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NASA NTRS2021

First Attempt of Global-scale Assimilation of Subdaily Scale Soil Moisture Estimates from CYGNSS and SMAP into a Land Surface Model

Soil moisture performs a key function in the hydrologic process and understanding the global-scale water cycle. However, estimations of soil moisture taken from current sun-synchronous orbit (SSO) satellites are limited in that they are neither spatially nor temporally continuous. This limitation creates discontinuous soil moisture observation from space and hampers our understanding of the fundamental processes that control the surface hydrologic cycle across both time and space domains. Here, we propose to use frequent soil moisture observations from NASA’s constellation of eight micro-satellites called the Cyclone Global Navigation Satellite System(CYGNSS) together with the Soil Moisture Active Passive (SMAP) to assimilate subdaily-scale soil moisture intoa land surface model(LSM). Our results, which are based on triple collocation analysis(TCA), show how current scientific advances in satellite systems can fill previous gaps in soil moisture observations in subdaily scale bypast observations, and eventually adds value to improvements in global scale soil moisture estimates in LSMs. Overall, TCA-based fractional mean square errors (fMSE) of LSM soil moisture are improved by 61% with the synergetic assimilation of CYGNSS data with SMAP soil moisture observations. However, assimilating satellite-based soil moisture over dense vegetation areas can degrade the performance of LSMs as these areas propagate erroneous soil moisture information to LSMs. To our knowledge, this study isthe first global assimilation of GNSS-based soil moisture observations in land surface models.

Hyunglok Kim↗

NASA NTRS2021

Bias Correction of Hydrologic Projections Strongly Impacts Inferred Climate Vulnerabilities in Institutionally Complex Water Systems

Water-resources planners use regional water management models (WMMs) to identify vulnerabilities to climate change. Frequently, dynamically downscaled climate inputs are used in conjunction with land-surface models (LSMs) to provide hydrologic streamflow projections, which serve as critical inputs for WMMs. Here, we show how even modest projection errors can strongly affect assessments of water availability and financial stability for irrigation districts in California. Specifically, our results highlight that LSM errors in projections of flood and drought extremes are highly interactive across timescales, path-dependent, and can be amplified when modeling infrastructure systems (e.g., misrepresenting banked groundwater). Common strategies for reducing errors in deterministic LSM hydrologic projections (e.g., bias correction) can themselves strongly distort projected climate vulnerabilities and misrepresent their inferred financial consequences. Overall, our results indicate a need to move beyond standard deterministic climate projection and error management frameworks that are dependent on single simulated climate change scenario outcomes.

Keyvan Malek↗

NASA NTRS2022

Assimilation of NASA’s Airborne Snow Observatory Snow Measurements for Improved Hydrological Modeling: A Case Study Enabled by the Coupled LIS/WRF-Hydro System

he NASA LIS/WRF-Hydro system is a coupled modeling framework that combines the modeling and data assimilation (DA) capabilities of the NASA Land Information System (LIS) with the multi-scale surface hydrological modeling capabilities of the WRF-Hydro model, both of which are widely used in both operations and research. This coupled modeling framework builds on the linkage between land surface models (LSMs), which simulate surface boundary conditions in atmospheric models, and distributed hydrologic models, which simulate horizontal surface and sub-surface flow, adding new land DA capabilities. In the present study, we employ this modeling framework in the Tuolumne River basin in central California. We demonstrate the added value of the assimilation of NASA Airborne Snow Observatory (ASO) snow water equivalent (SWE) estimates in the Tuolumne basin. This analysis is performed in both LIS as an LSM column model and LIS/WRF-Hydro, with hydrologic routing. Results demonstrate that ASO DA in the basin reduced snow bias by as much as 30% from an open-loop (OL) simulation compared to three independent datasets. It also reduces downstream streamflow runoff biases by as much as 40%, and improves streamflow skill scores in both wet and dry years. Analysis of soil moisture and evapotranspiration (ET) also reveals the impacts of hydrologic routing from WRF-Hydro in the simulations, which would otherwise not be resolved in an LSM column model. By demonstrating the beneficial impact of SWE DA on the improving streamflow forecasts, the article outlines the importance of such observational inputs for reservoir operations and related water management applications.

Hydrologic modeling↗

NASA NTRS2022

Assimilation of NASA's Airborne Snow Observatory Snow Measurements for Improved Hydrological Modeling: A Case Study Enabled by the Coupled LIS/WRF-Hydro System

The NASA LIS/WRF-Hydro system is a coupled modeling framework that combines the modeling and data assimilation (DA) capabilities of the NASA Land Information System (LIS) with the multi-scale surface hydrological modeling capabilities of the WRF-Hydro model, both of which are widely used in both operations and research. This coupled modeling framework builds on the linkage between land surface models (LSMs), which simulate surface boundary conditions in atmospheric models, and distributed hydrologic models, which simulate horizontal surface and sub-surface flow, adding new land DA capabilities. In the present study, we employ this modeling framework in the Tuolumne River basin in central California. We demonstrate the added value of the assimilation of NASA Airborne Snow Observatory (ASO) snow water equivalent (SWE) estimates in the Tuolumne basin. This analysis is performed in both LIS as an LSM column model and LIS/WRF-Hydro, with hydrologic routing. Results demonstrate that ASO DA in the basin reduced snow bias by as much as 30% from an open-loop (OL) simulation compared to three independent datasets. It also reduces downstream streamflow runoff biases by as much as 40%, and improves streamflow skill scores in both wet and dry years. Analysis of soil moisture and evapotranspiration (ET) also reveals the impacts of hydrologic routing from WRF-Hydro in the simulations, which would otherwise not be resolved in an LSM column model. By demonstrating the beneficial impact of SWE DA on the improving streamflow forecasts, the article outlines the importance of such observational inputs for reservoir operations and related water management applications.

Timothy M. Lahmers↗

NASA NTRSDate not supplied

An Observation-Driven Framework for Modeling Post-Fire Hydrologic Response: Evaluation for Two Central California Case Studies

In a warming climate, wildfires are becoming increasingly common, especially in semi-arid environments. Wildfires can disrupt forest ecosystems and induce changes to the land surface. Collectively, these impacts can alter the hydrologic response of a catchment following a fire, resulting in increased potential for surface runoff, reduced evapotranspiration, and, ultimately, a higher risk for flash flooding and mass wasting. The timescale for post-fire recovery of hydrological processes to return to pre-fire conditions is not well established due to the lack of ground measurements. Accurate characterization of fire impacts on hydrologic response is also challenging to simulate, given the complex interplay of various processes. Here, we present a generalized framework to quantify wildfire impacts on runoff generation. We consider the vegetation and soil disturbances as the primary contributors to post-fire floods. Using an ensemble modeling structure to account for parameter uncertainty and consider model sensitivity, remotely sensed leaf area index (LAI) is assimilated into a land surface model (LSM) to simulate vegetation disturbance, and the maximum land surface saturation LSM parameter is decreased to parameterize the soil disturbance following observed fires. We evaluated the impacts of fire-induced changes to LAI and soil saturation on hydrologic states like runoff and evapotranspiration. Analysis of two events in central California shows that 1) the LAI assimilation has a greater impact on water balance; and 2) the soil scheme captures a range of outcomes, with substantial impacts on surface runoff for some ensemble members, which could affect flood potential.

Timothy M Lahmers↗

NASA NTRS2025

An Observation-Driven Framework for Modeling Post-Fire Hydrologic Response: Evaluation for Two Central California Case Studies

In a warming climate, wildfires are becoming increasingly common, especially in semi-arid environments. Wildfires can disrupt forest ecosystems and induce changes to the land surface. Collectively, these impacts can alter the hydrologic response of a catchment following a fire, resulting in increased potential for surface runoff, reduced evapotranspiration, and, ultimately, a higher risk for flash flooding and mass wasting. The timescale of post-fire recovery of hydrological processes to return to pre-fire conditions is not well established due to the lack of ground measurements. Accurate characterization of the impacts of fire on hydrologic response is also challenging to simulate, given the complex interplay of various processes. Here, we present a generalized framework to quantify the impacts of wildfire on runoff generation. We consider the disturbances in the vegetation and soil as the two main factors contributing to post-fire floods. Using an ensemble modeling structure to account for parameter uncertainty, remotely sensed leaf area index (LAI) is assimilated into a land surface model (LSM) to simulate vegetation disturbance, and the maximum land surface saturation LSM parameter is decreased to parameterize the soil disturbance following observed fires. We consider the impacts of fire-induced changes to LAI and soil saturation on hydrologic states like runoff and evapotranspiration for two case studies. These case studies demonstrate the general applicability of hydrophobicity formulation to serve as a guideline for exploring the range of hydrologic responses post-fire.

Fire Hydrology↗

DOE OSTI2014

Position sensor for linear synchronous motors employing halbach arrays

A position sensor suitable for use in linear synchronous motor (LSM) drive systems employing Halbach arrays to create their magnetic fields is described. The system has several advantages over previously employed ones, especially in its simplicity and its freedom from being affected by weather conditions, accumulated dirt, or electrical interference from the LSM system itself.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2022

DenKv: Addressing Design Trade-offs of Key-value Stores for Scientific Applications

High-performance computing (HPC) facilities have employed flash-based storage tier near to compute nodes to absorb high I/O demand by HPC applications during periodic system-level checkpoints. To accelerate these checkpoints, proxy-based distributed key-value stores (PD-KVS) gained particular attention for their flexibility to support multiple backends and different network configurations. PD-KVS rely internally on monolithic KVS, such as LevelDB or RocksDB, to exploit the KV interface and query support. However, PD-KVS are unaware of the high redundancy factor in checkpoint data, which can be up to GBs to TBs, and therefore, tend to generate high write and space amplification on these storage layers. In this paper, we propose DenKv which is deduplication-extended node-local LSM-tree-based KVS. DenKv employs asynchronous partially inline dedup (APID) and aims to maintain the performance characteristics of LSM-tree-based KVS while reducing the write and space amplification problems. We implemented DenKv atop BlobDB and showed that our proposed solution maintains performance while reducing write amplification up to 2× and space amplification by 4× on average.

Khan, Awais↗

DOE OSTI2022

Unconventional Highly Active and Stable Oxygen Reduction Catalysts Informed by Computational Design Strategies

Abstract Discovering and engineering new materials with fast oxygen surface exchange kinetics and robust long‐term stability is essential for the large‐scale, economically viable commercialization of solid oxide fuel cell (SOFC) technology. The perovskite catalyst material BaFe 0.125 Co 0.125 Zr 0.75 O 3 (BFCZ75), predicted to be promising from recent density functional theory (DFT) calculations and unconventional due to its extremely high Zr content and low electronic conductivity, exhibits oxygen reduction reaction surface exchange rates on par with Ba 0.5 Sr 0.5 Co 0.8 Fe 0.2 O 3 (BSCF) and excellent stability at typical operating temperatures. New composite electrodes are engineered by integrating BFCZ75 with commercial electrode materials La 1– x Sr x MnO 3 (LSM) and La 1– x Sr x Co y Fe 1– y O 3 (LSCF) and achieve high performance as measured by low area specific resistance (ASR) values, with the LSCF/BFCZ75 ASR values comparable to top performing noncomposite electrode materials such as SrCo 0.8 Sc 0.2 O 3– δ , BaNb 0.05 Fe 0.95 O 3– δ and BaCo 0.7 Fe 0.22 Y 0.08 O 3– δ . The use of BFCZ75 as a composite with LSCF achieving low ASR values shows that BFCZ75 is highly active and can easily integrate into existing SOFC material supply chains, lowering the barrier for potential commercial application of new electrode materials. Finally, these findings point to a broader unexplored class of perovskite materials with high fractions of redox inactive species (e.g., Zr, Nb, and Ta) that may unlock new pathways to realizing improved commercial SOFCs.

Jacobs, Ryan↗

DOE OSTI2017

Development of High Power Density Metal‐Supported Solid Oxide Fuel Cells

Abstract Symmetric‐structure metal‐supported solid oxide fuel cells (MS‐SOFCs) are fabricated by infiltrating catalysts on both anode and cathode side. Various aspects of the infiltration process are optimized. Performance is found to be sensitive to precursor dilution, catalyst loading, and catalyst calcining temperature. For an optimized cell with lanthanum strontium manganite (LSM) as cathode and Sm 0.2 Ce 0.8 O 2− δ mixed with Ni (SDCN) as anode, peak power densities of 0.44, 1.1, and 1.9 W cm −2 are achieved at 600, 700, and 800 °C, respectively. A fully symmetric MS‐SOFC with SDCN as both the anode and cathode sides achieves moderate peak power densities of 0.12, 0.37, and 0.76 W cm −2 at 600, 700, and 800 °C, respectively. A solvent‐based infiltration technique is also explored and found to be more effective than capillary forces alone but not as effective as vacuum infiltration.

Tucker, Michael C.↗

DOE OSTI2016

Investigation of boundary-layer wind predictions during nocturnal low-level jet events using the Weather Research and Forecasting model

Simulations of two periods featuring three consecutive low level jet (LLJ) events in the US Upper Great Plains during the autumn of 2011 were conducted to explore the impacts of various setup configurations and physical process models on simulated flow parameters within the lowest 200 m above the surface, using the Weather Research and Forecasting (WRF) model. Sensitivities of simulated flow parameters to the horizontal and vertical grid spacing, planetary boundary layer (PBL) and land surface model (LSM) physics options, were assessed. Data from a Light Detection and Ranging (lidar) system, deployed to the Weather Forecast Improvement Project (WFIP; Finley et al. 2013) were used to evaluate the accuracy of simulated wind speed and direction at 80 m above the surface, as well as their vertical distributions between 120 and 40 m, covering the typical span of contemporary tall wind turbines. All of the simulations qualitatively captured the overall diurnal cycle of wind speed and stratification, producing LLJs during each overnight period, however large discrepancies occurred at certain times for each simulation in relation to the observations. 54-member ensembles encompassing changes of the above discussed configuration parameters displayed a wide range of simulated vertical distributions of wind speed and direction, and potential temperature, reflecting highly variable representations of stratification during the weakly stable overnight conditions. Root mean square error (RMSE) statistics show that different ensemble members performed better and worse in various simulated parameters at different times, with no clearly superior configuration . Simulations using a PBL parameterization designed specifically for the stable conditions investigated herein provided superior overall simulations of wind speed at 80 m, demonstrating the efficacy of targeting improvements of physical process models in areas of known deficiencies. However, the considerable magnitudes of the RMSE values of even the best performing simulations indicate ample opportunities for further improvements.

Mirocha, Jeff D.↗

DOE OSTI2022

Using advanced data structures to enable responsive security monitoring

Write-optimized data structures (WODS), offer the potential to keep up with cyberstream event rates and give sub-second query response for key items like IP addresses. These data structures organize logs as the events are observed. To work in a real-world environment and not fill up the disk, WODS must efficiently expire older events. As the basis for our research into organizing security monitoring data, we implemented a tool, called Diventi, to index IP addresses in connection logs using RocksDB (a write-optimized LSM tree). In this work, we extended Diventi to automatically expire data as part of the data structures’ normal operations. We guarantee that Diventi always tracks the N most recent events and tracks no more than N + k events for a parameter k < N, while ensuring the index is opportunistically pruned. To test Diventi at scale in a controlled environment, we used anonymized traces of IP communications collected at SuperComputing 2019. We synthetically extended the 2.4 billion connection events to 100 billion events. We tested Diventi vs. Elasticsearch, a common log indexing tool. In our test environment, Elasticsearch saw an ingestion rate of at best 37,000 events/s while Diventi sustained ingestion rates greater than 171,000 events/s. Our query response times were as much as 100 times faster, typically answering queries in under 80 ms. Furthermore, we saw no noticeable degradation in Diventi from expiration. We have deployed Diventi for many months where it has performed well and supported new security analysis capabilities.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Refining water and carbon fluxes modeling in terrestrial ecosystems via plant hydraulics integration

Plant hydraulics substantially affects terrestrial water and carbon cycles by modulating water transport and carbon assimilation. Despite improved drought simulations in certain ecosystems through their integration into land surface models (LSMs), the broader application of plant hydraulics in diverse ecosystems and hydroclimates is still underexplored. Here, in this study, we implemented the recently developed Noah-Multiparameterization Land Surface Model (Noah-MP LSM) equipped with a plant hydraulics scheme (Noah-MP-PHS) across 40 FLUXNET sites globally. Employing the Shuffled Complex Evolution-University of Arizona (SCE-UA) auto-calibration algorithm, we optimized key plant hydraulics parameters for these sites spanning eight vegetation types in both arid and humid climates. Noah-MP-PHS significantly improves the simulation of evapotranspiration (ET) and gross primary production (GPP) by better representing atmospheric and soil water stress compared to traditional soil hydraulic schemes (SHSs, such as Noah and CLM). The augmented Noah-MP-PHS models reduce surface flux overestimation and underestimation, exhibiting an average increase of 0.14 and 0.15 in Kling-Gupta Efficiency (KGE) compared to Noah and CLM, respectively. The explicit consideration of plant capacitance in PHS reveals substantial deep-layer and nocturnal root water uptake especially under dry conditions. We employed eXplainable Machine learning (XML) to quantify the model’s relative sensitivity to newly introduced leaf-, stem and root-related parameters in PHS. The sensitivity analysis reveals a rise in root parameter importance and a decline in leaf and stem parameters as conditions shift from humid to arid. These findings indicate that as aridity states vary, the most influential parameters affecting surface fluxes variation may change in parameter calibration for PHS applications. Our findings underscore the importance of incorporating plant hydraulics into LSMs to enhance simulations of terrestrial water and carbon dynamics. These findings are crucial for understanding ecosystem responses to global climate changes and guide the broader application of PHS at larger scales.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2011

Comparison of SOFC Cathode Microstructure Quantified using X-ray Nanotomography and Focused Ioni Beam-scanning Electron Microscopy

X-ray nanotomography and focused ion beam scanning electron microscopy (FIB-SEM) have been applied to investigate the complex 3D microstructure of solid oxide fuel cell (SOFC) electrodes at spatial resolutions of 45 nm and below. The application of near edge differential absorption for x-ray nanotomography and energy selected backscatter detection for FIB-SEM enable elemental mapping within the microstructure. Using these methods, non-destructive 3D x-ray imaging and FIB-SEM serial sectioning have been applied to compare three-dimensional elemental mapping of the LSM, YSZ, and pore phases in the SOFC cathode microstructure. The microstructural characterization of an SOFC cathode is reported based on these measurements. The results presented demonstrate the viability of x-ray nanotomography as a quantitative characterization technique and provide key insights into the SOFC cathode microstructure.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2010

Perovskite Sr2Fe1.5Mo0.5O6-δ as electrode materials for symmetrical solid oxide electrolysis cells

Perovskite Sr2Fe1.5Mo0.5O6-δ (SFM) has been successfully prepared by a microwave-assisted combustion method in air and employed as both anode and cathode in symmetrical solid oxide electrolysis cells (SOECs) for hydrogen production for the first time in this work. Influence of cell operating temperature, absolute humidity (AH) as well as applied direct current (DC) on the impedance of single cells with the configuration of SFM|La0.9Sr0.1Ga0.8Mg0.2O3 (LSGM)|SFM has been evaluated. Under open circuit conditions and 60 vol.% AH, the cell polarization resistance, RP is as low as 0.26 Ω cm2 at 900 °C. An electrolysis current of 0.88 A cm-2 and a hydrogen production rate as high as 380 mL cm-2 h have been achieved at 900 °C with an electrolysis voltage of 1.3 V and 60 vol.% AH. Further, the cell has demonstrated good stability in the long-term steam electrolysis test. The results showed that the cell electrolysis performance was even better than that of the reported strontium doped lanthanum manganite (LSM) – yttria stabilized zirconia (YSZ)|YSZ|Ni–YSZ cell, indicating that SFM could be a very promising electrode material for the practical application of SOEC technology.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2012

Atomic-Scale Mechanisms of Oxygen Electrode Delamination in Solid Oxide Electrolyzer Cells

Materials used for different components (electrodes, electrolyte, steel interconnects, etc.) of solid oxide electrolyzer cell (SOEC) devices for hydrogen production have to function in aggressive, corrosive environments and in the presence of electric fields. This results in a number of degradation processes at interfaces between components. In this study, we used a combination of first-principles, density-functional-theory (DFT) calculations and thermodynamic modeling to elucidate the main processes that contribute into the oxygen delamination in typical SOEC device consisting of yttria-stabilized zirconia (YSZ) electrolyte and Sr-doped LaMnO3 (LSM) oxygen electrode. We found that high temperature inter-diffusion of different atoms across the LSM/YSZ interface significantly affects structural stability of the materials and their interface. In particular, we found that La and Sr substitutional defects positioned in ZrO2 oxide and near LSM/YSZ interface significantly change oxygen transport which may develop pressure buildup in the interfacial region and eventually develop delamination process. Simple models for estimating these effects are proposed, and different possibilities for inhibiting and/or mitigating undesirable delamination processes are discussed.

08 HYDROGEN↗

DOE OSTI2017

Impact of vegetation dynamics on hydrological processes in a semi-arid basin by using a land surface-hydrology coupled model

Land surface models (LSMs) are widely used to understand the interactions between hydrological processes and vegetation dynamics, which is important for the attribution and prediction of regional hydrological variations. However, most LSMs have large uncertainties in their representations of ecohydrological processes due to deficiencies in hydrological parameterizations. In this study, the Community Land Model version 4 (CLM4) LSM was modified with an advanced runoff generation and flow routing scheme, resulting in a new land surface-hydrology coupled model, CLM-GBHM. Both models were implemented in the Wudinghe River Basin (WRB), which is a semi-arid basin located in the middle reaches of the Yellow River, China. Compared with CLM, CLM-GBHM increased the Nash Sutcliffe efficiency for daily river discharge simulation (1965–1969) from 0.03 to 0.23 and reduced the relative bias in water table depth simulations (2010–2012) from 32.4% to 13.4%. The CLM-GBHM simulations with static, remotely sensed and model-predicted vegetation conditions showed that the vegetation in the WRB began to recover in the 2000s due to the Grain for Green Program but had not reached the same level of vegetation cover as regions in natural eco-hydrological equilibrium. Compared with a simulation using remotely sensed vegetation cover, the simulation with a dynamic vegetation model that considers only climate-induced change showed a 10.3% increase in evapotranspiration, a 47.8% decrease in runoff, and a 62.7% and 71.3% deceleration in changing trend of the outlet river discharge before and after the year 2000, respectively. We conclude this result suggests that both natural and anthropogenic factors should be incorporated in dynamic vegetation models to better simulate the eco-hydrological cycle.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

Assessment of age, origin, and sustainability of fossil aquifers: A geochemical and remote sensing-based approach

An integrated approach was developed to assess the sustainability, origin, age, evolution, and groundwater potential of large fossil aquifers using the Mega Aquifer System (MAS) (area: 2 x 10(6) km(2)) in the Arabian Peninsula as a test site. A two-step exercise was adopted, the sustainability of the MAS was first investigated through the analysis of GRACE data and land surface model (LSM) outputs. Then, integrated geochemical, remote sensing, and field studies were conducted to address the age, origin, hydrogeological setting, and evolution of the southern sections of the MAS (Rub Al Khali Aquifer System (RAKAS)), the area identified from the analysis of GRACE and ISMs as being the most suited for sustainable development. Analysis of GRACE and ISMs revealed: (1) the MAS central and northern sections are experiencing high groundwater extraction (6.6 km(3)/yr) and depletion rates (-2.8 +/- 0.8 km(3)/yr) with minimum balancing potential through aquifer capture processes, yet sustainability could be achieved by reducing annual extraction by 2.8 km(3), and (2) the MAS southern sections (Rub Al Khali Aquifer System (RAKAS)) are experiencing low groundwater depletion rates (eastern RAKAS: -1.8 +/- 1.4 mm/yr) to steady-state conditions (western RAKAS: -0.73 +/- 1.4 mm/yr). Geochemical, remote sensing, and field investigations over the RAKAS revealed: (1) the presence of west to east trending drainage networks and large-scale groundwater flow systems consistent with a meteoric source (precipitation over Red Sea Hills); (2) increasing Cl-36 model ages along groundwater flow directions (up to 970,000 years), indicating aquifer recharge in wet Pleistocene periods; (3) progressive depletion in the O and H stable isotopic compositions of aquifers with increasing distance from the Red Sea Hills basement outcrops, indicating modest recharge during prevailing dry conditions; and (4) the presence of relatively fresh (TDS: 800-2800 mg/L) and nonradioactive (Ra-226 + Ra-228 < 0.185 Bq/kg) water in western RAKAS. Findings suggest that sustainable agricultural development is achievable at current extraction rates in western RAKAS and provide a replicable and cost-effective model.

Fossil aquifers↗