Distributed dynamic modelling of interrill overland flow

A distributed, dynamic, process-based model for interrill overland flow that has previously been shown to predict accurately both total runoff and runoff hydraulics for a site on semi-arid shrubland is assessed in terms of (i) its portability, (ii) its sensitivity to the quality of data inputs, and (iii) its sensitivity to the size of cell used in the model. It is found that the model can be used at another site, but only after modifications to take account of the local controls of runoff routing. The model is portable, but not readily so. The model is sensitive to both the quality of data input and the size of cell. Data input cannot be reduced by use of stochastic distribution of model parameters without significant loss of accuracy in model predictions, particularly of runoff hydraulics. Larger cells produce poorer predictions of the runoff hydrograph. It is concluded that process-based modelling of interrill runoff may not be a realistic tool for predicting soil erosion, but is one that may be useful for identification of our present poor understanding of erosion processes. Such models help to define the research agenda for soil erosion studies. © 1997 John Wiley & Sons, Ltd.     

Uncertainty and multiple objective calibration in regional water balance modelling: case study in 320 Austrian catchments

We examine the value of additional information in multiple objective calibration in terms of model performance and parameter uncertainty. We calibrate and validate a semi‐distributed conceptual catchment model for two 11‐year periods in 320 Austrian catchments and test three approaches of parameter calibration: (a) traditional single objective calibration (SINGLE) on daily runoff; (b) multiple objective calibration (MULTI) using daily runoff and snow cover data; (c) multiple objective calibration (APRIORI) that incorporates an a priori expert guess about the parameter distribution as additional information to runoff and snow cover data. Results indicate that the MULTI approach performs slightly poorer than the SINGLE approach in terms of runoff simulations, but significantly better in terms of snow cover simulations. The APRIORI approach is essentially as good as the SINGLE approach in terms of runoff simulations but is slightly poorer than the MULTI approach in terms of snow cover simulations. An analysis of the parameter uncertainty indicates that the MULTI approach significantly decreases the uncertainty of the model parameters related to snow processes but does not decrease the uncertainty of other model parameters as compared to the SINGLE case. The APRIORI approach tends to decrease the uncertainty of all model parameters as compared to the SINGLE case. Copyright © 2006 John Wiley & Sons, Ltd.     

Assessing the impact of the hydraulic properties of a crusted soil on overland flow modelling at the field scale

Soil surface crusts are widely reported to favour Hortonian runoff, but are not explicitly represented in most rainfall‐runoff models. The aim of this paper is to assess the impact of soil surface crusts on infiltration and runoff modelling at two spatial scales, i.e. the local scale and the plot scale. At the local scale, two separate single ring infiltration experiments are undertaken. The first is performed on the undisturbed soil, whereas the second is done after removal of the soil surface crust. The HYDRUS 2D two‐dimensional vertical infiltration model is then used in an inverse modelling approach, first to estimate the soil hydraulic properties of the crust and the subsoil, and then the effective hydraulic properties of the soil represented as a single uniform layer. The results show that the crust hydraulic conductivity is 10 times lower than that of the subsoil, thus illustrating the limiting role the crust has on infiltration. Moving up to the plot scale, a rainfall‐runoff model coupling the Richards equation to a transfer function is used to simulate Hortonian overland flow hydrographs. The previously calculated hydraulic properties are used, and a comparison is undertaken between a single‐layer and a double‐layer representation of the crusted soil. The results of the rainfall‐runoff model show that the soil hydraulic properties calculated at the local scale give acceptable results when used to model runoff at the plot scale directly, without any numerical calibration. Also, at the plot scale, no clear improvement of the results can be seen when using a double‐layer representation of the soil in comparison with a single homogeneous layer. This is due to the hydrological characteristics of Hortonian runoff, which is triggered by a rainfall intensity exceeding the saturated hydraulic conductivity of the soil surface. Consequently, the rainfall‐runoff model is more sensitive to rainfall than to the subsoil's hydrodynamic properties. Therefore, the use of a double‐layer soil model to represent runoff on a crusted soil does not seem necessary, as the increase of precision in the soil discretization is not justified by a better performance of the model. Copyright © 2005 John Wiley & Sons, Ltd.     

Uncertainty quantization of meteorological input and model parameters for hydrological modelling using a Bayesian-based integrated approach

The traditional treatment of uncertainty in hydrological modelling primarily attributes it to model parameters, but rarely systematically considers meteorological input errors, especially in quantifying the impact of meteorological input errors on parameter uncertainty. This study developed a Bayesian-based integrated approach to quantitatively investigate uncertainties in meteorological inputs (precipitation and temperature) and model parameters as well as the variation in parameter uncertainty due to meteorological input errors. Additionally, we analysed the propagation from these uncertainties to runoff response in snowmelt and non-snowmelt periods. The applicability and advantages of this approach were presented by applying of the Soil and Water Assessment Tool to the Shitoukoumen Reservoir Catchment. Differential Evolution Adaptive Metropolis-Markov Chain Monte Carlo was applied for the straightforward Bayesian inference the uncertainties of meteorological inputs and model parameters. On this basis, multilevel factorial analysis technology was used to quantitatively investigate the specific impact of the model parameters' individual and interactive effects due to meteorological input errors. Finally, the impact of meteorological input errors and model parameter uncertainty on the model performance were analysed and quantified systematically. The results showed that the meteorological input errors could affect the random characteristics of multiple model parameters. Moreover, meteorological input errors could further affect the model parameters' effects on annual average runoff. Overall, the above results have significant implications in enhancing hydrological model to simulate/predict runoff and understanding hydrological processes during different periods.     

Uncertainty in index flood modelling due to calibration data sizes

Regional frequency analysis is an important tool in estimating design flood for ungauged catchments. Index flood is an important component in regionalized flood formulas. In the past, many formulas have been developed based on various numbers of calibration catchments (e.g. from less than 20 to several hundred). However, there is a lack of systematic research on the model uncertainties caused by the number of calibration catchments (i.e. what is the minimum number of calibration catchment? and how should we choose the calibration catchments?). This study uses the statistical resampling technique to explore the impact of calibration catchment numbers on the index flood estimation. The study is based on 182 catchments in England and an index flood formula has been developed using the input variable selection technique in the data mining field. The formula has been used to explore the model uncertainty due to a range of calibration catchment numbers (from 15 to 130). It is found that (1) as expected, the more catchments are used in the calibration, the more reliable of the models developed are (i.e. with a narrower band of uncertainty); (2) however, poor models are still possible with a large number of calibration catchments (e.g. 130). In contrast, good models with a small number of calibration catchments are also achievable (with as low as 15 calibration catchments). This indicates that the number of calibration catchments is only one of the factors influencing the model performance. The hydrological community should explore why a smaller calibration data set could produce a better model than a large calibration data set. It is clear from this study that the information content in the calibration data set is equally if not more important than the number of calibration data. Copyright © 2011 John Wiley & Sons, Ltd.     

Capabilities and limitations of detailed hillslope hydrological modelling

Hillslope hydrological modelling is considered to be of great importance for the understanding and quantification of hydrological processes in hilly or mountainous landscapes. In recent years a few comprehensive hydrological models have been developed at the hillslope scale which have resulted in an advanced representation of hillslope hydrological processes (including their interactions), and in some operational applications, such as in runoff and erosion studies at the field scale or lateral flow simulation in environmental and geotechnical engineering. An overview of the objectives of hillslope hydrological modelling is given, followed by a brief introduction of an exemplary comprehensive hillslope model, which stimulates a series of hydrological processes such as interception, evapotranspiration, infiltration into the soil matrix and into macropores, lateral and vertical subsurface soil water flow both in the matrix and preferential flow paths, surface runoff and channel discharge. Several examples of this model are presented and discussed in order to determine the model's capabilities and limitations. Finally, conclusions about the limitations of detailed hillslope modelling are drawn and an outlook on the future prospects of hydrological models on the hillslope scale is given.The model presented performed reasonable calculations of Hortonian surface runoff and subsequent erosion processes, given detailed information of initial soil water content and soil hydraulic conditions. The vertical and lateral soil moisture dynamics were also represented quite well. However, the given examples of model applications show that quite detailed climatic and soil data are required to obtain satisfactory results. The limitations of detailed hillslope hydrological modelling arise from different points: difficulties in the representations of certain processes (e.g. surface crusting, unsaturated–saturated soil moisture flow, macropore flow), problems of small‐scale variability, a general scarcity of detailed soil data, incomplete process parametrization and problems with the interdependent linkage of several hillslopes and channel–hillslope interactions. Copyright © 1999 John Wiley & Sons, Ltd.     

The value of environmental modelling languages for building distributed hydrological models

An evaluation is made of the suitability of programming languages for hydrological modellers to create distributed, process‐based hydrological models. Both system programming languages and high‐level environmental modelling languages are evaluated based on a list of requirements for the optimal programming language for such models. This is illustrated with a case study, implemented using the PCRaster environmental modelling language to create a distributed, process‐based hydrological model based on the concepts of KINEROS‐EUROSEM. The main conclusion is that system programming languages are not ideal for hydrologists who are not computer programmers because the level of thinking of these languages is too strongly related to specialized computer science. A higher level environmental modelling language is better in the sense that it operates at the conceptual level of the hydrologist. This is because it contains operators that identify hydrological processes that operate on hydrological entities, such as two‐dimensional maps, three‐dimensional blocks and time‐series. The case study illustrates the advantages of using an environmental modelling language as compared with system programming languages in fulfilling requirements on the level of thinking applied in the language, the reusability of the program code, the lack of technical details in the program, a short model development time and learnability. The study shows that environmental modelling languages are equally good as system programming languages in minimizing programming errors, but are worse in generic application and performance. It is expected that environmental modelling languages will be used in future mainly for development of new models that can be tailored to modelling aims and the field data available. Copyright © 2002 John Wiley & Sons, Ltd.     

Quantifying the relative impact of hydrological and hydraulic modelling parameterizations on uncertainty of inundation maps

ABSTRACT

Flood risk management strongly relies on inundation models for river basin zoning in flood-prone and risk-free areas. Floodplain zoning is significantly affected by the diverse and concurrent uncertainties that characterize the modelling chain used for producing inundation maps. In order to quantify the relative impact of the uncertainties linked to a lumped hydrological (rainfall–runoff) model and a FLO-2D hydraulic model, a Monte Carlo procedure is proposed in this work. The hydrological uncertainty is associated with the design rainfall estimation method, while the hydraulic model uncertainty is associated with roughness parameterization. This uncertainty analysis is tested on the case study of the Marta coastal catchment in Italy, by comparing the different frequency, extent and depth of inundation simulations associated with varying rainfall forcing and/or hydraulic model roughness realizations. The results suggest a significant predominance of the hydrological uncertainty with respect to the hydraulic one on the overall uncertainty associated with the simulated inundation maps.     

Uncertainty analysis of flood inundation modelling using GLUE with surrogate models in stochastic sampling

A generalized likelihood uncertainty estimation (GLUE) method incorporating moving least squares (MLS) with entropy for stochastic sampling (denoted as GLUE‐MLS‐E) was proposed for uncertainty analysis of flood inundation modelling. The MLS with entropy (MLS‐E) was established according to the pairs of parameters/likelihoods generated from a limited number of direct model executions. It was then applied to approximate the model evaluation to facilitate the target sample acceptance of GLUE during the Monte‐Carlo‐based stochastic simulation process. The results from a case study showed that the proposed GLUE‐MLS‐E method had a comparable performance as GLUE in terms of posterior parameter estimation and predicted confidence intervals; however, it could significantly reduce the computational cost. A comparison to other surrogate models, including MLS, quadratic response surface and artificial neural networks (ANN), revealed that the MLS‐E outperformed others in light of both the predicted confidence interval and the most likely value of water depths. ANN was shown to be a viable alternative, which performed slightly poorer than MLS‐E. The proposed surrogate method in stochastic sampling is of practical significance in computationally expensive problems like flood risk analysis, real‐time forecasting, and simulation‐based engineering design, and has a general applicability in many other numerical simulation fields that requires extensive efforts in uncertainty assessment. Copyright © 2014 John Wiley & Sons, Ltd.     

Spatially distributed observations in constraining inundation modelling uncertainties

The performance of two modelling approaches for predicting floodplain inundation is tested using observed flood extent and 26 distributed floodplain level observations for the 1997 flood event in the town of Usti nad Orlici in the Czech Republic. Although the one‐dimensional hydrodynamic model and the integrated one‐ and two‐dimensional model are shown to perform comparably against the flood extent data, the latter shows better performance against the distributed level observations. Comparable performance in predicting the extent of inundation is found to be primarily as a result of the urban reach considered, with flood extent constrained by road and railway embankments. Uncertainty in the elevation model used in both approaches is shown to have little effect on the reliability in predicting flood extent, with a greater impact on the ability in predicting the distributed level observations. These results show that reliability of flood inundation modelling in urban reaches, where flood risk assessment is of more interest than in more rural reaches, can be improved greatly if distributed observations of levels in the floodplain are used in constraining model uncertainties. Copyright © 2005 John Wiley & Sons, Ltd.     

Systems modelling of stratospheric ozone transport and photochemistry

A scheme of a system of physical and chemical processes controlling the production, transport and destruction of ozone and its gaseous catalysts, as well as other related gases in the low and high stratosphere is presented. An account is made of temperature variations of the stratospheric layer resulting from changes in ozone content; also included is the effect of temperature variations on photochemical reaction rates and ozone and other gases transport between atmospheric layers. Parameters describing major relations of the system are inferred from the analysis of ozone and trace gas data and from the results of model calculations of interdependence between variations in temperature and ozone content of the layer.An analysis of minor fluctuations of the linearized system shows that photochemical processes are responsible for its aperiodic stability and that gas transport between atmospheric layers destabilizes the system.     

Evaluation of satellite-based rainfall products for hydrological modelling in Morocco

ABSTRACT

Several satellite-based precipitation estimates are becoming available at a global scale, providing new possibilities for water resources modelling, particularly in data-sparse regions and developing countries. This work provides a first validation of five different satellite-based precipitation products (TRMM-3B42 v6 and v7, RFE 2.0, PERSIANN-CDR, CMORPH1.0 version 0.x) in the 1785 km² Makhazine catchment (Morocco). Precipitation products are first compared against ground observations. Ten raingauges and four different interpolation methods (inverse distance, nearest neighbour, ordinary kriging and residual kriging with altitude) were used to compute a set of interpolated precipitation reference fields. Second, a parsimonious conceptual hydrological model is considered, with a simulation approach based on the random generation of model parameters drawn from existing parameter set libraries, to compare the different precipitation inputs. The results indicate that (1) all four interpolation methods, except the nearest neighbour approach, give similar and valid precipitation estimates at the catchment scale; (2) among the different satellite-based precipitation estimates verified, the TRMM-3B42 v7 product is the closest to observed precipitation, and (3) despite poor performance at the daily time step when used in the hydrological model, TRMM-3B42 v7 estimates are found adequate to reproduce monthly dynamics of discharge in the catchment. The results provide valuable perspectives for water resources modelling of data-scarce catchments with satellite-based rainfall data in this region.

Editor M.C. Acreman; Associate editor N. Verhoest     

Effects of the catchment runoff coefficient on the performance of TOPMODEL in rainfall–runoff modelling

Effects of the catchment runoff coefficient on the performance of TOPMODEL in simulating catchment rainfall–runoff relationships are investigated in this paper, with an aim to improve TOPMODEL's simulation efficiency in catchments with a low runoff coefficient. Application of TOPMODEL in the semi‐arid Yihe catchment, with an area of 2623 km² in the Yellow River basin of China, produced a Nash–Sutcliffe model efficiency of about 80%. To investigate how the catchment runoff coefficient affects the performance of TOPMODEL, the whole observed discharge series of the Yihe catchment is multiplied with a larger‐than‐unity scale factor to obtain an amplified discharge series. Then TOPMODEL is used to simulate the amplified discharge series given the original rainfall and evaporation data. For a set of different scale factors, TOPMODEL efficiency is plotted against the corresponding catchment runoff coefficient and it is found that the efficiency of TOPMODEL increases with the increasing catchment runoff coefficient before reaching a peak (e.g. about 90%); after the peak, however, the efficiency of TOPMODEL decreases with the increasing catchment runoff coefficient. Based on this finding, an approach called the discharge amplification method is proposed to enhance the simulation efficiency of TOPMODEL in rainfall–runoff modelling in catchments with a low runoff coefficient. Copyright © 2004 John Wiley & Sons, Ltd.     

One‐ and two‐dimensional modelling of overland flow in semiarid shrubland,Jornada basin,New Mexico

Two distributed parameter models, a one‐dimensional (1D) model and a two‐dimensional (2D) model, are developed to simulate overland flow in two small semiarid shrubland watersheds in the Jornada basin, southern New Mexico. The models are event‐based and represent each watershed by an array of 1‐m² cells, in which the cell size is approximately equal to the average area of the shrubs. Each model uses only six parameters, for which values are obtained from field surveys and rainfall simulation experiments. In the 1D model, flow volumes through a fixed network are computed by a simple finite‐difference solution to the 1D kinematic wave equation. In the 2D model, flow directions and volumes are computed by a second‐order predictor–corrector finite‐difference solution to the 2D kinematic wave equation, in which flow routing is implicit and may vary in response to flow conditions. The models are compared in terms of the runoff hydrograph and the spatial distribution of runoff. The simulation results suggest that both the 1D and the 2D models have much to offer as tools for the large‐scale study of overland flow. Because it is based on a fixed flow network, the 1D model is better suited to the study of runoff due to individual rainfall events, whereas the 2D model may, with further development, be used to study both runoff and erosion during multiple rainfall events in which the dynamic nature of the terrain becomes an important consideration. Copyright © 2006 John Wiley & Sons, Ltd.     

Influence of landscape aggregation in modelling snow-cover ablation and snowmelt runoff in a sub-arctic mountainous environment

Abstract

Appropriate representation of landscape heterogeneity at small to medium scales is a central issue for hydrological modelling. Two main hydrological modelling approaches, deductive and inductive, are generally applied. Here, snow-cover ablation and basin snowmelt runoff are evaluated using a combined modelling approach that includes the incorporation of detailed process understanding along with information gained from observations of basin-wide streamflow phenomena. The study site is Granger Basin, a small sub-arctic basin in the mountains of the Yukon Territory, Canada. The analysis is based on the comparison between basin-aggregated and distributed landscape representations. Results show that the distributed model based on “hydrological response” landscape units best describes the observed magnitudes of both snow-cover ablation and basin runoff, whereas the aggregated approach fails to represent the differential snowmelt rates and to describe both runoff volumes and dynamics when discontinuous snowmelt events occur.     

Solute transport by surface runoff from low‐angle slopes: theory and application

The removal of chemicals in solution by overland flow from agricultural land has the potential to be a significant source of chemical loss where chemicals are applied to the soil surface, as in zero tillage and surface‐mulched farming systems. Currently, we lack detailed understanding of the transfer mechanism between the soil solution and overland flow, particularly under field conditions. A model of solute transfer from soil solution to overland flow was developed. The model is based on the hypothesis that a solute is initially distributed uniformly throughout the soil pore space in a thin layer at the soil surface. A fundamental assumption of the model is that at the time runoff commences, any solute at the soil surface that could be transported into the soil with the infiltrating water will already have been convected away from the area of potential exchange. Solute remaining at the soil surface is therefore not subject to further infiltration and may be approximated as a layer of tracer on a plane impermeable surface. The model fitted experimental data very well in all but one trial. The model in its present form focuses on the exchange of solute between the soil solution and surface water after the commencement of runoff. Future model development requires the relationship between the mass transfer parameters of the model and the time to runoff to be defined. This would enable the model to be used for extrapolation beyond the specific experimental results of this study. The close agreement between experimental results and model simulations shows that the simple transfer equation proposed in this study has promise for estimating solute loss to surface runoff. Copyright © 2000 John Wiley & Sons, Ltd.     

Stochastic modelling of groundwater flow and solute transport in aquifers

This paper presents an introductory overview of recently developed stochastic theories for tackling spatial variability problems in predicting groundwater flow and solute transport. Advantages and limitations of the theories are discussed. Lastly, strategies based on the stochastic approaches to predict solute transport in aquifers are recommended.     

Numerical modelling of channel migration with application to laboratory rivers

The paper presents the development of a morphological model and its application to experimental model rivers.The model takes into account the key processes of channel migration,including bed deformation,bank failure and wetting and drying.Secondary flows in bends play an important role in lateral sediment transport,which further affects channel migration.A new formula has been derived to predict the near-bed secondary flow speed,in which the magnitude of the speed is linked to the lateral water level gradient.Since only non-cohesive sediment is considered in the current study,the bank failure is modelled based on the concept of submerged angle of repose.The wetting and drying process is modelled using an existing method.Comparisons between the numerical model predictions and experimental observations for various discharges have been made.It is found that the model predicted channel planform and cross-sectional shapes agree generally well with the laboratory observations.A scenario analysis is also carried out to investigate the impact of secondary flow on the channel migration process.It shows that if the effect of secondary flow is ignored,the channel size in the lateral direction will be seriously underestimated.     

Quantification of modelling uncertainty in existing Italian RC frames

Assessment of the seismic performance of existing structures requires due consideration of both aleatory and epistemic sources of uncertainty; the former being typically associated with the randomness in ground motion records and the latter with the uncertainty in numerical modelling. Using a numerical modelling approach calibrated to available experimental test data collected from the literature, the uncertainty associated with different modelling parameters for existing reinforced concrete frames in Italy was quantified via an extensive numerical study. This was done to quantify the propagation of modelling parameter type uncertainty to the overall dispersion of the demand parameters typically used in seismic assessment, namely peak storey drift and peak floor accelerations. In addition, the impact of such modelling uncertainty on the median intensity and dispersion of the collapse fragility function was also examined. From the results of this study, empirical values of modelling parameter uncertainty were quantified with a view to being used in the assessment of existing reinforced concrete frames with masonry infill designed prior to the introduction of seismic design provisions in Italy during the 1970s. Comparing these empirical values to those available in the literature, it is seen how the fundamental behaviour of the frames differs from more modern frames with ductile detailing to the extent that values available in guidelines such as FEMA P58 cannot be reasonably adopted for these structural typologies.