Unraveling phenological and stomatal responses to flash drought and implications for water and carbon budgets

Hydrology and earth system sciences, Год журнала: 2024, Номер 28(8), С. 1827 - 1851

Опубликована: Апрель 22, 2024

Abstract. In recent years, extreme droughts in the United States have increased frequency and severity, underlining a need to improve our understanding of vegetation resilience adaptation. Flash are events marked by rapid dry down soils due lack precipitation, high temperatures, air. These also associated with reduced preparation, response, management time windows before during drought, exacerbating their detrimental impacts on people food systems. Improvements actionable information for flash drought informed atmospheric land surface processes, including responses feedbacks from vegetation. Phenologic state, or growth stage, is an important metric modeling how modulates land–atmosphere interactions. Reduced stomatal conductance leads cascading effects carbon water fluxes. We investigate uncertainty phenology regulation propagates through non-drought periods coupling hydrology model predictive model. assess role partitioning carbon, water, energy fluxes carry out comparison against periods. selected study sites Kansas, USA, that were impacted 2012 AmeriFlux eddy covariance towers which provide ground observations compare estimates. Results show compounding precipitation vapor pressure deficit (VPD) distinguish other High VPD shuts modeled conductance, resulting rates evapotranspiration (ET), gross primary productivity (GPP), use efficiency (WUE) fall below those average conditions. Model estimates GPP ET decrease similar what observed winter, indicating plant function dormant months. results implications improving predictions

Язык: Английский

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The impacts of drought on water availability: spatial and temporal analysis in the Belt and Road region (2001–2020)

International Journal of Digital Earth, Год журнала: 2025, Номер 18(1)

Опубликована: Янв. 8, 2025

Climate change, population growth, and economic development exacerbate water scarcity. This study investigates the impact of drought on availability in Belt Road region using high-resolution remote sensing data from 2001 to 2020. The results revealed an average (precipitation minus evapotranspiration) 249 mm/year a declining trend region. Approximately 13% faces deficits (evapotranspiration exceeds precipitation), primarily arid semi-arid regions with high frequency. area deficit is expanding, intensity increasing. annual strongly related frequency droughts, i.e. decreases increased Drought exacerbates seasonal stress approximately one-third region, mainly Europe northern Asia, where frequently occurs during seasons low availability. more severe drought, larger negative anomaly critical role evapotranspiration variability also highlighted. research underscores importance understanding drought-induced changes availability, which crucial for sustainable resource management.

Язык: Английский

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Unveiling the role of past vapor pressure deficit through soil moisture in driving tropical vegetation productivity

Environmental Research Letters, Год журнала: 2024, Номер 19(10), С. 104040 - 104040

Опубликована: Авг. 29, 2024

Abstract The impact of soil moisture (SM) and vapor pressure deficit (VPD) on gross primary productivity (GPP) variability in ecosystems is a topic significant interest. Previous studies have predominantly focused real-time associations between SM, VPD, carbon uptake, attributing SM as the principal driver GPP due to its direct indirect effects through VPD. Using an information theory-based process network approach, we discovered that influence past mediated emerges across tropical regions. VPD conditions directly also affect alongside GPP, which subsequently impacts variability. Examining land-atmosphere feedback using theory reveals but not reverse. These causal structures explain consistent decline with increasing trends observed regions, are trends. Our findings emphasize importance considering by when analyzing complex land-vegetation-atmosphere interactions.

Язык: Английский

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Extrapolability Improvement of Machine Learning-Based Evapotranspiration Models via Domain-Adversarial Neural Networks

Environmental Modelling & Software, Год журнала: 2025, Номер unknown, С. 106383 - 106383

Опубликована: Фев. 1, 2025

Язык: Английский

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Modeling the Impact of Water Hyacinth on Evapotranspiration in the Chongón Reservoir Using Remote Sensing Techniques: Implications for Aquatic Ecology and Invasive Species Management

Hydrology, Год журнала: 2025, Номер 12(4), С. 80 - 80

Опубликована: Апрель 2, 2025

The proliferation of water hyacinth (Eichhornia crassipes) in the Chongón Reservoir, located within Parque Lago National Recreation Area Guayaquil, Ecuador, poses significant challenges to local aquatic ecosystem and resource management. This study assesses impact coverage on evapotranspiration rates over a 20-year period from 2002 2022 using remote sensing data geospatial analysis. Normalized Difference Vegetation Index (NDVI), derived Landsat satellite imagery, along with meteorological records, was utilized model spatial temporal dynamics its effects evapotranspiration. Our results indicate that fluctuates significantly between rainy dry seasons, increasing covering 10.42% reservoir area peak 42.33% 2017 during seasons. A strong positive correlation (r=0.92, p<0.001) found net daily loss due associated were higher season (mean 2309.90 mm/year) compared 1917.87 mm/year). These elevated contribute increased reservoir, potentially impacting availability for municipal agricultural use. Controlling spread is therefore crucial preserving reservoir’s ecological integrity ensuring sustainable findings this provide valuable insights informing management strategies aimed at mitigating invasive species freshwater resources maintaining health.

Язык: Английский

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Atmospheric drought indices in future projections

Nature Water, Год журнала: 2025, Номер unknown

Опубликована: Апрель 11, 2025

Язык: Английский

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Radiation, Air Temperature, and Soil Water Availability Drive Tree Water Deficit Across Temporal Scales in Canada's Western Boreal Forest

Geophysical Research Letters, Год журнала: 2024, Номер 51(8)

Опубликована: Апрель 10, 2024

Abstract Changes are projected for the boreal biome with complex and variable effects on forest vegetation including drought‐induced tree mortality loss. With soil atmospheric conditions governing drought intensity, specific drivers of trees water stress can be difficult to disentangle across temporal scales. We used wavelet analysis causality detection identify potential environmental controls (evapotranspiration, moisture, rainfall, vapor pressure deficit, air temperature photosynthetically active radiation) daily deficit longer periods dehydration in black spruce tamarack. Daily was controlled by radiation, temperature, causing greater stand evapotranspiration. Prolonged (multi‐day) were regulated radiation moisture. provide empirical evidence that continued warming drying will cause short‐term increases tamarack transpiration, but reduced availability.

Язык: Английский

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The intricacies of vegetation responses to changing moisture conditions

New Phytologist, Год журнала: 2024, Номер 244(6), С. 2156 - 2162

Опубликована: Окт. 6, 2024

A long-standing debate looks at whether air or soil dryness is more limiting to vegetation water use and productivity. The answer has large implications for future ecosystem functioning, as atmospheric predicted increase globally while changes in moisture are be far variable. Here, I review the complexities that contribute this debate, including strong coupling between dryness, widespread heterogeneity hydraulic traits, acclimations, adaptations stress. discuss solutions improve understanding modeling of sensitivity how different types observational data can used together gain insight into response stress across spatial temporal scales.

Язык: Английский

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Comparing the use of all data or specific subsets for training machine learning models in hydrology: A case study of evapotranspiration prediction

Journal of Hydrology, Год журнала: 2023, Номер 627, С. 130399 - 130399

Опубликована: Ноя. 2, 2023

Язык: Английский

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Exploring Optimal Complexity for Water Stress Representation in Terrestrial Carbon Models: A Hybrid‐Machine Learning Model Approach

Journal of Advances in Modeling Earth Systems, Год журнала: 2024, Номер 16(12)

Опубликована: Дек. 1, 2024

Abstract Terrestrial biosphere models offer a comprehensive view of the global carbon cycle by integrating ecological processes across scales, yet they introduce significant uncertainties in climate and biogeochemical projections due to diverse process representations parameter variations. For instance, different soil water limitation functions lead wide productivity ranges models. To address this, we propose Differentiable Land Model (DifferLand), novel hybrid machine learning approach replacing unknown with neural networks (NNs) learn from data. Using automatic differentiation, calibrated embedded NN physical model parameters against daily observations evapotranspiration, gross primary productivity, ecosystem respiration, leaf area index 16 FLUXNET sites. We evaluated six configurations where NNs simulate increasingly complex photosynthesis interactions test data sets find optimal structure‐performance tradeoff. Our findings show that simple univariate effectively captures site‐level fluxes on monthly timescale. Across aridity gradient, magnitude stress varies, but its functional form consistently converges piecewise linear relationship saturation at high levels. While incorporating more between meteorological drivers better fit finer time risk overfitting equifinality issues. study demonstrates have great potential parameterizations testing hypotheses. Nevertheless, careful tradeoffs are warranted light observational constraints translate retrieved relationships into robust understanding.

Язык: Английский

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