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基于贝叶斯正则化BP神经网络的DEM趋势面逼近

趋势面从宏观上揭示了研究对象的特性,在各领域发挥着重要作用。BP神经网络可以对复杂系统进行无限逼近,进而进行预测。建立了基于贝叶斯正则化BP神经网络的数字高程模型趋势面,与二次多项式建立的数字高程模型趋势面进行比较分析,证明了该方法的可行性和有效性。     

气候变化对江河流量变化趋势影响研究进展

气候变化对基于自然稳定气候假定的流量变化趋势的检测和水资源评价方法提出了挑战。在流量变化趋势的检测中分离出气候变化的影响,不仅对水资源管理和水利工程设计有重要的应用价值,而且有助于了解气候变化以何种方式、在何时、何地、已经或尚未对水文循环产生影响,对改进气候模型的模拟与预测有重要的科学价值。 统计方法是检验流量变化趋势显著性的有效工具。直接用气候模型模拟和预测未来径流变化的可靠性取决于模型对当代降水模拟的可信度。多个气候模型集合分析有可能在一定程度上减少模型对降水、径流模拟的不确定性。近年发展起来的多个气候模型集合分析与统计显著性检验技术结合的方法,有可能模拟并预测出气候强迫导致大尺度径流空间分布的变化。随着气候模型尤其是陆—气耦合的区域气候模型对降水模拟的改进,可以预见径流变化的检测、归因和预测的趋同化模拟已为期不远。将温室气体外强迫导致的水文气候变化作为一个因子引入到水资源评价中,对于水资源管理经济与生态评估,以及未来的发展规划将是一件十分重要的变革。      

Flood seasonality across Scandinavia—Evidence of a shifting hydrograph?

Fluvial flood events have substantial impacts on humans, both socially and economically, as well as on ecosystems (e.g., hydroecology and pollutant transport). Concurrent with climate change, the seasonality of flooding in cold environments is expected to shift from a snowmelt‐dominated to a rainfall‐dominated flow regime. This would have profound impacts on water management strategies, that is, flood risk mitigation, drinking water supply, and hydro power. In addition, cold climate hydrological systems exhibit complex interactions with catchment properties and large‐scale climate fluctuations making the manifestation of changes difficult to detect and predict. Understanding a possible change in flood seasonality and defining related key drivers therefore is essential to mitigate risk and to keep management strategies viable under a changing climate. This study explores changes in flood seasonality across near‐natural catchments in Scandinavia using circular statistics and trend tests. Results indicate strong seasonality in flooding for snowmelt‐dominated catchments with a single peak occurring in spring and early summer (March through June), whereas flood peaks are more equally distributed throughout the year for catchments located close to the Atlantic coast and in the south of the study area. Flood seasonality has changed over the past century seen as decreasing trends in summer maximum daily flows and increasing winter and spring maximum daily flows with 5–35% of the catchments showing significant changes at the 5% significance level. Seasonal mean daily flows corroborate those findings with higher percentages (5–60%) of the catchments showing statistically significant changes. Alterations in annual flood occurrence also point towards a shift in flow regime from snowmelt‐dominated to rainfall‐dominated with consistent changes towards earlier timing of the flood peak (significant for 25% of the catchments). Regionally consistent patterns suggest a first‐order climate control as well as a local second‐order catchment control, which causes inter‐seasonal variability in the streamflow response.     

Investigation into the daily precipitation variability in the Yangtze River Delta,China

In this article, by using the daily precipitation data measured at 58 meteorological stations, spatial and temporal variability of daily precipitation including zero rainfall values (called “precipitation”) and without zero rainfall values (called “rain”) and four precipitation extrema (P₀, P₂₀, P₅₀, and P₁₀₀ representing the daily precipitation with the magnitude smaller than 0.1 mm, bigger than 20 mm, 50 mm, and 100 mm per day, respectively) in the Yangtze River Delta (YRD) during 1958–2007 were analyzed, and the effects of urbanization were further investigated. Results indicate that (i) differing from the downward trends in 1958–1985, daily precipitation and rain in 1986–2007 show slowly downward trends in the mid YRD but show upward trends in the northern and southern YRD. (ii) Spatial and temporal variability of the rain is more complex than daily precipitation. Both of them become smaller but show more obvious fluctuations in 1986–2007. (iii) Urbanizations cause not only the urban rainfall island problem but also more obvious fluctuations of rain intensity in the mid YRD, reflecting more uncertainty of daily precipitation variability. (iv) Urbanizations have little effects on the variability of P₀ and P₁₀₀ but cause notable increases of P₂₀ and P₅₀. (v) The spatial variability of daily precipitation and precipitation extrema in 1958–1985 clearly shows a breakpoint at 30°20′N latitude, but the breakpoint disappears afterward because of the effects of urbanization. Copyright © 2012 John Wiley & Sons, Ltd.     

A study of variability of annual river flow of the southern African region

Abstract

Variability of river flow is investigated in 502 river flow gauging stations in nine countries of the southern African region with a view to document the spatial variability of the river flow regimes. Those regions where there is strong evidence of declining or increasing trend in annual runoff have been identified. The study has shown that runoff in the region ranges from over 320 mm year^?1 in the Lower Zambezi and the highlands of Tanzania to less than 10 mm year^?1 in the deserts of Namibia and the Kalahari. There is also evidence of declining runoff in parts of Zambia, Angola, Mozambique and the High Veld in South Africa. The recent decline seems to have started from around 1975.     

Low and high flow analyses and wavelet application for characterization of the Blue Nile River system

The low and high flow characteristic of the Blue Nile River (BNR) basin is presented. The study discusses low and high flow, flow duration curve (FDC) and trend analysis of the BNR and its major tributaries. Different probability density functions were fitted to better describe the low and high flows of the BNR and major tributaries in the basin. Wavelet analysis was used in understanding the variance and frequency‐time localization and detection of dominant oscillations in rainfall and flow. FDCs were developed, and low flow (below 50% exceedance) and high flow (over 75% exceedance) of the curves were analysed and compared. The Gravity Recovery and Climate Experiment (GRACE) satellite‐based maps of monthly changes in gravity converted to water equivalents from 2003 to 2006 for February, May and September showed an increase in the moisture influx in the BNR basin for the month of September, and loss of moisture in February and May. It was also shown that 2004 and 2005 were drier with less moisture influx compared to 2003 and 2006. On the basis of the Kolmogorov‐Smirnov, Anderson‐Darling and Chi‐square tests, Gen. Pareto, Frechet 3P, Log‐normal, Log‐logistics, Fatigue Life and Phased Bi‐Weibull distributions best describe the low and high flows within the BNR basin. This will be beneficial in developing flow hydrographs for similar ungauged watersheds within the BNR basin. The below 50% and above 75% exceedance on the FDC for five major rivers in addition to the BNR showed different characteristics depending on size, land cover, topography and other factors. The low flow frequency analysis of the BNR at Bahir Dar showed 0·55 m³/s as the monthly low flow with recurrence interval of 10 years. The wavelet analysis of the rainfall (at Bahir Dar and basin‐wide) and flows at three selected stations shows inter‐ and intra‐annual variability of rainfall and flows at various scales. Copyright © 2009 John Wiley & Sons, Ltd.     

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.     

Discrete wavelet‐based trend identification in hydrologic time series

Trend identification is a substantial issue in hydrologic series analysis, but it is also a difficult task in practice due to the confusing concept of trend and disadvantages of methods. In this article, an improved definition of trend was given as follows: ‘a trend is the deterministic component in the analysed data and corresponds to the biggest temporal scale on the condition of giving the concerned temporal scale’. It emphasizes the intrinsic and deterministic properties of trend, can clearly distinguish trend from periodicities and points out the prerequisite of the concerned temporal scale only by giving which the trend has its specific meaning. Correspondingly, the discrete wavelet‐based method for trend identification was improved. Differing from those methods used presently, the improved method is to identify trend by comparing the energy difference between hydrologic data and noise, and it can simultaneously separate periodicities and noise. Furthermore, the improved method can quantitatively estimate the statistical significance of the identified trend by using proper confidence interval. Analyses of both synthetic and observed series indicated the identical power of the improved method as the Mann–Kendall test in assessing the statistical significance of the trend in hydrologic data, and by using the former, the identified trend can adaptively reflect the nonlinear and nonstationary variability of hydrologic data. Besides, the results also showed the influences of three key factors (wavelet choice, decomposition level choice and noise content) on discrete wavelet‐based trend identification; hence, they should be carefully considered in practice. Copyright © 2012 John Wiley & Sons, Ltd.