Research Article of American Journal of Geographical Research and Reviews
Regionalisation of hydrological model parameters in nested catchmentss
Shailesh Kumar Singh
National Institute of Water and Atmospheric Research, Christchurch, New Zealand
A prediction in ungauged basins is one of the challenging tasks for a hydrologist of this century. Even though the physically based hydrological models can be the more appropriate in ungauged basins but data requirement limit the use. Conceptual hydrological models are simple and easy to use. But these model needs calibration before it can be used. Availability of data at all location in the basin limits the calibration of conceptual hydrological models. In this study, a calibration methodology is presented for discharge series limited condition using upstream and downstream data from nested catchment. It has been found that reasonable model parameters can be estimated for middle catchment using immediate upstream and downstream data. The regionalised parameter at the catchment outlet was tested at several locations inside the catchment to test the suitability of the outlet based model parameter for the interior location along the channel. It has been found that the model parameters obtained at the outlet of the catchment by regionalisation methods can be applied to the neighbouring points along the channel. A conceptual hydrological model, HBV-IWS was used for on upper Neckar catchment to demonstrate the methodology.
Keywords: Regionalisation, HBV-IWS, Upstream downstream
How to cite this article:
Shailesh Kumar Singh. Regionalisation of hydrological model parameters in nested catchments. American Journal of Geographical Research and Reviews, 2018; 1:8. DOI:10.28933/ajgrr-2018-02-0701
1 Ahmed, S., De Marsily, G., 1987. Comparison of geostatistical methods for estimating transmissivity using data on transmissivity and specific capacity. Water Resources Research, 23(9): 1717–1737. DOI:10.1029/WR023i009p01717
2 Bárdossy, A., 2007. Calibration of hydrological model parameters for ungauged catchments. Hydrology and Earth System Sciences Discussions, 11(2): 703-710.
3 Bardossy, A., Singh, S.K., 2011. Regionalization of hydrological model parameters using data depth. Hydrology Research, 42(5): 356-371.
4 Bárdossy, A., Singh, S.K., 2008. Robust estimation of hydrological model parameters. Hydrology and Earth System Sciences, 12(6): 1273-1283.
5 Bergstroem, S., Singh, V., others, 1995. The HBV model. Computer models of watershed hydrology.: 443-476.
6 Blöschl, G., 2005. Rainfall‐Runoff Modeling of Ungauged Catchments. Encyclopedia of Hydrological Sciences.
7 Fernandez, W., Vogel, R., Sankarasubramanian, A., 2000. Regional calibration of a watershed model. Hydrological Sciences Journal, 45(5): 689-707.
8 Götzinger, J., Bárdossy, A., 2007. Comparison of four regionalisation methods for a distributed hydrological model. Journal of Hydrology, 333(2): 374-384.
9 Hargreaves, G.H., Samani, Z.A., 1985. Reference crop evapotranspiration from ambient air temperature. American Society of Agricultural Engineers.
10 Hundecha, Y., 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(1): 281-295.
11 Nash, J.E., Sutcliffe, J., 1970. River flow forecasting through conceptual models part I—A discussion of principles. Journal of Hydrology, 10(3): 282-290.
12 Samaniego, L., Bárdossy, A., Kumar, R., 2010. Streamflow prediction in ungauged catchments using copula-based dissimilarity measures. Water Resources Research, 46(2): W02506.
13 Seibert, J., Beven, K.J., 2009. Gauging the ungauged basin: how many discharge measurements are needed? Hydrology and Earth System Sciences, 13(6): 883-892.
14 Singh, S.K., 2010a. Parameterization of Hydrological Model in Ungauged Catchments: A Regionalization Technique. LAP Lambert Academic Publishing AG & Co KG, Germany, ISBN-13: 978-3838375588 pp.
15 Singh, S.K., 2010b. Robust parameter estimation in gauged and ungauged basins. PhD Thesis Nr. 198, University of Stuttgart, Germany, http://dx.doi.org/10.18419/opus-360.
16 Singh, S.K., 2016. Long-term Streamflow Forecasting Based on Ensemble Streamflow Prediction Technique: A Case Study in New Zealand. Water Resources Management, 30(7): 2295-2309.
17 Singh, S.K., McMillan, H., Bárdossy, A., Chebana, F., 2016. Non-parametric catchment clustering using the data depth function. Hydrological Sciences Journal, 61(15): 2649-2667. DOI:10.1080/02626667.2016.1168927
18 Sivapalan, M. et al., 2003. IAHS Decade on Predictions in Ungauged Basins (PUB), 2003–2012: Shaping an exciting future for the hydrological sciences. Hydrological Sciences Journal, 48(6): 857-880.
19 Wagener, T., Sivapalan, M., Troch, P., Woods, R., 2007. Catchment classification and hydrologic similarity. Geography Compass, 1(4): 901-931.
20 Wagener, T., Wheater, H.S., 2006. Parameter estimation and regionalization for continuous rainfall-runoff models including uncertainty. Journal of hydrology, 320(1): 132-154.
21 Wang, B., Vaze, J., Zhanga, Y., Teng, J., 2013. Catchment grouping and regional calibration for predictions in ungauged basins, 20th International Congress on modelling and simulation, Adelaide, australia.
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