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1 Alemayehu, S. H.; Awulachew, Seleshi Bekele; Horlacher, H. B.; Cullmann, J.. 2010. Estimation of daily flow in ungauge catchment by coupling hydrological model and neural networks: case study. [Abstract only]. Paper presented at the Joint International Convention of 8th IAHS Scientific Assembly and 37th IAH Congress, Water: a vital resource under stress: how science can help, Hyderabad, India, 6-12 September 2009. 1p.
Rivers ; Flow ; Catchment areas ; Watersheds ; Hydrology ; Rainfall-runoff relationships ; Models ; Neural networks ; Case studies / Africa / Ethiopia / Blue Nile River
(Location: IWMI HQ Call no: e-copy only Record No: H043345)
http://iahs.info/hyderabad/CD-Hyderabad/kishore/pdf/4648_Alemayehu_Estimation%20of%20daily%20flow.pdf
https://vlibrary.iwmi.org/pdf/H043345.pdf
https://vlibrary.iwmi.org/pdf/H043345.pdf
(0.08 MB) (85.98 KB)
Prediction of hydrological variables for ungauged basins is still a big challenge, particularly in developing countries. In this paper, we coupled Kohonen neural network and WaSiM-ETH to estimate flow in ungauged basin. 25 sub-catchments of the Blue Nile River basin, Ethiopia, were grouped in to five hydrological homogenous groups using KNNs. The coupled model copied the whole set of optimized WaSiM parameters from the homogeneous group (which the ungauge river belongs to) to the ungauge river and WaSiM compute the daily flow for this ungauge river. The model generally overestimates the low flow part of the hydrograph. In most cases the model underestimate the peak flow on daily basis but fits nicely on 10 days and monthly time step due to aggregation of the daily flow in to 10 days and monthly flow. In general, the results for sub-catchments that their data has never been involved during calibration showed the coupled program is quite satisfactory.
2 Cullmann, J.; Dilley, M. (Ed.); Egerton, P.; Grasso, V. F. (Ed.); Honore, C.; Lucio, F.; Luterbacher, J.; Nullis, C.; Power, M.; Rea, A.; Repnik, M.; Stander, J.; Idle, T. (Ed.); Msemo, N. (Ed.); Baubion, N.; Roudier, P.; Woillez, M.- N.; Gomes, A. M.; Dobardzic, S.; Pina, C. L.; Naran, B.; Richmond, M.; Harding, J.; Macasil, M. L. K.; Chaponniere, E.; Hoyer, B.; Losenno, C.; Vaananen, E.; Baugh, C.; Prudhomme, C.; Brovko, E.; Giusti, S.; Hoogeveen, J.; Maher, S.; Neretin, L.; Pek, E.; Gutierrez, A.; Ramage, S.; Venturini, S.; Intsiful, J.; Barnwal, A.; Iqbal, F.; Aich, V.; Debevec, L.; Grey, S.; Sumner, T.; Marsden, K.; Katsanakis, R.; Sengupta, R.; Bensada, A.; Olhoff, A.; Ivanova, O.; Kappelle, M.; Nield, M.; Wang, Y.; Bertule, M.; Glennie, P.; Lloyd, G. J.; Benchwick, G.; Creitaru, L.; Larroquette, B.; Stephens, E.; Properzi, F.; Schade, M.; Bogdanova, A.- M.; Kull, D.; de France, J.; Aich, V.; Alexieva, A.; Bastani, H.; Berit, A.; Berod, D.; Bode, G.; Boscolo, R.; Chernov, I.; de Coning, E.; Eggleston, S.; Ehlert, K.; Delju, A.; Douris, J.; Gallo, I.; Kim, H.; Migraine, J.- B.; Msemo, N.; Polcher, J.; Sparrow, M.; Stefanski, R.; Tripathi, R.; Vara, R. L. S.; Woolnough, S.; Zuniga, J. A.; Christiana, P.; Luo, T.; Saccoccia, L. 2021. 2021 state of climate services: water. Geneva, Switzerland: WMO. 46p. (WMO No.1278)
Water resources ; Climate change ; Information services ; Early warning systems ; Socioeconomic aspects ; Communities ; Flooding ; Water stress ; Drought ; Forecasting ; Governance ; Water supply ; Gender ; Decision making ; Disasters ; Economic losses ; Hurricanes ; Resilience ; Policies ; Hydroelectric power generation ; Meteorological stations ; Disaster risk management ; Disaster risk reduction ; Natural disasters ; Case studies / Asia / Thailand / Africa / Gambia / Europe / Slovakia / North America / Central America / Hondura / Caribbean / South America
(Location: IWMI HQ Call no: e-copy only Record No: H050659)
(4.62 MB) (4.62 MB)
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