Are artificial neural network techniques relevant for the estimation of longitudinal dispersion coefficient in rivers? / Les techniques de réseaux de neurones artificiels sont-elles pertinentes pour estimer le coefficient de dispersion longitudinale en rivières?

Abstract

Abstract Accurate application of the longitudinal dispersion model requires that specially designed experimental studies are performed in the river reach under consideration. Such studies are usually very expensive, so in order to quantify the longitudinal dispersion coefficient, as an alternative approach, various researchers have proposed numerous empirical formulae based on hydraulic and morphometric characteristics. The results are presented of the application of artificial neural networks as a parameter estimation technique. Five different cases were considered with the network trained for different arrangements of input nodes, such as channel depth, channel width, cross-sectionally averaged water velocity, shear velocity and sinuosity index. In the case where the sinuosity index is included as an input node, the results turned out to be better than those presented by other authors.     

Relations indices de Végétation–Pluie au Burkina Faso: Cas du Bassin Versant du Nakambé/Relationship between Rainfall and Vegetation Indexes in Burkina Faso: A Case Study of the Nakambé Basin

Abstract

This work deals with the problem of the use of remote sensing data derived from NOAA/AVHRR observations for monitoring the West African Sahel climatic variability. NDVI is widely used in hydrological and climatological research, and in the study of global climatic changes. The relationships between NDVI and climatic parameters are not well established yet and are the focus of many studies. The relationships between NDVI and rainfall were studied at a 10-day time step in the Nakambe River basin in Burkina Faso in the Sahelo-Sudanian area over the years 1982–1999. Good correlations were found in the annual evolution of these two variables. The statistical analysis shows a significant relationship between NDVI and the sum of the annual rainfall with determination coefficients greater than 0.80. At the spatial scale of 0.5° × 0.5°, the determination coefficient ranges from 0.91 to 0.96. It was also found that the NDVI is a good indicator of the determination of the beginning and the end of the rainy season. It gives reasonably good results in comparison with the other methods commonly used in the study region.     

Trend detection in river flow series: 1. Annual maximum flow / Détection de tendance dans des séries de débit fluvial: 1. Débit maximum annuel

Abstract

Results of a study on change detection in hydrological time series of annual maximum river flow are presented. Out of more than a thousand long time series made available by the Global Runoff Data Centre (GRDC) in Koblenz, Germany, a worldwide data set consisting of 195 long series of daily mean flow records was selected, based on such criteria as length of series, currency, lack of gaps and missing values, adequate geographical distribution, and priority to smaller catchments. The analysis of annual maximum flows does not support the hypothesis of ubiquitous growth of high flows. Although 27 cases of strong, statistically significant increase were identified by the Mann-Kendall test, there are 31 decreases as well, and most (137) time series do not show any significant changes (at the 10% level). Caution is advised in interpreting these results as flooding is a complex phenomenon, caused by a number of factors that can be associated with local, regional, and hemispheric climatic processes. Moreover, river flow has strong natural variability and exhibits long-term persistence which can confound the results of trend and significance tests.     

Influences of coupled wind–water processes on suspended sediment grain size: an example from tributaries of the Yellow River / Influences de processus couplés éoliens-hydriques sur la granulométrie des matières en suspension: exemple d'affluents du Fleuve Jaune

Abstract

Some unique coupled wind–water erosion processes exist in the desert-loess transitional zone in the middle Yellow River basin. Based on data from 40 stations on 29 rivers, a study was made on the influence of such processes on suspended sediment grain-size characteristics of the tributaries of the Yellow River. Results show that the percentage of >0.05-mm grain size decreases with the increased annual mean precipitation, but increases with the increase in the annual mean number of sand-dust storm days. The percentage of <0.01-mm grain size increases with the increase in the annual mean precipitation, but decreases with the increase in the annual number of sand-dust storm days. Based on annual mean data from 40 stations, multiple regression equations were established between the percentages of >0.05-mm grain size (r _>0.05) and <0.01-mm grain size (r _<0.01), annual mean precipitation (P _m) and annual mean number of sand-dust storm days (D _ss). On this basis, the relative contributions of the variations in D _ss and P _m to the variation in r _>0.05 and r _<0.01 were estimated. The results indicate that the variation in sand-dust storm frequency exerts greater influences on the variation in grain-size characteristics of suspended load than does the variation in annual mean precipitation. With the increase in the coupled wind–water processes index, expressed by P _m/D _ss, the percentage of >0.05-mm grain size in suspended sediment decreases and the percentage of <0.01-mm grain size increases. With the variation in P _m/D _ss, different combinations of r _>0.05 with r _<0.01 appear, which have some influence on the formation of hyperconcentrated flows. There exist some optimal ratios of coarse to fine fractions in suspended sediment that make sediment concentrations of hyperconcentrated flows the highest. The optimal r _>0.05/r _<0.01 value is related to some range of the index P _m/D _ss. When the P _m/D _ss index falls in this range, the optimum combination of relative coarse with fine sediments in the suspended load appears, and thus results in the peak values of sediment concentration.     

Pluie ou neige? Dispositif de mesures pluviographiques dans les Andes de Bolivie et interprétation des enregistrements/Rainfall or snowfall? Device for measuring the precipitation phase in the Bolivian Andes and analysis of the records

Abstract

Abstract The knowledge of the precipitation phase, solid or liquid, is important in high mountains, in order to use models of water and energy balances. During an experiment led in the Bolivian Andes, a complete weather station was installed at an altitude close to 4800 m, including two raingauge recorders, the first one with added antifreeze and oil, based on weight measurement, and the other one with tipping buckets. This device allowed a realistic partition of the liquid and solid phases in this region of tropical mountains, where the observed snow pack at the ground level is strongly influenced by the extremely high solar radiation and where the snow cover is ephemeral. The automation of the ?raingauges? method, compared with several other classical methods, shows satisfactory results.     

Partial L-moments for the analysis of censored flood samples / Utilisation des L-moments partiels pour l’analyse d’échantillons tronqués de crues

Abstract

Abstract A parameter estimation method is proposed for fitting the generalized extreme value (GEV) distribution to censored flood samples. Partial L-moments (PL-moments), which are variants of L-moments and analogous to ?partial probability weighted moments?, are defined for the analysis of such flood samples. Expressions are derived to calculate PL-moments directly from uncensored annual floods, and to fit the parameters of the GEV distribution using PL-moments. Results of Monte Carlo simulation study show that sampling properties of PL-moments, with censoring flood samples of up to 30% are similar to those of simple L-moments, and also that both PL-moment and LH-moments (higher-order L-moments) have similar sampling properties. Finally, simple L-moments, LH-moments, and PL-moments are used to fit the GEV distribution to 75 annual maximum flow series of Nepalese and Irish catchments, and it is found that, in some situations, both LH- and PL-moments can produce a better fit to the larger flow values than simple L-moments.     

Accounting for sparsely observed rainfall space—time variability in a rainfall—runoff model of a semiarid Tunisian basin/Prise en compte d'observations peu denses de la variabilité spatiotemporelle de la pluie dans une modélisation pluie—débit d'un bassin semi-aride Tunisien

Abstract

The management of water excesses and deficits is a major task in semiarid Mediterranean regions, where the variability of rainfall inputs is high at different time and space scales. Thus intense hydrometeorological events, which generate both potential resource and hazards, are of major interest. A simple method is proposed, with the example of the Skhira basin (192 km²) in central Tunisia, to account for the event space–time variability of rainfall in a rainfall–runoff model, in order to check its influence on the shape, magnitude and timing of resulting hydrographs. The transfer function used is a geomorphology-based unit hydrograph with an explicit territorial significance. Simulations made for highly variable events show the relevance of this method, seen as the first step of a downward approach, and its robustness with respect to the quality and the density of rainfall data.     

A revised approach to the UKIH method for the calculation of baseflow / Une approche améliorée de la méthode de l'UKIH pour le calcul de l'écoulement de base

Abstract

A revised approach to the calculation of baseflow using the method originally proposed by the United Kingdom Institute of Hydrology is presented. The revisions resolve two aspects of the method that lead to less than optimal results; that is, the calculation of values of baseflow that exceed the corresponding values of streamflow and the dependence of the calculated values on the origin of the five-day segmentation of the input streamflow data. The approach is illustrated using streamflow monitoring information that is typical for areas of southern Ontario, Canada, where baseflow is primarily the result of groundwater discharge.     

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.     

Assessing uncertainties in a conceptual water balance model using Bayesian methodology / Estimation bayésienne des incertitudes au sein d’une modélisation conceptuelle de bilan hydrologique

Abstract

Abstract The aim of this study was to estimate the uncertainties in the streamflow simulated by a rainfall–runoff model. Two sources of uncertainties in hydrological modelling were considered: the uncertainties in model parameters and those in model structure. The uncertainties were calculated by Bayesian statistics, and the Metropolis-Hastings algorithm was used to simulate the posterior parameter distribution. The parameter uncertainty calculated by the Metropolis-Hastings algorithm was compared to maximum likelihood estimates which assume that both the parameters and model residuals are normally distributed. The study was performed using the model WASMOD on 25 basins in central Sweden. Confidence intervals in the simulated discharge due to the parameter uncertainty and the total uncertainty were calculated. The results indicate that (a) the Metropolis-Hastings algorithm and the maximum likelihood method give almost identical estimates concerning the parameter uncertainty, and (b) the uncertainties in the simulated streamflow due to the parameter uncertainty are less important than uncertainties originating from other sources for this simple model with fewer parameters.