Jean Hounkpè, D. F. Badou, A. Bossa, Yacouba Yira, J. Adounkpe, E. Alamou, E. Lawin, L. Sintondji, A. Afouda, E. Amoussou
{"title":"Assessment of flood discharge sensitivity to climate indexes in West Africa","authors":"Jean Hounkpè, D. F. Badou, A. Bossa, Yacouba Yira, J. Adounkpe, E. Alamou, E. Lawin, L. Sintondji, A. Afouda, E. Amoussou","doi":"10.5194/piahs-384-219-2021","DOIUrl":null,"url":null,"abstract":"Abstract. Floods are natural disasters that widely affect people and goods.\nIts frequency and magnitude are projected to substantially increase due to\nthe ongoing environmental change. At regional and national levels, some\nefforts have been made in predicting floods at a short-term range. However,\nthe usefulness of flood prediction increases as the time lead increases. The\nobjective of this work is therefore to investigate flood sensitivity to\nclimate indexes in West Africa as a basis for seasonal flood forecasting.\nThe methodology consists of optimizing the relationship between Annual\nMaximal Discharge (AMD), a proxy for flood discharge and various climate\nindexes using correlation coefficient, linear regression and statistical\nmodeling based on 56 river gauging stations across West Africa. The climate\nindexes considered are the Sea Surface Temperature (SST) of the Tropical\nNorthern Atlantic (TNA), SST of the Tropical Southern Atlantic (TSA), the\nSea Level Pressure (SLP) of the Southern Oscillation Indexes (SOI) and the\ndetrended El-Nino Southern Oscillation indexes. It was found that SOI/SLP\nindexes are the most strongly related to the AMD for the investigated\nstations with generally high, positive, and statistically significant\ncorrelation. The TSA/SST indexes indicated both positive and negative\nstatistically significant correlations with river discharge in the region.\nThe percentage change in AMD per unit change in SOI/SLP for most of the\nstatistically significant stations is within 10 % and 50 % indicating a\nstrong relationship between these two variables. This relationship could\nserve as a basis for seasonal flood forecasting in the study area.\n","PeriodicalId":53381,"journal":{"name":"Proceedings of the International Association of Hydrological Sciences","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the International Association of Hydrological Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5194/piahs-384-219-2021","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Earth and Planetary Sciences","Score":null,"Total":0}
引用次数: 0
Abstract
Abstract. Floods are natural disasters that widely affect people and goods.
Its frequency and magnitude are projected to substantially increase due to
the ongoing environmental change. At regional and national levels, some
efforts have been made in predicting floods at a short-term range. However,
the usefulness of flood prediction increases as the time lead increases. The
objective of this work is therefore to investigate flood sensitivity to
climate indexes in West Africa as a basis for seasonal flood forecasting.
The methodology consists of optimizing the relationship between Annual
Maximal Discharge (AMD), a proxy for flood discharge and various climate
indexes using correlation coefficient, linear regression and statistical
modeling based on 56 river gauging stations across West Africa. The climate
indexes considered are the Sea Surface Temperature (SST) of the Tropical
Northern Atlantic (TNA), SST of the Tropical Southern Atlantic (TSA), the
Sea Level Pressure (SLP) of the Southern Oscillation Indexes (SOI) and the
detrended El-Nino Southern Oscillation indexes. It was found that SOI/SLP
indexes are the most strongly related to the AMD for the investigated
stations with generally high, positive, and statistically significant
correlation. The TSA/SST indexes indicated both positive and negative
statistically significant correlations with river discharge in the region.
The percentage change in AMD per unit change in SOI/SLP for most of the
statistically significant stations is within 10 % and 50 % indicating a
strong relationship between these two variables. This relationship could
serve as a basis for seasonal flood forecasting in the study area.