BRANCHING-TYPE MODELS OF FLOW THROUGH POROUS MEDIA

Abstract

Some time ago the authors investigated a random-graph model for explaining the mechanics of flow through porous media. In the present paper this earlier approach is further extended; first, to the discussion of a three-dimensional random-graph model and second, to an investigation of lateral dispersion in porous media. Comparisons with experimental results are given.     

Testing the applicability of a kinematic wave-based distributed hydrological model in two climatically contrasting catchments

Abstract

Steep mountainous areas account for 70% of all river catchments in Japan. To predict river discharge for the mountainous catchments, many studies have applied distributed hydrological models based on a kinematic wave approximation with surface and subsurface flow components (DHM-KWSS). These models reproduce observed river discharge of catchments in Japan well; however, the applicability of a DHM-KWSS to catchments with different geographical and climatic conditions has not been sufficiently examined. This research applied a DHM-KWSS to two river basins that have different climatic conditions from basins in Japan to examine the transferability of the DHM-KWSS model structure. Our results show that the DHM-KWSS model structure explained flow regimes for a wet river basin as well as a large flood event in an arid basin; however, it was unable to explain long-term flow regimes for the arid basin case study.     

Modélisation pluie–débit journalière par des modèles conceptuels et ȁboîte noireȁ; test d’un modèle neuroflou / Daily rainfall–runoff modelling using conceptual and black box models; testing a neuro-fuzzy model

Abstract

Abstract Four rainfall–runoff models were applied on a daily time step and tested in the Cheffia basin, situated in the northeast of Algeria. The models belong to two categories: conceptual models–the GR3j model and the CREC model with eight parameters, and ?black box? models–the ARMAX model and a neuro-fuzzy model, which combines neural structure and fuzzy logic. The models were compared over two periods, one dry and the other wet. This comparison allowed a better model for the rainfall–runoff process to be proposed, on a daily time step, by combining the conceptual approach with a neuro-fuzzy system.     

Fuzzy logic model approaches to daily pan evaporation estimation in western Turkey / Estimation de l’évaporation journalière du bac dans l’Ouest de la Turquie par des modèles à base de logique floue

Abstract

Abstract Evaporation is one of the fundamental elements in the hydrological cycle, which affects the yield of river basins, the capacity of reservoirs, the consumptive use of water by crops and the yield of underground supplies. In general, there are two approaches in the evaporation estimation, namely, direct and indirect. The indirect methods such as the Penman and Priestley-Taylor methods are based on meteorological variables, whereas the direct methods include the class A pan evaporation measurement as well as others such as class GGI-3000 pan and class U pan. The major difficulty in using a class A pan for the direct measurements arises because of the subsequent application of coefficients based on the measurements from a small tank to large bodies of open water. Such difficulties can be accommodated by fuzzy logic reasoning and models as alternative approaches to classical evaporation estimation formulations were applied to Lake Egirdir in the western part of Turkey. This study has three objectives: to develop fuzzy models for daily pan evaporation estimation from measured meteorological data, to compare the fuzzy models with the widely-used Penman method, and finally to evaluate the potential of fuzzy models in such applications. Among the measured meteorological variables used to implement the models of daily pan evaporation prediction are the daily observations of air and water temperatures, sunshine hours, solar radiation, air pressure, relative humidity and wind speed. Comparison of the classical and fuzzy logic models shows a better agreement between the fuzzy model estimations and measurements of daily pan evaporation than the Penman method.     

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.     

Investigations du caractère multifractal des débits maximaux annuels de crue / Investigation of multifractality of maximum annual flood discharges

Abstract

Abstract The multifractal analysis of maximum annual flood discharges at 55 stations of the Tunisian gauging network allows one to associate the various statistical moments of surface discharges of the basins through a scale-invariant law. On this basis, a random cascades model is identified. The scale-invariant law obtained for extreme values represents a theoretical foundation for empirical models proposed since the 1960s which link extreme values, and their associated hazards, with surfaces of drainage areas.     

USE OF PRECIPITATION RECORDS IN THE CORRELATION OF STREAMFLOW RECORDS

Abstract

An empirical study using three pairs of stream basins in Eastern United States showed that the regression of monthly streamflow from one basin on that from a nearby basin generally was improved by use of a regression model which included, as an additional variable, the difference in precipitation on the two basins.     

Improving streamflow estimation in ungauged basins using a multi-modelling approach

ABSTRACT

In this study, a multi-modelling approach is proposed for improved continuous daily streamflow estimation in ungauged basins using regionalization—the process of transferring hydrological data from gauged to ungauged watersheds. Four regionalization models, two data-driven and two hydrological, were used for continuous daily streamflow estimation. Comparison of the individual models reveals that each of the four models performed well on a limited number of ungauged basins while none of them performed well for the entire 90 selected watersheds. The results obtained from the four models are evaluated and reported in a deterministic way by a model combination approach along with its uncertainty range consisting of 16 ensemble members. It is shown that a combined model of the four individual models performed well on all 90 watersheds and the ensemble range can account for the uncertainty of models. The combined model was more efficient and appeared more robust compared to the individual models. Furthermore, continuous ranked probability scores (CRPS) calculated for the ensemble model outputs indicate better performance compared to individual models and competitive with the combined model.

EDITOR A. Castellarin ASSOCIATE EDITOR G. Di Baldassarre     

Pulse generation models for daily intermittent streamflows / Modèles de génération d’impulsions pour des débits journaliers intermittents

Abstract

Abstract Generating pulses and then converting them into flow are two main steps of daily streamflow generation. Three pulse generation models have been proposed on the basis of Markov chains for the purpose of generating daily intermittent streamflow time series in this study. The first one is based on two two-state Markov chains, whereas the second uses a three-state Markov chain. The third model uses harmonic analysis and fits Fourier series to the three-state Markov chain. Results for a daily intermittent streamflow data series show a good performance of the proposed models.     

Data time-step dependency of conceptual rainfall—streamflow model parameters: an empirical study with implications for regionalisation

Abstract

Employing 1-, 2-, 4-, 6-, 12- and 24-hourly data sets for two catchments (10.6 and 298 km²) in Wales, the calibrated parameters of a unit hydrograph-based model are shown to change substantially over that range of data time steps. For the smaller basin, each model parameter reaches, or approaches, a stable value as the data time step decreases, providing a straightforward method of estimating time-step independent model parameter values. For the larger basin, the model parameters also reach, or approach, stable values using hourly data, but, for reasons given in the paper, interpretation of the results is more difficult. Model parameter sensitivity analyses are presented that give insights into the relative precision on the parameters for both catchments. The paper discusses the importance of accounting for model parameter data time-step dependency in pursuit of a reduction in the uncertainty associated with estimates of flow in ungauged basins, and suggests that further work along these lines be undertaken using different catchments and models.     

Regional models of flow-duration curves of perennial and intermittent streams and their use for calibrating the parameters of a rainfall–runoff model

Abstract

One of the main challenges faced by hydrologists and water engineers is the estimation of variables needed for water resources planning and management in ungauged river basins. To this end, techniques for transposing information, such as hydrological regional analyses, are widely employed. A method is presented for regionalizing flow-duration curves (FDCs) in perennial, intermittent and ephemeral rivers, based on the extended Burr XII probability distribution. This distribution shows great flexibility to fit data, with accurate reproduction of flow extremes. The performance analysis showed that, in general, the regional models are able to synthesize FDCs in ungauged basins, with a few possible drawbacks in the application of the method to intermittent and ephemeral rivers. In addition to the regional models, we summarize the experience of using synthetic FDCs for the indirect calibration of the Rio Grande rainfall–runoff model parameters in ungauged basins.

Editor D. Koutsoyiannis

Citation Costa, V., Fernandes, W., and Naghettini, M., 2013. Regional models of flow-duration curves of perennial and intermittent streams and their use for calibrating the parameters of a rainfall–runoff model. Hydrological Sciences Journal, 59 (2), 262–277.     

Improving generalization of artificial neural networks in rainfall–runoff modelling / Amélioration de la généralisation de réseaux de neurones artificiels pour la modélisation pluie-débit

Abstract

Artificial neural networks (ANNs) are general-purpose techniques that can be used for nonlinear data-driven rainfall–runoff modelling. The key issue to construct a good model by means of ANNs is to understand their structural features and the problems related to their construction. Indeed, the quantity and quality of data, the type of noise and the mathematical properties of the algorithm for estimating the usual large number of parameters (weights) are crucial for the generalization performances of ANNs. However, it is well known that ANNs may suffer from poor generalization properties due to the high number of parameters and non-Gaussian data noise. Therefore, in the first part of this paper, the features and problems of ANNs are discussed. Eight Avoiding Overfitting Techniques are then presented, considering that these are methods for improving the generalization of ANNs. For this reason, they have been tested on two case studies—rainfall–runoff data from two drainage basins in the south of Italy—in order to gain insight into their properties and to investigate if there is one that absolutely gives the best performance.     

DISCONTINUITY OF DISCHARGE OF UKRAINIAN RIVERS

Synopsis

The application of mathematical models for simulating the processes of the hydrological cycle is considered and the results of applying a translated version of the stanford watershed model to the River Clyde in Scotland are presented.     

Simple water balance modelling of surface reservoir systems in a large data-scarce semiarid region / Modélisation simple du bilan hydrologique de systèmes de réservoirs de surface dans une grande région semi-aride pauvre en données

Abstract

Abstract Water resources in dryland areas are often provided by numerous surface reservoirs. As a basis for securing future water supply, the dynamics of reservoir systems need to be simulated for large river basins, accounting for environmental change and an increasing water demand. For the State of Ceará in semiarid Northeast Brazil, with several thousands of reservoirs, a simple deterministic water balance model is presented. Within a cascade-type approach, the reservoirs are grouped into six classes according to storage capacity, rules for flow routing between reservoirs of different size are defined, and water withdrawal and return flow due to human water use is accounted for. While large uncertainties in model applications exist, particularly in terms of reservoir operation rules, model validation against observed reservoir storage volumes shows that the approach is a reasonable simplification to assess surface water availability in large river basins. The results demonstrate the large impact of reservoir storage on downstream flow and stress the need for a coupled simulation of runoff generation, network redistribution and water use.     

Soil moisture assessment in the alluvial basins associated with seismic activity of northwest Anatolia,Turkey, using Landsat TM/ETM satellite imagery / Estimation de l’humidité du sol associée à l’activité sismique dans les bassins alluviaux du nord-ouest de l’Anatolie (Turquie) par l’imagerie satellitaire Landsat TM/ETM

Abstract

Abstract The aim of this study is to detect seasonal surface temperature changes and to estimate soil moisture conditions based on the evaporative cooling principle of damp ground in the alluvial basins of northwest Anatolia, Turkey, using Landsat TM/ETM data. According to analysis of satellite sensor data acquired on different dates, soil moisture is greatest in the spring season in the basins. Soil moisture decreases toward the summer and autumn. The 17 August 1999 earthquake occurred in the high surface temperature (low soil moisture) period, and the 12 November 1999 earthquake occurred in the low surface temperature (high soil moisture) period. It is possible to conclude that the urban-rural settlements and industrial developments on the loose deposits of the Adapazari, ?zmit and Düzce depressions have been affected by the seasonal changes in the local ground conditions.     

Effects of temporal resolution on hydrological model parameters and its impact on prediction of river discharge / Effets de la résolution temporelle sur les paramètres d'un modèle hydrologique et impact sur la prévision de l'écoulement en rivière

Abstract

Temporal resolution of rainfall plays an important role in determining the hydrological response of river basins. Rainfall temporal variability can be considered as one of the most critical elements when dealing with input data of rainfall—runoff models. In this paper, a typical lumped rainfall—runoff model is applied to long- and short-term runoff prediction using rainfall data sets with different temporal resolution, including daily, hourly and 10-min interval data, and the dependency of model performance on the time interval of the rainfall data is discussed. Furthermore, the effect of temporal resolution on model parameter values is analysed. As results, rainfall data with shorter temporal resolution provide better performance in short-term river discharge estimation, especially for storm discharge estimation. The most accurate results are obtained on the peak discharge and recession part of the hydrograph by using 10-min interval rainfall data. It is concluded that model parameter values are influenced not only by the temporal resolution of calculation but also by the rainfall intensity—duration relationship. This study provides useful information about determination of hydrological model parameters using data of different temporal resolutions.     

Incorporating groundwater recharge and discharge functions into an existing monthly rainfall–runoff model/Incorporation de fonctions de recharge et de vidange superficielle de nappes au sein d’un modèle pluie-débit mensuel existant

Abstract

Abstract There is an urgent need for an integrated surface water and groundwater modelling tool that is suitable for southern African conditions and can be applied at various basin scales for broad strategic water resource planning purposes. The paper describes two new components (recharge and groundwater discharge) that have been added to an existing monthly time-step rainfall–runoff model that is widely used in the southern African subcontinent. The new components are relatively simple, consistent with the existing model formulation, but based on accepted groundwater flow principles and well understood groundwater parameters. The application of the revised model on two basins in southern Africa with quite different baseflow characteristics has demonstrated that the new components have a great deal of potential, even if the improvement is only to be able to simulate the groundwater baseflow component of total runoff more explicitly. More comprehensive testing and comparison of the results with existing groundwater and geohydrological data is required, while some extensions to the new components need to be considered to ensure that the model can be considered applicable to a wide range of basin and climate types.     

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.     

Comparison of grey and phase-space rainfall forecasting models using a fuzzy decision method / Comparaison grâce à une méthode de décision floue des modèles gris et d’espace des phases pour la prévision de pluie

Abstract

Abstract This work applies a fuzzy decision method to compare the performance of the grey model with that of the phase-space model, in forecasting rainfall one to three hours ahead. Four indices and two statistical tests are used to evaluate objectively the performance of the forecasting models. However, a trade-off must be made in choosing a suitable model because various indices may lead to different judgements. Therefore, a fuzzy decision model was applied to solve this problem and to make the optimum decision. The results of fuzzy decision making demonstrate that the grey model outperforms the phase-space model for forecasting one hour ahead, but the phase-space model performs better for forecasting two or three hours ahead.     

Prediction of base flows from basin characteristics: a case study from Zimbabwe / Prévision de débits de base à partir de caractéristiques du bassin: une étude de cas au Zimbabwe

Abstract

Abstract Base flows make up the flows of most rivers in Zimbabwe during the dry season. Prediction of base flows from basin characteristics is necessary for water resources planning of ungauged basins. Linear regression and artificial neural networks were used to predict the base flow index (BFI) from basin characteristics for 52 basins in Zimbabwe. Base flow index was positively related to mean annual precipitation (r = 0.71), basin slope (r = 0.76), and drainage density (r = 0.29), and negatively related to mean annual evapotranspiration (r = –0.74), and proportion of a basin with grasslands and wooded grasslands (r = –0.53). Differences in lithology did not significantly affect BFI. Linear regression and artificial neural networks were both suitable for predicting BFI values. The predicted BFI was used in turn to derive flow duration curves of the 52 basins and with R ² being 0.89–0.99.