Field Calibration Research Articles

Improving soil water storage with no‐till cover cropping in the Mississippi River Alluvial Basin

AbstractExcessive tillage reduces soil water storage and increases surface runoff. Cover crops can modify the effect of tillage on soil water dynamics, but limited information is available for the Mississippi River Alluvial Basin. This study was conducted to determine whether soil–water dynamics could be manipulated through conservation production systems affecting surface residue management. Effects of tillage (conventional tillage [CT] vs. no‐tillage [NT]) and cover cropping (no cover crop and Austrian pea [Pisum sativum L.] cover crop [CC]) on soil water balance during the CC season in sorghum (Sorghum bicolor L.) and cotton (Gossypium hirsutum L.) crops were modeled using the root zone water quality model for a site near Stoneville, MS, on “Commerce” silty‐loam soil. Capacitance sensors measured soil volumetric water content to 120 cm during CC growth in 2019 and 2020. Field calibration of sensors reduced root mean square error from 0.05 to 0.03 m3 m−3. Pooled across years, NT increased volumetric water content in the 0–40 and 40–120 soil layers by 8.5% and 6.8%, respectively, compared to CT. Regardless of the CC treatment and cropping system, NT reduced surface runoff by 24.5% over its conventional counterpart, while soil water storage increased from 2.35 to 5.23 cm within the 1.2‐m profile, resulting in a 17% increase in consumptive use of water (evapotranspiration). CC treatments did not impact soil water storage and consumptive water use. The results demonstrate that NT systems can affect water dynamics by increasing infiltration and soil water storage in the humid subtropical region of the United States.

Calibration of accelerometer and magnetometer sensors of MWD systems in directional drilling application

Measurement while drilling (MWD) tools include accelerometers, magnetometers and temperature sensors. The accuracy of these sensors are highly important in measuring inclination and Azimuth angle parameters in a directional well. These factors can increase costs when drilling a directional well. During the past years, many efforts have been made to increase the accuracy of these tools. Accuracy of accelerometer and magnetometer sensors are influenced by scale, bias and non-orthogonal errors. Considering that MWD systems work in a wide range of temperatures (for example 0 °C–150 °C), the temperature parameter should also be added to the factors affecting the errors. Here, after making a sample of MWD tool, a method to calibrate the tool using mathematical model based on total field calibration algorithm, least square method and the transfer matrix is presented. Calibrated parameters at ambient temperature are calculated with acceptable speed. Then, a method for calculating temperature coefficients in the desired range is provided. Compared to the case where temperature coefficients are not considered, the obtained results show a significantly increased accuracy of Inclination and Azimuth parameters through the use of these coefficients.

Determination of the neutron scattering contribution in a neutron calibration field based on MNSR

Recently, the idea of using the radiation field of the Isfahan MNSR neutron radiography beamline has been proposed for the calibration of neutron detectors and dosimeters. Examining the contribution of scattered neutrons in the neutron calibration field (NCF) is one of the key challenges in the calibration process. The aim of this study is determination and quantification the scattering contribution in the proposed NCF at the Isfahan MNSR based on Monte-Carlo calculation and experiments using the Semi-Empirical Method (SEM), Reduced-Fitting Method (RFM), and Generalized Fit Method (GFM). There is good agreement between the results, which shows that the characterization approach of the NCF is reliable. The maximum contribution of scattered neutrons with increasing distance up to 80 cm from the beamline outlet was obtained less than 14%, which meets the recommended range of ISO-8529.

Transferability Assessment of OBD-Related Calibration and Validation Activities from the Vehicle to HiL Applications

With the Euro 7 pollutant emission legislation currently under discussion, advanced and more efficient exhaust aftertreatment systems are being developed. The technologies required for these are leading to an increase in the number of components and control systems requiring diagnoses strategies under the on-board diagnostics (OBD) legislation. With concurrent shorter development times and significant reductions in budgets allocated to conventional powertrain development, challenges in the field of OBD calibration and verification are already rising sharply. In response to these challenges, hardware-in-the-loop (HiL) approaches have been successfully introduced to support and replace conventional development methods. The use of complex simulation models significantly improves the quality of calibrations while minimizing the number of required prototype vehicles and test resources, thus reducing development costs. This paper presents a feasibility study for moving OBD-related calibration and validation tasks from the vehicle to a HiL platform. In this context, the calibration and verification process of an active diagnostic for monitoring the condition of the three-way catalyst (TWC) and the oxygen sensors in the exhaust aftertreatment system is presented. It is shown that all relevant signals are simulated with sufficient accuracy to ensure a robust transfer from the vehicle to a HiL test bench. Special attention is given to the simulation of aged components and their influence on the emission behavior of the system. Furthermore, it is discussed that transferring OBD tasks from the vehicle to the HiL test bench could result in significant savings in development time and a reduction in the number of physical prototype vehicles and test resources required.

Design of Calibration System for Multi-Channel Thermostatic Metal Bath

Abstract The use of the thermostatic metal bath is becoming more and more extensive and the requirements for its precision and reliability are also increasing. To meet the needs of the metal bath calibration, a 12-channel thermostatic metal bath temperature field calibration system based on a four-wire PT100 has been designed. The system design includes a front-end temperature measurement component, which consists of a four-wire PT100 and a thermostatic block, and a signal processing component, which consists of a bidirectional constant current source excitation unit, a signal conditioning unit and a high-precision acquisition unit. The STM32f407 is used as the main control chip, and the analog channel selector is used for 12-channel selection. The constant current source is used for signal excitation, the proportional method is used to measure the PT100 resistance, and an acquisition circuit with a high-precision 32-bit ADS1263 analog-to-digital converter is used to amplify, filter and convert the analog signal. After piecewise linear fitting and system calibration, the temperature measurement accuracy can reach 0.4 mK, which meets the calibration requirements of the thermostatic metal bath.

Development of Heliostat Field Calibration Methods

In this work, three patent pending calibration methods for heliostat fields of central receiver systems (CRS) developed by the Solar-Institut Jülich (SIJ) of the FH Aachen University of Applied Sciences are presented. The calibration methods can either operate in a combined mode or in stand-alone mode. The first calibration method, method A, foresees that a camera matrix is placed into the receiver plane where it is subjected to concentrated solar irradiance during a measurement process. The second calibration method, method B, uses an unmanned aerial vehicle (UAV) such as a quadrocopter to automatically fly into the reflected solar irradiance cross-section of one or more heliostats (two variants of method B were tested). The third calibration method, method C, foresees a stereo central camera or multiple stereo cameras installed e.g. on the solar tower whereby the orientations of the heliostats are calculated from the location detection of spherical red markers attached to the heliostats. The most accurate method is method A which has a mean accuracy of 0.17 mrad. The mean accuracy of method B variant 1 is 1.36 mrad and of variant 2 is 1.73 mrad. Method C has a mean accuracy of 15.07 mrad. For method B there is great potential regarding improving the measurement accuracy. For method C the collected data was not sufficient for determining whether or not there is potential for improving the accuracy.

Uptake behavior of polycyclic aromatic compounds during field calibrations of the XAD-based passive air sampler across seasons and locations

Abstract. Polycyclic aromatic compounds (PACs) continue to demand attention due to their widespread presence and well-established health implications. Given that incomplete combustion is a major contributor to PACs and inhalation constitutes a crucial human exposure pathway, a comprehensive understanding of the concentrations, spatial distributions, and fates of a broad range of PACs in the atmosphere is important. Passive air samplers (PASs) are a commonly utilized technique for PAC sampling and monitoring. In this study, we present the results from two 1-year calibration experiments, one starting in summer and the other in winter, using a passive air sampler equipped with XAD resin as the sorbent (XAD-PAS). Throughout both experiments, PACs were consistently sorbed during the initial 6-month period. However, the sorbed amounts for many PACs exhibited a decrease after half a year of deployment. Three hypotheses to explain this phenomenon were explored, including the uptake of atmospheric particles, evaporation from the sorbent, and reactions with photo-oxidants. All had to be rejected based on the obtained data, additional laboratory experiments, and model results. Model simulations were further used to (i) confirm that a loss process must be invoked to explain the observed uptake behavior and (ii) estimate the kinetics of that loss process for different PACs. Sampling rates (SRs) for 28 PACs derived from the linearized uptake curves during the first 6 months of deployment were comparable to those of other semi-volatile organic compounds obtained during the same calibration experiment, and they also demonstrate a consistent negative correlation with volatility.

Digital Signal Compensation and Sounding Depth Analysis of Portable Frequency-Domain Electromagnetic Exploration System.

Low-resistivity objects produce eddy currents when excited with electromagnetic waves of a certain frequency and then generate an eddy electromagnetic field. A portable frequency-domain electromagnetic exploration system can be used to identify this eddy electromagnetic field, and then the low-resistivity objects can be positioned. At present, portable frequency-domain electromagnetic method (FEM) exploration systems use analog signal compensation, and the sounding depth is generally calculated using empirical formulas. In order to improve the rationality of signal compensation, this paper puts forward a digital signal compensation technology, including a device design, an information extraction method, and a primary field calibration method, and makes an exploration prototype based on the digital signal compensation technology. Using 10 nV as the minimum potential detection capability, the sounding depth of the portable FEM was analyzed, and it was found that when investigating a target with the same depth, a lower frequency required a larger emission current. If this could not be met, the sounding depth became smaller, and a phenomenon appeared in which the lower the operating frequency, the smaller the sounding depth. Through the detection of known underground garages, the apparent conductivity and normalized secondary field anomalies with higher sensitivity were obtained, which indicates that the detection system based on the digital signal compensation technology is effective in practical exploration. Via long-distance detection experiments on cars, it was confirmed that the sounding depth of the portable multi-frequency FEM in practical work indeed decreases with a decrease in the operating frequency.

Applying Density-Based Clustering for the Analysis of Emission Events in Real Driving Emissions Calibration

Further reducing greenhouse gas and pollutant emissions from road vehicles is a major task for the automotive industry. Stricter regulations regarding emissions and fleet fuel consumption require the continuous development of new powertrains and methods. In particular, the combination of hybrid powertrains on the technical side and the focus on real driving emissions (RDE) on the legislative side pose significant challenges to the vehicle calibration process. Against this background, new test methods and environments are being investigated to counteract the high number of interactions between hybrid drive systems and quasi-infinite test conditions due to RDE. Complementary to new test environments, innovative methods for data analysis are needed that allow the exploitation of the complete potential of measurement data. The application of such a method in the field of emission calibration is presented in this paper. For this purpose, a clustering method (HDBSCAN) is applied to critical sequences from emission tests. Within this presentation, the clustering process is based on a single signal only. This paper shows how signals of various characteristics can be processed with dynamic time warping and generically structured with the clustering method used. Here, 959 single events are automatically categorized into 24 clusters. This provides a new basis for system evaluation, enabling the automatic identification, categorization, and prioritization of calibration weaknesses. Using twelve signals of different characteristics, the generic usability of the clustering method is demonstrated.

Wobbling nature of gamma passing rate as a function of calibration field sizes in patient-specific quality assurance

Abstract Purpose: This study aimed to investigate the influence of calibration field size on the gamma passing rate (GPR) in patient-specific quality assurance (PSQA). Methods: Two independent detectors, PTW OCTAVIUS 4D (4DOCT) and Arc Check, were utilised in volumetric modulated arc therapy plans for 26 patients (14 with Arc Check and 12 with 4DOCT). Plans were administered using Varian Unique machine (with 4DOCT) and Varian TrueBeam (with Arc Check), each employing different calibration factors (CFs): 4 × 4, 6 × 6, 8 × 8, 10 × 10, 12 × 12 and 15 × 15 cm2 field sizes. Gamma analysis was conducted with 2%2mm, 2%3mm and 3%3mm gamma criteria. Results: GPR exhibited variations across different CFs. GPR demonstrated an increasing trend below 10 × 10 cm² CFs, while it displayed a decreasing trend above 10 × 10 cm². Both detectors exhibited similar GPR patterns. The correlation between 4DOCT and Arc Check was strong in tighter criteria (2%2mm) with an R² value of 0·9957, moderate criteria (2%3mm) with an R² value of 0·9868, but reduced in liberal criteria (3%3mm) with an R² value of 0·4226. Conclusion: This study demonstrates that calibration field sizes significantly influence GPR in PSQA. This study recommends the plan specific calibration field must obtain to calibrate the QA devices for modulated plans.

Design Method and Teeth Contact Simulation of PEEK Involute Spline Couplings.

In order to design an involute spline made of PEEK (polyetheretherketone)-based material with better performance and improve the design rules of involute splines, initially, an involute splines design theory for PEEK (polyetheretherketone)-based materials is presented, which combines international standards (ISO 4156, 1. 2. 3, 2005), American standards (ANSI B92.2M. 1989), and traditional empirical formulas. Second, using the involute splines calibration method in international standards as a guide, we developed the involute splines calibration method for PEEK-based materials by estimating the impact of energy consumption caused by viscoelasticity on temperature field calibration. Next, the contact characteristics of the designed spline were analyzed using ABAQUS2022 software to confirm the accuracy and reliability of the design and calibration methods. Finally, finite element simulation was used to analyze the influence of different pressure angles, moduli, combined lengths, and other parameters on the contact characteristics of the spline in order to realize the optimal design of PEEK-based material involute splines, to offer a theoretical foundation and improved design methodology for cylindrical straight-tooth involute splines.

A facile approach for estimating radio-frequency field strength of low-receptivity nuclei

Radio-frequency (RF) field calibration is essential in NMR spectroscopy. A common practice is to collect a nutation curve by varying the pulse length in a direct single-pulse excitation experiment or in a cross-polarization magic-angle spinning with a flip-back pulse experiment. From the null points on this curve, one can calculate the RF field strength. Nevertheless, the practical implementation is not always straightforward or can even be unrealizable, especially for low-receptivity nuclei owing to their associated low sensitivity. Several researchers used an approach that involves utilizing other nuclei with more sensitivity but nearly identical Larmor frequencies to that of the nucleus of interest. However, such an approach has not been a common practice so far. In this work, we have systematically revisited this approach using 3.2 mm rotors on different sets of nuclei covering a Larmor frequency range up to 80 MHz. The effect of solid- and solution-states on RF field strength measurements has been investigated. The detection of each set of nuclei is then carried out with a resonant circuit in the NMR probe consisting of identical coils and capacitors. Our methodology is illustrated by recording 135/137Ba NMR spectra of BaTiO3 without prior 135/137Ba RF field calibration.

Development and validation of a rapid multicompartment body composition model using 3-dimensional optical imaging and bioelectrical impedance analysis

Background & AimsThe multicompartment approach to body composition modeling provides a more precise quantification of body compartments in healthy and clinical populations. We sought to develop and validate a simplified and accessible multicompartment body composition model using 3-dimensional optical (3DO) imaging and bioelectrical impedance analysis (BIA). MethodsSamples of adults and collegiate-aged student-athletes were recruited for model calibration. For the criterion multicompartment model (Wang-5C), participants received measures of scale weight, body volume (BV) via air displacement, total body water (TBW) via deuterium dilution, and bone mineral content (BMC) via dual energy x-ray absorptiometry. The candidate model (3DO-5C) used stepwise linear regression to derive surrogate measures of BV using 3DO, TBW using BIA, and BMC using demographics. Test-retest precision of the candidate model was assessed via root mean square error (RMSE). The 3DO-5C model was compared to criterion via mean difference, concordance correlation coefficient (CCC), and Bland-Altman analysis. This model was then validated using a separate dataset of 20 adults. Results67 (31 female) participants were used to build the 3DO-5C model. Fat-free mass (FFM) estimates from Wang-5C (60.1 ± 13.4 kg) and 3DO-5C (60.3 ± 13.4 kg) showed no significant mean difference (-0.2 ± 2.0 kg; 95% limits of agreement [LOA] -4.3 to +3.8) and the CCC was 0.99 with a similar effect in fat mass that reflected the difference in FFM measures. In the validation dataset, the 3DO-5C model showed no significant mean difference (0.0 ± 2.5 kg; 95% LOA -3.6 to +3.7) for FFM with almost perfect equivalence (CCC = 0.99) compared to the criterion Wang-5C. Test-retest precision (RMSE = 0.73 kg FFM) supports the use of this model for more frequent testing in order to monitor body composition change over time. ConclusionsBody composition estimates provided by the 3DO-5C model are precise and accurate to criterion methods when correcting for field calibrations. The 3DO-5C approach offers a rapid, cost-effective, and accessible method of body composition assessment that can be used broadly to guide nutrition and exercise recommendations in athletic settings and clinical practice.

On-orbit geometric calibration and preliminary accuracy verification of GaoFen-14 (GF-14) optical two linear-array stereo camera

ABSTRACT The GaoFen-14 (GF-14) satellite is China’s most recent high-resolution earth observation satellite system. It is equipped with a two linear-array stereo camera and is intend for topographic mapping at 1:10,000-scale without ground control points (GCPs). The technical parameters of payloads will change once the satellite enters orbit. As a result, strict on-orbit geometric calibration is necessary. This study performs the on-orbit geometric calibration of the GF-14 stereo camera using ground calibration data. The exterior orientation errors are corrected by a comprehensive bias matrix, internal orientation errors are described by a fifth order polynomial. The results of Yinchuan calibration field show that the planar accuracy is better than 286 m (RMS) before calibration, and improved to 2.11 m (front camera) and 1.51 m (back camera) by external orientation, and further improved to 1.46 m (front camera) and 0.99 m (back camera) after internal calibration. The front intersection accuracy reaches 0.67 m in plane (RMS) and 1.10 m in elevation (RMS), respectively. Checking by multiple global check points (CKPs), the planar and elevation RMS reaches 2.38 m (5.09 m in CE90) and 2.08 m (3.43 m in LE90), respectively.

A DYNAMIC SPATIAL FILTERING APPROACH TO MITIGATE UNDERESTIMATION BIAS IN FIELD CALIBRATED LOW-COST SENSOR AIR POLLUTION DATA.

Low-cost air pollution sensors, offering hyper-local characterization of pollutant concentrations, are becoming increasingly prevalent in environmental and public health research. However, low-cost air pollution data can be noisy, biased by environmental conditions, and usually need to be field-calibrated by collocating low-cost sensors with reference-grade instruments. We show, theoretically and empirically, that the common procedure of regression-based calibration using collocated data systematically underestimates high air pollution concentrations, which are critical to diagnose from a health perspective. Current calibration practices also often fail to utilize the spatial correlation in pollutant concentrations. We propose a novel spatial filtering approach to collocation-based calibration of low-cost networks that mitigates the underestimation issue by using an inverse regression. The inverse-regression also allows for incorporating spatial correlations by a second-stage model for the true pollutant concentrations using a conditional Gaussian Process. Our approach works with one or more collocated sites in the network and is dynamic, leveraging spatial correlation with the latest available reference data. Through extensive simulations, we demonstrate how the spatial filtering substantially improves estimation of pollutant concentrations, and measures peak concentrations with greater accuracy. We apply the methodology for calibration of a low-cost PM2.5 network in Baltimore, Maryland, and diagnose air pollution peaks that are missed by the regression-calibration.

Evaluating Landsat-9 TIRS-2 calibrations and land surface temperature retrievals against ground measurements using multi-instrument spatial and temporal sampling along transects

High-resolution TIR data are essential for a wide range of studies, e.g., in environmental monitoring, urban effects, water stress, agricultural productivity, and land/water resources. Landsat series provides high-resolution TIR data, but data accuracy must be ensured to contribute to these fields. After the calibration problems of Landsat 8 (L8) TIRS due to a stray light effect, efforts were made in the design of Landsat 9 (L9) TIRS-2 to mitigate this effect. In any case, field calibration and validation activities are necessary to evaluate the accuracy of recently launched sensors. These activities require high-quality ground TIR radiance data that are representative at satellite spatial resolution and that quantify spatial–temporal fluctuations at the experimental sites concurrently to satellite overpasses. However, these requirements are not always accomplished in the literature.This paper provides vicarious calibrations of the L9 TIRS-2 data with accurate ground measurements acquired using multi-instrument spatial and temporal sampling in a rice paddy area from December 2021 to August 2023, in order to contribute to the calibration and validation of L9 TIRS-data.In March 1, 2023 L9 TIRS-2 scenes started to be reprocessed and calibration was updated. Both the original calibration and that after reprocessing were evaluated. Close results were obtained for band 10 (b10). When comparing satellite brightness temperatures and those determined from in situ LSTs, systematic differences of −0.3 K were shown, with root-mean-square differences (RMSDs) of 0.5 K. Results for band 11 showed a bias of −0.1 K for the original data and of 0.2 K after the reprocessing, with RMSDs of 0.6 K.The L2 LST product generated operationally from b10 data was also evaluated, together with alternative single-channel (SC) algorithms. A bias (RMSD) of 0.4 K (1.1 K) was obtained for the product. However, negative biases were shown both with the radiative transfer equation used on b10 radiances and the alternative SC algorithm.Finally, we validated six types of split-window (SW) algorithms applied to L9 TIRS-2 data before and after the reprocessing. A systematic difference of about −0.6 K between SW LST biases when using the reprocessed and original data was observed. In any case, for most of the algorithms with original and reprocessed data, LST biases and standard deviations were within the recommended threshold of 1 K, which proves the good performance of L9 TIRS-2 data to monitor LST at high spatial resolution.

Estimation of Reference Gamma Radiation Field for Calibration of Radiation Monitors

Estimation of Reference Gamma Radiation Field for Calibration of Radiation Monitors

Magnetic field regression using artificial neural networks for cold atom experiments

Accurately measuring magnetic fields is essential for magnetic-field sensitive experiments in areas like atomic, molecular, and optical physics, condensed matter experiments, and other areas. However, since many experiments are often conducted in an isolated environment that is inaccessible to experimentalists, it can be challenging to accurately determine the magnetic field at the target location. Here, we propose an efficient method for detecting magnetic fields with the assistance of an artificial neural network (NN). Instead of measuring the magnetic field directly at the desired location, we detect fields at several surrounding positions, and a trained NN can accurately predict the magnetic field at the target location. After training, we achieve a below 0.3% relative prediction error of magnetic field magnitude at the center of the vacuum chamber, and successfully apply this method to our erbium quantum gas apparatus for accurate calibration of magnetic field and long-term monitoring of environmental stray magnetic field. The demonstrated approach significantly simplifies the process of determining magnetic fields in isolated environments and can be applied to various research fields across a wide range of magnetic field magnitudes.

Accelerated 2D Cartesian MRI with an 8-channel local B0 coil array combined with parallel imaging.

In MRI, the magnetization of nuclear spins is spatially encoded with linear gradients and radiofrequency receiverssensitivity profiles to produce images, which inherently leads to a long scan time. Cartesian MRI, as widely adopted for clinical scans, can be accelerated with parallel imaging and rapid magnetic field modulation during signal readout. Here, by using an 8-channel local coil array, the modulation scheme optimized for sampling efficiency is investigated to speed up 2D Cartesian scans. An 8-channel local coil array is made to carry sinusoidal currents during signal readout to accelerate 2D Cartesian scans. An MRI sampling theory based on reproducing kernel Hilbert space is exploited to visualize the efficiency of nonlinear encoding in arbitrary sampling duration. A field calibration method using current monitors for local coils and the ESPIRiT algorithm is proposed to facilitate image reconstruction. Image acceleration with various modulation field shapes, aliasing control, and distinct modulation frequencies are scrutinized to find an optimized modulation scheme. A safety evaluation is conducted. In vivo 2D Cartesian scans are accelerated by the local coils. For 2D Cartesian MRI, the optimal modulation field by this local array converges to a nearly linear gradient field. With the field calibration technique, it accelerates the in vivo scans (i.e., proved safe) by threefold and eightfold free of visible artifacts, without and with SENSE, respectively. The nonlinear encoding analysis tool, the field calibration method, the safety evaluation procedures, and the in vivo reconstructed scans make significant steps to push MRI speed further with the local coil array.

HMS-REST v1.0: A plugin for the HEC-HMS model to provide RESTful services

Web technologies facilitating location-independent participation and broad knowledge sharing are critically important for open science and participative management and decision-making. Therefore, it is crucial to enable hydrological models to run in a web environment. In this study, a representational state transfer (REST) interface is proposed for the Hydrologic Engineering Center Hydrologic Modeling System (HEC-HMS) model. The web service interface (named HMS-REST) was built based on the Java API and Jython script system of HEC-HMS. HMS-REST allows users to retrieve and write model inputs and outputs and perform model execution. These functionalities were evaluated via a case study of pseudoensemble flood forecasting using a data set of six historical flood events from the Chuanchang watershed, southeastern China. Satisfactory performance was achieved in pseudoensemble flood forecasting in terms of the peak flow, total flood volume, peak flow timing and overall hydrograph fitting. This case study indicates that HMS-REST and HEC-HMS can be effectively integrated and demonstrates that the use of HEC-HMS with a web-based interface can facilitate pragmatic applications of the HEC-HMS model in the fields of model calibration, flood simulation and forecasting, and participatory decision-making.