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Exploratory studies into seasonal flow forecasting potential for large lakes

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Exploratory studies into seasonal flow forecasting potential for large lakes. / Sene, Kevin; Tych, Wlodzimierz; Beven, Keith John.

In: Hydrology and Earth System Sciences, Vol. 22, 09.01.2018, p. 127-141.

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@article{f1dc3cdc9b6d45f481956b71018952ac,
title = "Exploratory studies into seasonal flow forecasting potential for large lakes",
abstract = " In seasonal flow forecasting applications, one factor which can help predictability is a significant hydrological response time between rainfall and flows. On account of storage influences, large lakes therefore provide a useful test case although, due to the spatial scales involved, there are a number of modelling challenges related to data availability and understanding the individual components in the water balance. Here some possible model structures are investigated using a range of stochastic regression and transfer function techniques with additional insights gained from simple analytical approximations. The methods were evaluated using records for two of the largest lakes in the world – Lake Malawi and Lake Victoria – with forecast skill demonstrated several months ahead using water balance models formulated in terms of net inflows. In both cases slight improvements were obtained for lead times up to 4–5 months from including climate indices in the data assimilation component. The paper concludes with a discussion of the relevance of the results to operational flow forecasting systems for other large lakes.",
author = "Kevin Sene and Wlodzimierz Tych and Beven, {Keith John}",
year = "2018",
month = jan
day = "9",
doi = "10.5194/hess-22-127-2018",
language = "English",
volume = "22",
pages = "127--141",
journal = "Hydrology and Earth System Sciences",
issn = "1027-5606",
publisher = "Copernicus Gesellschaft mbH",

}

RIS

TY - JOUR

T1 - Exploratory studies into seasonal flow forecasting potential for large lakes

AU - Sene, Kevin

AU - Tych, Wlodzimierz

AU - Beven, Keith John

PY - 2018/1/9

Y1 - 2018/1/9

N2 - In seasonal flow forecasting applications, one factor which can help predictability is a significant hydrological response time between rainfall and flows. On account of storage influences, large lakes therefore provide a useful test case although, due to the spatial scales involved, there are a number of modelling challenges related to data availability and understanding the individual components in the water balance. Here some possible model structures are investigated using a range of stochastic regression and transfer function techniques with additional insights gained from simple analytical approximations. The methods were evaluated using records for two of the largest lakes in the world – Lake Malawi and Lake Victoria – with forecast skill demonstrated several months ahead using water balance models formulated in terms of net inflows. In both cases slight improvements were obtained for lead times up to 4–5 months from including climate indices in the data assimilation component. The paper concludes with a discussion of the relevance of the results to operational flow forecasting systems for other large lakes.

AB - In seasonal flow forecasting applications, one factor which can help predictability is a significant hydrological response time between rainfall and flows. On account of storage influences, large lakes therefore provide a useful test case although, due to the spatial scales involved, there are a number of modelling challenges related to data availability and understanding the individual components in the water balance. Here some possible model structures are investigated using a range of stochastic regression and transfer function techniques with additional insights gained from simple analytical approximations. The methods were evaluated using records for two of the largest lakes in the world – Lake Malawi and Lake Victoria – with forecast skill demonstrated several months ahead using water balance models formulated in terms of net inflows. In both cases slight improvements were obtained for lead times up to 4–5 months from including climate indices in the data assimilation component. The paper concludes with a discussion of the relevance of the results to operational flow forecasting systems for other large lakes.

U2 - 10.5194/hess-22-127-2018

DO - 10.5194/hess-22-127-2018

M3 - Journal article

VL - 22

SP - 127

EP - 141

JO - Hydrology and Earth System Sciences

JF - Hydrology and Earth System Sciences

SN - 1027-5606

ER -