Development of an operational low-flow index for hydrological drought monitoring over Europe. Issue 3 (17th February 2017)

• Record Type: Journal Article
• Authors: Cammalleri, Carmelo; Vogt, Jürgen; Salamon, Peter
• Is Part Of: Hydrological sciences journal. Volume 62:Issue 3(2017)
• Page Start: 346
• Page End: 358
• Publication Date: 2017-02-17
• Subjects: Streamflow drought -- European Drought Observatory (EDO) -- LISFLOOD model; Hydrology -- Periodicals; 551.4805
• DOI: 10.1080/02626667.2016.1240869
• Languages: English
• ISSNs: 0262-6667

Abstract

ABSTRACT: Near real-time monitoring of hydrological drought requires the implementation of an index capable of capturing the dynamic nature of the phenomenon. Starting from a dataset of modelled daily streamflow data, a low-flow index was developed based on the total water deficit of the discharge values below a certain threshold. In order to account for a range of hydrological regimes, a daily 95th percentile threshold was adopted, which was computed by means of a 31-day moving window. The observed historical total water deficits were statistically fitted by means of the exponential distribution and the corresponding probability values were used as a measure of hydrological drought severity. This approach has the advantage that it directly exploits daily streamflow values, as well as allowing a near real-time update of the index at regular time steps (i.e. 10 days, or dekad). The proposed approach was implemented on discharge data simulated by the LISFLOOD model over Europe during the period 1995–2015; its reliability was tested on four case studies found within the European drought reference database, as well as against the most recent summer drought observed in Central Europe in 2015. These validations, even if only qualitative, highlighted the ability of the index to capture the timing (starting date and duration) of the main historical hydrological drought events, and its good performance in comparison with the commonly used standardized runoff index (SRI). Additionally, the spatial evolution of the most recent event was captured well in a simulated near real-time test case, suggesting the suitability of the index for operational implementation within the European Drought Observatory.