Pores in Marcellus Shale: A Neutron Scattering and FIB-SEM Study
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bio-inspired, mechanical behavior, carbon sequestr↗
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Testbed and Simulation-based Evaluation of Privacy-preserving Algorithms for Smart Grid AMI Networks
Although smart meters are deployed in a lot of countries as a result of aiming to make the power grid more resilient and efficient, the data collection process from smart meters in Smart Grid (SG) has still challenges that relate to consumer privacy. Referred to as Advanced Metering Infrastructure (AMI), the data collected and transmitted through this AMI can leak sensitive information about the consumers if it is sent as plaintext. While a number of solutions have been proposed in the past, the deployment of these solutions in real-life was not possible since the actual AMIs were not accessible to researchers. Therefore, a lot of solutions relied on simulations which may not be able to capture the performance of these solutions. In this paper, we pick a widely used homomorphic-based aggregation and implement it in a realistic testbed so that it can be compared with a simulation-based solution. Specifically, we develop a system that provides privacy with the Paillier cryptosystem and twofactor authentication with ECDSA and OpenSSL certificates. In order to test the system, an IEEE 802.11s-based SG AMI network testbed is constructed with Beaglebone Black boards that imitate the behavior of smart meters. The same network is also simulated in widely used ns-3. The results showed that ns-3 simulation and testbed results are parallel in most cases and the proposed system can perform effectively. However, there are still many differences that need to be taken into account in deploying real systems.
97 MATHEMATICS AND COMPUTING↗
MIC-DP: A Scalable Correlation-Aware Differential Privacy Framework for High-Dimensional Data
Conventional differential privacy (DP) assumes record independence, limiting effectiveness on real-world datasets with temporal, spatial, or structural correlations. These dependencies undermine privacy guarantees and degrade utility in domains like healthcare, IoT, and smart city analytics. We propose Maximum Information Correlated Differential Privacy (MIC-DP), a novel framework that dynamically calibrates noise based on statistical dependencies. MIC-DP uses the Maximum Information Coefficient (MIC) to capture both linear and nonlinear correlations without explicit modeling, enabling adaptive sensitivity adjustment and improved privacy–utility trade-offs. Evaluations on healthcare (MIMIC), demographic (ACI), and synthetic datasets show that MIC-DP reduces mean absolute error (MAE) by up to 5.2% under strict privacy budgets (ϵ≤1), with aggregate utility improvements reaching 18% across datasets and evaluation metrics. MIC-DP provides formal (ϵ,δ)-privacy guarantees, scales efficiently with feature count, and supports deployment in moderate-scale, privacy-sensitive applications. Its tunable performance and runtime efficiency make MIC-DP suitable for privacy-sensitive applications where low-latency analytics and strong privacy guarantees must coexist. These results demonstrate MIC-DP’s effectiveness as a correlation-aware solution for practical DP.
Yang, Wenjun [Univ. of Washington, Tacoma, WA (Uni↗
Globally Gridded Groundwater Extraction Volumes and Costs under Six Depletion and Ponded Depth Targets
This repository contains simulated outputs from superwell – a hydro-economic tool for long-term assessment of groundwater cost and supply – providing globally gridded groundwater extractable volumes and associated unit costs ($/km³) for accessible groundwater production, based on a variety of user-defined depletion and ponded depth scenarios. Key model documentation: Niazi, H., Ferencz, S. B., Graham, N. T., Yoon, J., Wild, T. B., Hejazi, M., Watson, D. J., & Vernon, C. R. (2025). Long-term hydro-economic analysis tool for evaluating global groundwater cost and supply: Superwell v1.1. Geoscientific Model Development, 18(5), 1737-1767. https://doi.org/10.5194/gmd-18-1737-2025 Find the source code of the superwell model on GitHub: https://github.com/JGCRI/superwell Repository Overview Main output: superwell_outputs.7z contains 6 files (4.5 GB) named as superwell_py_deep_all_0.*PD_0.*DL.csv. These files present superwell outputs of global groundwater extraction volumes and cost estimates on a 0.5° scale for six scenarios with different Ponded Depth (PD; 0.3 and 0.6 m) and Depletion Limit (DL; 5%, 25%, and 40% of available volume) targets over the entire pumping lifetime of a grid cell superwell_py_deep_all_0.3PD_0.25DL_sample_100.csv contains superwell outputs for 100 data points sampled to match the global inputs' distribution superwell_py_deep_all_0.3PD_0.25DL_Grid_72548.csv contains superwell output for a single grid cell concept_v5.png provides an overview of the superwell workflow Outputs Description year_number: year of pumping depletion_limit: set depletion limit (DL) as a volume fraction of total available groundwater Mappings: continent, country, gcam_basin_id, Basin_long_name, grid_id: geographic identifiers and basin information Inputs: grid_area (km²): area of the grid cell whyclass: hydrogeological classification of the aquifer permeability (m/day), porosity (%), total_thickness (m), depth_to_water (m): aquifer properties. The geo-processed input data has been published separately: https://doi.org/10.57931/2307831 Model outputs: orig_aqfr_sat_thickness (m), aqfr_sat_thickness (m): original and remaining/instantaneous saturated thickness of the aquifer hydraulic_conductivity (m/day), transmissivity (m²/day): hydraulic properties of the aquifer radius_of_influence (m), areal_extent (km²): well radius and area of influence from the center of the well number_of_wells (-): number of wells in a grid cell determined by a ratio of well area and grid area max_drawdown (m), drawdown (m), drawdown_interference (m): well and aquifer drawdown during extraction total_head (m): total lift for the groundwater (depth to water plus drawdown) total_well_length (m): total depth of wells drilled well_yield (m³/day): pumping rate or well yield power (kW), energy (kWh): power and energy required for pumping groundwater Volume Outputs: volume_produced_perwell (m³), cumulative_vol_produced_perwell (m³): production volume metrics per well volume_produced_allwells (m³), cumulative_vol_produced_allwells (m³): aggregate extraction volumes for all wells in a grid cell available_volume (m³): available groundwater in storage for the grid cell as determined by aquifer properties depleted_vol_fraction: fraction of total volume pumped over available volumes in a grid cell (same as depletion limit) Cost Outputs: well_installation_cost ($): well installation cost based on the hydrogeological complexity of the aquifer annual_capital_cost, maintenance_cost, nonenergy_cost ($): nonenergy costs energy_cost_rate ($/kWh): electricity rate energy_cost ($): energy cost of pumping groundwater total_cost_perwell ($), total_cost_allwells ($): total annual energy and non-energy cost for each and all wells in a grid cell a unit_cost ($/m³), unit_cost_per_km3 ($/km³), unit_cost_per_acreft ($/acre-ft): total cost of pumping a unit of groundwater, indicated for different spatial units Key Resources Model documentation: Niazi, H., Ferencz, S., Graham, N., Yoon, J., Wild, T., Hejazi, M., Watson, D., & Vernon, C. (2024; In-prep). Long-term Hydro-economic Assessment Tool for Evaluating Global Groundwater Cost and Supply: Superwell v1. Geoscientific Model Development. Input data: Niazi, H., Watson, D., Hejazi, M., Yonkofski, C., Ferencz, S., Vernon, C., Graham, N., Wild, T., & Yoon, J. (2024). Global Geo-processed Data of Aquifer Properties by 0.5° Grid, Country and Water Basins. MSD-LIVE Data repository. https://doi.org/10.57931/2307831 superwell source code: https://github.com/JGCRI/superwell Cite as Niazi, H., Ferencz, S., Yoon, J., Graham, N., Wild, T., Hejazi, M., Watson, D., & Vernon, C. (2024). Globally Gridded Groundwater Extraction Volumes and Costs under Six Depletion and Ponded Depth Targets. MSD-LIVE Data repository. https://doi.org/10.57931/2307832 Contact Reach out to Hassan Niazi or Stephen Ferencz or open an issue in the superwell repository for questions or suggestions.
Earth Systems↗
An innovative approach for performance enhancement of 320 Gbps free space optical communication system over turbulent channel
Free space optical (FSO) communication systems have recently gained huge attention as possible last mile solution in delivering high speed data services for terrestrial applications. However the FSO link performance, particularly the link range is significantly limited by the severity of atmospheric adversities affecting the channel. In this paper we advocate the use of multi-hop relay techniques to transmit wavelength division multiplexed (WDM) signal over the FSO channel. Since weather induced impairments in FSO links are distance dependent phenomena, hence relay transmission allows substantial performance enhancement by alleviating channel losses while, WDM provides cost effective solution in improving the transmission capacity. With aggregate link losses as high as 40 dB/km, the proposed 32 channel—10 Gbps (320 Gbps) FSO link has been evaluated by comparing bit error rate (BER) performances and eye patterns over different turbulent regimes. Gain optimized EDFA amplification and conventional electrical amplification have been employed to realize amplify-and-forward (A–F) multi-hop transmission in the proposed link with the former delivering more inspiring BER performance of over the latter. Our simulation results indicate that for receiver SNR of 35 dB, BER improvement up to five orders of magnitude can achieved using triple relay FSO link in contrast to direct link operating under similar conditions. Additionally, it is also observed during the analysis that for target BER of 10{sup −5}, incorporation of triple relay enhances the link range by approximately 1200 m over direct link. However on the flip side, our investigations also revealed that as the number of relay nodes is increased, the SNR gain for specified BER does increase but the magnitude of gain declines. The proposed link was designed and investigated using OptiSystem™ 14.2.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Stabilization of amyloidogenic immunoglobulin light chains by small molecules
In Ig light-chain (LC) amyloidosis (AL), the unique antibody LC protein that is secreted by monoclonal plasma cells in each patient misfolds and/or aggregates, a process leading to organ degeneration. As a step toward developing treatments for AL patients with substantial cardiac involvement who have difficulty tolerating existing chemotherapy regimens, we introduce small-molecule kinetic stabilizers of the native dimeric structure of full-length LCs, which can slow or stop the amyloidogenicity cascade at its origin. Specifically, a protease-coupled fluorescence polarization-based high-throughput screen was employed to identify small molecules that kinetically stabilize LCs. NMR and X-ray crystallographic data demonstrate that at least one structural family of hits bind at the LC–LC dimerization interface within full-length LCs, utilizing variable-domain residues that are highly conserved in most AL patients. Stopping the amyloidogenesis cascade at the beginning is a proven strategy to ameliorate postmitotic tissue degeneration.
59 BASIC BIOLOGICAL SCIENCES↗
How production networks amplify economic growth
Technological improvement is the most important cause of long-term economic growth. In standard growth models, technology is treated in the aggregate, but an economy can also be viewed as a network in which producers buy goods, convert them to new goods, and sell the production to households or other producers. We develop predictions for how this network amplifies the effects of technological improvements as they propagate along chains of production, showing that longer production chains for an industry bias it toward faster price reduction and that longer production chains for a country bias it toward faster growth. These predictions are in good agreement with data from the World Input Output Database and improve with the passage of time. The results show that production chains play a major role in shaping the long-term evolution of prices, output growth, and structural change.
99 GENERAL AND MISCELLANEOUS↗
Improved Stability of a Model IgG3 by DoE-Based Evaluation of Buffer Formulations
Formulating appropriate storage conditions for biopharmaceutical proteins is essential for ensuring their stability and thereby their purity, potency, and safety over their shelf-life. Using a model murine IgG3 produced in a bioreactor system, multiple formulation compositions were systematically explored in a DoE design to optimize the stability of a challenging antibody formulation worst case. The stability of the antibody in each buffer formulation was assessed by UV/VIS absorbance at 280 nm and 410 nm and size exclusion high performance liquid chromatography (SEC) to determine overall solubility, opalescence, and aggregate formation, respectively. Upon preliminary testing, acetate was eliminated as a potential storage buffer due to significant visible precipitate formation. An additional 2 4 full factorial DoE was performed that combined the stabilizing effect of arginine with the buffering capacity of histidine. From this final DoE, an optimized formulation of 200 mM arginine, 50 mM histidine, and 100 mM NaCl at a pH of 6.5 was identified to substantially improve stability under long-term storage conditions and after multiple freeze/thaw cycles. Therefore, our data highlights the power of DoE based formulation screening approaches even for challenging monoclonal antibody molecules.
59 BASIC BIOLOGICAL SCIENCES↗
Dereplication, Aggregation and Scoring Tool (DAS Tool) v1.0
Communities of uncultivated microbes are critical to ecosystem function and microorganism health, and a key objective of metagenomic studies is to analyze organism-specific metabolic pathways and reconstruct community interaction networks. This requires accurate assignment of genes to genomes, yet existing binning methods often fail to predict a reasonable number of genomes and report many bins of low quality and completeness. Furthermore, the performance of existing algorithms varies between samples and biotypes. Here, we present a dereplication, aggregation and scoring strategy, DAS Tool, that combines the strengths of a flexible set of established binning algorithms. DAS Tools applied to a constructed community generated more accurate bins than any automated method. Further, when applied to samples of different complexity, including soil, natural oil seeps, and the human gut, DAS Tool recovered substantially more near-complete genomes than any single binning method alone. Included were three genomes from a novel lineage . The ability to reconstruct many near-complete genomes from metagenomics data will greatly advance genome-centric analyses of ecosystems.
SIEBER, CHRISTIAN↗
Streamlined Approach for Environmental Restoration (SAFER) Plan for Corrective Action Unit 575: Area 15 Miscellaneous Sites, Nevada National Security Site, Nevada
This Streamlined Approach for Environmental Restoration (SAFER) Plan addresses the actions needed to achieve closure for Corrective Action Unit (CAU) 575, Area 15 Miscellaneous Sites, identified in the Federal Facility Agreement and Consent Order (FFACO). CAU 575 comprises the following four corrective action sites (CASs) located in Area 15 of the Nevada National Security Site: 15-19-02, Waste Burial Pit, 15-30-01, Surface Features at Borehole Sites, 15-64-01, Decontamination Area, 15-99-03, Aggregate Plant This plan provides the methodology for field activities needed to gather the necessary information for closing each CAS. There is sufficient information and process knowledge from historical documentation and investigations of similar sites regarding the expected nature and extent of potential contaminants to recommend closure of CAU 575 using the SAFER process. Additional information will be obtained by conducting a field investigation to document and verify the adequacy of existing information, to affirm the predicted corrective action decisions, and to provide sufficient data to implement the corrective actions. This will be presented in a closure report that will be prepared and submitted to the Nevada Division of Environmental Protection (NDEP) for review and approval.
54 ENVIRONMENTAL SCIENCES↗
Enhancing segmentation fairness through curriculum learning and progressive loss: a centralized and federated perspective on radiograph analysis
Bias in medical image segmentation can lead to unequal performance across demographic subgroups, raising concerns about fairness and reliability in clinical AI systems. While deep learning models have achieved high segmentation accuracy, ensuring equitable performance across race and gender remains a significant challenge, particularly in privacy-sensitive healthcare environments. This study investigates fairness-aware medical image segmentation for hip and knee radiographs using deep learning models evaluated in both centralized and Federated Learning (FL) settings. We introduce Curriculum Learning (CL) strategies and Progressive Loss (PL) functions to regulate sample difficulty during training. In addition, we propose two novel fairness-oriented federated learning algorithms, Federated Intersection over Union (FedIoU) and Federated Intersection over Union with Outlier Analysis (FedIoUoutlier). Experiments are conducted using multiple segmentation backbones and simulated multi-site data partitions derived from the Osteoarthritis Initiative dataset. Model performance is evaluated using Intersection over Union (IoU), IoU standard deviation, Skewed Error Ratio (SER), and Min-Max Disparity across race and gender subgroups. Statistical significance was verified using paired t-tests to compare per-sample IoU performance against baseline configurations. Across both hip and knee segmentation tasks, curriculum learning and progressive loss strategies consistently improved segmentation accuracy and reduced demographic performance disparities in centralized training. In federated settings, fairness-aware aggregation further enhanced performance. Notably, FedIoUoutlier combined with balanced curriculum learning and tiered progressive loss achieved the highest mean IoU while yielding the lowest SER and Min-Max Disparity, indicating improved fairness without sacrificing accuracy. In several configurations, federated models matched or exceeded the performance of optimized centralized models, with statistically significant improvements in per-sample IoU over baseline configurations. The results demonstrate that structured training strategies and fairness-aware federated aggregation can jointly improve accuracy, stability, and demographic fairness in medical image segmentation. By integrating curriculum learning, progressive loss, and novel FL algorithms, this work provides a practical pathway toward equitable and privacy-preserving AI systems for medical imaging.
97 MATHEMATICS AND COMPUTING↗
Elastic knowledge base of bcc Ti alloys from first-principles calculations and CALPHAD-based modeling
Here, titanium alloys are being investigated as suitable materials for load-bearing implants because of their biocompatibility and mechanical properties. Stress shielding, a common issue with the current load-bearing implant materials, occurs due to a Young’s modulus (E) mismatch between bone (~10–40 GPa) and implants (such as Ti-6Al-4V ~ 110 GPa), which leads to bone dying around the implant and ultimately implant failure. Reducing the Young’s modulus of Ti alloys may overcome the issues of stress shielding and improve implant materials. In the present work, first-principles calculations have been used to predict the single crystal elastic stiffness coefficients (c ij ’s) for the Ti-containing ternary alloys Ti-X-Y(X ≠ Y = Mo, Nb, Sn, Ta, Zr) in the bcc lattice. It is found that the ternary Ti-X-Y (X ≠ Y = Mo, Nb, Ta) alloys behave similarly; so do the ternary Ti-X-Sn (X = Mo, Nb, Ta) alloys and the Ti-X-Zr (X = Mo, Nb, Ta) alloys. This is expected due to the similarity between the Mo, Nb and Ta elements. The results also show that the Ti-Zr-X alloys stabilized the bcc phase at lower alloying concentrations. The polycrystalline aggregate properties are also estimated from the c ij ’s, including bulk modulus, shear modulus and Young’s modulus. The results show that Ti-alloys with compositions close to the bcc stability limit have the lowest E. In combination with previous predictions, a complete elastic database has been established using theCALPHAD (CALculation of PHAse Diagram) based modeling approach. The database results are compared with the E of higher order Ti alloys and shown to be able to predict the E accurately. This complete data-base forms a foundation to tailor Ti alloys for desired elastic properties.
36 MATERIALS SCIENCE↗
Rosiglitazone activation of PPARγ-dependent signaling is neuroprotective in mutant huntingtin expressing cells
Peroxisome proliferator-activated receptor gamma (PPARγ) is a crucial transcription factor for neuroprotection in several brain diseases. Using a mouse model of Huntington's Disease (HD), we recently showed that PPARγ not only played a major function in preventing HD, but also oral intake of a PPARγ agonist (thiazolidinedione, TZD) significantly reduced the formation of mutant Huntingtin (mHtt) aggregates in the brain (e.g., cortex and striatum). The molecular mechanisms by which PPARγ exerts its HD neuroprotective effects remain unresolved. We investigated whether the PPARγ agonist (rosiglitazone) mediates neuroprotection in the mHtt expressing neuroblastoma cell line (N2A). Here we show that rosiglitazone upregulated the endogenous expression of PPARγ, its downstream target genes (including PGC1α, NRF-1 and Tfam) and mitochondrial function in mHtt expressing N2A cells. Rosiglitazone treatment also significantly reduced mHtt aggregates that included ubiquitin (Ub) and heat shock factor 1 (HSF1), as assessed by a filter-retardation assay, and increased the levels of the functional ubiquitin–proteasome system (UPS), HSF1 and heat shock protein 27/70 (HSP27/70) in N2A cells. Moreover, rosiglitazone treatment normalized endoplasmic reticulum (ER) stress sensors Bip, CHOP and ASK1, and significantly increased N2A cell survival. Taken together, these findings unveil new insights into the mechanisms by which activation of PPARγ signaling protects against the HD-mediated neuronal impairment. Further, our data also support the concept that PPARγ may be a novel therapeutic target for treating HD.
60 APPLIED LIFE SCIENCES↗
Observation of propane cluster size distributions during nucleation and growth in a Laval expansion
We report on molecular-level studies of the condensation of propane gas and propane/ethane gas mixtures in the uniform (constant pressure and temperature) postnozzle flow of Laval expansions using soft single-photon ionization by vacuum ultraviolet light and mass spectrometric detection. The whole process, from the nucleation to the growth to molecular aggregates of sizes of several nanometers (∼5 nm), can be monitored at the molecular level with high time-resolution (∼3 μs) for a broad range of pressures and temperatures. For each time, pressure, and temperature, a whole mass spectrum is recorded, which allows one to determine the critical cluster size range for nucleation as well as the kinetics and mechanisms of cluster-size specific growth. The detailed information about the size, composition, and population of individual molecular clusters upon condensation provides unique experimental data for comparison with future molecular-level simulations.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Radiation-Induced Degradation of Concrete in NPPs
Nuclear power plants life extensions to 60 and potentially 80 years of operation have renewed interest in long-term material degradation. One material being considered is concrete. Swelling of aggregates driven by radiation induced displacements of atoms is currently considered to be the most probable leading contributor to the radiation induced degradation of concrete mechanical properties. In the biological shields of nuclear plants atom displacements are dominated by neutron contributions while gamma-ray contributions are negligible. For a number of minerals, which are common constituents of aggregates, in concrete it was shown that ~95% of the dpa is generated by neutrons with energies above 0.1 MeV. Neutrons with energies above 1 MeV contribute only ~20 to 25% to the dpa. Therefore, if neutron fluence is used as correlation parameter for the concrete degradation, the neutron fluence energy cut-off of 0.1 MeV should be used. Based on the projected neutron fluence values (E > 0.1 MeV) in the concrete biological shields of the US pressurized water reactor fleet and the available data on radiation effects on concrete, some decrease in mechanical properties of concrete cannot be ruled out during extended operation beyond 60 years.
Remec, Igor↗
Dynamical Arrest, Structural Disorder, and Optimization of Organic Photovoltaic Devices
This project describes fundamental experimental and theoretical work that relates to charge separation and migration in the solid, heterogeneous or aggregated state. Marcus theory assumes a system in equilibrium with all possible solvent (dipolar) configurations, with rapid interconversion among these on the ET timescale. This project has addressed the more general situation where the medium is at least partially frozen on the ET timescale, i.e. under conditions of dynamical arrest. The approach combined theory and experiment and includes: (1) Computer simulations of model systems, (2) Development of analytical procedures consistent with computer experiment and (3) Experimental studies and testing of the formal theories on this data. Electron transfer processes are unique as a consequence of the close connection between kinetics, spectroscopy and theory, which is an essential component of this work.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
The Cost of Saving Electricity: A Multi-Program Cost Curve for Programs Funded by U.S. Utility Customers
This study analyzed the cost performance of electricity efficiency programs implemented by 116 investor-owned utilities between 2009 and 2015 in 41 states, representing about three-quarters of the total spending on U.S. efficiency programs. We applied our typology to characterize efficiency programs along several dimensions (market sector, technology, delivery approach, and intervention strategy) and report the costs incurred by utilities and other program administrators to achieve electricity savings as a result of the programs. Such cost performance data can be used to compare relative costs of different types of efficiency programs, evaluate efficiency options alongside other electricity resources, benchmark local efficiency programs against regional and national cost estimates, and assess the costs of meeting state efficiency policies. The savings-weighted average cost of saved electricity for the period was $0.025/kilowatt-hour (kWh). The cost of saved electricity for programs that targeted residential customers was $0.021/kWh, compared to $0.025/kWh for programs for commercial and industrial customers. Ultimately, we developed an aggregate program savings “cost curve” for the actual electricity efficiency resource during the period that provides insights into the relative costs of various types of efficiency programs and the savings contribution of each program type to the efficiency resource at a national level.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Sensitivity Analysis of Drivers Water Shortage in the Los Angeles Region During Drought
The code and detailed step-by-step instructions for generating the model output data, processing results, and analysis and plotting are provided at https://github.com/IMMM-SFA/Ferencz_et_al_2026_ER_Water. The PyArtes model is a python adaptation of the Artes model. PyArtes uses many of the same input data and optimization model architecture as Artes. Documentation for the PyArtes model is provided in the Supplement to the paper. The primary data product are simulated monthly water shortages for indoor and outdoor demand under a large ensemble of drought scenarios (>13,000). The droughts are hypothetical and are not based on historical time series data of supply sources - though historical data did help inform ranges explored for supply parameters. Demands are informed by recent 2017-2021 water supply data. Demands used for the model can be accessed at https://github.com/IMMM-SFA/Ferencz_et_al_2026_ER_Water. Simulations resolve demand for over 90 water providers in the study region. The results report 36 months of water shortage data for each indoor and outdoor demand node. The study also developed a multilayer perceptron (MLP) neural network trained on a subset of the simulated shortage ensemble to emulate worst annual water shortage for a given set of parameter multipliers -- provided the parameter values fall within the ranges sampled in the ensemble. Emulated water shortages for synthetic ensembles are in the MLP-generated shortages folder. The MLP model was used to generate larger ensembles to support Sobol analysis that would have been extremely computationally expensive to simulate. Datasets provided in this repository*: Simulated shortages. These results are used for the analysis for Figures 5, 8, and 9 in the paper, and also to train the MLP emulator. .zip file containing outputs for the 13,312 scenario ensemble. Separate .csv files for indoor and outdoor shortage for each scenario. Rows = demand ids (~100), Columns = months (36) Units = acre-feet/month of shortage (shortage = monthly demand - supply). 1 acft = 1233.48 m^3 .csv files of aggregated shortages derived from the 13,312 ensemble Rows = scenarios (13,312), Columns = demand ids (~100) Units = acre-feet/year (either worst annual shortage or total shortage over the 3-year drought) .csv file of the parameter multipliers scenarios for the ensemble .csv file of the parameter ranges and baseline values the multipliers were applied to MLP-generated shortages. These results are used for Figures 4, 6, and 7 in the paper. mwd higher folder: scenario ensembles, emulated worst year total shortages (acft), and Sobol results Emulated shortages. Rows = scenarios, columns = demand ids, units acft Sobol results. Rows = demand ids, columns Sobol (S1, ST, or 95% confidence interval) value for each parameter mwd lower folder: scenario ensembles, emulated worst year total shortages (acft), and Sobol results same organization as mwd higher MLP performance: performance metrics (R^2, RMSE, BIAS, MAPE) for the testing subset (20% or 2,662 scenarios) and simulated vs emulated worst year shortage (acre-feet/year) for every demand node, MWD wholesale regions, and the entire study region (LAC). Supporting data for figures. Figure plotting scripts in the associated GitHub repo. These files support analysis and visualization. Geospatial Data used for plotting simulated water shortages and Sobol results. Dictionary of full names for demand nodes in the model and estimates of water supply by source type informed by Artes input files and California Urban Water Management Planning data: https://water.ca.gov/Programs/Water-Use-And-Efficiency/Urban-Water-Use-Efficiency/Urban-Water-Management-Plans *Readme files provided for each folder.
drought↗