheses) of hydrologic processes and scaling behavior. Our approach, which we term the Structure for Unifying Multiple Modeling Alternatives (SUMMA), formulates a general set of conservation equations, providing the flexibility to experiment with different spatial representations, different flux parameterizations, different model parameter values, and different time stepping schemes. In this paper, we introduce the general approach used in SUMMA, detailing the spatial organization and model simplifications, and how different representations of multiple physical processes can be combined within a single modeling framework. We discuss how SUMMA can be used to systematically pursue the method of multiple working hypotheses in hydrology. In particular, we discuss how SUMMA can help tackle major hydrologic modeling challenges, including defining the appropriate complexity of a model, selecting among competing flux parameterizations, representing spatial variability across a hierarchy of scales, identifying potential improvements in computational efficiency and numerical accuracy as part of the numerical solver, and improving understanding of the various sources of model uncertainty.

A synthesis of space‐time variability in storm response: Rainfall, runoff generation, and routing

We propose an analytical method to identify the importance of different components of the hydrological cycle during storm events in humid temperate catchments. Hydrological response is the result of numerous complex interactions among hydrological inputs (e.g., rain and radiation) and landscape properties (e.g., vegetation, topography, and soil properties) through a number of hydrological processes at the land surface. The multitude of such interactions makes it difficult to identify the dominant controls on catchment response and on catchment-to-catchment variability within any particular river basin. The method we develop expresses the variability of catchment-averaged storm runoff rates in terms of the space and time variability of hydrological inputs and landscape properties, with particular emphasis on the processes of runoff generation and runoff routing. Given suitable data on rainfall, land surface, and channel network properties, the equations we obtain can be used to indicate the dominant sources of between-catchment variability in storm runoff. We illustrate the use of this method for a 10-hour storm over a 420 km2 study catchment.

Spatial distribution of soil moisture over 6 and 30 cm depth, Mahurangi river catchment, New Zealand

Ground-based measurement of the spatial distribution of soil moisture can be difficult because sampling is essentially made at a point and the choice of both sample depth and sample spacing affects the interpretation of the measurements. Hydrological interest has generally been in soil moisture of the root zone. Microwave Remote Sensing methods are now available that allow the interpretation of spatial distributions of soil moisture, however, their signals respond to moisture in the upper few centimetres of soil. These instruments are still being developed, but one of the questions surrounding their application is how to interpret the surface moisture in a hydrological context. In this study we compare measurements of soil moisture in 0-30 cm of soil with those in 0-6 cm to examine how representative this surface measure is with regard to the root zone. Detailed spatial measurements of soil moisture were conducted at three pasture sites in the 50 km2 Mahurangi River catchment of northern New Zealand as part of a comprehensive hydrology project; MARVEX (MAhurangi River Variability EXperiment). In three field sites, on each of three occasions, field measurements were made using both 30 and 6 cm dielectric-based instruments. Spatial grids of several hundred moisture measurements were collected over 0-30 cm and compared with those collected simultaneously over 0-6 cm. Results indicate that temporal and spatial issues interfere with correlation of the two sets of series. Rapid wetting of 0-6 cm compared with 0-30 cm is seen following storm activity. Some evidence of the decoupling of moisture content response is also evident when sites are measured on days following a storm. Rapid, but not unrealistic, response to intense rainfall was also observed. Implications are that detailed and accurate knowledge of local soil conditions and a sound model of soil water redistribution are required before surface soil moisture measurements can be used to infer root zone behaviour. Such knowledge was not available in this study, from either published data or field observation. In this study, without suitable a priori knowledge, soil property information was found via calibration.

Patterns of similarity of seasonal water balances : A window into streamflow variability over a range of time scales

Recent hydrologic synthesis efforts have presented evidence that the seasonal water balance is at the core of overall catchment responses, and understanding it will assist in predicting signatures of streamflow variability at other time scales, including interannual variability, the flow duration curve, low flows, and floods. In this study, we group 321 catchments located across the continental U.S. into several clusters with similar seasonal water balance behavior. We then delineate the boundaries between these clusters on the basis of a similarity framework based on three hydroclimatic indices that represent aridity, precipitation timing, and snowiness. The clustering of catchments based on the seasonal water balance has a strong relationship not only with regional patterns of the three climate indices but also with regional ecosystem, soil, and vegetation classes, which point to the strong dependence of these physiographic characteristics on seasonal climate variations and the hydrologic regimes. Building on these catchment clusters, we demonstrate that the seasonal water balance does have an imprint on signatures of streamflow variability over a wide range of time scales (daily to decadal) and a wide range of states (low flows to floods). The seasonal water balance is well integrated into variability at seasonal and longer time scales, but is only partly reflected in the signatures at shorter time scales, including flooding responses. Overall, the seasonal water balance has proven to be a similarity measure that serves as a link between both short-term hydrologic responses and long-term adaptation of the landscape with climate.

A unified approach for process-based hydrologic modeling: 2. Model implementation and case studies

This work advances a unified approach to process-based hydrologic modeling, which we term the “Structure for Unifying Multiple Modeling Alternatives (SUMMA).” The modeling framework, introduced in the companion paper, uses a general set of conservation equations with flexibility in the choice of process parameterizations (closure relationships) and spatial architecture. This second paper specifies the model equations and their spatial approximations, describes the hydrologic and biophysical process parameterizations currently supported within the framework, and illustrates how the framework can be used in conjunction with multivariate observations to identify model improvements and future research and data needs. The case studies illustrate the use of SUMMA to select among competing modeling approaches based on both observed data and theoretical considerations. Specific examples of preferable modeling approaches include the use of physiological methods to estimate stomatal resistance, careful specification of the shape of the within-canopy and below-canopy wind profile, explicitly accounting for dust concentrations within the snowpack, and explicitly representing distributed lateral flow processes. Results also demonstrate that changes in parameter values can make as much or more difference to the model predictions than changes in the process representation. This emphasizes that improvements in model fidelity require a sagacious choice of both process parameterizations and model parameters. In conclusion, we envisage that SUMMA can facilitate ongoing model development efforts, the diagnosis and correction of model structural errors, and improved characterization of model uncertainty.

MODELING THE SPATIAL VARIABILITY OF SUBSURFACE RUNOFF USING A TOPOGRAPHIC INDEX

We propose a new topographic index for use in regions with rapid subsurface runoff which is spatially variable. By considering field measurements we suggest that the pattern of recharge to the saturated zone is controlled by both the prestorm catchment-average wetness and the pattern of saturated zone thickness. The major distinguishing assumptions of this index are that (1) the soil lies above an impermeable layer; (2) saturated hydraulic conductivity does not vary with depth; (3) the pattern of recharge can be estimated using a simple nonlinear function of both local and catchment-average saturated zone thickness. The index predicts patterns of both subsurface runoff and saturated zone thickness: spatial patterns change as catchment wetness varies. Subsurface runoff is predicted to be most uniform when the catchment is wettest, and as the catchment dries out, runoff decreases most quickly at the driest locations in the catchment. This index is able to reproduce significant features of observed spatial patterns of subsurface stormflow for a variety of prestorm conditions and can also be used as the basis for a rainfall-runoff model.

A novel framework for discharge uncertainty quantification applied to 500 UK gauging stations

Abstract Benchmarking the quality of river discharge data and understanding its information content for hydrological analyses is an important task for hydrologic science. There is a wide variety of techniques to assess discharge uncertainty. However, few studies have developed generalized approaches to quantify discharge uncertainty. This study presents a generalized framework for estimating discharge uncertainty at many gauging stations with different errors in the stage‐discharge relationship. The methodology utilizes a nonparametric LOWESS regression within a novel framework that accounts for uncertainty in the stage‐discharge measurements, scatter in the stage‐discharge data and multisection rating curves. The framework was applied to 500 gauging stations in England and Wales and we evaluated the magnitude of discharge uncertainty at low, mean and high flow points on the rating curve. The framework was shown to be robust, versatile and able to capture place‐specific uncertainties for a number of different examples. Our study revealed a wide range of discharge uncertainties (10–397% discharge uncertainty interval widths), but the majority of the gauging stations (over 80%) had mean and high flow uncertainty intervals of less than 40%. We identified some regional differences in the stage‐discharge relationships, however the results show that local conditions dominated in determining the magnitude of discharge uncertainty at a gauging station. This highlights the importance of estimating discharge uncertainty for each gauging station prior to using those data in hydrological analyses.

The relative roles of climate, soil, vegetation and topography in determining seasonal and long-term catchment dynamics

Abstract This paper develops and demonstrates a preliminary set of coupled analytical models for the seasonality and annual water balance of catchments. We include the effects of temporal variability of atmospheric forcing and the interaction of nonlinear catchment processes, while assuming that climate, soil and vegetation are effectively uniform over the catchment. The models make predictions for the water balance of the canopy, root zone, saturated zone and catchment system, as functions of 6 dimensionless similarity parameters. These parameters quantify: (i) climate dryness; (ii) interception capacity relative to rainfall; (iii) combined climate seasonality and rootzone storage; (iv) subsurface flow responsiveness; (v) saturated subsurface flow capacity, relative to mean annual rainfall rate; and (vi) a geomorphological exponent controlling the expansion of saturated area fraction. The model can provide estimates of throughfall, evaporation, drainage, subsurface flow, saturated area and catchment yield. Testing of these estimates is in progress. The coupled models can be used to predict hydrological differences between catchments using differences in the dimensionless parameters. The sensitivity of water balance to each of the similarity parameters can be presented graphically or analytically, so that dominant controls on water balance can be identified as functions of climate and catchment properties. The principal application we envisage is as a simple method to transfer measurements to ungauged catchments.

Dominant flood generating mechanisms across the United States

River flooding can have severe societal, economic, and environmental consequences. However, limited understanding of the regional differences in flood-generating mechanisms results in poorly understood historical flood trends and uncertain predictions of future flood conditions. Through systematic data analyses of 420 catchments we expose the primary drivers of flooding across the contiguous United States. This is achieved by exploring which flood-generating processes control the seasonality and magnitude of maximum annual flows. The regional patterns of seasonality and interannual variabilities of maximum annual flows are, in general, poorly explained by rainfall characteristics alone. For most catchments soil moisture dependent precipitation excess, snowmelt, and rain-on-snow events are found to be much better predictors of the flooding responses. The continental-scale classification of dominant flood-generating processes we generate here emphasizes the disparity in timing and variability between extreme rainfall and flooding and can assist predictions of flooding and flood risk within the continental U.S.