Assessment of the reliability of popular satellite products in characterizing the water balance of the Yangtze River Basin, China

Zhang, Dan; Zhang, Qi; Werner, Adrian D.; Renying, GU

doi:10.2166/nh.2016.138

Cited by 8 publications

(17 citation statements)

References 59 publications

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“…Some data products are only recommended for specific conditions. For example, the gridded precipitation product TRMM is only recommended for subtropical and tropical precipitation (Armanios & Fisher, 2014;Rusli et al, 2021;Soltani et al, 2020;D. Zhang et al, 2016;S.…”

Section: Discussion and Future Research Opportunitiesmentioning

confidence: 99%

“…Multi-year regional-scale DDWB have employed the Gravity Recovery and Climate Experiment (GRACE) global terrestrial water storage anomaly product, which combines all water on the land surface and subsurface including soil water content, groundwater, surface water, and water stored in plant biomass (Armanios & Fisher, 2014;Lv et al, 2017;Rusli et al, 2021;Soltani et al, 2020;Sriwongsitanon et al, 2020;S. Wang et al, 2014;D. Zhang et al, 2016;Zheng et al, 2022).…”

Section: Changes In Water Storage Datamentioning

confidence: 99%

“…Eliminating snow and ice-related water budget components could lead to improper modeling of subsequent processes, such as runoff or groundwater percolation that may be important to adjacent land use areas. Lack of available data on surface water inflows and outflows, such as runoff or streamflow in entirely remote sensing-based water budgets could contribute to water budget non-closure (Armanios & Fisher, 2014;Soltani et al, 2020;D. Zhang et al, 2016;S.…”

Section: Water Budget Closure Simplifying Assumptionsmentioning

confidence: 99%

“…Zhang et al, 2016). Eliminating components without data can be justifiable at specific scales, such as the assumptions of negligible surface runoff at annual time scales at regional scales such as in a large watershed (Armanios & Fisher, 2014;Soltani et al, 2020;D. Zhang et al, 2016;S.…”

Section: Water Budget Closure Simplifying Assumptionsmentioning

confidence: 99%

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A Decade of Data‐Driven Water Budgets: Synthesis and Bibliometric Review

Moyers,

Sabie,

Waring

et al. 2023

Water Resources Research

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Scarce water resources across the globe have prompted the development of data‐driven water budgets to account for and distribute limited water more effectively across various land uses and purposes. Data‐driven approaches for estimating individual water budget components have been extensively developed and subsequently reviewed (e.g., evapotranspiration, precipitation, groundwater, surface water, runoff), but the state of the art of data‐driven approaches for estimating and integrating complete water budgets has not been the subject of a review paper to our knowledge. In this review, we fill this void by reviewing 81 systematically identified publications from the last decade (2012–2022) on data‐driven water budget approaches. We describe the current state of measurements and data products for data‐driven water budgets for various spatiotemporal scales. Our analysis suggests that spatiotemporal parameters drive the approach for data‐driven water budgets, with larger spatiotemporal scales relying more on satellite remote sensing data products and smaller spatiotemporal scales relying more on ground‐based monitoring. The incorporation of satellite remote sensing data products and ground‐based monitoring was common across various spatiotemporal scales and enabled the estimation of complete water budgets in areas of limited data availability. We conclude that improved reporting of simplifying assumptions, uncertainty analysis methods, and data sources are required for the alignment of water budget estimations between resource managers at varied spatiotemporal scales. Our review calls for the standardization of data‐driven water budget reporting protocols to improve the interpretability of data‐driven water budgets across decision‐makers working at various spatiotemporal scales.

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Section: Discussion and Future Research Opportunitiesmentioning

confidence: 99%

Section: Changes In Water Storage Datamentioning

confidence: 99%

Section: Water Budget Closure Simplifying Assumptionsmentioning

confidence: 99%

Section: Water Budget Closure Simplifying Assumptionsmentioning

confidence: 99%

See 2 more Smart Citations

A Decade of Data‐Driven Water Budgets: Synthesis and Bibliometric Review

Moyers,

Sabie,

Waring

et al. 2023

Water Resources Research

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“…Effective management of water resources in arid and semi-arid environments requires accurate tools to quantify key components of the hydrological cycle such as the evapotranspiration (ET). More than 70% of precipitation received in arid environments is returned to the atmosphere via ET annually (Zhang et al, 2016;Dzikiti et al, 2018). Consequently, ET is a major component in the processes and models of climate change, water balance, groundwater recharge, net primary productivity, floods, droughts and irrigation (Fisher et al, 2008;Műnch et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

Comparison of two remote sensing models for estimating evapotranspiration: algorithm evaluation and application in seasonally arid ecosystems in South Africa

et al. 2019

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Remote sensing tools are becoming increasingly important for providing spatial information on water use by different ecosystems. Despite significant advances in remote sensing based evapotranspiration (ET) models in recent years, important information gaps still exist on the accuracy of the models particularly in arid and semi-arid environments. In this study, we evaluated the Penman-Monteith based MOD16 and the modified Priestley-Taylor (PT-JPL) models at the daily time step against three measured ET datasets. We used data from two summer and one winter rainfall sites in South Africa. One site was dominated by native broad leaf and the other by fine leafed deciduous savanna tree species and C 4 grasses. The third site was in the winter rainfall Cape region and had shrubby fynbos vegetation. Actual ET was measured using open-path eddy covariance systems at the summer rainfall sites while a surface energy balance system utilizing the large aperture boundary layer scintillometer was used in the Cape. Model performance varied between sites and between years with the worst estimates (R 2 <0.50 and RMSE>0.80 mm/d) observed during years with prolonged mid-summer dry spells in the summer rainfall areas. Sensitivity tests on MOD16 showed that the leaf area index, surface conductance and radiation budget parameters had the largest effect on simulated ET. MOD16 ET predictions were improved by: (1) reformulating the emissivity expressions in the net radiation equation; (2) incorporating representative surface conductance values; and (3) including a soil moisture stress function in the transpiration sub-model. Implementing these changes increased the accuracy of MOD16 daily ET predictions at all sites. However, similar adjustments to the PT-JPL model yielded minimal improvements. We conclude that the MOD16 ET model has the potential to accurately predict water use in arid environments provided soil water stress and accurate biome-specific parameters are incorporated. Citation: Sebinasi DZIKITI, Nebo Z JOVANOVIC, Richard DH BUGAN, Abel RAMOELO, Nobuhle P MAJOZI, Alecia NICKLESS, Moses A CHO, David C LE MAITRE, Zanele NTSHIDI, Harrison H PIENAAR. 2019. Comparison of two remote sensing models for estimating evapotranspiration: algorithm evaluation and application in seasonally arid ecosystems in South Africa. Journal of Arid Land, 11(4): 495-512. https://doi.

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