Error Control of Iterative Linear Solvers for Integrated Groundwater Models

An open problem that arises when using modern iterative linear solvers, such as the preconditioned conjugate gradient method or Generalized Minimum RESidual (GMRES) method, is how to choose the residual tolerance in the linear solver to be consistent with the tolerance on the solution error. This problem is especially acute for integrated groundwater models, which are implicitly coupled to another model, such as surface water models, and resolve both multiple scales of flow and temporal interaction terms, giving rise to linear systems with variable scaling. This article uses the theory of “forward error bound estimation” to explain the correspondence between the residual error in the preconditioned linear system and the solution error. Using examples of linear systems from models developed by the US Geological Survey and the California State Department of Water Resources, we observe that this error bound guides the choice of a practical measure for controlling the error in linear systems. We implemented a preconditioned GMRES algorithm and benchmarked it against the Successive Over-Relaxation (SOR) method, the most widely known iterative solver for nonsymmetric coefficient matrices. With forward error control, GMRES can easily replace the SOR method in legacy groundwater modeling packages, resulting in the overall simulation speedups as large as 7.74×. This research is expected to broadly impact groundwater modelers through the demonstration of a practical and general approach for setting the residual tolerance in line with the solution error tolerance and presentation of GMRES performance benchmarking results

Passiflora incarnata attenuation of neuropathic allodynia and vulvodynia apropos GABA-ergic and opioidergic antinociceptive and behavioural mechanisms

Background: Passiflora incarnata is widely used as an anxiolytic and sedative due to its putative GABAergic properties. Passiflora incarnata L. methanolic extract (PI-ME) was evaluated in an animal model of streptozotocininduced diabetic neuropathic allodynia and vulvodynia in rats along with antinociceptive, anxiolytic and sedative activities in mice in order to examine possible underlying mechanisms. Methods: PI-ME was tested preliminary for qualitative phytochemical analysis and then quantitatively by proximate and GC-MS analysis. The antinociceptive property was evaluated using the abdominal constriction assay and hot plate test. The anxiolytic activity was performed in a stair case model and sedative activity in an open field test. The antagonistic activities were evaluated using naloxone and/or pentylenetetrazole (PTZ). PI-ME was evaluated for prospective anti-allodynic and anti-vulvodynic properties in a rat model of streptozotocin induced neuropathic pain using the static and dynamic testing paradigms of mechanical allodynia and vulvodynia. Results: GC-MS analysis revealed that PI-ME contained predominant quantities of oleamide (9-octadecenamide), palmitic acid (hexadecanoic acid) and 3-hydroxy-dodecanoic acid, among other active constituents. In the abdominal constriction assay and hot plate test, PI-ME produced dose dependant, naloxone and pentylenetetrazole reversible antinociception suggesting an involvement of opioidergic and GABAergic mechanisms. In the stair case test, PI-ME at 200 mg/kg increased the number of steps climbed while at 600 mg/kg a significant decrease was observed. The rearing incidence was diminished by PI-ME at all tested doses and in the open field test, PI-ME decreased locomotor activity to an extent that was analagous to diazepam. The effects of PI-ME were antagonized by PTZ in both the staircase and open field tests implicating GABAergic mechanisms in its anxiolytic and sedative activities. In the streptozotocin-induced neuropathic nociceptive model, PI-ME (200 and 300 mg/kg) exhibited static and dynamic anti-allodynic effects exemplified by an increase in paw withdrawal threshold and paw withdrawal latency. PI-ME relieved only the dynamic component of vulvodynia by increasing flinching response latency. Conclusions: These findings suggest that Passiflora incarnata might be useful for treating neuropathic pain. The antinociceptive and behavioural findings inferring that its activity may stem from underlying opioidergic and GABAergic mechanisms though a potential oleamide-sourced cannabimimetic involvement is also discussed

Drought resilience of the California Central Valley surface-groundwater-conveyance system

A series of drought simulations were performed for the California Central Valley using computer applications developed by the California Department of Water Resources and historical datasets representing a range of droughts from mild to severe for time periods lasting up to 60 years. Land use, agricultural cropping patterns, and water demand were held fixed at the 2003 level and water supply was decreased by amounts ranging between 25 and 50%, representing light to severe drought types. Impacts were examined for four hydrologic subbasins, the Sacramento Basin, the San Joaquin Basin, the Tulare Basin, and the Eastside Drainage. Results suggest the greatest impacts are in the San Joaquin and Tulare Basins, regions that are heavily irrigated and are presently overdrafted in most years. Regional surface water diversions decrease by as much as 70%. Stream-to-aquifer flows and aquifer storage declines were proportional to drought severity. Most significant was the decline in ground water head for the severe drought cases, where results suggest that under these scenarios the water table is unlikely to recover within the 30-year model-simulated future. However, the overall response to such droughts is not as severe as anticipated and the Sacramento Basin may act as ground-water insurance to sustain California during extended dry periods

Drought Analyses Of The California Central Valley Surface

A series of drought simulations were performed using the California Department of Water Resources codes and historical datasets representing a range of droughts from mild to severe for time periods lasting up to 60 years. Land use, agricultural cropping patterns, and water demand were held fixed at the 1973-2003 mean and water supply decreased by effective amounts ranging between 25 and 50 percent for the Central Valley, representing light to severe drought types. An examination of the impacts include four sub-basins, the Sacramento Basin, the San Joaquin Basin, the Tulare Basin, and the Eastside Drainage. Model output results suggest the greatest impacts are at the San Joaquin and Tulare Basins, regions that are heavily irrigated. Surface diversions decrease by as much as 42 percent in these regions. Stream-to-aquifer flows reversed and aquifer storage dropped. Most significant was the decline in groundwater head for the severe drought cases, where results suggest the water table is unlikely to recovery within the foreseeable future. However, the overall response to such droughts is not as severe as anticipated and the northern Central Valley may act as groundwater insurance to sustain California during extended dry periods

Groundwater Withdrawal Prediction Using Integrated Multitemporal Remote Sensing Data Sets and Machine Learning

Effective monitoring of groundwater withdrawals is necessary to help mitigate the negative impacts of aquifer depletion. In this study, we develop a holistic approach that combines water balance components with a machine learning model to estimate groundwater withdrawals. We use both multitemporal satellite and modeled data from sensors that measure different components of the water balance and land use at varying spatial and temporal resolutions. These remote sensing products include evapotranspiration, precipitation, and land cover. Due to the inherent complexity of integrating these data sets and subsequently relating them to groundwater withdrawals using physical models, we apply random forests -- a state of the art machine learning algorithm -- to overcome such limitations. Here, we predict groundwater withdrawals per unit area over a highly monitored portion of the High Plains aquifer in the central United States at 5 km resolution for the Years 2002-2019. Our modeled withdrawals had high accuracy on both training and testing data sets (R2 ≈ 0.99 and R2 ≈ 0.93, respectively) during leave-one-out (year) cross validation with low mean absolute error (MAE) ≈ 4.31 mm and root-mean-square error (RMSE) ≈ 13.50 mm for the year 2014. Moreover, we found that even for the extreme drought year of 2012, we have a satisfactory test score (R2 ≈ 0.84) with MAE ≈ 9.72 mm and RMSE ≈ 24.17 mm. Therefore, the proposed machine learning approach should be applicable to similar regions for proactive water management practices

T-type calcium channels contribute to colonic hypersensitivity in a rat model of irritable bowel syndrome

The symptoms of irritable bowel syndrome (IBS) include significant abdominal pain and bloating. Current treatments are empirical and often poorly efficacious, and there is a need for the development of new and efficient analgesics aimed at IBS patients. T-type calcium channels have previously been validated as a potential target to treat certain neuropathic pain pathologies. Here we report that T-type calcium channels encoded by the CaV3.2 isoform are expressed in colonic nociceptive primary afferent neurons and that they contribute to the exaggerated pain perception in a butyrate-mediated rodent model of IBS. Both the selective genetic inhibition of CaV3.2 channels and pharmacological blockade with calcium channel antagonists attenuates IBS-like painful symptoms. Mechanistically, butyrate acts to promote the increased insertion of CaV3.2 channels into primary sensory neuron membranes, likely via a posttranslational effect. The butyrate-mediated regulation can be recapitulated with recombinant CaV3.2 channels expressed in HEK cells and may provide a convenient in vitro screening system for the identification of T-type channel blockers relevant to visceral pain. These results implicate T-type calcium channels in the pathophysiology of chronic visceral pain and suggest CaV3.2 as a promising target for the development of efficient analgesics for the visceral discomfort and pain associated with IBS