A “monster” that made the SMAR conceptual model “right for the wrong reasons”

  • Goswami M
  • O'Connor K
N/ACitations
Citations of this article
19Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

In earlier studies involving simulation of the Fergus River flows in Ireland, the conceptual Soil Moisture Accounting and Routing (SMAR) model had been found to consistently outperform a number of black-box models. Subsequently, in investigating any loss of flow through this catchment's subsurface karstic features, it was verified from the overall long-term water balance that such losses were substantial. This raised the awkward question of why the volume-conservative SMAR model had performed so well on this considerably non-conservative catchment. Further analyses revealed that, to compensate for the excess volume of total runoff generated by the model's conservative water balance component, the memory length of the surface runoff response function had been unrealistically curtailed in the optimization process, effectively truncating that function and thereby violating the conservation property of the routing process. This embarrassing revelation called for reconsideration of the model structure to account more sensibly for actual losses, while still achieving high model efficiency. This paper highlights not only the discovery of the karstic Fergus catchment as a "hydrological monster", in the context of the SMAR model, but also why conservative models perform poorly in such cases. In an attempt to "tame the monster", better simulation of the observed flows was achieved by conceptually adapting the SMAR model, in a pragmatic empirical manner, by simply modifying its water balance component. © 2010 IAHS Press.

Cite

CITATION STYLE

APA

Goswami, M., & O’Connor, K. M. (2010). A “monster” that made the SMAR conceptual model “right for the wrong reasons.” Hydrological Sciences Journal, 55(6), 913–927. https://doi.org/10.1080/02626667.2010.505170

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free