Prediction of runoff hydrographs in ungauged basins - Runoff Prediction in Ungauged Basins: Synthesis across Processes, Places and Scales - page 251

Figure 10.23. Nash - Sutcliffe
performance for a-priori parameters
and calibrated parameters in the
MOPEX model inter-comparison
project performed in 12 catchments
in south-east USA. (a) Daily runoff
performance; (b) monthly runoff
performance. Different symbols
denote different models. From Duan
et al. (2006) .

1.0

a) b)

0.8

0.6

0.4

0.2

0

0 0.2 0.4 0.6 0.8 1.0 0 0.2 0.4 0.6 0.8 1.0

NSE ( a priori ) NSE ( a priori )

Figure 10.24. Results of sprinkling experiments in the Austrian Alps. The larger runoff coefficients in summer and autumn are due to soil
compaction by cattle. Redrawn from Kohl and Markart ( 2002 ). Photo: G. Markart.

Because of these difficulties, parameters of physics-
based models applied in gauged catchments are often
allowed some degree of calibration within a physically
justifiable range to adjust some of the measurement or
estimation biases. For ungauged catchments, it may there-
fore be of value to transfer these parameters from similar
catchments in the region by one of the methods outlined in
the sections below, in addition to measuring the parameters
in the field (or estimating them from remotely sensed data).
In fact, estimating the parameters from two or more differ-
ent sources will likely increase their reliability. The dis-
tinction between the calibration parameters of conceptual

models and physics-based parameters is therefore not a
sharp one, there is a gradual transition from what one
would call a calibration parameter and a process-based
parameter, depending on the type and extent of information
available in any particular case.

10.4.4 Transfer of calibrated model parameters from
gauged catchments
Most of the parameters in conceptual models cannot be
measured or inferred from measurements but need to be
transposed from gauged catchments in the region. The