GRACE‐FO and ECOSTRESS Synergies Constrain Fine‐Scale Impacts on the Water Balance

Pascolini‐Campbell, Madeleine; Fisher, Joshua B.; Reager, J. T.

doi:10.1029/2021gl093984

Cited by 9 publications

(4 citation statements)

References 48 publications

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“…Accurate agricultural ET measures are crucial to characterize anthropogenic impacts on the hydrological cycle 31 and enact effective water management 18 , 32 . Previously, agricultural ET has been estimated by (i) simulating crop water demand based on crop type and climate and (ii) removing naturally available water by subtracting precipitation 19 , 22 .…”

Section: Discussionmentioning

confidence: 99%

Field-scale crop water consumption estimates reveal potential water savings in California agriculture

Boser,

Caylor,

Larsen

et al. 2024

Nat Commun

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Efficiently managing agricultural irrigation is vital for food security today and into the future under climate change. Yet, evaluating agriculture’s hydrological impacts and strategies to reduce them remains challenging due to a lack of field-scale data on crop water consumption. Here, we develop a method to fill this gap using remote sensing and machine learning, and leverage it to assess water saving strategies in California’s Central Valley. We find that switching to lower water intensity crops can reduce consumption by up to 93%, but this requires adopting uncommon crop types. Northern counties have substantially lower irrigation efficiencies than southern counties, suggesting another potential source of water savings. Other practices that do not alter land cover can save up to 11% of water consumption. These results reveal diverse approaches for achieving sustainable water use, emphasizing the potential of sub-field scale crop water consumption maps to guide water management in California and beyond.

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Section: Discussionmentioning

confidence: 99%

Field-scale crop water consumption estimates reveal potential water savings in California agriculture

Boser,

Caylor,

Larsen

et al. 2024

Nat Commun

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“…The expectation is that the soil moisture limitation will be expressed in the vegetation structure or other spectral characteristics (e.g., leaf pigments, water content). Soil moisture (and ground water) are difficult to measure directly across space, but remote sensing-based GPP estimates could likely be improved with explicit characterization of gridded water availability, such as with the Evaporative Stress Index 60 or with newer sensors such as SMAP 61 or GRACE 62 .…”

Section: Discussionmentioning

confidence: 99%

“…Here, we examine how the water-energy limitation spectrum affects the sensitivity of GPP to meteorological drought across the Northern Hemisphere ( >30°N) 39 . We use a newly available compilation of long-term eddy covariance (EC) observations from >60 longterm sites with ≥10 years of data within a given season (spring (61), summer (62), or fall ( 63)) (Supplemental Fig. S1, Supplemental Table S1), and analyze GPP sensitivities to drought using precipitation, air temperature, and photosynthetically active radiation (PAR) as meteorological descriptors.…”

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confidence: 99%

Increased photosynthesis during spring drought in energy-limited ecosystems

Miller,

Wolf,

Fisher

et al. 2023

Nat Commun

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Drought is often thought to reduce ecosystem photosynthesis. However, theory suggests there is potential for increased photosynthesis during meteorological drought, especially in energy-limited ecosystems. Here, we examine the response of photosynthesis (gross primary productivity, GPP) to meteorological drought across the water-energy limitation spectrum. We find a consistent increase in eddy covariance GPP during spring drought in energy-limited ecosystems (83% of the energy-limited sites). Half of spring GPP sensitivity to precipitation was predicted solely from the wetness index (R2 = 0.47, p < 0.001), with weaker relationships in summer and fall. Our results suggest GPP increases during spring drought for 55% of vegetated Northern Hemisphere lands ( >30° N). We then compare these results to terrestrial biosphere model outputs and remote sensing products. In contrast to trends detected in eddy covariance data, model mean GPP always declined under spring precipitation deficits after controlling for air temperature and light availability. While remote sensing products captured the observed negative spring GPP sensitivity in energy-limited ecosystems, terrestrial biosphere models proved insufficiently sensitive to spring precipitation deficits.

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“…The European Space Agency (ESA) designed the Soil Moisture and Ocean Salinity mission to understand two important parts of the water cycle (Jackson et al., 2011; Kerr et al., 2001). The Orbiting Carbon Observatory missions improve our understanding of the global carbon cycle (Crisp et al., 2004; Eldering et al., 2017), and the ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) provides critical metrics on plant heat stress and water uptake (Fisher et al., 2020; Pascolini‐Campbell et al., 2021; Xiao et al., 2021). These missions were each optimized to measure a specific quantity or for a particular application that dictated all hardware and mission design decisions.…”

Section: Introductionmentioning

confidence: 99%

Intrinsic Dimensionality as a Metric for the Impact of Mission Design Parameters

et al. 2022

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High‐resolution space‐based spectral imaging of the Earth's surface delivers critical information for monitoring changes in the Earth system as well as resource management and utilization. Orbiting spectrometers are built according to multiple design parameters, including ground sampling distance (GSD), spectral resolution, temporal resolution, and signal‐to‐noise ratio. Different applications drive divergent instrument designs, so optimization for wide‐reaching missions is complex. The Surface Biology and Geology component of NASA's Earth System Observatory addresses science questions and meets applications needs across diverse fields, including terrestrial and aquatic ecosystems, natural disasters, and the cryosphere. The algorithms required to generate the geophysical variables from the observed spectral imagery each have their own inherent dependencies and sensitivities, and weighting these objectively is challenging. Here, we introduce intrinsic dimensionality (ID), a measure of information content, as an applications‐agnostic, data‐driven metric to quantify performance sensitivity to various design parameters. ID is computed through the analysis of the eigenvalues of the image covariance matrix, and can be thought of as the number of significant principal components. This metric is extremely powerful for quantifying the information content in high‐dimensional data, such as spectrally resolved radiances and their changes over space and time. We find that the ID decreases for coarser GSD, decreased spectral resolution and range, less frequent acquisitions, and lower signal‐to‐noise levels. This decrease in information content has implications for all derived products. ID is simple to compute, providing a single quantitative standard to evaluate combinations of design parameters, irrespective of higher‐level algorithms, products, applications, or disciplines.

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GRACE‐FO and ECOSTRESS Synergies Constrain Fine‐Scale Impacts on the Water Balance

Abstract: Water balance-based estimates of evapotranspiration (ET) using observations of mass change from the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) satellites have been found to diverge from state-of-the-art land hydrology assimilation model ET (

Cited by 9 publications

References 48 publications

Field-scale crop water consumption estimates reveal potential water savings in California agriculture

Field-scale crop water consumption estimates reveal potential water savings in California agriculture

Increased photosynthesis during spring drought in energy-limited ecosystems

Intrinsic Dimensionality as a Metric for the Impact of Mission Design Parameters

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