全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

Rain-Flow Modelling Using the GR4J Model for Flood Risk Management in the Oti Watershed (Togo)

DOI: 10.4236/ojmh.2024.144012, PP. 213-230

Keywords: Modeling, Génie Rural à 4 Paramètres Journaliers (GR4J), Floods, Kling-Gupta Efficiency (KGE), Oti Watershed, Risk

Full-Text   Cite this paper   Add to My Lib

Abstract:

In recent years, West Africa has been confronted with hydro-climatic disasters causing crises in both urban and rural areas. The tragedy in the occurrence of such events lies in the recurrent aspect of high water and associated floods. The devastating floods observed in Africa’s major rivers have revealed the need to understand the causes of these phenomena and to predict their behavior in order to improve the safety of exposed people and property. The aim of this study is to reproduce flood flows using the GR4J (Rural Engineering Four Daily Parameters) model to analyze flood risk in the Oti watershed in Togo. Daily data on flows (m3/s), potential evapotranspiration (mm/day) and average precipitation (mm) over the basin from 1961-2022 collected at the National Meteorological Agency of Togo (ANAMET) and the Department of Water Resources in Lome, were used with the R software package airGR. The Data from the West African Cordex program from 1961-2100 were used to analyze projected flows. The results obtained show the GR4J model’s effectiveness in reproducing flood flows, indicating that observed flows are well simulated during the calibration and validation periods, with KGE values ranging from 0.73 to 0.85 at calibration and 0.62 to 0.81 at validation. These KGE values reflect the good performance of the GR4J model in simulating flood flows in the watershed. However, a deterioration in the KGE value was observed over the second validation period. Under these conditions, there may be false or missed alerts for flood prediction, and the use of this model should be treated with the utmost caution for decision-support purposes.

References

[1]  Amoussou, E. (2015) Analyse hydrométéorologique des crues dans le bassin versant du Mono en Afrique de l’Ouest avec un modèle conceptuel pluie-débit. Rapport à publier avec la Fondation Maison des Sciences de l’Homme (FMSH).
https://shs.hal.science/halshs-01143318v1
[2]  Panthou, G. (2013) Analyse des extrêmes pluviométriques en Afrique de l’Ouest et de leurs évolutions au cours des 60 dernières années. Université de Grenoble.
[3]  Koumassi, D.H. (2019) Caracterisation spatiale du risque d’inondation dans le bassin versant de la volta au Bénin. Colloque Internationale de l’AIC, 211-2016.
[4]  Amoussou, E. (2010) Variabilité pluviométrique et dynamique hydro-sédimentaire du bassin-versant du complexe fluvio-lagunaire Mono-Ahémé-Couffo (Afrique de l’Ouest). Thèse de Doctorat, Université de Bourgogne, 315 p. + annexes.
[5]  Amoussou, E., Tramblay, Y., Totin, H.S.V., Mahé, G. and Camberlin, P. (2014) Dynamique et modélisation des crues dans le bassin du Mono à Nangbéto (Togo/Bénin). Hydrological Sciences Journal, 59, 2060-2071.
https://doi.org/10.1080/02626667.2013.871015
[6]  Kodja, D.J., Mahé, G., Amoussou, E., Boko, M. and Paturel, J.-E. (2018) Assessment of the Performance of Rainfall-Runoff Model GR4J to Simulate Streamflow in Ouémé Watershed at Bonou’s Outlet (West Africa).
https://doi.org/10.20944/preprints201803.0090.v1
[7]  Nonki, R.M., Amoussou, E., Tshimanga, R.M., Koubodana Houteta, D., Kodja, D.J., Kemgang Ghomsi, F.E., et al. (2024) Performance Assessment of Daily GR Conceptual Rainfall-Runoff Models in the Upper Benue River (cameroon) Using Airgr Packages. Proceedings of IAHS, 385, 319-326.
https://doi.org/10.5194/piahs-385-319-2024
[8]  Sambou, S., Sane, M.L., Leye, I., Ndione, D.M., Kane, S. and Badji, M.L. (2021) Calage et validation de SWAT sur le bassin versant du Bafing (Fleuve Sénégal) en amont de bafing Makana: Vers une application à la gestion du barrage de Manantali. Proceedings of the International Association of Hydrological Sciences, 384, 363-366.
https://doi.org/10.5194/piahs-384-363-2021
[9]  Tran Tuan, T. (2024) Multiple Conceptual Hydrological Models for Simulating Streamflow in Data-Sparse River Basins: An Application of the Vietnamese Cau River Basin. Water Practice & Technology, 19, 2944-2958.
https://doi.org/10.2166/wpt.2024.181
[10]  Mehta, D., Hadvani, J., Kanthariya, D. and Sonawala, P. (2023) Effect of Land Use Land Cover Change on Runoff Characteristics Using Curve Number: A GIS and Remote Sensing Approach. International Journal of Hydrology Science and Technology, 16, 1-16.
https://doi.org/10.1504/ijhst.2023.131824
[11]  Yin, Z., Ottlé, C., Ciais, P., Zhou, F., Wang, X., Jan, P., et al. (2021) Irrigation, Damming, and Streamflow Fluctuations of the Yellow River. Hydrology and Earth System Sciences, 25, 1133-1150.
https://doi.org/10.5194/hess-25-1133-2021
[12]  Hundecha, Y. and Bárdossy, A. (2004) Modeling of the Effect of Land Use Changes on the Runoff Generation of a River Basin through Parameter Regionalization of a Watershed Model. Journal of Hydrology, 292, 281-295.
https://doi.org/10.1016/j.jhydrol.2004.01.002
[13]  Dutta, P. and Sarma, A.K. (2020) Hydrological Modeling as a Tool for Water Resources Management of the Data-Scarce Brahmaputra Basin. Journal of Water and Climate Change, 12, 152-165.
https://doi.org/10.2166/wcc.2020.186
[14]  Ragettli, S., Cortés, G., McPhee, J. and Pellicciotti, F. (2013) An Evaluation of Approaches for Modelling Hydrological Processes in High‐Elevation, Glacierized Andean Watersheds. Hydrological Processes, 28, 5674-5695.
https://doi.org/10.1002/hyp.10055
[15]  Le Lay, M., Saulnier, G., Galle, S., Seguis, L., Métadier, M. and Peugeot, C. (2008) Model Representation of the Sudanian Hydrological Processes: Application on the Donga Catchment (Benin). Journal of Hydrology, 363, 32-41.
https://doi.org/10.1016/j.jhydrol.2008.09.006
[16]  Kapoor, A., Pathiraja, S., Marshall, L. and Chandra, R. (2023) Deepgr4j: A Deep Learning Hybridization Approach for Conceptual Rainfall-Runoff Modelling. Environmental Modelling & Software, 169, Article ID: 105831.
https://doi.org/10.1016/j.envsoft.2023.105831
[17]  Devia, G.K., Ganasri, B.P. and Dwarakish, G.S. (2015) A Review on Hydrological Models. Aquatic Procedia, 4, 1001-1007.
https://doi.org/10.1016/j.aqpro.2015.02.126
[18]  Solomatine, D.P. and Wagener, T. (2011) Hydrological Modeling. In: Wilderer, P., Ed., Treatise on Water Science, Elsevier, 435-457.
https://doi.org/10.1016/b978-0-444-53199-5.00044-0
[19]  Le Lay, M. (2006) Modélisation hydrologique dans un contexte de variabilité hydroclimatique. Une approche comparative pour l’étude du cycle hydrologique à méso-échelle au Bénin, PhD Thesis, LTHE/UJF/INPG, 251 p.
[20]  Vissin, E.W. (2007) Impact de la variabilité climatique et de la dynamique des états de surface sur les écoulements du bassin béninois du fleuve Niger. Thèse de Doctorat de l’Université de Bourgogne, 280 p.
[21]  Kouamé, K.F.C. (2024) Approche de la prévision des crues fluviales à partir d’une modélisation hydrologique: Cas du modèle GR4J appliqué au bassin versant aménagé du fleuve Sassandra à l’exutoire de Soubré (Sud-ouest de la Côte d’Ivoire). Revue Espace Géographique et Société Marocaine, No. 83, 127-145.
[22]  Alipour, M.H. and Kibler, K.M. (2018) A Framework for Streamflow Prediction in the World’s Most Severely Data-Limited Regions: Test of Applicability and Performance in a Poorly-Gauged Region of China. Journal of Hydrology, 557, 41-54.
https://doi.org/10.1016/j.jhydrol.2017.12.019
[23]  Sirisena, T.A.J.G., Maskey, S. and Ranasinghe, R. (2020) Hydrological Model Calibration with Streamflow and Remote Sensing Based Evapotranspiration Data in a Data Poor Basin. Remote Sensing, 12, Article No. 3768.
https://doi.org/10.3390/rs12223768
[24]  Feng, D., Lawson, K. and Shen, C. (2021) Mitigating Prediction Error of Deep Learning Streamflow Models in Large Data‐Sparse Regions with Ensemble Modeling and Soft Data. Geophysical Research Letters, 48, e2021GL092999.
https://doi.org/10.1029/2021gl092999
[25]  Lu, D., Konapala, G., Painter, S.L., Kao, S. and Gangrade, S. (2021) Streamflow Simulation in Data-Scarce Basins Using Bayesian and Physics-Informed Machine Learning Models. Journal of Hydrometeorology, 22, 1421-1438.
https://doi.org/10.1175/jhm-d-20-0082.1
[26]  Komi, K. (2016) Flood Risk Assessment in Poorly Gauged River Basins—A Case Study of the Oti River Basin, Togo, West Africa. Dissertation, PhD of University of Abomey-Calavi (Benin Republic), 161 p.
[27]  Mounirou, A., Laroche, C., Paturel, J.-C. and Mar, A.L. (2005) Détermination de la connaissance hydrométrique minimale nécessaire et suffisante pour une estimation raisonnable des paramètres d’un modèle de transformation pluie-débit au pas de temps mensuel. Rapport d’activités de recherche, PNRH 2003, 134 p.
[28]  Koungbanane, D., Totin Vodounon, S.H., Amoussou, E., Zahiri, P.E. and Laré, L.Y. (2019) Variabilité hydro-climatique et risques d’inondation dans le bassin versant de l’Oti au Togo. Revue de Géographie de lUniversité de Ouagadougou, 1, 1-17.
[29]  Koungbanane, D., Lemou, F., Djangbedja, M. and Totin, H.S.V. (2023) Impacts socio-économiques et environnementaux des risques d’inondation dans le bassin versant de l’Oti au Togo (Afrique de l’Ouest). VertigO
[30]  Descroix, L., Genthon, P., Amogu, O., Rajot, J., Sighomnou, D. and Vauclin, M. (2012) Change in Sahelian Rivers Hydrograph: The Case of Recent Red Floods of the Niger River in the Niamey Region. Global and Planetary Change, 98, 18-30.
https://doi.org/10.1016/j.gloplacha.2012.07.009
[31]  Mul, M., Obuobie, E., Appoh, R., Kankam, Y., Bekoe-Obeng, E., Amisigo, B., Logah, Y., Ghansah, B. and McCartney, M. (2015) Évaluation des ressources en eau du bassin de la Volta. Programme des Nations Unies pour l’Environnement.
[32]  Kankpénandja, L. (2002) Contribution à l’étude géomorphologique de la plaine alluviale du Kpendjal (Région des Savanes). Mémoire de maîtrise en Géographie, Université de Lomé, 136 p.
[33]  Oudin, L., Hervieu, F., Michel, C., Perrin, C., Andréassian, V., Anctil, F., et al. (2005) Which Potential Evapotranspiration Input for a Lumped Rainfall-Runoff Model? Part 2—Towards a Simple and Efficient Potential Evapotranspiration Model for Rainfall-Runoff Modelling Journal of Hydrology, 303, 290-306.
https://doi.org/10.1016/j.jhydrol.2004.08.026
[34]  Giorgi, F., Jones, C. and Asrar, G.R. (2009) L’expérience CORDEX: Répondre aux besoins d’information climatologique à l’échelle régionale. Bulletin de lOMM, 58, 175 177.
[35]  Kodja, D.J. (2018) Indicateurs des événements hydroclimatiques extrêmes dans le bassin-versant de l’Oueme à l’exutoire de Bonou en Afrique de l’ouest. Thèse de Doctorat, Université de Montpellier, 287 p.
[36]  Kay, A.L. and Davies, H.N. (2008) Calculating Potential Evaporation from Climate Model Data: A Source of Uncertainty for Hydrological Climate Change Impacts. Journal of Hydrology, 358, 221-239.
https://doi.org/10.1016/j.jhydrol.2008.06.005
[37]  Houessou, S. (2016) Les inondations et les risques prévisionnels lies aux barrages hydroélectriques dans la basse vallée du mono. Thèse de Doctorat de Géographie, Université d’Abomey-Calavi, 198 p.
[38]  Perrin, C. (2002) Vers une amélioration d’un modèle global pluie-débit au travers d’une approche comparative. Towards an Improved Version of a Lumped Rain-Fall-runoff Model through a Comparative Approach. La Houille Blanche, 88, 84-91.
https://doi.org/10.1051/lhb/2002089
[39]  Perrin, C., Michel, C. and Andréassian, V. (2003) Improvement of a Parsimonious Model for Streamflow Simulation. Journal of Hydrology, 279, 275-289.
https://doi.org/10.1016/s0022-1694(03)00225-7
[40]  Coron, L., Thirel, G., Delaigue, O., Perrin, C. and Andréassian, V. (2017) The Suite of Lumped GR Hydrological Models in an R Package. Environmental Modelling & Software, 94, 166-171.
https://doi.org/10.1016/j.envsoft.2017.05.002
[41]  Gupta, H.V., Kling, H., Yilmaz, K.K. and Martinez, G.F. (2009) Decomposition of the Mean Squared Error and NSE Performance Criteria: Implications for Improving Hydrological Modelling. Journal of Hydrology, 377, 80-91.
https://doi.org/10.1016/j.jhydrol.2009.08.003
[42]  Kling, H., Fuchs, M. and Paulin, M. (2012) Runoff Conditions in the Upper Danube Basin under an Ensemble of Climate Change Scenarios. Journal of Hydrology, 424, 264-277.
https://doi.org/10.1016/j.jhydrol.2012.01.011
[43]  Issaou, L. (2014) Risques climatiques dans le Sud-Togo: Manifestations, impacts et stratégies d’adaptation. Thèse de Doctorat de Géographie de l’Université de Lomé, 264 p.
[44]  Le Barbé, L., Alé, G., Millet, B., Texier, H., Borel, Y. and Gualde, R. (1993) Les ressources en eaux superficielles de la République du Bénin. Edition ORSTOM, 540 p.
[45]  Totin, V.S.H., Amoussou, E., Odoulami, L., Boko, M. and Blivi, B.A. (2016) Seuils pluviométriques des niveaux de risque d’inondation dans le bassin de l’Ouémé au Bénin (Afrique de l’Ouest). XXIXe Colloque de lAssociation Internationale de Climatologie, Lausanne, 6-9 July 2016, 369-374.
[46]  IPCC (2001) Impact of Climate Change in the Regions: Vulnerability Assessment in Africa. Report of the Intergovernmental Panel on Climate Change, 1-3.
[47]  Kodja, D.J. (2011) Prévision des crues dans le bassin-versant du Zou à Atcherigbé avec le modèle GR2M. Mémoire de Maîtrise, DGAT/FLASH/UAC, 104 p.

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133