Simple power-law models to predict flow metrics for water resource and risk management along the Mekong tributaries. [Abstract only]

Increasing demographic pressure, economic development and resettlement policies in the Lower Mekong Basin induce greater population dependency on river flow to satisfy growing domestic and agricultural water demands. This dependency is particularly tight in upland areas where alternative water resou...

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Autores principales: Lacombe, Guillaume, Douangsavanh, Somphasith, Vogel, R., McCartney, Matthew P., Chemin, Yann H., Rebelo, Lisa-Maria, Sotoukee, Touleelor
Formato: Conference Paper
Lenguaje:Inglés
Publicado: 2014
Materias:
Acceso en línea:https://hdl.handle.net/10568/67590
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author Lacombe, Guillaume
Douangsavanh, Somphasith
Vogel, R.
McCartney, Matthew P.
Chemin, Yann H.
Rebelo, Lisa-Maria
Sotoukee, Touleelor
author_browse Chemin, Yann H.
Douangsavanh, Somphasith
Lacombe, Guillaume
McCartney, Matthew P.
Rebelo, Lisa-Maria
Sotoukee, Touleelor
Vogel, R.
author_facet Lacombe, Guillaume
Douangsavanh, Somphasith
Vogel, R.
McCartney, Matthew P.
Chemin, Yann H.
Rebelo, Lisa-Maria
Sotoukee, Touleelor
author_sort Lacombe, Guillaume
collection Repository of Agricultural Research Outputs (CGSpace)
description Increasing demographic pressure, economic development and resettlement policies in the Lower Mekong Basin induce greater population dependency on river flow to satisfy growing domestic and agricultural water demands. This dependency is particularly tight in upland areas where alternative water resources (groundwater) are scarce. As a result, communities tend to live closer to rivers, and so are more vulnerable to floods. This situation requires improved knowledge of flow variability for better management of water resources and risks. Unfortunately, stream flow measurements are scarce, especially in remote areas inhabited by the poorest and most vulnerable populations. Several water resource models have been developed to simulate and predict flows in the Lower Mekong Basin. However, most of these models have been designed to predict flow along the Mekong mainstream, precluding accurate assessments in headwater catchments. In most cases, their complexity and lack of transparency restricts potential users to modelling experts, and largely excludes those practitioners working closely with affected populations. The most integrated and informative way to characterize flow, at a specific location on a river, is to compute a flow duration curve which provides the percentage of time (duration) any particular flow is exceeded over a historical period. Using hydro-meteorological records from more than 60 gauged catchments in the Lower Mekong Basin, and a 90-meter digital elevation model, we used multiple linear regressions to develop power-law models predicting flow duration curves. These simple equations allow assessment of low, medium and high flow metrics, at any point on rivers in the Lower Mekong Basin, using easily determined geomorphological and climate characteristics. We believe that this parsimonious, transparent and highly predictive tool (89% <R2< 95%) can be used by a wide range of practitioners working in the fields of livelihood, water infrastructure engineering and agriculture.
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spelling CGSpace675902025-11-07T08:38:45Z Simple power-law models to predict flow metrics for water resource and risk management along the Mekong tributaries. [Abstract only] Lacombe, Guillaume Douangsavanh, Somphasith Vogel, R. McCartney, Matthew P. Chemin, Yann H. Rebelo, Lisa-Maria Sotoukee, Touleelor water resources risk management statistical methods models river basins catchment areas Increasing demographic pressure, economic development and resettlement policies in the Lower Mekong Basin induce greater population dependency on river flow to satisfy growing domestic and agricultural water demands. This dependency is particularly tight in upland areas where alternative water resources (groundwater) are scarce. As a result, communities tend to live closer to rivers, and so are more vulnerable to floods. This situation requires improved knowledge of flow variability for better management of water resources and risks. Unfortunately, stream flow measurements are scarce, especially in remote areas inhabited by the poorest and most vulnerable populations. Several water resource models have been developed to simulate and predict flows in the Lower Mekong Basin. However, most of these models have been designed to predict flow along the Mekong mainstream, precluding accurate assessments in headwater catchments. In most cases, their complexity and lack of transparency restricts potential users to modelling experts, and largely excludes those practitioners working closely with affected populations. The most integrated and informative way to characterize flow, at a specific location on a river, is to compute a flow duration curve which provides the percentage of time (duration) any particular flow is exceeded over a historical period. Using hydro-meteorological records from more than 60 gauged catchments in the Lower Mekong Basin, and a 90-meter digital elevation model, we used multiple linear regressions to develop power-law models predicting flow duration curves. These simple equations allow assessment of low, medium and high flow metrics, at any point on rivers in the Lower Mekong Basin, using easily determined geomorphological and climate characteristics. We believe that this parsimonious, transparent and highly predictive tool (89% <R2< 95%) can be used by a wide range of practitioners working in the fields of livelihood, water infrastructure engineering and agriculture. 2014 2015-07-30T06:07:05Z 2015-07-30T06:07:05Z Conference Paper https://hdl.handle.net/10568/67590 en Open Access application/pdf Lacombe, Guillaume; Douangsavanh, Somphasith; Vogel, R.; McCartney, Matthew; Chemin, Yann; Rebelo, Lisa-Maria; Sotoukee, Touleelor. 2014. Simple power-law models to predict flow metrics for water resource and risk management along the Mekong tributaries. [Abstract only] Paper presented at the International Conference on Sustainability in the Water-Energy-Food Nexus, Bonn, Germany, 19-20 May 2014. pp.59.
spellingShingle water resources
risk management
statistical methods
models
river basins
catchment areas
Lacombe, Guillaume
Douangsavanh, Somphasith
Vogel, R.
McCartney, Matthew P.
Chemin, Yann H.
Rebelo, Lisa-Maria
Sotoukee, Touleelor
Simple power-law models to predict flow metrics for water resource and risk management along the Mekong tributaries. [Abstract only]
title Simple power-law models to predict flow metrics for water resource and risk management along the Mekong tributaries. [Abstract only]
title_full Simple power-law models to predict flow metrics for water resource and risk management along the Mekong tributaries. [Abstract only]
title_fullStr Simple power-law models to predict flow metrics for water resource and risk management along the Mekong tributaries. [Abstract only]
title_full_unstemmed Simple power-law models to predict flow metrics for water resource and risk management along the Mekong tributaries. [Abstract only]
title_short Simple power-law models to predict flow metrics for water resource and risk management along the Mekong tributaries. [Abstract only]
title_sort simple power law models to predict flow metrics for water resource and risk management along the mekong tributaries abstract only
topic water resources
risk management
statistical methods
models
river basins
catchment areas
url https://hdl.handle.net/10568/67590
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