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At least 577 records · Page 32

In-situ observation of pre-, co- and post-seismic shear slip at 1.5 km depth

Understanding the initiation and arrest of earthquakes is one of the long-standing challenges of seismology. Here we report on direct observations of borehole displacement by a meter-sized shear rupture induced by pressurization of metamorphic rock at 1.5 km depth. We observed the acceleration of sliding, followed by fast co-seismic slip and transient afterslip. Total displacements were about 7, 5.5 and 9.5 micrometers, respectively for the observed pre-slip, co-seismic slip and afterslip. The observed pre-slip lasted about 0.4 seconds. Co-seismic slip was recorded by the 1 kHz displacement recording and a 12-component array of 3-C accelerometers sampled at 100 kHz. The observed afterslip is consistent with analytical models of arrest in a velocity-strengthening region and subsequent stress relaxation. < p >The observed slip vector agrees with the activation of a bedding plane within the phyllite, which is corroborated by relocated seismic events that were observed during the later stages of the injection experiment.

Schoenball, Martin↗

Drivers for the cracking of multilayer polyamide‐based backsheets in field photovoltaic modules: In‐depth degradation mapping analysis

Abstract There is a lack of understanding on the root cause of cracking of photovoltaic (PV) backsheets due to the challenge of multilayer characterization and the complicated failure modes at the submodule level. In this work, the in‐depth degradation mapping of field‐exposed polyamide‐based (PA‐based) PV module backsheets was studied, with the major focus on the identification of underlying drivers for the through cracking (in between the solar cells). PV modules were retrieved from five different locations, comprising a variety of climates, including humid subtropical, hot‐summer Mediterranean, tropical savanna climate, and hot arid. A suite of microscale cross‐sectional characterizations, including chemical changes, fluorescence intensity, and modulus as a function of distance from the air surface of the backsheet, was performed. Results showed more advanced signs of degradation of the inner layer than the outer layer in the cracking region. Increases in the modulus were identified as the major indicator for the cracking. Moreover, a rudimentary test by immersion in acetic acid, which forms during photodegradation of the ethylene‐vinyl acetate copolymer (EVA) encapsulant, showed the first‐time direct evidence that acetic acid can largely accelerate the chemical degradation and facilitate the cracking of PA inner layer. This study suggests that the field cracking of PA‐based backsheet can be attributed to the combined effects of chemical degradation and physical reorganization (chemi‐crystallization) under cyclic thermomechanical stresses. Therefore, it is important to consider effects of local microclimates and interlayer infection to understand the heterogeneous nature of backsheet failures.

Lyu, Yadong↗

Key predictors of soil organic matter vulnerability to mineralization differ with depth at a continental scale

Abstract Soil organic matter (SOM) is the largest terrestrial pool of organic carbon, and potential carbon-climate feedbacks involving SOM decomposition could exacerbate anthropogenic climate change. However, our understanding of the controls on SOM mineralization is still incomplete, and as such, our ability to predict carbon-climate feedbacks is limited. To improve our understanding of controls on SOM decomposition, A and upper B horizon soil samples from 26 National Ecological Observatory Network (NEON) sites spanning the conterminous U.S. were incubated for 52 weeks under conditions representing site-specific mean summer temperature and sample-specific field capacity (−33 kPa) water potential. Cumulative carbon dioxide respired was periodically measured and normalized by soil organic C content to calculate cumulative specific respiration (CSR), a metric of SOM vulnerability to mineralization. The Boruta algorithm, a feature selection algorithm, was used to select important predictors of CSR from 159 variables. A diverse suite of predictors was selected (12 for A horizons, 7 for B horizons) with predictors falling into three categories corresponding to SOM chemistry, reactive Fe and Al phases, and site moisture availability. The relationship between SOM chemistry predictors and CSR was complex, while sites that had greater concentrations of reactive Fe and Al phases or were wetter had lower CSR. Only three predictors were selected for both horizon types, suggesting dominant controls on SOM decomposition differ by horizon. Our findings contribute to the emerging consensus that a broad array of controls regulates SOM decomposition at large scales and highlight the need to consider changing controls with depth.

59 BASIC BIOLOGICAL SCIENCES↗

The Median Isn’t the Message: soil nutrient hot spots have a disproportionate influence on biogeochemical structure across years, seasons, and depths

Abstract Soil nutrient distribution is heterogeneous in space and time, potentially altering nutrient acquisition by trees and microorganisms. Ecologists have distinguished “hot spots” (HSs) as areas with enhanced and sustained rates of nutrient fluxes relative to the surrounding soil matrix. We evaluated the spatial and temporal patterns in nutrient flux HSs in two mixed-conifer forest soils by repeatedly sampling the soil solution at the same spatial locations (horizontally and vertically) over multiple seasons and years using ion exchange resins incubated in situ. The climate of these forests is Mediterranean, with intense fall rains occurring following summers with little precipitation, and highly variable winter snowfall. Hot spots formed most often for NO 3 − and Na + . Although nutrient HSs often occurred in the same spatial location multiple times, HSs persisted more often for PO 4 3− NH 4 + , and NO 3 − , and were more transient for Ca 2+ , Mg 2+ , and Na + . Sampling year (annual precipitation ranged from 558 to 1223 mm) impacted the occurrence of HSs for most nutrients, but season was only significant for PO 4 3− , NH 4 + , NO 3 − , and Na + , with HSs forming more often after fall rains than after spring snowmelt. The frequency of HSs significantly decreased with soil depth for all nutrients, forming most commonly immediately below the surficial organic horizon. Although HSs accounted for less than 17% of the sampling volume, they were responsible for 56–88% of PO 4 3− , NH 4 + , and NO 3 − resin fluxes. Our results suggest that macronutrient HSs have a disproportional contribution to soil biogeochemical structure, with implications for vegetation nutrient acquisition strategies and biogeochemical models. Graphical abstract

54 ENVIRONMENTAL SCIENCES↗

Semi-automatic image annotation using 3D LiDAR projections and depth camera data

Efficient image annotation is necessary to utilize deep learning object recognition neural networks in nuclear safeguards, such as for the detection and localization of target objects like nuclear material containers (NMCs). This capability can help automate the inventory accounting of different types of NMCs within nuclear storage facilities. The conventional manual annotation process is labor-intensive and time-consuming, hindering the rapid deployment of deep learning models for NMC identifications. This paper introduces a novel semi-automatic method for annotating 2D images of nuclear material containers (NMCs) by combining 3D light detection and ranging (LiDAR) data with color and depth camera images collected from a handheld scan system. The annotation pipeline involves an operator manually marking new target objects on a LiDAR-generated map, and projecting these 3D locations to images, thereby automatically creating annotations from the projections. The semi-automatic approach significantly reduces manual efforts and the expertise in image annotation that is required to perform the task, allowing deep learning models to be trained on-site within a few hours. The paper compares the performance of models trained on datasets annotated through various methods, including semi-automatic, manual, and commercial annotation services. The evaluation demonstrates that the semi-automatic annotation method achieves comparable or superior results, with a mean average precision (mAP) above 0.9, showcasing its efficiency in training object recognition models. Additionally, the paper explores the application of the proposed method to instance segmentation, achieving promising results in detecting multiple types of NMCs in various formations.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Physicochemical properties of the Portland cement-based mortar exposed to deep seafloor conditions at a depth of 1680 m

Achieving breakthroughs in marine technologies requires the development of infrastructures submerged in deep-sea environments, whose physicochemical effects on cement-based materials considerably differ from those of shallow seas. However, very few studies focused on the cement-based materials subjected to deep-sea conditions. This work investigates the changes in the compressive strength and phase composition of the cement mortar kept on the seafloor with a depth of 1680 m for 608 d. The mortar specimens salvaged from the seafloor exhibited severe visible damages, including softened mashy structures and significantly decreased compressive strengths. The obtained X-ray diffraction, scanning electron microscopy, and nuclear magnetic resonance data revealed that the dissolution of portlandite, decalcification of calcium (alumino) silicate hydrate, and formation of brucite, magnesium (alumino) silicate hydrate, a hydrotalcite-like phase, thaumasite, and ettringite likely contributed to the disintegration of mortar, which could be further accelerated by the low temperature of the deep-sea environment.

36 MATERIALS SCIENCE↗

Stable electrospray signal on a microfabricated glass chip with three-dimensional open edge and tiered depth geometries

This paper presents the microfabrication and performance of a three-dimensional electrospray ionization (ESI) emitter tip made from glass, which achieves stable current signals important for chemical analysis. Our novel microfabrication process and custom-built signal conditioning hardware provides the advantage of providing accurate features and steady signals. The fabrication process relies on standard microfabrication techniques (i.e., deposition, photolithography, and wet etching). This fabrication method involves the novel application of two layers of positive and negative photoresists in addition to Parafilm® wax tape. Open edge and tiered depth details were successfully created from a multilayer planar mask. This is a benefit for integrated miniaturized and microfluidic systems that often require micro features for their functionality but relatively large millimeter size features for their physical periphery. We demonstrate the fundamental performance of electrospray with this microfluidic chip. The emitter tip was fixed on a linear axis stage with high resolution (10 μm) to finely control the tip distance from a metal counter electrode plate. Further, a custom printed circuit board system was built to safely control four voltages applied to the microchip ports from a single high voltage power supply. To readily form the electrospray, non-aqueous solvents were used for their low viscosity and a constant voltage of +2.7 kV was applied to the sheath electrospray microchannel. The liquid being sprayed was 80/20 (v/v) methanol/acetonitrile with 0.1% acetic acid in the sheath microchannel and with ammonium acetate (10–40 mM) in its remaining microchannels. The electrospray signal was measured in response to varying the distance (1.4 to 1.6mm) between the electrospray emitter tip and a metal counter electrode plate in addition to the varying concentration of the background electrolyte, ammonium acetate. Stable and repeatable electrospray signal showed linear relationships with emitter tip distance and concentration (r 2 ≥ 0.95).

42 ENGINEERING↗

Effect of epitope variant co-delivery on the depth of CD8 T cell responses induced by HIV-1 conserved mosaic vaccines

To stop the HIV-1 pandemic, vaccines must induce responses capable of controlling vast HIV-1 variants circulating in the population as well as those evolved in each individual following transmission. Numerous strategies have been proposed, of which the most promising include focusing responses on the vulnerable sites of HIV-1 displaying the least entropy among global isolates and using algorithms that maximize vaccine match to circulating HIV-1 variants by vaccine cocktails of optimized complementing sequences. In this study, we investigated CD8 T cell responses induced by a bi-valent mosaic of highly conserved HIVconsvX regions delivered by a combination of simian adenovirus ChAdOx1 and poxvirus MVA. We compared partially and fully mono- and bi-valent prime-boost regimens and their ability to elicit T cells recognizing natural epitope variants using an interferon-g enzyme-linked immunospot (ELISPOT) assay. We used 11 well-defined CD8 T cell epitopes in two mouse haplotypes and, for each epitope, assessed recognition of the two vaccine forms together with the other most frequent epitope variants in the HIV-1 database. We conclude that for the magnitude and depth of epitope recognition, CD8 T cell responses benefitted in most comparisons from the combined bi-valent mosaic and envisage the main advantage of the bi-valent vaccine during its deployment to diverse populations.

59 BASIC BIOLOGICAL SCIENCES↗

Satellite-based aerosol optical depth estimates over the continental U.S. during the 2020 wildfire season: Roles of smoke and land cover

Wildfires produce smoke that can affect an area >1000 times the burn extent, with far-reaching human health, ecologic, and economic impacts. Accurately estimating aerosol load within smoke plumes is therefore crucial for understanding and mitigating these impacts. We evaluated the effectiveness of the latest Collection 6.1 MODIS Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm in estimating aerosol optical depth (AOD) across the U.S. during the historic 2020 wildfire season. We compared satellite-based MAIAC AOD to ground-based AERONET AOD measurements during no-, light-, medium-, and heavy-smoke conditions identified using the Hazard Mapping System Fire and Smoke Product. This smoke product consists of maximum extent smoke polygons digitized by analysts using visible band imagery and classified according to smoke density. We also examined the strength of the correlations between satellite- and ground-based AOD for major land cover types under various smoke density levels. MAIAC performed well in estimating AOD during smoke-affected conditions. Correlations between MAIAC and AERONET AOD were strong for medium- (r = 0.91) and heavy-smoke (r = 0.90) density, and MAIAC estimates of AOD showed little bias relative to ground-based AERONET measurements (normalized mean bias = 3 % for medium, 5 % for heavy smoke). During two high AOD, heavy smoke episodes, MAIAC underestimated ground-based AERONET AOD under mixed aerosol (i.e., smoke and dust; median bias = −0.08) and overestimated AOD under smoke-dominated (median bias = 0.02) aerosol. MAIAC most overestimated ground-based AERONET AOD over barren land (mean NMB = 48 %). Our findings indicate that MODIS MAIAC can provide robust estimates of AOD as smoke density increases in coming years. Increased frequency of mixed aerosol and expansion of developed land could affect the performance of the MAIAC algorithm in the future, however, with implications for evaluating wildfire-associated health and welfare effects and air quality standards.

54 ENVIRONMENTAL SCIENCES↗

Depth-Dependent Understanding of Cathode Electrolyte Interphase (CEI) on the Layered Li-Ion Cathodes Operated at Extreme High Temperature

The high-temperature operation of Li-ion batteries is highly dependent on the stability of the cathode electrolyte interphase (CEI) formed during lithiation-delithiation reactions. However, knowledge on the nature of the CEI is limited and its stability under extreme temperatures is not well understood. Therefore, herein, we investigate a proof-of-concept study on stabilizing CEI on model LiNi 0.33 Mn 0.33 Co 0.33 O 2 (NMC333) at extreme operation condition of 100 oC using thermally stable pyrrolidinium based ionic liquid electrolyte. The electrochemical lithiation-delithiation reactions at 100 oC and the CEI evolution upon different cycling conditions are investigated. Further, the depth-dependent CEI chemistry was investigated using energy tunable synchrotron-based hard X-ray photoelectron spectroscopy (HAXPES). Overall, the results reveal that the high temperature operation accelerated the CEI formation compared to room temperature, and the surface of the interphase layer is rich in boron-based inorganic moieties than the deeper surface. Further, bulk sensitive X-ray absorption spectroscopy (XAS) was used to investigate the transition metal redox contributors during high temperature electrochemical reactions, similar to room temperature, the Ni2+/4+redox couple is the only charge compensating redox couple during high temperature operation. Finally, the physical nature of the conformal CEI on the cathode particles was visualized with high-resolution transmission electron microscopy, which confirms that the significant degradation of cathode particles without conformal CEI is due to the transformation of layer to spinel formation at extreme temperature. In this study, understanding this high temperature interfacial chemistry of NMC cathodes through advanced spectroscopy and microscopy will shed light on transforming ambient temperature Li-ion chemistry to high temperature applications.

25 ENERGY STORAGE↗

Distribution of Copper States, Phases, and Defects across the Depth of a Cu-Doped CdTe Solar Cell

Copper has been used as a p-type dopant in cadmium telluride (CdTe) for decades. However, the density of Cu atoms in the finished device is much higher than that of holes, which means that most Cu atoms are not activated as acceptors during incorporation. Furthermore, studies have demonstrated that the distribution of copper (Cu) atoms across the device is highly inhomogeneous, with reports citing Cu substitution on Cd sites and segregation to grain boundaries. Fast diffusion along these boundaries and Cu accumulation at the CdTe/CdS interface have also been observed and validated computationally. These levels of inhomogeneity make it difficult to accurately characterize and correlate the performance with the nature of the Cu atomic species present. To address this challenge, we utilize X-ray microscopy and, specifically, nanoscale fluorescence-mode X-ray absorption near-edge structure to resolve the atomic Cu environment throughout the depth of the CdTe layer. Our results suggest that the majority of Cu atoms are in the form of Cu x Te phases (or similar local environments) near the ZnTe|CdTe interface, Cu x O phases in the CdTe absorber, and present in various oxidation states, including Cu 1+ and Cu 2+ , near the CdS/CdTe junction. Here this work also provides experimental evidence for the first time of the presence of CuS around the ZnTe|CdTe interface and the hypothesized Cu Cd -Cl i complex in the CdTe absorber.

14 SOLAR ENERGY↗

Controlling Magnetization Vector Depth Profiles of La 0.7 Sr 0.3 CoO 3 /La 0.7 Sr 0.3 MnO 3 Exchange Spring Bilayers via Interface Reconstruction

The La 0.7 Sr 0.3 CoO 3–δ /La 0.7 Sr 0.3 MnO 3–δ (LSCO/LSMO) bilayer system is an ideal perovskite oxide platform for investigating interface reconstruction and its effect on their magnetic properties. Previous studies have shown that LSCO can separate into magnetic sublayers, which possess distinct trends as the total LSCO thickness increases. Here, we used polarized neutron reflectometry to quantify changes in the magnetic and chemical depth profiles, and it confirms the formation of ~12 Å-thick interfacial LSCO and LSMO layers, characterized by a decreased nuclear scattering length density compared to the bulk of the layers. This decrease is attributed to the combined effects of oxygen vacancy formation and interfacial charge transfer, which lead to magnetically active Co 2+ ions with ionic radii larger than the Co 3+ /Co 4+ ions typically found in bulk LSCO or single-layer films. The interfacial magnetization values, as well as Co 2+ ion and oxygen vacancy concentrations, depend strongly on the LSCO layer thickness. These results highlight the sensitive interplay of the cation valence states, oxygen vacancy concentration, and magnetization at interfaces in perovskite oxide multilayers, demonstrating the potential to tune their functional properties via careful design of their structure.

36 MATERIALS SCIENCE↗

Oxygen Vacancy Evolution at Li x V 2 O 5 /LiPON Solid State Electrochemical Interfaces Using Depth Resolved Cathodoluminescence Spectroscopy

The formation of oxygen vacancies at buried LiPON/ Li x V 2 O 5 interfaces has been observed on a near-nanometer scale and nondestructively using depth-resolved cathodoluminescence spectroscopy (DRCLS) and interfacial markers. Before electrochemical cycling, as-deposited LiPON/Li x V 2 O 5 exhibits a 1.6 eV defect optical emission, which density functional theory calculations identify as originating from oxygen vacancies. This defect appears first within a few nanometers of the buried LiPON/Li x V 2 O 5 interface without cycling, indicating that spontaneous O diffusion from the Li x V 2 O 5 lattice into LiPON may have caused these interface-localized oxygen vacancy defects. DRCLS measured the intensity and spatial distribution of this oxygen vacancy signal as a function of electrochemical cycling in a LiPON/Li x V 2 O 5 half-cell, showing oxygen vacancy signal increasing and moving deeper into the electrode with increased cycle number. Significant electrochemical irreversibility was also observed, with poor Coulombic efficiency and a 15% drop in capacity over 50 cycles. Theoretical simulations predict that the presence of oxygen vacancies increases the energy barrier for lithium diffusion significantly, indicating that this aggregation of oxygen vacancies could be another battery degradation mechanism accompanying lithiation induced phase changes.

36 MATERIALS SCIENCE↗

Depth-Dependent Emission from Silver Dopants in Single CdSe Nanoplatelets

Dopants in semiconductor nanostructures offer tremendous control over electronic, optical, and magnetic properties beyond what is achievable in bulk materials. We demonstrate that the broad dopant emission in semiconductor nanoplatelets effectively maps the electron wave function across the nanoplatelet thickness. Both the emission energy and lifetime of the dopant transition depend strongly on the depth of the dopant within the nanoplatelet. This dependence arises from the electrostatic self-interaction of the charged dopant, which varies with proximity to the dielectric discontinuity at the nanoplatelet surface. Through comprehensive single-particle spectroscopy of silver-doped CdSe nanoplatelets, we verify that acceptors near the center emit at higher energies with shorter lifetimes, while those near the surface emit at lower energies with longer lifetimes. This spatial mapping also reveals unusual two-color emission from individual nanoplatelets, with enhanced Auger recombination yielding exceptional photon antibunching (>90% purity) at room temperature, suggesting potential applications in quantum information technologies.

cadmium selenide↗

On the Breakdown of ENSO's Relationship With Thermocline Depth in the Central-Equatorial Pacific

Recent classification of El Nino-Southern Oscillation (ENSO) into two types, Eastern (EP) and Central (CP) events, has highlighted the importance of the central Pacific. We show here that the local correlation between ENSO subsurface temperatures (T sub ) in the upper 100-m and thermocline depth anomalies breaks down in the central equatorial Pacific, whereas T sub remains well correlated with sea surface height anomalies. This observed difference in the central equatorial Pacific is simulated by almost all climate models. It arises from a vertically slanted Tsub anomaly structure that is unique to the central equatorial Pacific. We show that this feature is an adiabatic response to wind-driving that is even present in a linear dynamic model, as long as the model has enough baroclinic modes to adequately represent the observed vertical complexity. Our findings have implications for better understanding the different importance of thermocline feedback in CP and EP events.

58 GEOSCIENCES↗

The Diurnal Variation of the Aerosol Optical Depth at the ARM SGP Site

Abstract This study examines the diurnal variation of the aerosol optical depth (AOD) at 355 nm observed by Raman lidar (RL) at the Atmospheric Radiation Measurement Program Southern Great Plains (SGP) site under both clear and cloudy‐sky conditions. Here only cloudy‐skies when the lidar signal is not fully attenuated are considered. The daytime AOD and its variation from the RL showed an excellent agreement with the Aerosol Robotic Network, demonstrating that the RL‐retrieved AOD is not affected by solar background contamination. The climatological annual‐mean daytime‐mean AOD is only slightly larger than the nighttime‐mean AOD (by 1%–3%). However, day‐to‐day variations are observed such that the daytime‐ and nighttime‐mean AOD difference for a given day can be large (about 95% of days have differences within 0.2). The seasonal AOD diurnal range (i.e., the difference between the maximum and minimum values) relative to the mean was 10%–15% except in the winter when it was 44%. The seasonal‐mean cloudy‐sky AOD diurnal variation is similar to that for clear‐sky, except that the AODs are larger (the annual‐mean cloudy‐sky AOD is larger than the clear‐sky by 24%). The aerosol lidar ratio diurnal variations are also examined, which are 10%–20% for all seasons with a minimum near 9 a.m. to 15 p.m. for all seasons except winter. Also presented is the annual‐mean AOD from the Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite at SGP site: its daytime AOD is about 0.1 smaller than nighttime AOD because of daytime solar background contamination.

54 ENVIRONMENTAL SCIENCES↗

Experimental Whole-Ecosystem Warming Enables Novel Estimation of Snow Cover and Depth Sensitivities to Temperature, and Quantification of the Snow-Albedo Feedback Effect

Climate change is reducing the amount, duration, and extent of snow across high-latitude ecosystems. But, in landscapes where persistent winter snow cover develops, experimental platforms to specifically investigate interactions between warming and changes in snowpack, and impacts on ecosystem processes, have been lacking. We leveraged a whole-ecosystem warming experiment in a boreal peatland forest to quantify how snow duration, depth, and fractional cover vary with warming of up to +9°C. We found that every snow-related quantity we examined declined precipitously as the amount of warming increased. The importance of deep, continuous snow cover for moderating shallow soil temperature is highlighted by an increase in soil temperature variance and the frequency of short-duration freeze-thaw cycles in the warmer plots. We used a paired-plot approach to estimate the magnitude of the snow-albedo feedback effect, and demonstrate that albedo-driven warming linked to reduced snow cover varies between December (+0.4°C increase in maximum air temperature) and March (+1.2°C increase) because of differences in insolation. Overall, results show that even modest future warming will have profound impacts on northern winters and cold-season ecosystem processes. Plot-level data from this warming experiment, and emergent relationships between warming and quantities related to snow cover and duration, could be of enormous value for testing and improving the representation of snow processes in simulation models, especially under future climate scenarios that are outside of the range of historically observed variability.

54 ENVIRONMENTAL SCIENCES↗

Machine Learning Calibration of Groundwater Table Depth in ELM: Impact on Land Surface Hydrology and Land‐Atmosphere Fluxes

Accurate representation of groundwater table depth (GWTD) is crucial for simulating hydrological cycling in Earth system models (ESM). Nevertheless, there is a notable gap in the literature regarding the validation of GWTD simulations in ESMs and their subsequent impact on downstream hydrological components. This study explores the calibration of parameterization of global GWTD using machine learning within the Energy Exascale Earth System Model (E3SM) Land Model (ELM). Despite achieving significant gains in simulating GWTD through calibration, offline ELM simulations unexpectedly show that these improvements do not translate to substantial enhancements in model performance for other key hydrological variables, including soil moisture (SM), runoff, groundwater contribution to runoff or base flow index (BFI), and evapotranspiration and its partitioning. The performance in SM and runoff was even degraded in some regions, while BFI was mostly overestimated. Although there is significant improvement in GWTD within the critical range of 1–5 m, where groundwater traditionally influences land surface energy fluxes, these improvements occurred mostly in humid areas where the impact of GWTD on surface processes is minimal. Although the impacts of model calibration are generally small in offline ELM simulations, coupled land-atmosphere simulations exhibit much stronger responses to GWTD calibration, highlighting the role of land-atmosphere feedbacks in Earth system modeling. These findings underscore the need for integrated calibration strategies that simultaneously optimize multiple hydrological variables. However, if a single-variable approach is necessary, it is crucial to establish clear priorities for calibration, identifying the most critical variables that have the greatest impact on overall model performance.

Fang, Yilin [Pacific Northwest National Laboratory↗