Regionalisation of hydrological responses under land-use change and variable data quality

Visessri, S. and McIntyre, N. (2015) Regionalisation of hydrological responses under land-use change and variable data quality. Hydrological Sciences Journal, 61 2: 302-320. doi:10.1080/02626667.2015.1006226

Author Visessri, S.
McIntyre, N.
Title Regionalisation of hydrological responses under land-use change and variable data quality
Journal name Hydrological Sciences Journal   Check publisher's open access policy
ISSN 2150-3435
Publication date 2015-12-09
Year available 2015
Sub-type Article (original research)
DOI 10.1080/02626667.2015.1006226
Open Access Status Not yet assessed
Volume 61
Issue 2
Start page 302
End page 320
Total pages 19
Place of publication Abingdon, Oxfordshire, United Kingdom
Publisher Taylor and Francis
Language eng
Subject 2312 Water Science and Technology
Abstract Estimating river flows at ungauged sites is generally recognised as an important area of research. In countries or regions with rapid land development and sparse hydrological gauging networks, three particular challenges may arise—data scarcity, data quality, and hydrological non-stationarity. Using data from 44 gauged sub-catchments of the upper Ping catchment in northern Thailand from the period 1995–2006, three relevant flow response indices (runoff coefficient, base flow index and seasonal elasticity of flow) were regionalised by regression against available catchment properties. The runoff coefficient was the most successfully regionalised, followed by base flow index and lastly the seasonal elasticity. The non-stationarity (represented by the differences between two 6-year sub-periods) was significant both in the flow response indices and in land use indices; however relationships between the two sets of indices were weak. The regression equations derived from regionalisation were not helpful in predicting the non-stationarity in the flow indices except somewhat for the runoff coefficient. A partly subjective data quality scoring system was devised, and showed the clear influence of rainfall and flow data quality on regionalisation uncertainty. Recommendations towards improving data support for hydrological regionalisation in Thailand include more relevant soils databases, improved records of abstractions and investment in the gauge network. Widening of the regionalisation beyond the upper Ping and renewed efforts at using remotely sensed rainfall data are other possible ways forward.
Keyword Predictions in ungauged basins
Rainfall–runoff indices
Data quality
Land-use change
Ping basin
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2016 Collection
Sustainable Minerals Institute Publications
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