Assessing and optimizing high-resolution global river streamflow estimates with triple collocation analysis

Sun, M., Tangdamrongsub, N., Sun, Y., Dong, J., Sutanudjaja, E., & Smilovic, M. ORCID: https://orcid.org/0000-0001-9651-8821 (2026). Assessing and optimizing high-resolution global river streamflow estimates with triple collocation analysis. Journal of Hydrology 669 e135122. 10.1016/j.jhydrol.2026.135122.

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Abstract

Accurate river discharge data are essential for effective water resource management, flood forecasting, drought mitigation, and ecological sustainability. However, the global river gauge network remains sparse, outdated, and often inaccessible, particularly in developing or remote regions, limiting our ability to monitor and manage hydrological systems. In response, global hydrological models have emerged as critical tools for estimating streamflow, yet their accuracy and applicability require systematic evaluation. This study assesses the performance of three global hydrological models—Community Water Model (CWatM), PCRaster Global Water Balance (PCR-GLOBWB), and H08—at both high (5 arcmin) and low (30 arcmin) spatial resolutions. Observed discharge data from 1,707 Global Runoff Data Centre (GRDC) stations and 62 stations in Thailand were used for evaluation. Additionally, two data fusion methods—Triple Collocation (TC) and simple averaging—were employed to enhance streamflow simulations by integrating outputs from the three models. Results show that CWatM, particularly at high resolution, consistently outperforms PCR-GLOBWB and H08, while all models demonstrate stronger performance in Europe than in other regions. Both TC and averaging methods improve simulation accuracy compared to individual models, with TC offering the highest overall performance, especially when using H08 as the reference system. Resolution analysis reveals that high-resolution models yield more accurate estimates in most regions. This study highlights the value of multi-model integration and resolution optimization in enhancing global streamflow simulation. The findings provide practical guidance for model selection and data fusion strategies, particularly in improving hydrological assessments for ungauged or poorly monitored regions.

Item Type:	Article
Research Programs:	Biodiversity and Natural Resources (BNR) Biodiversity and Natural Resources (BNR) > Water Security (WAT)
Depositing User:	Luke Kirwan
Date Deposited:	24 Feb 2026 12:42
Last Modified:	24 Feb 2026 12:42
URI:	https://pure.iiasa.ac.at/21348

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