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]

The conflict of the human-water relationships (HWR) has further increased the water-related risks, such as water environment deterioration, water shortages, and even regional violent conflicts for obtaining usable water resources. Knowing how to evaluate and regulate the discordant HWR to form a balanced growth between sustainable socio-economy and water resources protection has become a critical issue in water resources management. The harmony theory method, which provides a new perspective for solving the conflict between humans and water, has been widely used in current studies. However, this method focuses less on the quantitative study of the balance status of HWR. This study proposes a harmony theory-based HWR evaluation method that contains a systematic process of harmony assessment, indicator identification, harmony balance constraints, and harmony regulation for assessing and regulating the discordant HWR. The Henan Province of China, which has a complicated HWR, was selected as a case study to apply and verify the approach proposed in this study. The results indicated that (1) Henan Province showed a poor harmony status. The human–water harmony degree of 18 distinctions in the province varied from 0.41 to 0.76, showing an increasing trend from 2006 to 2018, indicating that the HWR was gradually improving in recent years. (2) The human–water harmony degree showed that HWR in the southwest part of Henan Province, with less human activities, was better than that in its northeast part, which had faster social development. Sanmenxia City, located in the west part of the province, had the highest human–water harmony degree because of the recent water control projects implemented in the city, indicating that human production measures could effectively help improve HWR. (3) At present, Henan Province has serious discordant indicators in these three aspects (water system health, humanistic system development, and human-water system coordination), which proves that it is still facing pressure from both socio-economy sustainable development and water resources protection. Our results provide insight into water resources management in Henan Province and other similar regions. [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]