用于水文分析和水力设计的间歇性流域高流量和低流量频率曲线

IF 3.9 3区 环境科学与生态学 Q1 ENGINEERING, CIVIL Stochastic Environmental Research and Risk Assessment Pub Date : 2024-05-09 DOI:10.1007/s00477-024-02732-0
Gokhan Sarigil, Yonca Cavus, Hafzullah Aksoy, Ebru Eris
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引用次数: 0

摘要

研究了日溪流数据流量持续时间曲线 (FDC) 的上百分位数和下百分位数,以绘制频率曲线。高流量采用超标概率为 1%、5% 和 10%的上百分位数(Q1、Q5、Q10),低流量采用不超标概率为 10%、5% 和 1%的下百分位数(Q90、Q95、Q99)。中位值(Q50)用于代表溪流的平均状况。对 FDC 的较低百分位数采用了基于总概率定理的混频分析,并将零值考虑在内。案例研究针对土耳其西部库库克-门德斯河流域的三个间歇性溪流测量站(SGS)进行。总体评估结果表明,各 SGS 的最佳拟合概率分布函数在低流量时变化不大,而在高流量时,每个 SGS 都有自己的概率分布函数。利用确定的概率分布函数计算了不同重现期的上百分位数、下百分位数和中位数。计算值绘制成大流量百分位数和小流量百分位数的频率曲线。频率曲线在高流量和低流量条件下的水文分析、水资源管理和水力设计中具有重要的实用价值。它们还有待于进一步开发,以实现区域化,其适用性也可扩展到流域内的非测量地点。
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Frequency curves of high and low flows in intermittent river basins for hydrological analysis and hydraulic design

Upper and lower percentiles of Flow Duration Curves (FDCs) of daily streamflow data were investigated to develop frequency curves. Upper percentiles with exceedance probability of 1, 5 and 10% (Q1, Q5, Q10) were used for high flows, and lower percentiles with non-exceedance probability of 10, 5 and 1% (Q90, Q95, Q99) for low flows. Median value (Q50) was covered to represent the average conditions of streamflow. A mixed frequency analysis based on the total probability theorem taking zero values into account was applied for the lower percentiles of FDC. Case studies were performed for three intermittent Streamflow Gauging Stations (SGSs) from Kucuk Menderes River Basin in western Turkey. An overall assessment of results shows that the best-fit probability distribution function does not change from one SGS to another considerably for low flows while each SGS has its own probability distribution function for high flows. Upper and lower percentiles, and median value were calculated at various return periods by using the identified probability distribution functions. The calculated values were plotted in the form of frequency curves of high flow percentiles and low flow percentiles. The frequency curves have a practically significant potential use in hydrological analysis, water resources management and hydraulic design under high and low flow conditions. They are yet open to further development for regionalization and their applicability can be extended to ungauged sites in river basins.

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来源期刊
CiteScore
7.10
自引率
9.50%
发文量
189
审稿时长
3.8 months
期刊介绍: Stochastic Environmental Research and Risk Assessment (SERRA) will publish research papers, reviews and technical notes on stochastic and probabilistic approaches to environmental sciences and engineering, including interactions of earth and atmospheric environments with people and ecosystems. The basic idea is to bring together research papers on stochastic modelling in various fields of environmental sciences and to provide an interdisciplinary forum for the exchange of ideas, for communicating on issues that cut across disciplinary barriers, and for the dissemination of stochastic techniques used in different fields to the community of interested researchers. Original contributions will be considered dealing with modelling (theoretical and computational), measurements and instrumentation in one or more of the following topical areas: - Spatiotemporal analysis and mapping of natural processes. - Enviroinformatics. - Environmental risk assessment, reliability analysis and decision making. - Surface and subsurface hydrology and hydraulics. - Multiphase porous media domains and contaminant transport modelling. - Hazardous waste site characterization. - Stochastic turbulence and random hydrodynamic fields. - Chaotic and fractal systems. - Random waves and seafloor morphology. - Stochastic atmospheric and climate processes. - Air pollution and quality assessment research. - Modern geostatistics. - Mechanisms of pollutant formation, emission, exposure and absorption. - Physical, chemical and biological analysis of human exposure from single and multiple media and routes; control and protection. - Bioinformatics. - Probabilistic methods in ecology and population biology. - Epidemiological investigations. - Models using stochastic differential equations stochastic or partial differential equations. - Hazardous waste site characterization.
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