Geostatistical regionalization of low-flow indices: PSBI and Top-Kriging
2010
Recent studies highlight that geostatistical interpolation, which has been originally developed
for the spatial interpolation of point data, can be effectively applied to the problem
of regionalization of hydrometric information. This study compares two innovative
5 geostatistical approaches for the prediction of low-flows in ungauged basins. The first
one, named Physiographic-Space Based Interpolation (PSBI), performs the spatial interpolation
of the desired streamflow index (e.g., annual streamflow, low-flow index,
flood quantile, etc.) in the space of catchment descriptors. The second technique,
named Topological kriging or Top-Kriging, predicts the variable of interest along river
10 networks taking both the area and nested nature of catchments into account. PSBI
and Top-Kriging are applied for the regionalization of Q355 (i.e., the streamflow that
is equalled or exceeded 355 days in a year, on average) over a broad geographical
region in central Italy, which contains 51 gauged catchments. Both techniques are
cross-validated through a leave-one-out procedure at all available gauges and applied
15 to a subregion to produce a continuous estimation of Q355 along the river network extracted
from a 90m DEM. The results of the study show that Top-Kriging and PSBI
present complementary features and have comparable performances (Nash-Sutcliffe
efficiencies in cross-validation of 0.89 and 0.83, respectively). Both techniques provide
plausible and accurate predictions of Q355 in ungauged basins and represent promising
20 opportunities for regionalization of low-flows.
Keywords:
- Correction
- Source
- Cite
- Save
- Machine Reading By IdeaReader
38
References
2
Citations
NaN
KQI