A formulation for diagnostic anomaly models

It is shown that the anomaly model governing the difference between two integrations of the equations of motion can be written in a form that is formally linear in the anomalies, by choosing the basic state to be the mean of the results of the two integrations.     

沉积模型和储层随机建模

沉积模型是地层分析的重要工具，可以分为比例尺模型、概念模型和数学模型三大类型，其中数学模型又可分为确定性模型和随机模型。在实际地层分析及模拟工作中，特别是在小尺度问题的研究中，采用随机模型(或称统计学模型)往往更为有利。储层随机建模技术，作为这方面研究的典范，近年来成为储层预测和风险评价的一项较为有效的手段。然而，由于研究目标的复杂性，不同沉积模型之间的嵌套制约关系亦应引起重视。     

On the prediction of the Toce alpine basin floods with distributed hydrologic models

With the objective of improving flood predictions, in recent years sophisticated continuous hydrologic models that include complex land‐surface sub‐models have been developed. This has produced a significant increase in parameterization; consequently, applications of distributed models to ungauged basins lacking specific data from field campaigns may become redundant. The objective of this paper is to produce a parsimonious and robust distributed hydrologic model for flood predictions in Italian alpine basins. Application is made to the Toce basin (area 1534 km²). The Toce basin was a case study of the RAPHAEL European Union research project, during which a comprehensive set of hydrologic, meteorological and physiographic data were collected, including the hydrologic analysis of the 1996–1997 period. Two major floods occurred during this period. We compare the FEST04 event model (which computes rainfall abstraction and antecedent soil moisture conditions through the simple Soil Conservation Service curve number method) and two continuous hydrologic models, SDM and TDM (which differ in soil water balance scheme, and base flow and runoff generation computations). The simple FEST04 event model demonstrated good performance in the prediction of the 1997 flood, but shows limits in the prediction of the long and moderate 1996 flood. More robust predictions are obtained with the parsimonious SDM continuous hydrologic model, which uses a simple one‐layer soil water balance model and an infiltration excess mechanism for runoff generation, and demonstrates good performance in both long‐term runoff modelling and flood predictions. Instead, the use of a more sophisticated continuous hydrologic model, the TDM, that simulates soil moisture dynamics in two layers of soil, and computes runoff and base flow using some TOPMODEL concepts, does not seem to be advantageous for this alpine basin. Copyright © 2006 John Wiley & Sons, Ltd.     

A process-based,distributed hydrologic model based on a large-scale method for surface–subsurface coupling

Process-based watershed models are useful tools for understanding the impacts of natural and anthropogenic influences on water resources and for predicting water and solute fluxes exported from watersheds to receiving water bodies. The applicability of process-based hydrologic models has been previously limited to small catchments and short time frames. Computational demands, especially the solution to the three-dimensional subsurface flow domain, continue to pose significant constraints. This paper documents the mathematical development, numerical testing and the initial application of a new distributed hydrologic model PAWS (Process-based Adaptive Watershed Simulator). The model solves the governing equations for the major hydrologic processes efficiently so that large scale applications become relevant. PAWS evaluates the integrated hydrologic response of the surface–subsurface system using a novel non-iterative method that couples runoff and groundwater flow to vadose zone processes approximating the 3D Richards equation. The method is computationally efficient and produces physically consistent solutions. All flow components have been independently verified using analytical solutions and experimental data where applicable. The model is applied to a medium-sized watershed in Michigan (1169 km²) achieving high performance metrics in terms of streamflow prediction at two gages during the calibration and verification periods. PAWS uses public databases as input and possesses full capability to interact with GIS datasets. Future papers will describe applications to other watersheds and the development and application of fate and transport modules.     

Estimation of the accuracy of geopotential models

Summary The new Geopotential Model Testing (GMT) method has been theoretically developed and practically applied. It is free of any hypothesis, the limiting factors are the accuracy of the geocentric position of the GMT sites and of their normal heights, as well as the accuracy of the geopotential value W₀ on the geoid used as the testing value given a-priori. The GMT procedure occurs on the physical Earth's surface, no reductions are applied. No limits as regards the magnitude of the heights above sea level of the GMT sites are required. The rms error at discrete points of the most recent geopotential model JGM-3 comes out at about ± 1·5 m.     

Grand canyon—a quantitative approach to the erosion and weathering of a stratified bedrock

A new method is proposed for solving a differential equation arising from weathering-limited development of a valley. Allowance is made for horizontal stratification and overhang can be allowed to develop. The model is applied to the Grand Canyon and comments are included on its relevance.     

FROM YELLOW RIVER MODELS TO MODELING OF RIVERS

1INTRODUCTIONTheYellowRiverisadreamtoserioushydraulicengineerswholovechallenge.Historically,theriveristhe"sorrowofChina."Itisalsooneofthefirstriverssubjecttoscientificmodelingattheearlystageofdevelopmentofphysicalscalemodels.ThecontroversyearlythiscenturybetweenthemodelresultsofHubertEngels(1854-1945)andthoseofOt-toFranzius(1878-1936)effectivelydelayedtheChinesegovernment'sdecisiononhowtheriverwastoberegUlatedwithlevees.ChinahasalonghistoryofobservingandregulatingtheYellowRiver.There…     

Accuracy of kinematic wave and diffusion wave approximations for time-independent flows

Errors in the kinematic wave and diffusion wave approximations for time-independent (or steady-state) cases of channel flow were derived for three types of boundary conditions: zero flow at the upstream end, and critical flow depth and zero depth gradient at the downstream end. The diffusion wave approximation was found to be in excellent agreement with the dynamic wave approximation, with errors in the range 1–2% for values of KF (? 7.5), where K is the kinematic wave number and F₀ is the Froude number. Even for small values of KF (e.g. KF²₀ = 0.75), the errors were typically less than 15%. The accuracy of the diffusion wave approximation was greatly influenced by the downstream boundary condition. The error of the kinematic wave approximation was found to be less than 13% in the region 0.1 ? x ? 0.95 for KF = 7.5 and was greater than 30% for smaller values of KF (? 0.75). This error increased with strong downstream boundary control.     

A comparison of local and aggregated climate model outputs with observed data

Abstract

We compare the output of various climate models to temperature and precipitation observations at 55 points around the globe. We also spatially aggregate model output and observations over the contiguous USA using data from 70 stations, and we perform comparison at several temporal scales, including a climatic (30-year) scale. Besides confirming the findings of a previous assessment study that model projections at point scale are poor, results show that the spatially integrated projections are also poor.

Citation Anagnostopoulos, G. G., Koutsoyiannis, D., Christofides, A., Efstratiadis, A. & Mamassis, N. (2010) A comparison of local and aggregated climate model outputs with observed data. Hydrol. Sci. J. 55(7), 1094–1110.     

Accuracy of kinematic wave and diffusion wave approximations for space-independent flows on infiltrating surfaces with lateral inflow neglected in the momentum equation

Error equations for the kinematic wave and diffusion wave approximations with lateral inflow neglected in the momentum equation are derived under simplified conditions for space-independent flows. These equations specify error as a function of time in the flow hydrograph. The kinematic wave, diffusion wave and dynamic wave solutions are parameterized through a dimensionless parameter γ which is dependent on the initial conditions. This parameter reflects the effect of initial flow depth, channel-bed slope, lateral inflow, infiltration and channel roughness when the initial condition is non-vanishing; it reflects the effect of bed slope, channel roughness and acceleration due to gravity when the initial condition is vanishing. The error equations are found to be the Riccati equation. The structure of the error equations in the case when the momentum equation neglects lateral inflow is different from that when the lateral inflow is included.     

Modeling long term lake variations by physically based stochastic dynamic models

Several physically based stochastic dynamic models (SDM) are described including year-to-year variations of water volume in terminal and non-terminal lakes, streamflow of lake-fed rivers, and salinity of an inland sea (the Sea of Azov). All of these models are based upon the SDM of water volume of terminal lakes developed by Kritzky and Menkel in 1946 in co-operation with Kolomogorov. Explicit formulae are derived for second order statistical moments of the output processes, including variance, correlation function, spectra, etc., under the assumption that the forcing functions from stationary random sequences. The least-squares prediction problem is solved for both stationary and non-stationary cases. Some of the processes are shown to possess high statistical predictability. Actual predictions are compared with independent observations. Problems for further study are stated.     

Comparison of infiltration models

Fourteen popular, representative infiltration models, some physically based, some semi‐empirical and some empirical, were selected for a comparative evaluation. Using the Nash and Sutcliffe efficiency criterion, the models were evaluated and compared for 243 sets of infiltration data collected from field and laboratory tests conducted in India and the USA on soils ranging from coarse sand to fine clay. Based on a relative grading scale, the semi‐empirical Singh–Yu general model, Holtan model and Horton model were graded respectively as 6·52, 5·57 and 5·48 out of 10. The empirical Huggins and Monke model, modified Kostiakov and Kostiakov model were graded as 5·57, 5·30 and 5·22, respectively. The physically based non‐linear and linear models of Smith–Parlange were graded as 5·48 and 5·22, respectively. Other models were ranked lower than these models. All the models generally performed poorly in field tests on Georgia's sandy soils, except the Robertsdale loamy sand. Copyright © 2003 John Wiley & Sons, Ltd.     

Artificial neural networks for daily rainfall—runoff modelling

Abstract

The application of artificial neural network (ANN) methodology for modelling daily flows during monsoon flood events for a large size catchment of the Narmada River in Madhya Pradesh (India) is presented. The spatial variation of rainfall is accounted for by subdividing the catchment and treating the average rainfall of each subcatchment as a parallel and separate lumped input to the model. A linear multiple-input single-output (MISO) model coupled with the ANN is shown to provide a better representation of the rainfall-runoff relationship in such large size catchments compared with linear and nonlinear MISO models. The present model provides a systematic approach for runoff estimation and represents improvement in prediction accuracy over the other models studied herein.     

ACCURACY OF KINEMATIC WAVE AND DIFFUSION WAVE APPROXIMATIONS FOR TIME-INDEPENDENT FLOW WITH MOMENTUM EXCHANGE INCLUDED

Errors in the kinematic wave and diffusion wave approximation for time-independent (or steady-state) cases of channel flow with momentum exchange included were derived for three types of boundary conditions: zero flow at the upstream end, and critical flow depth and zero depth gradient at the downstream end. The diffusion wave approximation was found to be in excellent agreement with the dynamic wave approximation, with errors of less than 1% for KF²₀≥7·5 and up to 12% for KF²₀≤0·75 for the upstream boundary condition of zero discharge and finite depth, where K is the kinematic wave number and F₀ is the Froude number. The kinematic wave approximation was reasonably accurate except at the channel boundaries and for small values of KF²₀ (≤1). The accuracy of these approximations was significantly influenced by the downstream boundary condition both in terms of the error magnitude and the segment of the channel reach for which these approximations would be applicable. © 1997 by John Wiley & Sons, Ltd.     

Estimation of daily space–time precipitation series for macroscale hydrological modelling

An important problem in modelling macroscale basins, especially for sparsely observed regions, is the lack of precipitation information. Alternatives to using straightforward interpolated surface observations include the utilization of more advanced interpolation techniques and the use of additional precipitation information from atmospheric models. Conventional and geostatistical methods are applied for optimal interpolation and assimilation of observed and model precipitation. Various time-series of daily areal precipitation distributions are produced and compared using not only an internal precipitation validation, but also an objective verification based on stream flow simulations. The Mackenzie River Basin in north-western Canada is used as the study area and hydrological simulations are carried out with the model SLURP. It was found that better interpolation techniques and the use of combined precipitation data can improve the hydrological simulations and that the enhancements are related to the relative size of the simulation units used. © 1998 John Wiley & Sons, Ltd.     

Response of hydrology to climate change in the southern Appalachian Mountains using Bayesian inference

Predicting long‐term consequences of climate change on hydrologic processes has been limited due to the needs to accommodate the uncertainties in hydrological measurements for calibration, and to account for the uncertainties in the models that would ingest those calibrations and uncertainties in climate predictions as basis for hydrological predictions. We implemented a hierarchical Bayesian (HB) analysis to coherently admit multiple data sources and uncertainties including data inputs, parameters, and model structures to identify the potential consequences of climate change on soil moisture and streamflow at the head watersheds ranging from low to high elevations in the southern Appalachian region of the United States. We have considered climate change scenarios based on three greenhouse gas emission scenarios of the Interovernmental Panel on Climate Change: A2, A1B, and B1 emission scenarios. Full predictive distributions based on HB models are capable of providing rich information and facilitating the summarization of prediction uncertainties. With predictive uncertainties taken into account, the most pronounced change in soil moisture and streamflow would occur under the A2 scenario at both low and high elevations, followed by the A1B scenario and then by the B1 scenario. Uncertainty in the change of soil moisture is less than that of streamflow for each season, especially at high elevations. A reduction of soil moisture in summer and fall, a reduction or slight increase of streamflow in summer, and an increase of streamflow in winter are predicted for all three scenarios at both low and high elevations. The hydrological predictions with quantified uncertainties from a HB model could aid more‐informed water resource management in developing mitigation plans and dealing with water security under climate change. Copyright © 2012 John Wiley & Sons, Ltd.     

Mean equatorial gravity derived from various geopotential models

Summary Mean equatorial gravity has been computed from geopotential models GEM-10C, GEM-7, GEM-T1, GEM-T2, GEM-T3, JGM-1, JGM-2, JGM-3 and OSU91A and compared to the normal equatorial gravity, _e=978 032·699 × 10^–5 m s^–2, computed from four given parameters defining the Earth's level ellipsoid. In all models g_e>_e.     

Bed load transport in braided gravel-bed stream models

Bed load transport rate was measured in ten self-formed small-scale gravel braided streams developed in a laboratory flume at several different values of steady discharge and flume gradient. The streams are approximate Froude models of typical prototype braided streams but of no particular river. Slight viscous effects may be present in the models because particle Reynolds numbers are close to 70. Total bed load discharge was measured every fifteen minutes throughout each 60 hour run. In addition, 80 channel cross-sections were measured in each run to establish the average channel geometry. Total bed load transport rate correlates well with total discharge and total stream power, although at a given stream power bed load discharge is greater when braiding is less intense and the width/depth ratio is lower. Analysis using unit stream power and cross-section average bed shear stress reveals that the laboratory data conform to existing empirical bed load transport relationships. However, comparison with field data from gravel-bed rivers shows discrepancies that may be due to differences in bed material size gradation and bed sediment structure. At constant discharge, wide fluctuations in bed load discharge occur with some regularity. Periods range from 2 to 10 hours in the models, which is equivalent to several tens of hours in a prototype. The presence of these long-period fluctuations compounds the problems of field measurement of bed load in braided streams.     

Vertical distribution features of atmospheric water vapour in the Po valley area

Two sets of radiosounding measurements, taken at different hours from some stations in the Po Valley area, were examined in order to obtain the values of precipitable waterw and determine the shapes of the vertical distribution curves of absolute humidity. From these curves, we calculated the bestfit values of scale heightsH ₁ andH ₂ in the 0÷5 km and 5÷10 km altitude intervals, respectively. The analysis of the radiosounding data clearly shows that parametersw andH ₁ are closely related to the evolutionary features of the meteorological conditions on synoptic scale and are influenced, to a lesser extent, by the diurnal variations in the atmospheric ground layer. Seasonal average curves of temperature and absolute humidity, as functions of altitude, were also defined from the radiosounding measurements taken at various hours of the day. Moreover, interpolation methods in time (applied to a 12-hour range) and in space (range of about 300 km) were proposed for determining parametersw andH ₁ from the radiosounding measurements taken at different hours from the same station or from different stations at the same hour. Reliability tests, made by comparing the same station or from different stations at the same hour. Reliability tests, made by comparing the values given by the interpolation methods with those directly obtained from the radiosounding measurements, show that these evaluations ofw andH ₁ are affected by standard errors of estimate, which are comparable to the errors usually made in analyzing the radiosounding data.