The Sensitivity of US Wildfire Occurrence to Pre-Season Soil Moisture Conditions Across Ecosystems

It is generally accepted that year-to-year variability in moisture conditions and drought are linked with increased wildfire occurrence. However, quantifying the sensitivity of wildfire to surface moisture state at seasonal lead-times has been challenging due to the absence of a long soil moisture record with the appropriate coverage and spatial resolution for continental-scale analysis. Here we apply model simulations of surface soil moisture that numerically assimilate observations from NASA's Gravity Recovery and Climate Experiment (GRACE) mission with the US Forest Service"TM"s historical Fire-Occurrence Database over the contiguous United States. We quantify the relationships between pre-fire-season soil moisture and subsequent-year wildfire occurrence by land-cover type and produce annual probable wildfire occurrence and burned area maps at 0.25-degree resolution. Cross-validated results generally indicate a higher occurrence of smaller fires when months preceding fire season are wet, while larger fires are more frequent when soils are dry. This result is consistent with the concept of increased fuel accumulation under wet conditions in the pre-season. These results demonstrate the fundamental strength of the relationship between soil moisture and fire activity at long lead-times and are indicative of that relationship's utility for the future development of national-scale predictive capability

Parameter estimation of the fractional-order Hammerstein–Wiener model using simplified refined instrumental variable fractional-order continuous time

© 2017 The Authors. Published by IET. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.1049/iet-cta.2017.0284This study proposes a direct parameter estimation approach from observed input–output data of a stochastic single-input–single-output fractional-order continuous-time Hammerstein–Wiener model by extending a well known iterative simplified refined instrumental variable method. The method is an extension of the simplified refined instrumental variable method developed for the linear fractional-order continuous-time system, denoted. The advantage of this novel extension, compared with published methods, is that the static output non-linearity of the Wiener model part does not need to be invertible. The input and output static non-linear functions are represented by a sum of the known basis functions. The proposed approach estimates the parameters of the linear fractional-order continuous-time subsystem and the input and output static non-linear functions from the sampled input–output data by considering the system to be a multi-input–single-output linear fractional-order continuous-time model. These extra inputs represent the basis functions of the static input and output non-linearity, where the output basis functions are simulated according to the previous estimates of the fractional-order linear subsystem and the static input non-linear function at every iteration. It is also possible to estimate the classical integer-order model counterparts as a special case. Subsequently, the proposed extension to the simplified refined instrumental variable method is considered in the classical integer-order continuous-time Hammerstein–Wiener case. In this paper, a Monte Carlo simulation analysis is applied for demonstrating the performance of the proposed approach to estimate the parameters of a fractional-order Hammerstein–Wiener output model

Laser ion source for low charge heavy ion beams

For heavy ion inertial fusion application, a combination of a laser ion source and direct plasma injection scheme into an RFQ is proposed. The combination might provide more than 100 mA of singly charged heavy ion beam from a single laser shot. A planned feasibility test with moderate current is also discussed

Design of delayed fractional state variable filter for parameter estimation of fractional nonlinear models

This paper presents a novel direct parameter estimation method for continuous-time fractional nonlinear models. This is achieved by adapting a filter-based approach that uses the delayed fractional state variable filter for estimating the nonlinear model parameters directly from the measured sampled input–output data. A class of fractional nonlinear ordinary differential equation models is considered, where the nonlinear terms are linear with respect to the parameters. The nonlinear model equations are reformulated such that it allows a linear estimator to be used for estimating the model parameters. The required fractional time derivatives of measured input–output data are computed by a proposed delayed fractional state variable filter. The filter comprises of a cascade of all-pass filters and a fractional Butterworth filter, which forms the core part of the proposed parameter estimation method. The presented approaches for designing the fractional Butterworth filter are the so-called, square root base and compartmental fractional Butterworth design. According to the results, the parameters of the fractional-order nonlinear ordinary differential model converge to the true values and the estimator performs efficiently for the output error noise structure

Design and Performance of the Matching Beamline Between the Bnl Ebis and an Rfq.

A part of a new EBIS-based heavy ion preinjector, the low energy beam transport (LEBT) section between the high current EBIS and the RFQ is a challenging design, because it must serve many functions. In addition to the requirement to provide an efficient matching between the EBIS and the RFQ, this line must serve as a fast ''switchyard'', allowing singly charged ions from external sources to be transported into the EBIS trap region, and extracted, highly charged ions to be deflected to off-axis diagnostics (time-of-flight or emittance). The space charge of the 5-10 mA extracted heavy ion beam is a major consideration in the design, and the space charge force varies for different ion beams having Q/m from 1-0.16. The line includes electrostatic lenses, spherical and parallel-plate deflectors, magnetic solenoid, and diagnostics for measuring current, charge state distributions, emittance, and profile. A prototype of this beamline has been built, and results of tests are presented

Time of Day and its Association with Risk of Death and Chance of Discharge in Critically Ill Patients: A Retrospective Study.

Outcomes following admission to intensive care units (ICU) may vary with time and day. This study investigated associations between time of day and risk of ICU mortality and chance of ICU discharge in acute ICU admissions. Adult patients (age ≥ 18 years) who were admitted to ICUs participating in the Austrian intensive care database due to medical or surgical urgencies and emergencies between January 2012 and December 2016 were included in this retrospective study. Readmissions were excluded. Statistical analysis was conducted using the Fine-and-Gray proportional subdistribution hazards model concerning ICU mortality and ICU discharge within 30 days adjusted for SAPS 3 score. 110,628 admissions were analysed. ICU admission during late night and early morning was associated with increased hazards for ICU mortality; HR: 1.17; 95% CI: 1.08-1.28 for 00:00-03:59, HR: 1.16; 95% CI: 1.05-1.29 for 04:00-07:59. Risk of death in the ICU decreased over the day; lowest HR: 0.475, 95% CI: 0.432-0.522 for 00:00-03:59. Hazards for discharge from the ICU dropped sharply after 16:00; lowest HR: 0.024; 95% CI: 0.019-0.029 for 00:00-03:59. We conclude that there are "time effects" in ICUs. These findings may spark further quality improvement efforts

Trialling water treatment residuals in the remediation of former mine site soils: investigating improvements achieved for plants, earthworms and soil solution.

During clarification processes of raw water a vast amount of by-product known as drinking water treatment residuals (WTRs) are produced, being principally composed of hydroxides of the Al or Fe salts added during water treatment plus the impurities they remove. Aluminium-based (Al-WTR) and iron-based (Fe-WTR) materials were applied at 10% w/w to degraded, bare (un-vegetated) soils from a restored coal mining site in central England (pH <3.9) to study their potential amelioration effects on earthworm mortality, biomass yield of seedling plants and element concentrations in plant tissues, earthworm tissues and in soil solutions. A separate treatment with agricultural lime was also conducted for comparison to evaluate whether any observed improvements were attributable to the liming capacity of the WTRs. After completion of the trials all samples were subjected to a wet-dry cycle and the experiments were repeated (i.e. simulating longer-term effects in the field). Both types of WTRs significantly increased biomass of plants and, in some treatments, survival of earthworms was also enhanced compared to non-amended soils. Excess plant tissue element concentrations and element concentrations in soil solutions were reduced in amended soils. The implications are that adding WTRs to mining impacted soils is a potentially viable, sustainable and low cost remediation method that could be used globally to improve the soil condition. This article is protected by copyright. All rights reserved