Search

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 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]

• SWAT model was modified to examine the capability of PET products in improving hydrological simulation accuracy. • Distributed input and higher spatial resolution of PET products are more conducive to hydrological modeling. • The input of PET products has a great impact on streamflow and baseflow, followed by surface runoff. • The accuracy of PET products should be improved from both improving PET products and considering water budget closure. Terrestrial evapotranspiration (ET), which links water and energy exchanges between atmosphere, land surface and underground water, significantly affects hydrological modelling. However, accurate ET estimation is still a great challenge for hydrological models. Currently, most hydrological models obtain ET mainly from their built-in potential evapotranspiration (PET) modules due to lack of observations. Note that the ET obtained in this way cannot be verified by observations and inevitably brings large model uncertainty. Fortunately, several PET products have been produced based on satellite remote sensing and/or reanalysis climate model output with global coverage and high spatiotemporal resolution, providing a great opportunity for tunning hydrological models. However, the accuracy of global gridded PET products varies in different regions. It is still unknown whether PET products can improve the accuracy of hydrological simulation, and how different resolutions and input types (lumped/distributed) of PET products affect the performance of hydrological models. The question about how hydrological models will be further developed in combination with PET products is also not well answered, given the complexity in interaction between ET and other water cycle variables. In this study, a modified Soil and Water Assessment Tool (SWAT) was chosen to examine the capability of PET products in improving hydrological simulation in terms of surface runoff, streamflow and baseflow, together with the Shaying River Basin in China as a case study. Two Moderate Resolution Imaging Spectroradiometer (MODIS) PET products were employed to form various PET scenarios. Results indicate that PET products are significantly different from the PET simulated by the SWAT built-in PET module in terms of spatial distribution and magnitudes. According to statistical metrics, the use of PET products to replace the SWAT built-in PET module can improve the accuracy of hydrological simulation compared with the original SWAT using its built-in PET module. The distributed input and higher spatial resolution of PET products are more conducive to improve the accuracy of hydrological simulation. Our research shows that both improving the accuracy of PET products and balancing water budget closure are critical for accurate hydrological modeling. These conclusions obtained based on MODIS products were further verified against a hourly PET data product (hPET). This study provides insights into understanding the use of PET products in improving the accuracy of hydrological simulation. The study findings can provide a beneficial reference for the further development of hydrological models in combination with PET products. [ABSTRACT FROM AUTHOR]

• New method is proposed to assess accuracy of satellite products in ungauged basins. • Mutual cancellation in product errors is avoided in water budget closure. • Results of proposed method are examined by the application of FORM. • The proposed method showed lower dependence on precipitation. Remote sensing products have been widely used in water resources assessment and management. However, the accuracy varies in different products. Water budget closure provides an important breakthrough for better assessing the uncertainties and quantifying error sources of satellite-based data products using water budget imbalance, especially in ungauged basins where conventional verification methods are not applicable. However, the commonly used assessment methods mainly refer to closure residual of water budget Δ Re s or its proportion to corresponding mean precipitation (P) Δ Re s / P , which have apparent limitations due to the dimensional effects in the former method and the high dependence on precipitation in the latter one. More critically, these two methods do not consider measured values (referring to in-situ values in gauged basins or average values of multiple satellite products in ungauged basins as in this study) as benchmarks of water budget components in the assessment of satellite-based hydrological data products, resulting in a wrong choice because the closure result is subject to the mutual cancellation in the errors of water budget components from different satellite-based products. This study proposes a novel error-based method to assess the accuracy of satellite-based hydrological data products for both gauged and ungauged basins based on water budget equation, measured values, and the omission error (OE) which is generally overlooked in existing studies. The method is applied to a typical closed basin, the Tarim River Basin (TRB) of China, to verify the applicability and reliability of the proposed method. Sixty combinations of water budget components from various satellite sources can be designed based on five precipitation (P) products, four evapotranspiration (ET) products and three terrestrial water storage change (TWSC) products. First order reliability method (FORM) is employed to assess the reliability of water budget closure results caused by the errors of satellite sources. The results indicated that different combinations produced different annual Δ Re s and Δ Re s / P , indicating great water budget closure errors for different combinations due to errors in different satellite sources. The OE error from satellite-based hydrological data products of water budget components clearly showed a greater impact on water budget imbalance than water budget components, indicating that OE error is important for understanding quality of satellite products. By comparing the results of Δ Re s and Δ Re s / P , it can be seen that our proposed method had great advantages in assessment of satellite products with a low dependence on P, and a better comparability between different combinations. The value of our assessment criterion ranges from 0 to 1 which is easier to understand in practice. The combinations of water budget components from TRMM_3B43 (P), GPM_3IMERGHH (P), GLDAS_NOAH025 (ET), and GRACE (TWSC) products show satisfactory water budget closure results in TRB using our proposed method. The proposed method provides a new aspect for assessing the accuracy of satellite-based hydrological data products especially in ungauged basins, which provides insights into water resources management in basins. [ABSTRACT FROM AUTHOR]

Temporally continuous daily actual evapotranspiration (ET) data play a critical role in water resource management in arid areas. As a typical remotely sensed land surface temperature (LST)-based ET model, the surface temperature-vegetation index (Ts-VI) triangle model provides direct monitoring of ET, but these estimates are temporally discontinuous due to cloud contamination. In this work, we present a gap-filling algorithm (TSVI_DNN) using a deep neural network (DNN) with the Ts-VI triangle model to obtain temporally continuous daily actual ET at regional scale. The TSVI_DNN model is evaluated against in situ measurements in an arid area of China during 2009–2011 and shows good agreement with eddy covariance (EC) observations. The temporal coverage was improved from 16.1% with the original Ts-VI tringle model to 67.1% with the TSVI_DNN model. The correlation coefficient (R), root mean square error (RMSE), bias, and mean absolute difference (MAD) are 0.9, 0.86 mm d−1, −0.16 mm d−1, and 0.65 mm d−1, respectively. When compared with the National Aeronautics and Space Administration (NASA) official MOD16 version 6 ET product, estimates of ET using TSVI_DNN are improved by approximately 49.2%. The method presented here can potentially contribute to enhanced water resource management in arid areas, especially under climate change. [ABSTRACT FROM AUTHOR]