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Shanshan Deng, Suxia Liu, and Xingguo Mo

correspond to the significance levels of 0.1, 0.05, and 0.01. Second, the mean values of the estimates and the GRACE data are used to show the level of imbalance between the input and output of the water budget. Since the mean value of the TWSC monthly series in each grid is the mass change rate on a monthly scale, it reflects the regional water balance. The imbalance in the GRACE data can be regarded as the real changes in the water cycle caused by climate change or anthropogenic influences because of

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Michael G. Bosilovich, Franklin R. Robertson, and Junye Chen

the formulation of the budgets is discussed by Rienecker et al. (2007) and Suarez et al. (2011) . 3. Water and energy budgets a. Global mean climatology TFK09 collect the global energy budget data from various sources, observational and reanalyses, and close it with consistency arguments from dataset intercomparisons, to determine estimates for principal energy flux components and balance. However, each term exhibits large variations among the different observing systems and reanalyses, so any

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Yonghui Lei, Jiancheng Shi, Chuan Xiong, and Dabin Ji

partitioning the water balance into atmospheric and terrestrial components ( Peixoto and Oort 1992 ; Oki et al. 1995 ; Trenberth and Guillemot 1998 ), the net water flux is present in both atmospheric and terrestrial water budgets, as shown in Eqs. (1) and (2) : (1) P − E = − ∂ W ∂ t − ∇ ⋅ V q , (2) P − E = ∂ S ∂ t + R , where W is the total column water vapor in the atmosphere; − ∇ ⋅ V q is the vertically integrated moisture convergence, where V and q are the horizontal wind and specific

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Kai Tong, Fengge Su, and Chunhong Li

water over the past 50 years. A 10-yr-long (2001–10) modeling study in four lakes (including Nam Co Lake) in the southern-central TP indicated that the glacier-melt contribution to the total basin runoff volume played a less important role than precipitation-induced runoff in nonglacierized land areas ( Biskop et al. 2016 ). In Nam Co Lake, long-term (1980–2010) changes in the water budget and lake level were simulated using a dynamic water balance model by Wu et al. (2014) , and glacier melt

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Yu Ren, Haipeng Yu, Chenxi Liu, Yongli He, Jianping Huang, Lixia Zhang, Huancui Hu, Qiang Zhang, Siyu Chen, Xiaoyue Liu, Meng Zhang, Yun Wei, Yaoxian Yan, Weiwei Fan, and Jie Zhou

and Farquhar 2011 ; Wang and Hejazi 2011 ; Xu et al. 2014 ; W. Wang et al. 2016 ; Wu et al. 2017 ; Tian et al. 2018 ; Li et al. 2020 ; Gao et al. 2020 ). By utilizing Budyko equations in CA, we aim to acquire a better understanding of the contributions of climate change to wet/dry trends from the perspective of the surface water balance. In addition to the surface water budget, the atmospheric water budget is another important aspect for measuring dry and wet changes. Dominguez et al

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Jefferson S. Wong, Xuebin Zhang, Shervan Gharari, Rajesh R. Shrestha, Howard S. Wheater, and James S. Famiglietti

the occurrence of hydrological extremes, and resolving the complex interactions of the land surface, oceans and atmosphere. This could be achieved by accurate and reliable estimation of the terrestrial water budget components. With the increase of data availability for each water budget component from various sources (e.g., satellite remote sensing, climate model reanalysis), the water balance and its uncertainty can be better assessed and quantified at regional or continental scales. This is

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Sanaa Hobeichi, Gab Abramowitz, Steefan Contractor, and Jason Evans

(2018) have characterized the performance of multiple precipitation datasets through an approach that combines ground-based observation of multiple hydrologic variables along with performance metrics based on surface water budget closure. Their approach offers advancement over previous studies by allowing a more reliable evaluation of precipitation datasets over regions with sparse observations by relying on the physical conservation constraints offered by the water balance. In the same context

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Chuanhao Wu, Pat J.-F. Yeh, Haichun Wu, Bill X. Hu, and Guoru Huang

temporal variability of climatic forcing involves various region-specific processes such as snow thawing–melting and vegetation growth ( Zeng and Cai 2016 ). Although advances have been made to quantify the Δ S effects on the water balances estimation within the Budyko framework, our knowledge on the roles of Δ S in water balance partition and its influences on BM performance at the shorter time scales is still limited given the large spatiotemporal variability in most water budget variables and the

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Xiaoyin Liu, Junzeng Xu, Shihong Yang, Jiangang Zhang, and Yijiang Wang

that soil heat storage was released slowly over the several hours after sunset ( Masseroni et al. 2015 ; Liu et al. 2018 ). This explains why, in rice fields, Cs events occurred much later than Cc events. c. Importance and contribution of vapor condensation to the rice field water budget While vapor condensation was well recognized as an important hydrometeorological process and water balance component in arid or semiarid areas, information on vapor condensation in humid areas was scarce. The

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S. Irmak and M.S. Kukal

vegetation in units of depth (e.g., millimeters of H 2 O), which cannot be derived from any of its constituent indicators alone. They directly affect plant stomatal behavior, surface energy balance and water budgets of cropping systems ( Haghighi et al. 2018 ; Grossiord et al. 2020 ), and thus, are critical to analyze for agricultural applications. While fundamental climate variables are adequately analyzed, compound variables of agricultural relevance are not comprehensively addressed for Turkish

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