Combining rainfall data from rain gauges and TRMM in hydrological modelling of Laotian data-sparse basins

Xing Liu,Xiao Dong Li,Shi Xiang Cai,Yu Yan Fan,Xiao Xia Wang,Tian Qi Ao,Fa Ming Liu

doi:10.1007/s13201-015-0330-y

Xing Liu, Xiao Dong Li + Show 5 more

Open Access

https://doi.org/10.1007/s13201-015-0330-y

Copy DOI

Abstract

At present, prediction of streamflow simulation in data-sparse basins of the South East Asia is a challenging task due to the absence of reliable ground-based rainfall information, while satellite-based rainfall estimates are immensely useful to improve our understanding of spatio-temporal variation of rainfall, particularly for data-sparse basins. In this study the TRMM 3B42 V7 and its bias-corrected data were, respectively, used to drive a physically based distributed hydrological model BTOPMC to perform daily streamflow simulations in Nam Khan River and Nam Like River basins during the years from 2000 to 2004 so as to investigate the potential use of the TRMM in complementing rain gauge data in hydrological modelling of data-sparse basins. The results show that although larger difference exists in the high streamflow process and the low streamflow process, the daily simulations fed with TRMM precipitation data could basically reflect the daily streamflow processes at the four stations and determine the time to peak. Furthermore, the calibrated parameters in the Nam Khan River basin are more suitable than that in the Nam Like River basin. By comparing the two precipitation data, it indicates that the integration of TRMM precipitation data and rain gauge data have a promising prospect on the hydrological process simulation in data-sparse basin.

Highlights

Precipitation is one of the most important factors in the process of hydrological cycle
The TRMM 3B42 V7 daily precipitation and its bias-corrected data were, respectively, used to drive the distributed hydrological model to perform daily streamflow simulations at the Ban Pak Bak station, Ban Mout station located in Nam Khan River basin and Kasi station and Hin Heup station located in Nam Like River basin during the 5-year period from 2000 to 2004 so as to assess the feasibility of the TRMM precipitation on streamflow process simulation in Laos data-sparse basins
The Nash–Sutcliffe coefficient (NSCE) and volume ratio (Vr) values indicate that the calibrated parameters perform better at Nam Khan River basin than at Nam Like River basin

Summary

Introduction

Precipitation is one of the most important factors in the process of hydrological cycle. Precipitation estimates are mainly derived from two sources, i.e., rain gauge station observations and ground radar measurements. Because of its problem of limited coverage area, high costs of establishing and maintaining infrastructure, etc., there is no perfect radar network of many regions (Gu et al 2010). It still cannot meet the requirements of study carried out on large-scale basins. These drawbacks of conventionally obtained rainfall data impose a remarkable limitation on the application of distributed hydrological model.

Objectives

Results

Conclusion