Simulating streamflow in ungauged catchments using regionalization
methods in southeast Iran
Abstract
Simulating streamflow in ungauged catchments is a challenge for the
management of surface water resources around the world, especially in
dry regions. Here, we transfer parameters of two HBV and IHACRES
hydrological models from gauged (donor) to ungauged catchments using
three main regionalization approaches including Physical Similarity
(PS), Multiple Regression (MR), Spatial Proximity (SP) and an integrated
approach, which is basically an extension of PS approach through Inverse
Distance Weighted (IDW) method (IDW-PS). We use a set of 21 catchments
in Hamoun-Jazmourian River Basin in southeast Iran, to compare
regionalization approaches. The results indicate that (1) generally, the
HBV model performs slightly better than IHACRES model in calibration,
verification, and regionalization, (2) the physical similarity method
under 2 to 4 donor catchments and multiple regression method provide the
best and least satisfactory results respectively. The IDW-PS method
improves the performance of IDW method, (3) for the physical similarity,
eight Catchment Descriptors (CDs) in four main groups of climate,
physiographic, location, and land use perform best in prediction
performance, (5) the HBV parameters related to snow and runoff
components, are associated with highest and lowest uncertainties
respectively. For the IHACRES, the most and least robustness parameters
are plant stress threshold factor, f and the proportion of slow flow to
total flow, vs respectively. Testing the parameter transferability using
main approaches of regionalization at two distinct climate regions
located in such an extensive river basin is a novelty. The results
suggest that the methodology used in this study is rather suitable to
simulate streamflow time series of ungauged catchments in the southeast
Iran. However, further research is still needed to use this approach in
other river basins of Iran.