Baez-Villanueva, O. M., Zambrano-Bigiarini, M., Miralles, D. G., Beck, H. E., Siegmund, J. F., Alvarez-Garreton, C., et al. (2024). On the timescale of drought indices for monitoring streamflow drought considering catchment hydrological regimes. Hydrol. Earth Syst. Sci., 28(6), 1415–1439.
Abstract: There is a wide variety of drought indices, yet a consensus on suitable indices and temporal scales for monitoring streamflow drought remains elusive 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 suitable 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 examined 100 near-natural catchments in Chile with four hydrological regimes, using the standardised precipitation index (SPI), standardised precipitation evapotranspiration index (SPEI), empirical standardised soil moisture index (ESSMI), and standardised snow water equivalent index (SWEI), aggregated across various temporal scales. Cross-correlation and event coincidence analysis were applied between these indices and the standardised streamflow index at a temporal scale of 1 month (SSI-1), as representative of streamflow drought events. Our results underscore that there is not a single drought index and temporal scale best suited to characterise all streamflow droughts in Chile, and their suitability largely depends on catchment memory. Specifically, in snowmelt-driven catchments characterised by a slow streamflow response to precipitation, the SPI at accumulation periods of 12-24 months serves as the best proxy for characterising streamflow droughts, with median correlation and coincidence rates of approximately 0.70-0.75 and 0.58-0.75, respectively. In contrast, the SPI at a 3-month accumulation period is the best proxy over faster-response rainfall-driven catchments, with median coincidence rates of around 0.55. Despite soil moisture and snowpack being key variables that modulate the propagation of meteorological deficits into hydrological ones, meteorological indices are better proxies for streamflow drought. Finally, to exclude the influence of non-drought periods, we recommend using the event coincidence analysis, a method that helps assessing the suitability of meteorological, soil moisture, and/or snow drought indices as proxies for streamflow drought events.
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Sanchez, R., Briones, M. J., Gamboa, A., Monsalve, R., Berroeta, D., & Valenzuela, L. (2023). Delimitation of burned areas in Chile based on dNBR thresholds adjusted according to region and land cover. Rev. de Teledeteccion, 61, 43–58.
Abstract: The delimitation of burned areas is an important step for the study of forest fires, and the use of satellite remote sensing allows a scalable methodology. Previous studies use a dNBR threshold to determine the presence of burned areas, but this threshold is affected by vegetation variability determined by the geography of the study area and land use coverage. For them, the difference in the normalized index of burned areas (dNBR) was used to study the mega fires that affected the central zone of Chile in the summer of 2017. An automated methodology was developed that, based on satellite images and polygons of the burned areas provided by the National Forestry Corporation of Chile (CONAF) generates a set of dNBR thresholds differentiated by administrative region and land use. The application of differentiated dNBR thresholds significantly improves the accuracy of the burnt area delimitation model, although it does not achieve satisfactory results for all land uses. This methodological advance will make it possible to improve the design and control of policies for the prevention, conservation and restoration of ecosystems affected by forest fires.
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