Uncertainty,entropy, scaling and hydrological stochastics. 2. Time dependence of hydrological processes and time scaling / Incertitude,entropie, effet d'échelle et propriétés stochastiques hydrologiques. 2. Dépendance temporelle des processus hydrologiques et échelle temporelle

Abstract

The well-established physical and mathematical principle of maximum entropy (ME), is used to explain the distributional and autocorrelation properties of hydrological processes, including the scaling behaviour both in state and in time. In this context, maximum entropy is interpreted as maximum uncertainty. The conditions used for the maximization of entropy are as simple as possible, i.e. that hydrological processes are non-negative with specified coefficients of variation and lag-one autocorrelation. In the first part of the study, the marginal distributional properties of hydrological processes and the state scaling behaviour were investigated. This second part of the study is devoted to joint distributional properties of hydrological processes. Specifically, it investigates the time dependence structure that may result from the ME principle and shows that the time scaling behaviour (or the Hurst phenomenon) may be obtained by this principle under the additional general condition that all time scales are of equal importance for the application of the ME principle. The omnipresence of the time scaling behaviour in numerous long hydrological time series examined in the literature (one of which is used here as an example), validates the applicability of the ME principle, thus emphasizing the dominance of uncertainty in hydrological processes.     

Middle pleistocene variations in palaeoclimate,palaeoenvironment and vegetation of the las tablas de daimiel national park (Spain)

The Middle Pleistocene palaeoclimate and palaeoenvironment evolution of the Las Tablas de Daimiel wetlands is described using a combination of sedimentology, pollen and δ¹³C and δ¹⁸O isotopic records of Unit B of core LT‐199906. This unit mostly contains fluvial and palustrine sediments. U/Th and amino acid racemization (AAR) dating and a comparison of the δ¹⁸O curve of Unit B with oceanic records suggests that Unit B spans the period from the end of Marine Isotope Stage (MIS) 10 (340 ka) to the first stages of MIS 7 (ca. 210 ka). MIS 9 was characterised by a regional vegetation dominated by Cupressaceae, with Pinus as a tree element. The water level was high and temperatures were very probably higher than during the Holocene. MIS 8 and the first substages of MIS 7 (7e, 7d and 7c) were dominated by xerophilous steppe vegetation in lowlands (elevations around 610 m above sea level) near to the wetland. At higher altitudes, far away from the wetland, there were fewer Pinus than in MIS 9, and a greater presence of warm, temperate and cool climate tree elements. The aquatic system in MIS 9 became shallower, with eutrophication and the accumulation of organic matter occurring; temperatures were similar to or lower than those of the Holocene. Copyright © 2011 John Wiley & Sons, Ltd.     

Relationship between precipitation phase and air temperature: comparison between the Bolivian Andes and the Swiss Alps / Relation entre phase de précipitation et température de l'air: comparaison entre les Andes Boliviennes et les Alpes Suisses

Abstract

Determining the precipitation phase—rain or snow—is an important factor in modelling discharge in mountainous basins. In a study carried out in the outer tropical Andes Cordillera of Bolivia, half-hourly determination of precipitation phase was obtained by applying a suitable expert system, taking 11 meteorological parameters into consideration that are measured over 21 months at an altitude close to 4800 m. Straightforward relationships between the determined precipitation phase and observed air temperature were analysed in histograms that contain percentage occurrences of snowfall, rainfall and mixed precipitation events for 0.5°C air temperature increments. The graph shows a nearly identical distribution of percentage occurrences of snowfall in the Andes to that on a 1600-m high site in the Swiss Alps. This result suggests that, for hydrological modelling purposes in the outer tropical Andes, the same rain/snow threshold temperature as in the compared Swiss site can be applied.     

Trend detection in river flow series: 2. Flood and low-flow index series / Détection de tendance dans des séries de débit fluvial: 2. Séries d'indices de crue et d'étiage

Abstract

Major floods in Europe and North America during the past decade have provoked the question of whether or not they are an effect of a changing climate. This study investigates changes in observational data, using up to 100-year-long daily mean river flow records at 21 stations worldwide. Trends in seven flood and low-flow index series are assessed using Mann-Kendall and linear regression methods. Emphasis was on the comparison of trends in these flow index series, particularly in peak-over-threshold (POT) series as opposed to annual maximum (AM) river flow series. There is a larger number of significant trends in the AM than in the POT flood magnitude series, probably relating to the way the series are constructed. Low flood peaks occurring at the beginning or end of a time series with trend may be too low to be selected for the POT analysis. However, one peak per year will always be selected for the AM series, making the slope steeper and/or the series longer, resulting in a more significant trend. There is no general pattern of increasing or decreasing numbers or magnitudes of floods, but there are significant increases in half of the low-flow series.     

An integrated approach to the estimation of streamflow drought quantiles / Une méthode intégrée d’estimation des quantiles de sécheresse hydrologique

Abstract

Abstract An approach was developed for combining streamflow drought information from synthetic (generated) data with data reconstructed based on palaeoclimatic information (tree ring widths). The tree ring data were used to reconstruct streamflow in periods when no streamflow data were collected. The reconstructed data were then used as a source of historical data for estimating drought severity quantiles. The generated data were obtained using a nearest neighbour resampling method while the tree ring reconstruction was accomplished using a regression model. The application of the approach was to data from the Athabasca River in Alberta, Canada. The results demonstrate the feasibility and the utility of the approach for obtaining more accurate and precise estimates of extreme drought severity quantiles.     

Modelling uncertainties in short-term reservoir operation using fuzzy sets and a genetic algorithm / Modélisation d’incertitudes dans la gestion de barrage à court terme grâce à des ensembles flous et à un algorithme génétique

Abstract

Abstract Various uncertainties are inherent in modelling any reservoir operation problem. Two of these are addressed in this study: uncertainty involved in the expression of reservoir penalty functions, and uncertainty in determining the target release value. Fuzzy set theory was used to model these uncertainties where the preferences of the decision maker for the fuzzified parameters are expressed as membership functions. Nonlinear penalty functions are used to determine the penalties due to deviations from targets. The optimization was performed using a genetic algorithm with the objectives to minimize the total penalty and to maximize the level of satisfaction of the decision maker with fuzzified input parameters. The proposed formulation was applied to the problem of finding the optimal release and storage values, taking Green reservoir in Kentucky, USA as a case study. The approach offers more flexibility to reservoir decision-making by demonstrating an efficient way to represent subjective uncertainties, and to deal with non-commensurate objectives under a fuzzy multi-objective environment.     

Soil moisture estimation using ERS 2 SAR data: a case study in the Solani River catchment/Estimation de l’humidité du sol grâce à des données ERS-2 SAR: étude de cas dans le bassin de la rivière Solani

Abstract

Abstract The information regarding spatial and temporal variation of soil moisture in a catchment is of utmost importance in hydrological, as well as many other studies. Point measurements from gravimetric and other methods for soil moisture determination are insufficient to understand the spatial behaviour of soil moisture in a region. Microwave remote sensing data from active sensors on board various satellites are increasingly being used to map spatial distribution of soil moisture within the 0–10 cm top surface. The northern part of India has a network of large rivers and canals and, therefore, spatial and temporal distribution of soil moisture in this region has a significant bearing on the hydrology of the region. In this paper, results on estimation of soil moisture from an ERS-2 SAR image in the catchment of the Solani River (a tributary to the River Ganga) in and around the town of Roorkee, India, have been presented. The radar backscatter coefficient for each pixel of the image has been modelled from the digital numbers of the SAR image. Gravimetric measurements have been made simultaneously during the satellite pass to determine the concurrent value of volumetric soil moisture at a large number of sample points within the satellite sweep area. The backscatter coefficient is found to vary from –30 dB to –42 dB for a variation in soil moisture from 30 to 75%. Regression analyses between volumetric soil moisture and both the digital numbers and backscatter coefficients were performed. Strong correlations between volumetric soil moisture and digital number were observed with R ² values of 0.84, 0.75 and 0.83 for bare soil, vegetative and combined surfaces, respectively. A similar trend was observed with the relationship between backscatter and volumetric soil moisture with R ² values of 0.60, 0.89 and 0.67 for bare soil, vegetative and combined surfaces, respectively. These results demonstrate the utilization of SAR data for estimation of spatial distribution of soil moisture in the region of the present study.     

Experience of the International Association of Geoanalysts as a Certifying Body

Reference materials (RMs) to support geoanalysis have a long history, dating back to the issuance of G-1 and W-1 in 1951. This paper addresses only one aspect of the most recent part of that history, the experience of the International Association of Geoanalysts (IAG) as a certifying body. In 2002, the Certification Committee of the IAG met in Potsdam to discuss becoming a certifying body able to produce RMs for the geoanalytical community. Following that meeting, the IAG developed and published a protocol to assure that IAG RMs would meet International Organization for Standardization (ISO) guidelines to the fullest extent possible. Many practical problems arise in the application of the recommendations of the ISO Guides to any one specific certification project. The recommendations describe the ideal; achievable reality is always somewhat less than that ideal, presenting a significant challenge to the IAG as a certifying body. This paper will summarise experience to date, while focusing on the most challenging issues, deriving uncertainties compliant with the Guide to Uncertainty in Measurement (GUM) and establishing traceability of certified values (CVs).     

A Modified Neural Network for Improving River Flow Prediction/Un Réseau de Neurones Modifié pour Améliorer la Prévision de L'Écoulement Fluvial

Abstract

Artificial neural network (ANN) models provide huge potential for simulating nonlinear behaviour of hydrological systems. However, the potential of ANN is yet to be fully exploited due to the problems associated with improving the model generalization performance. Generalization refers to the ability of a neural network to correctly process input data that have not been used for calibrating the neural network model. In the hydrological context, better generalization performance implies higher precision of forecasting. The primary objectives of this study are to explore new measures for improving the generalization performance of an ANN-based rainfall–runoff model, and to evaluate the applicability of the new measures. A modified neural network model (entitled goal programming (GP) neural network) for modelling the rainfall–runoff process has been developed, in which three enhancements are made as compared to the widely-used backpropagation (BP) network. The three enhancements are (a) explicit integration of hydrological prior knowledge into the neural network learning; (b) incorporation of a modified training objective function; and (c) reduction of network sensitivity to input errors. Seven watersheds across a range of climatic conditions and watershed areas in China were selected for examining the alternative networks. The results demonstrate that the GP consistently outperformed the BP both in the calibration and verification periods and three proposed measures yielded improvement of performance.     

Temporal dynamics of evapotranspiration in semiarid native forests in Brazil and Spain using remote sensing

Evapotranspiration (ET) plays an important role in integrated water resource planning, development and management. This process is particularly relevant in semiarid regions. The aim of this study is, hence, to compare spatial and temporal patterns of actual ET, as well as the temporal trends in two different semiarid forests, Caatinga (Brazil) and Tierra de Pinares (Spain). We used the surface energy balance algorithm for land (SEBAL) to assess actual evapotranspiration (ET_a) in both areas. In the Brazilian semiarid forest, Caatinga is the main vegetation, while it is Pinares in Spain. For this purpose, 69 Landsat-5 and 42 Landsat-8 images (1995–2019) were used. The Mann–Kendall test was applied to assess the occurrence of trends in precipitation, temperature and potential ET data; and the Temporal Stability Index (TSI) to know which areas have greater seasonal ET_a. The annual amplitude of the potential evapotranspiration (ET₀) is the same in both areas, however, the Caatinga values are higher. In the Caatinga forest, when ET₀ presents its highest values throughout the year, ET_a presents the lowest, and vice versa. In the Pinares forest, ET_a follows the ET₀ dynamics during the year, and the difference between ET₀ and ET_a is maximum during the summer. The Caatinga forest showed a greater spatial variation of ET_a than the Pinares forest as well as a greater extension with lower temporal stability of ET_a than the Pinares forest. Both the Caatinga forest and the Pinares forest showed significant positive trends in annual ET₀ and ET_a. We estimate that the value of ET_a increases more rapidly in Pinares than in the Brazilian Caatinga. Taking Caatinga as a hydrological mirror, some consequences are expected to Pinares, such as significant changes in the water balance, increase of biodiversity vulnerability, and reduction of water availability in soil and reservoirs.