## Appendix A
(2011)_ [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; et al. The coupled routing and excess storage (CREST) distributed hydrological model. _Hydrol. Sci. J._**2011**, _56_, 84-98. [CrossRef]
* _[PERSON] et al. (2016)_ [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] A method for probabilistic flash flood forecasting. _J. Hydrol._**2016**, _541_, 480-494. [CrossRef]
* _[PERSON] et al. (2017)_ [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Hydrological Modeling and Capacity Building in the Republic of Namibia. _Bull. Am. Meteorol. Soc._**2017**, _98_, 1697-1715. [CrossRef]
* _[PERSON] et al. (2017)_ [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Assessing the potential of satellite-based precipitation estimates for flood frequency analysis in ungauged or poorly gauged tributaries of China's Yangtze River basin. _J. Hydrol._**2017**, _550_, 478-496. [CrossRef]
* _[PERSON] et al. (2018)_ [PERSON]; [PERSON]; [PERSON] Using high-resolution satellite precipitation for flood frequency analysis: Case study over the Connecticut River Basin. _J. Flood Risk Manag._**2018**, _11_, S514-S526. [CrossRef]* [PERSON] et al. (2021) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Mapping dynamic non-perennial stream networks using high-resolution distributed hydrologic simulation: A case study in the upper blue river basin. _J. Hydrol._**2021**, _600_, 126522. [CrossRef]
* [PERSON] et al. (2017) [PERSON]; [PERSON]; [PERSON]; [PERSON] Refining a Distributed Linear Reservoir Routing Method to Improve Performance of the CREST Model. _J. Hydrol. Eng._**2017**, _22_, 04016061. [CrossRef]
* [PERSON] et al. (1992) [PERSON]; [PERSON]; [PERSON] Effective and efficient global optimization for conceptual rainfall-runoff models. _Water Resour. Res._**1992**, _28_, 1015-1031. [CrossRef]
* [PERSON] (2007) [PERSON]; [PERSON]; [PERSON] Comparison of Near-Real-Time Precipitation Estimates from Satellite Observations. _Bull. Am. Meteorol. Soc._**2007**, _88_, 47-64. [CrossRef]
* [PERSON] et al. (2021) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Multi-Criteria Performance Evaluation of Gridded Precipitation and Temperature Products in Data-Sparse Regions. _Atmosphere_**2021**, _12_, 1597. [CrossRef]
* [PERSON] and [PERSON] (2023) [PERSON]; [PERSON] Advantages of GSMaP Data for Multi-Timescale Precipitation Estimation in Luzon. _Earth Space Sci._**2023**, _10_, e2023 EA002980. [CrossRef]
* [PERSON] et al. (2023) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Evaluation and Applicability Analysis of GPM Satellite Precipitation over Mainland China. _Remote Sens._**2023**, _15_, 2866. [CrossRef]
* [PERSON] (1994) [PERSON] _Two-Layer Variable Infiltration Capacity Land Surface Representation for General Circulation Models_; University of Washington: Seattle, WA, USA, 1994. * [PERSON] and [PERSON] (2013) [PERSON]; [PERSON] Estimation of Satellite Rainfall Error Variance Using Readily Available Geophysical Features. _IEEE Trans. Geosci. Remote Sens._**2013**, _52_, 288-304. [CrossRef]
* [PERSON] et al. (2017) [PERSON]; [PERSON]; [PERSON]; [PERSON] Decomposing the satellite precipitation error propagation through the rainfall-runoff processes. _Adv. Water Resour._**2017**, _109_, 253-266. [CrossRef]
* [PERSON] et al. (2014) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Effects of Resolution of Satellite-Based Rainfall Estimates on Hydrologic Modeling Skill at Different Scales. _J. Hydrometeorol._**2014**, _15_, 593-613. [CrossRef]
* [PERSON] (2004) [PERSON]; [PERSON] Effect of precipitation sampling error on simulated hydrological fluxes and states: Anticipating the Global Precipitation Measurement satellites. _J. Geophys. Res. Atmos._**2004**, _109_.