Identification of Hydrological Droughts in Lithuanian Rivers

Gintarė Kugytė, Gintaras Valiuškevičius
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引用次数: 2

Abstract

Globally, hydrological droughts are most commonly identified based on various indices calculated from water flow values. However, the water flow rate is calculated from a flow rate curve that needs to be updated constantly, so it takes a long time to resolve its true value. For this reason, the possibility of identifying a hydrological drought on the basis of hourly and prompt treated water levels seems much more attractive. 8 water gauging stations (WGS) operating along 7 important rivers and covering the hydrological areas of visas in the Lithuanian region were selected for the study. In this study, a modified SPI function of the R programming language SPEI package (traditionally used to calculate the standardized precipitation index, SPI) was applied for the streamflow drought index (SDI) calculations. Given how it was applied to the SDI calculation, just like the baseline data, this was the ten-day mean water flow and then the water level. The suitability of water level data for SDI calculations was assessed by analyzing the relationships between SWLI (Standartized Water Level Index) calculated from water level data and SDI calculated from water flow information. SWLI and SDI in all 8 WGS are closely interconnected. It was found that the possibility of recurrence of droughts of different severity identified by both methods is significantly influenced by the profile of the river bed in a specific section. In areas where riverbanks have steeper slopes, the SWLI and SDI similarly describes the water situation and the recurrence of droughts. It is believed that a modified SDI methodology (SWLI), which is based on water level data, may become a good alternative in our country for identifying hydrological droughts. Keywords: Lithuanian rivers, hydrological drought, identification of droughts, water level, SDI, SWLI.
立陶宛河流水文干旱的鉴定
在全球范围内,水文干旱最常用的识别方法是根据水流值计算的各种指数。但是,水流的流量是根据流量曲线计算的,需要不断更新,因此需要较长的时间来求解其真实值。因此,根据每小时和及时处理过的水位确定水文干旱的可能性似乎更有吸引力。研究选择了沿7条重要河流运行的8个水位监测站(WGS),覆盖立陶宛地区签证的水文区域。本研究采用R编程语言SPEI包(传统上用于计算标准化降水指数SPI)的改进SPI函数,对径流干旱指数(SDI)进行计算。考虑到如何将其应用于SDI计算,就像基线数据一样,这是十天的平均水流量,然后是水位。通过分析水位数据计算的标准化水位指数(SWLI)与水流信息计算的SDI之间的关系,评价水位数据对SDI计算的适用性。所有8个WGS的SWLI和SDI密切相关。研究发现,两种方法确定的不同严重程度的干旱再次发生的可能性受到特定河段河床剖面的显著影响。在河岸坡度较陡的地区,swi和SDI同样描述了水资源状况和干旱的复发情况。基于水位数据的改进SDI方法(SWLI)可能成为我国识别水文干旱的一种较好的替代方法。关键词:立陶宛河流,水文干旱,干旱识别,水位,SDI, SWLI
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