Critical drought intensity-duration-frequency curves based on total probability theorem-coupled frequency analysis

Abstract

A methodology using the standardised precipitation index is proposed to develop critical drought intensity-duration-frequency (IDF) curves. We define dry periods within which we recognise droughts of different durations. The most severe drought for each drought duration in each year is called the critical drought. The total probability theorem-coupled frequency analysis is used to determine the bestfit probability distribution function of drought severity, which is then converted to intensity. The generalised extreme value probability distribution function is found to best fit the critical drought severity. The methodology is implemented using monthly precipitation data for a meteorological station in Turkey. The critical drought intensity decreases linearly with increasing drought duration, whereas the return period increases exponentially when the drought becomes more severe. The site-specific IDF curves furnished with an empirical relationship between the intensity and return period allow one to characterise the drought not by an index-based intensity but by its return period. This kind of presentation is physically easier to understand, in particular for stakeholders and decision makers in practice.

SPI-Based Drought Classification in Italy: Influence of Different Probability Distribution Functions

“…Coherently with the IDF used for defining the design storm intensity [29], the drought IDF curves provide a link between three essential characteristics of drought events, that are, intensity (or severity), duration and frequency of occurrence. Such tool has been applied over the last years in several countries, by using different approaches [30][31][32][33].…”

Intermittency as an indicator of drought in streamflow and groundwater

“…For example; the excessive use of freshwater, the industrial and agricultural water needs, and the alteration on land use and land cover characteristics due to urbanization cause changes in the water balance of river basins, often in the form of droughts which is a big concern for the future. Therefore, intensive research efforts have been performed to better understand the drought through conceptualization, modelling, and case studies (Aksoy et al, 2021; Cavus & Aksoy, 2019, 2020; Eris et al, 2020; Mishra & Singh, 2010; Song et al, 2021; van Loon, 2015). A large number of economic sectors such as agriculture, energy, industry, tourism, ecology, etc.…”

“…We conduct this study based on a large gathering of local‐scale data to prove the hypothesis, and to understand how drought in streamflow and groundwater might be triggered. Monthly precipitation, monthly temperature, daily streamflow, and monthly groundwater level data were acquired from three river basins in Turkey where drought was investigated recently by Aksoy et al (2018), Cetin et al (2018), Cavus (2019), Cavus and Aksoy (2019, 2020), Eris et al (2020), Aksoy et al (2021). For Gediz and Ergene river basins, frequency analysis of low flows in intermittent rivers was also investigated by Eris et al (2019) and the daily flow duration curves were modelled by Burgan and Aksoy (2022).…”

“…In this study, a databased analysis was performed to understand how streamflow discharge and groundwater level change with intermittency, and if the intermittency can be taken as an indicator for drought in streamflow and groundwater. We conduct this study based on a large gathering Eris et al (2020), Aksoy et al (2021). For Gediz and Ergene river basins, frequency analysis of low flows in intermittent rivers was also investigated by Eris et al (2019) and the daily flow duration curves were modelled by Burgan and Aksoy (2022).…”

The impacts of climate changes on watershed streamflow and total dissolved nitrogen in Danjiang Watershed, China

“…The changes reflecting on the watershed scale will result in changes in local precipitation and temperature, which in turn would modify the watershed hydrochemical process and lead to changes in streamflow and non-point source pollution features (Arab Amiri & Gocić2021). A higher drought or flood risk can be observed in different regions owing to heavier evapotranspiration, earlier and more snowmelt, and extreme precipitation (Aksoy et al 2021;. In addition, more non-point source pollution loads can be observed in most farmland-dominated watersheds, leading to higher risks of water quality degradation and eutrophication.…”