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A good water budget involving four variables, including precipitation (P), evapotranspiration (ET), streamflow (R), and terrestrial water storage change (TWSC), is reflected in two aspects: a high accuracy against observations for each budget component and the low water budget closure residual error (ΔRes). Due to the lack of consideration of observations of budget components in existing water budget closure assessment methods (BCMs), when the ΔRes of budget components is low, their error against respective observations may still be high. In this study, we assess the water budget closure accuracy of satellite/reanalysis-based hydrological data products over mainland China based on six popular P products and multiple datasets of additional budget components (ET, R, and TWSC). The results indicated that the ΔRes changes between ±15 mm over mainland China. Satellite P products such as GPM IMERG showed better performance by comparing them with rain gauge-based observations. However, reanalysis P products such as GLDAS and FLDAS showed a better water budget closure since the selected datasets of additional budget components (ET and R) are also derived from reanalysis datasets. This indicates that these same data sources for budget components make it easier to close the water budget. The further development of satellite P products should consider the closure of the water budget with other water cycle variables. [ABSTRACT FROM AUTHOR]

• A new method was proposed to merge multiple satellite-based precipitation products (SPPs) • The method estimates grid scale errors of SPPs based on water budget closure. • The method was verified by comparing with original SPPs and three merging methods. • The performance of SPPs was slightly reduced when enforcing water budget closure. Merging multiple satellite/reanalysis-based precipitation products (SPPs) is a critical way to improve the accuracy of spatial precipitation (P) estimation. In this paper, a new method was proposed to merge multiple SPPs by considering rain gauge-based observations and water budget closure. Based on the errors of SPPs at gauged regions, the proposed method first estimates the mesh-based errors of SPPs as the intermediate variable using the error in water budget closure and then calculates the respective merging weights of SPPs in data merging. The performance of this proposed method was verified by comparing its results with the input of original SPPs and the data merged by five existing merging methods in mainland China at mesh scale and in nine major basins. Two scenarios were designed for the period from 2003.02 to 2016.12 at a monthly temporal resolution − with and without water budget closure constraints. Seven popular SPPs were considered, including GPM IMERG, PERSIANN, GSMaP, CHIRPS, ERA5, CFSV2, and TerraClimate. The results showed that the proposed method improved the P estimates in terms of CC, RMSE, MAE, PBIAS and KGE in both scenarios, and that closing the terrestrial water budget would slightly reduce the accuracy of SPPs against observations. The reduction percentage is about 5% in term of CC and KGE, and 12% in term of RMSE. This study is the first attempt to merge SPPs and gauge-based rain observation with consideration of water budget closure. It provides not only an effective and robust tool for the merging of multiple SPPs, but also important insights into the further development of SPP merging methods by considering water budget closure. [ABSTRACT FROM AUTHOR]

• A method was proposed for enforcing water budget closure by combining observations of budget components. • The method was verified in nine basins in mainland China by comparing with existing methods. • Proposed method improved budget corrected data by approximately 5-14% based on RMSE, MAE, KGE, and POD. Enforcing water budget closure is critical for providing consistent estimates of budget components to understand water movement between the atmosphere and the terrestrial land surface. However, existing water budget closure correction (BCC) methods do not consider improving the performance of budget-corrected datasets when closing the water budget. This study proposes a method for enforcing terrestrial water budget closures and improving the estimation of budget components by combining budget component measurements and introducing an error adjustment factor of ET. The proposed method first corrects raw budget component datasets based on their measurements and then enforces the water budget closure of the pre-corrected datasets using existing BCC methods. The proposed method was verified by comparing it with existing BCC methods in nine major basins in mainland China. Nine precipitation (P), four evapotranspiration (ET), two simulated runoff (R), and four terrestrial water storage change datasets were selected to comprehensively evaluate the performance of the proposed method. The results showed that the water budget closure constraint based on existing BCC methods improved the performance of datasets with low accuracy. However, the performance is not significantly improved or even reduced for datasets with high accuracy. Compared with existing BCC methods, the performance of budget-corrected datasets using the proposed method improved by approximately 8, 86, 8, 5, and 14% according to the statistical metrics root mean square error, percent bias, mean absolute error, Kling–Gupta efficiency, and probability of detection, respectively. [ABSTRACT FROM AUTHOR]