The need for operational reasoning in data‐driven rating curve prediction of suspended sediment

The use of data‐driven modelling techniques to deliver improved suspended sediment rating curves has received considerable interest in recent years. Studies indicate an increased level of performance over traditional approaches when such techniques are adopted. However, closer scrutiny reveals that, unlike their traditional counterparts, data‐driven solutions commonly include lagged sediment data as model inputs, and this seriously limits their operational application. In this paper, we argue the need for a greater degree of operational reasoning underpinning data‐driven rating curve solutions and demonstrate how incorrect conclusions about the performance of a data‐driven modelling technique can be reached when the model solution is based upon operationally invalid input combinations. We exemplify the problem through the re‐analysis and augmentation of a recent and typical published study, which uses gene expression programming to model the rating curve. We compare and contrast the previously published solutions, whose inputs negate their operational application, with a range of newly developed and directly comparable traditional and data‐driven solutions, which do have operational value. Results clearly demonstrate that the performance benefits of the published gene expression programming solutions are dependent on the inclusion of operationally limiting, lagged data inputs. Indeed, when operationally inapplicable input combinations are discounted from the models and the analysis is repeated, gene expression programming fails to perform as well as many simpler, more standard multiple linear regression, piecewise linear regression and neural network counterparts. The potential for overstatement of the benefits of the data‐driven paradigm in rating curve studies is thus highlighted. Copyright © 2011 John Wiley & Sons, Ltd.     

The influence of relative sediment supply on riverine habitat heterogeneity

The diversity of aquatic habitats in streams is linked to physical processes that act at various spatial and temporal scales. Two components of many that contribute to creating habitat heterogeneity in streams are the interaction between sediment supply and transport capacity and the presence of local in-stream structures, such as large woody debris and boulders. Data from previously published flume and field studies and a new field study on tributaries to the South Yuba River in Nevada County, California, USA, were used to evaluate the relationship between habitat heterogeneity, local in-stream structural features and relative sediment supply. Habitat heterogeneity was quantified using spatial heterogeneity measures from the field of landscape ecology. Relative sediment supply, as expressed by the sediment supply/transport capacity ratio, which controls channel morphology and substrate textures, two key physical habitat characteristics, was quantified using a dimensionless bedload transport ratio, q. Calculated q values were plotted against an ecologically meaningful heterogeneity index, Shannon's Diversity Index, measured for each study reach, as well as the percent area of in-stream structural elements. The results indicate two potential mechanisms for how relative sediment supply may drive geomorphic diversity in natural river systems at the reach scale. When less mobile structural elements form a small proportion of the reach landscape, the supply/capacity ratio dictates the range of sediment textures and geomorphic features observed within the reach. In these settings, channels with a moderate relative sediment supply exhibit the highest textural and geomorphic diversity. In contrast, when less mobile structural elements are abundant, forced local scour and deposition creates high habitat heterogeneity, even in the presence of high relative sediment supply.     

Data-driven modelling approaches for socio-hydrology: opportunities and challenges within the Panta Rhei Science Plan

ABSTRACT

“Panta Rhei – Everything Flows” is the science plan for the International Association of Hydrological Sciences scientific decade 2013–2023. It is founded on the need for improved understanding of the mutual, two-way interactions occurring at the interface of hydrology and society, and their role in influencing future hydrologic system change. It calls for strategic research effort focused on the delivery of coupled, socio-hydrologic models. In this paper we explore and synthesize opportunities and challenges that socio-hydrology presents for data-driven modelling. We highlight the potential for a new era of collaboration between data-driven and more physically-based modellers that should improve our ability to model and manage socio-hydrologic systems. Crucially, we approach data-driven, conceptual and physical modelling paradigms as being complementary rather than competing, positioning them along a continuum of modelling approaches that reflects the relative extent to which hypotheses and/or data are available to inform the model development process.

EDITOR D. Koutsoyiannis; ASSOCIATE EDITOR not assigned     

Climate change and agriculture: A perspective on priorities for economic policy

Research on the effects of climate change on U.S. agriculture and world grain markets suggests that adaptation will occur with relatively small effects on total production. Additional research shows that reducing emission of greenhouse gases from U.S. agricultural production is relatively expensive compared to encouraging reforestation as an offset to emissions of carbon dioxide. Nevertheless, continued population growth and the increasing inequality of income across countries are likely to exacerbate the adverse effects of climate change. Concepts of sustainability should be expanded to cover industrial as well as agricultural production, and promote the efficient use of fossil fuels in general. Dealing with climate change effectively will require international cooperation and a willingness to address population growth and the divergence of incomes between rich and poor countries.     

Scientific objectives of the Solar Mesosphere Explorer mission

The 1981–82 Solar Mesosphere Explorer (SME) mission is described. The SME experiment will provide a comprehensive study of mesospheric ozone and the processes which form and destroy it. Five instruments will be carried on the spinning spacecraft to measure the ozone density and its altitude distribution from 30 to 80 km, monitor the incoming solar ultraviolet radiation, and measure other atmospheric constituent which affect ozone. The polar-orbiting spacecraft will be placed into a 3pm-3 am Sun-synchronous orbit. The atmospheric measurements will scan the Earth's limb and measure: (1) the mesospheric and stratospheric ozone density distribution by inversion of Rayleigh-scattered ultraviolet limb radiance, and the thermal emission from ozone at 9.6 m; (2) the water vapor density distribution by inversion of thermal emission at 6.3 m; (3) the ozone photolysis rate by inversion of the O₂(¹g) 1.27 m limb radiance; (4) the temperature profile by a combination of narrow-band and wide-band measurements of the 15 m thermal emission by CO₂; and, (5) theNO₂ density distribution by inversion of Rayleighscattered limb radiance at 0.439 m. The solar ultraviolet monitor will measure both the 0.2–0.31 m spectral region and the Lyman-alpha (0.1216 m) contribution to the solar irradiance. This combination of measurements will provide a rigorous test of the photochemical equilibrium theory of the mesospheric oxygen-hydrogen system, will determine what changes occur in the ozone distribution as a result of changes in the incoming solar radiation, and will detect changes that may occur as a result of meteorological disturbances.     

One- and multi-component models of the upper photosphere based on molecular spectra

Spectroheliograms taken in the CN(0, 0) violet band near 3883 Å show very small scale network and cell structures with high contrast. The bandhead itself, which is a broad feature due to overlap of several CN lines, allows the diagnostic simplicity of a continuum since motions, magnetic fields, and broadening mechanisms are unimportant. We have obtained spectroheliograms in the bandhead and center-to-limb photoelectric spectra of CN(0, 0) at Kitt Peak National Observatory. From the photoelectric spectra and a detailed analysis of the formation of the CN(0, 0) spectrum we derive a best-fit one-component upper photospheric model differing from that of the HSRA and recommend a change in solar carbon abundance from the HSRA value of logA _c = 8.55 to logA _c = 8.25. From the calibrated spectroheliograms we consider a multi-component model to account for the observed fine structure intensity variations.Staff Member, Laboratory Astrophysics Division, National Bureau of Standards.Visiting Astronomer at Kitt Peak National Observatory, which is operated by the Association of Universities for Research in Astronomy, Inc., under contract with the National Science Foundation.     

Estimation and propagation of error in measurements of river channel movement from aerial imagery

Rates of river channel migration or widening are only valid if it can be demonstrated that the amount of change in the measured parameters exceeds the measurement errors. However, it is still uncommon to see estimates of errors presented alongside rates of river channel change measured from aerial photography. Here, detailed methods are presented for the estimation of errors in quantifying channel migration rates that can be easily applied to GIS‐based analysis of planform change. In addition, the impact of relaxing assumptions regarding error independence between image dates and systematic registration errors is presented and discussed. Copyright © 2005 John Wiley & Sons, Ltd.     

Corroded cobbles in Southern Death Valley: Their relationship to honeycomb weathering and lake shorelines

In southern Death Valley, pits similar in morphology to honeycomb weathering (herein referred to as corrosion pits) occur on the surfaces of cobbles that are associated with wave-produced benches. The pitted cobbles include a variety of igneous, metamorphic, and siliciclastic rocks; corrosion pits are rare to absent in limestones or dolomites. Pit morphology is controlled by cobble lithology. In massive rocks the pits are arcuate, elongate, and gently tapering; corrosion of laminated or foliated rocks has produced irregular, more jagged pits. The presence of desert varnish has strongly inhibited the corrosion process. The corroded cobbles are inferred to reflect both chemical and physical weathering of rocks along Pleistocene lacustrine strandlines. Corrosion took place through salt-weathering and/or heat-moisture expansion processes and through chemical dissolution of selected minerals as a result of splash-zone wetting and drying. The ancient lake waters may have had high pH and high total dissolved solids contents. The recognition of corroded cobbles may be important in the reconstruction of the position of ancient shorelines for certain types of alkaline lakes and in the reconstruction of their ancient chemistries.     

Load or concentration,logged or unlogged? Addressing ten years of uncertainty in neural network suspended sediment prediction

This paper addresses current inconsistencies in methodological approaches for neural network modelling of suspended sediment. An expansion in the number of case studies being published over the last decade has yet to result in agreed guidelines on whether suspended sediment load or concentration should be modelled, and whether log‐transformation of data is either necessary or potentially beneficial. This contrasts with the well‐recognized guidelines that direct traditional sediment rating curve studies. The paper reports a comprehensive set of single‐input single‐output neural network suspended sediment modelling experiments performed on two catchments in Puerto Rico. It examines the impact of internal complexity, input variable choice and data transformation on the form, consistency and physical rationality of model outputs, the existence of localized overfitting and the usefulness of global performance metrics. Sound guidance on whether to model sediment load or concentration, and whether to model log‐transformed data is provided. Copyright © 2011 John Wiley & Sons, Ltd.     

A discrete Bayesian network to investigate suspended sediment concentrations in an Alpine proglacial zone

In this study, a Bayesian Network (BN) is used to model the suspended sediment concentrations (SSC) in the catchments of the glaciers Noir and Blanc in the Ecrins National Park, France, and at the distal end of the proglacial zone into which both torrents drain. Relationships between air temperature, glacier discharge and SSC are represented as random variables; thereby taking the natural next step from proposed modified rating curve methods which increasingly approximate random variable approaches. Hydrological relationships are propagated through the network via conditional probability distributions computed from 980 field records obtained at three monitoring sites during July 2005. Rainfall affected data are removed from the modelling process. A two‐sample Kolmogorov–Smirnov goodness‐of‐fit (two‐sample KS) test (n = 5) shows good agreement between the probability distributions of SSC predicted by the BN, and those recorded in the field at the outflow of the proglacial zone over an air temperature range of 5–25 °C. The BN performs poorly for air temperatures between 25 and 30 °C and this is attributed to limited field records covering this temperature range. Discussion of the significant limitations surrounding the widespread application of BNs in hydrological modelling are offered with a focus on data volume and temporal limitations. Copyright © 2008 John Wiley & Sons, Ltd.