Community-based early warning systems for flood risk mitigation in Nepal
This paper focuses on the use of community-based early warning systems for flood resilience in Nepal. The first part of the work outlines the evolution and current status of these community-based systems, highlighting the limited lead times currently available for early warning. The second part of t...
Main Authors: | , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Copernicus Publications
2017-03-01
|
Series: | Natural Hazards and Earth System Sciences |
Online Access: | http://www.nat-hazards-earth-syst-sci.net/17/423/2017/nhess-17-423-2017.pdf |
id |
doaj-444eb3ffe0c14d62b3ad56cdc374c8a9 |
---|---|
record_format |
Article |
spelling |
doaj-444eb3ffe0c14d62b3ad56cdc374c8a92020-11-24T23:28:11ZengCopernicus PublicationsNatural Hazards and Earth System Sciences1561-86331684-99812017-03-0117342343710.5194/nhess-17-423-2017Community-based early warning systems for flood risk mitigation in NepalP. J. Smith0S. Brown1S. Dugar2Lancaster Environment Centre, Lancaster University, Lancaster, UKPractical Action Consulting, Rugby, UKPractical Action Consulting, Kathmandu, NepalThis paper focuses on the use of community-based early warning systems for flood resilience in Nepal. The first part of the work outlines the evolution and current status of these community-based systems, highlighting the limited lead times currently available for early warning. The second part of the paper focuses on the development of a robust operational flood forecasting methodology for use by the Nepal Department of Hydrology and Meteorology (DHM) to enhance early warning lead times. The methodology uses data-based physically interpretable time series models and data assimilation to generate probabilistic forecasts, which are presented in a simple visual tool. The approach is designed to work in situations of limited data availability with an emphasis on sustainability and appropriate technology. The successful application of the forecast methodology to the flood-prone Karnali River basin in western Nepal is outlined, increasing lead times from 2–3 to 7–8 h. The challenges faced in communicating probabilistic forecasts to the last mile of the existing community-based early warning systems across Nepal is discussed. The paper concludes with an assessment of the applicability of this approach in basins and countries beyond Karnali and Nepal and an overview of key lessons learnt from this initiative.http://www.nat-hazards-earth-syst-sci.net/17/423/2017/nhess-17-423-2017.pdf |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
P. J. Smith S. Brown S. Dugar |
spellingShingle |
P. J. Smith S. Brown S. Dugar Community-based early warning systems for flood risk mitigation in Nepal Natural Hazards and Earth System Sciences |
author_facet |
P. J. Smith S. Brown S. Dugar |
author_sort |
P. J. Smith |
title |
Community-based early warning systems for flood risk mitigation in Nepal |
title_short |
Community-based early warning systems for flood risk mitigation in Nepal |
title_full |
Community-based early warning systems for flood risk mitigation in Nepal |
title_fullStr |
Community-based early warning systems for flood risk mitigation in Nepal |
title_full_unstemmed |
Community-based early warning systems for flood risk mitigation in Nepal |
title_sort |
community-based early warning systems for flood risk mitigation in nepal |
publisher |
Copernicus Publications |
series |
Natural Hazards and Earth System Sciences |
issn |
1561-8633 1684-9981 |
publishDate |
2017-03-01 |
description |
This paper focuses on the use of community-based early warning systems for
flood resilience in Nepal. The first part of the work outlines the evolution
and current status of these community-based systems, highlighting the limited
lead times currently available for early warning. The second part of the
paper focuses on the development of a robust operational flood forecasting
methodology for use by the Nepal Department of Hydrology and Meteorology
(DHM) to enhance early warning lead times. The methodology uses data-based
physically interpretable time series models and data assimilation to generate
probabilistic forecasts, which are presented in a simple visual tool. The
approach is designed to work in situations of limited data availability with
an emphasis on sustainability and appropriate technology. The successful
application of the forecast methodology to the flood-prone Karnali River
basin in western Nepal is outlined, increasing lead times from 2–3 to
7–8 h. The challenges faced in communicating probabilistic forecasts
to the last mile of the existing community-based early warning systems across
Nepal is discussed. The paper concludes with an assessment of the
applicability of this approach in basins and countries beyond Karnali and
Nepal and an overview of key lessons learnt from this initiative. |
url |
http://www.nat-hazards-earth-syst-sci.net/17/423/2017/nhess-17-423-2017.pdf |
work_keys_str_mv |
AT pjsmith communitybasedearlywarningsystemsforfloodriskmitigationinnepal AT sbrown communitybasedearlywarningsystemsforfloodriskmitigationinnepal AT sdugar communitybasedearlywarningsystemsforfloodriskmitigationinnepal |
_version_ |
1725550437781733376 |