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Novel Drought Hazard Monitoring Framework for Decision Support Under Data Scarcity

8 pagesPublished: September 20, 2018

Abstract

Droughts are among the weather-related disasters, which affects most people around the world. Its large spatial extent and slowly, creeping onset, makes it difficult to define its start and end. Indeed, monitoring and early warning systems for drought hazards are recognized as critical activities of risk governance. Nevertheless, in many regions of the world, the scarcity of direct observations of climatological and hydrological variables, hinder an adequate follow-up and investigation of this phenomenon. This paper introduces a novel framework to generate drought hazard maps and time series, at national and regional levels, based on univariate and multivariate standardized drought indices. Notably, we utilize freely and globally available, gridded datasets of hydrological variables derived from remote sensing and data assimilation systems (e.g., rainfall, soil moisture, streamflow), which are verified against in situ measurements. A good performance of the framework is documented through the comparison of results against observed drought events in Mexico. This paves the road towards its use in other regions of the world, where data scarcity is an issue for drought monitoring activities.

Keyphrases: drought hazard monitoring, drought magnitude, standardized drought indices

In: Goffredo La Loggia, Gabriele Freni, Valeria Puleo and Mauro De Marchis (editors). HIC 2018. 13th International Conference on Hydroinformatics, vol 3, pages 1744-1751.

BibTeX entry
@inproceedings{HIC2018:Novel_Drought_Hazard_Monitoring,
  author    = {Roberto A. Real-Rangel and Adrián Pedrozo-Acuña and J. Agustín Breña-Naranjo and Víctor H. Alcocer-Yamanaka},
  title     = {Novel Drought Hazard Monitoring Framework for Decision Support Under Data Scarcity},
  booktitle = {HIC 2018. 13th International Conference on Hydroinformatics},
  editor    = {Goffredo La Loggia and Gabriele Freni and Valeria Puleo and Mauro De Marchis},
  series    = {EPiC Series in Engineering},
  volume    = {3},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2516-2330},
  url       = {/publications/paper/lJKd},
  doi       = {10.29007/1l5w},
  pages     = {1744-1751},
  year      = {2018}}
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