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1. Monitoring Terrestrial Water Storage, Drought and Seasonal Changes in Central Oklahoma With Ambient Seismic Noise

   https://doi.org/10.1029/2023GL103419  

   Zhang, Shuo; Luo, Bingxu; Ben‐Zion, Yehuda; Lumley, David_E; Zhu, Hejun (September 2023, Geophysical Research Letters)

   Abstract Significant imbalances in terrestrial water storage (TWS) and severe drought have been observed around the world as a consequence of climate changes. Improving our ability to monitor TWS and drought is critical for water‐resource management and water‐deficit estimation. We use continuous seismic ambient noise to monitor temporal evolution of near‐surface seismic velocity,dv/v, in central Oklahoma from 2013 to 2022. The deriveddv/vis found to be negatively correlated with gravitational measurements and groundwater depths, showing the impact of groundwater storage on seismic velocities. The hydrological effects involving droughts and recharge of groundwater occur on a multi‐year time scale and dominate the overall derived velocity changes. The thermoelastic response to atmospheric temperature variations occurs primarily on a yearly timescale and dominates the superposed seasonal velocity changes in this study. The occurrences of droughts appear simultaneously with local peaks ofdv/v, demonstrating the sensitivity of near‐surface seismic velocities to droughts. 

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2. Global groundwater droughts are more severe than they appear in hydrological models: An investigation through a Bayesian merging of GRACE and GRACE-FO data with a water balance model

   https://doi.org/10.1016/j.scitotenv.2023.169476  

   Forootan, Ehsan; Mehrnegar, Nooshin; Schumacher, Maike; Schiettekatte, Leire Anne; Jagdhuber, Thomas; Farzaneh, Saeed; van Dijk, Albert I.J.M.; Shamsudduha, Mohammad; Shum, C.K. (February 2024, Science of The Total Environment)

   Zhang, Kai (Ed.)

   Realistic representation of hydrological drought events is increasingly important in world facing decreased freshwater availability. Index-based drought monitoring systems are often adopted to represent the evolution and distribution of hydrological droughts, which mainly rely on hydrological model simulations to compute these indices. Recent studies, however, indicate that model derived water storage estimates might have difficulties in adequately representing reality. Here, a novel Markov Chain Monte Carlo - Data Assimilation (MCMC-DA) approach is implemented to merge global Terrestrial Water Storage (TWS) changes from the Gravity Recovery And Climate Experiment (GRACE) and its Follow On mission (GRACE-FO) with the water storage estimations derived from the W3RA water balance model. The modified MCMC-DA derived summation of deep rooted soil and groundwater storage estimates is then used to compute 0.5∘ standardized groundwater drought indices globally to show the impact of GRACE/GRACE-FO DA on a global index-based hydrological drought monitoring system. Our numerical assessment covers the period of 2003–2021, and shows that integrating GRACE/GRACE-FO data modifies the seasonality and inter-annual trends of water storage estimations. Considerable increases in the length and severity of extreme droughts are found in basins that exhibited multiyear water storage fluctuations and those affected by climate teleconnections. 

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3. Asymmetric response of Amazon forest water and energy fluxes to wet and dry hydrological extremes reveals onset of a local drought‐induced tipping point

   https://doi.org/10.1111/gcb.16933  

   Restrepo‐Coupe, Natalia; O’Donnell Christoffersen, Bradley; Longo, Marcos; Alves, Luciana F.; Campos, Kleber Silva; da Araujo, Alessandro C.; de Oliveira, Jr, Raimundo C.; Prohaska, Neill; da Silva, Rodrigo; Tapajos, Raphael; et al (September 2023, Global Change Biology)

   Abstract Understanding the effects of intensification of Amazon basin hydrological cycling—manifest as increasingly frequent floods and droughts—on water and energy cycles of tropical forests is essential to meeting the challenge of predicting ecosystem responses to climate change, including forest “tipping points”. Here, we investigated the impacts of hydrological extremes on forest function using 12+ years of observations (between 2001–2020) of water and energy fluxes from eddy covariance, along with associated ecological dynamics from biometry, at the Tapajós National Forest. Measurements encompass the strong 2015–2016 El Niño drought and La Niña 2008–2009 wet events. We found that the forest responded strongly to El Niño‐Southern Oscillation (ENSO): Drought reduced water availability for evapotranspiration (ET) leading to large increases in sensible heat fluxes (H). PartitioningETby an approach that assumes transpiration (T) is proportional to photosynthesis, we found that water stress‐induced reductions in canopy conductance (G_s) droveTdeclines partly compensated by higher evaporation (E). By contrast, the abnormally wet La Niña period gave higherTand lowerE, with little change in seasonalET. Both El Niño‐Southern Oscillation (ENSO) events resulted in changes in forest structure, manifested as lower wet‐season leaf area index. However, only during El Niño 2015–2016, we observed a breakdown in the strong meteorological control of transpiration fluxes (via energy availability and atmospheric demand) because of slowing vegetation functions (via shutdown ofG_sand significant leaf shedding). Drought‐reducedTandG_s, higherHandE, amplified by feedbacks with higher temperatures and vapor pressure deficits, signaled that forest function had crossed a threshold, from which it recovered slowly, with delay, post‐drought. Identifying such tipping point onsets (beyond which future irreversible processes may occur) at local scale is crucial for predicting basin‐scale threshold‐crossing changes in forest energy and water cycling, leading to slow‐down in forest function, potentially resulting in Amazon forests shifting into alternate degraded states. 

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4. Decoupling of Ecological and Hydrological Drought Conditions in the Limpopo River Basin Inferred from Groundwater Storage and NDVI Anomalies

   https://doi.org/10.3390/hydrology10080170  

   Kim, Kyung Y; Scanlon, Todd; Bakar, Sophia; Lakshmi, Venkataraman (August 2023, Hydrology)

   Droughts are projected to increase in intensity and frequency with the rise of global mean temperatures. However, not all drought indices equally capture the variety of influences that each hydrologic component has on the duration and magnitude of a period of water deficit. While such indices often agree with one another due to precipitation being the major input, heterogeneous responses caused by groundwater recharge, soil moisture memory, and vegetation dynamics may lead to a decoupling of identifiable drought conditions. As a semi-arid basin, the Limpopo River Basin (LRB) is a severely water-stressed region associated with unique climate patterns that regularly affect hydrological extremes. In this study, we find that vegetation indices show no significant long-term trends (S-statistic 9; p-value 0.779), opposing that of the modeled groundwater anomalies (S-statistic -57; p-value 0.05) in the growing season for a period of 18 years (2004–2022). Although the Mann-Kendall time series statistics for NDVI and drought indices are non-significant when basin-averaged, spatial heterogeneity further reveals that such a decoupling trend between vegetation and groundwater anomalies is indeed significant (p-value < 0.05) in colluvial, low-land aquifers to the southeast, while they remain more coupled in the central-west LRB, where more bedrock aquifers dominate. The conclusions of this study highlight the importance of ecological conditions with respect to water availability and suggest that water management must be informed by local vegetation species, especially in the face of depleting groundwater resources. 

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5. Probabilistic estimates of drought impacts on agricultural production: Drought Impacts on Agriculture

   https://doi.org/10.1002/2017GL073606  

   Madadgar, Shahrbanou; AghaKouchak, Amir; Farahmand, Alireza; Davis, Steven J. (August 2017, Geophysical Research Letters)

   Increases in the severity and frequency of drought in a warming climate may negatively impact agricultural production and food security. Unlike previous studies that have estimated agricultural impacts of climate condition using single-crop yield distributions, we develop a multivariate probabilistic model that uses projected climatic conditions (e.g., precipitation amount or soil moisture) throughout a growing season to estimate the probability distribution of crop yields. We demonstrate the model by an analysis of the historical period 1980–2012, including the Millennium Drought in Australia (2001–2009). We find that precipitation and soil moisture deficit in dry growing seasons reduced the average annual yield of the five largest crops in Australia (wheat, broad beans, canola, lupine, and barley) by 25–45% relative to the wet growing seasons. Our model can thus produce region- and crop-specific agricultural sensitivities to climate conditions and variability. Probabilistic estimates of yield may help decision-makers in government and business to quantitatively assess the vulnerability of agriculture to climate variations. We develop a multivariate probabilistic model that uses precipitation to estimate the probability distribution of crop yields. The proposed model shows how the probability distribution of crop yield changes in response to droughts. During Australia's Millennium Drought precipitation and soil moisture deficit reduced the average annual yield of the five largest crops. 

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