On the time scale of meteorological, soil moisture, and snow drought indices to assess streamflow drought over catchments with different hydrological regime: a case study using a hundred Chilean catchments

Abstract. A wide variety of drought indices exist today without consensus on suitable indices and temporal scales for monitoring streamflow drought across diverse hydrological settings. Considering the growing interest in spatially-distributed indices for ungauged areas, this study addresses the following questions: i) what temporal scales of precipitation-based indices are most adequate to assess streamflow drought in catchments with different hydrological regimes?, ii) do soil moisture indices outperform meteorological indices as proxies for streamflow drought?, iii) are snow indices more effective than meteorological indices for assessing streamflow drought in snow-influenced catchments? To answer these questions, we used one hundred near-natural catchments with four main types of hydrological regimes. The Standardised Precipitation Index (SPI), Standardised Precipitation and Evapotranspiration Index (SPEI), Empirical Standardised Soil Moisture Index (ESSMI), and standardised Snow Water Equivalent Index (SWEI) were computed across various time scales over the catchments for 1979–2020. Cross-correlation and event coincidence analysis were applied between these indices and the Standardised Streamflow Index at a temporal scale of one month (SSI-1), as representative of streamflow drought events. Finally, the linear correlation values and precursor coincidence rates were analysed for all catchments simultaneously, and separated by the hydrological regime. Our results indicate that i) there is no single meteorological, soil moisture, or snow drought index and temporal scale that could be used to characterise all streamflow droughts across Chile, and ii) the greater the snow influence in a catchment, the larger the temporal scale of the drought index to be used as proxy of streamflow drought. Finally, to avoid considering the influence of non-drought periods when analysing time series of drought indices, we suggest that future studies use the event coincidence analysis to evaluate which meteorological, soil moisture, and/or snow drought indices can be used as proxies of streamflow drought events.