{"id":61,"date":"2026-10-17T11:26:06","date_gmt":"2026-10-17T11:26:06","guid":{"rendered":"https:\/\/therisk.global\/systems-modelling\/?page_id=61"},"modified":"2026-10-17T11:26:06","modified_gmt":"2026-10-17T11:26:06","slug":"methods","status":"publish","type":"page","link":"https:\/\/therisk.global\/systems-modelling\/research\/methods\/","title":{"rendered":"Methods and uncertainty"},"content":{"rendered":"\n<!-- Nexus network page \u00b7 https:\/\/therisk.global\/systems-modelling\/research\/methods\/ \u00b7 source template \u00b7 generated by integrations\/wordpress\/network\/build.mjs, never edit this file --><script type=\"text\/x-nexus\" class=\"_iub_cs_skip\" id=\"nxe-fig-engine\" 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:where([role=\"tablist\"],[role=\"toolbar\"],[hidden],button,.nx-theme-toggle,.nx-live-slot){display:none}#nxe-n15cqr1j.nxe img{max-width:100%;height:auto}<\/style><svg class=\"nx-defs\" aria-hidden=\"true\" focusable=\"false\" width=\"0\" height=\"0\"><defs><linearGradient id=\"nx-gi\" x1=\"0\" y1=\"0\" x2=\"1\" y2=\"1\"><stop offset=\"0\" class=\"nx-gi-a\"\/><stop offset=\"0.55\" class=\"nx-gi-b\"\/><stop offset=\"1\" class=\"nx-gi-c\"\/><\/linearGradient><linearGradient id=\"nx-giu\" gradientUnits=\"userSpaceOnUse\" x1=\"0\" y1=\"0\" x2=\"800\" y2=\"0\"><stop offset=\"0\" class=\"nx-gi-a\"\/><stop offset=\"0.55\" class=\"nx-gi-b\"\/><stop offset=\"1\" class=\"nx-gi-c\"\/><\/linearGradient><linearGradient id=\"nx-gp\" x1=\"0\" y1=\"0\" x2=\"1\" y2=\"1\"><stop offset=\"0\" class=\"nx-gp-a\"\/><stop offset=\"1\" class=\"nx-gp-b\"\/><\/linearGradient><\/defs><\/svg><section class=\"nx-hero\" data-layout=\"split\" aria-labelledby=\"nx-title-1\"><div class=\"nx-container\"><div class=\"nx-theme-toggle\" role=\"group\" aria-label=\"Appearance of this page\" hidden><button type=\"button\" data-mode=\"light\" aria-pressed=\"false\">Light<\/button><button type=\"button\" data-mode=\"dark\" aria-pressed=\"false\">Dark<\/button><button type=\"button\" data-mode=\"auto\" aria-pressed=\"true\">Auto<\/button><\/div><div class=\"nx-folio\" aria-label=\"Document reference\"><strong>G-P19 \u00b7 EVIDENCE \u00b7 methods<\/strong>GCRI dossier \u00b7 service level R0<\/div><div class=\"nx-hero-grid\"><div class=\"nx-hero-text\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">GCRI<\/span><span class=\"nx-eyebrow\" aria-hidden=\"true\">\u00b7<\/span><span class=\"nx-eyebrow\">Systems Science and Modelling<\/span><span class=\"nx-eyebrow\" aria-hidden=\"true\">\u00b7<\/span><span class=\"nx-eyebrow\">In development<\/span><\/div><div class=\"nx-accent-row\"><span class=\"nx-accent-rule\" aria-hidden=\"true\"><\/span><span>Methods and uncertainty<\/span><\/div><h1 id=\"nx-title-1\" class=\"nx-hero-title\">Methods and uncertainty<\/h1><p class=\"nx-tagline\">The methods Systems Science and Modelling relies on, the assumptions they carry and the limits of what they can show.<\/p><div class=\"nx-actions\"><a class=\"nx-btn\" data-variant=\"primary\" href=\"https:\/\/therisk.global\/systems-modelling\/contact\/\">Make an enquiry <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a class=\"nx-btn\" data-variant=\"secondary\" href=\"https:\/\/therisk.global\/systems-modelling\/research\/\">Back to Research and evidence<\/a><\/div><dl class=\"nx-facts\"><div><dt class=\"nx-eyebrow\">Publisher<\/dt><dd>The Global Centre for Risk and Innovation<\/dd><\/div><div><dt class=\"nx-eyebrow\">Field<\/dt><dd>Methods and modelling, Risk management and systemic risk, Research and evidence<\/dd><\/div><div><dt class=\"nx-eyebrow\">Status<\/dt><dd>In development<\/dd><\/div><div><dt class=\"nx-eyebrow\">Service level<\/dt><dd>R0: information and enquiries<\/dd><\/div><\/dl><\/div><div data-lv-fill=\"console\" data-lv-id=\"workbench\"><div class=\"nx-window\"><div class=\"nx-window-bar\" aria-hidden=\"true\"><span class=\"nx-window-dots\"><span><\/span><span><\/span><span><\/span><\/span><span><strong>GCRI<\/strong> \u00b7 Systems Science and Modelling \u00b7 Evidence register<\/span><span class=\"nx-window-note\">Illustrative<\/span><\/div><div class=\"nx-figure-frame\" data-scene=\"true\"><figure class=\"nx-fk nx-cx\" data-fk=\"cx-systems-evidence-register\" data-cx=\"systems.evidence-register\" data-variant=\"hero\" aria-label=\"Evidence register: illustrative console with placeholder names and values\"><div class=\"nx-fk-head\"><div class=\"nx-fk-heading\"><h2 class=\"nx-fk-title\">Evidence register<\/h2><p class=\"nx-fk-sub\">Systems science \u00b7 Methods and uncertainty<\/p><\/div><\/div><div class=\"nx-cx-status\"><span class=\"nx-fk-pill\" data-state=\"info\"><i aria-hidden=\"true\"><\/i>Register current<\/span><span class=\"nx-cx-prod\">GCRI \u00b7 Systems Science and Modelling<\/span><\/div><div class=\"nx-cx-grid\"><div class=\"nx-fk-panel nx-cx-p\" data-w=\"4\" data-t=\"table\"><div class=\"nx-fk-panel-head\"><div><h4 class=\"nx-fk-panel-title\">Indicators<\/h4><p class=\"nx-fk-panel-sub\">unit \u00b7 cadence \u00b7 label<\/p><\/div><\/div><div class=\"nx-fk-tablewrap\" data-fk-view=\"table:cx-systems-evidence-register-t0\"><table class=\"nx-fk-table\" data-fk-table=\"cx-systems-evidence-register-t0\" aria-label=\"Indicators\"><thead><tr><th scope=\"col\" data-col=\"c0\" aria-sort=\"none\"><button type=\"button\" data-fk-sort=\"c0\">Indicator<\/button><\/th><th scope=\"col\" data-col=\"c1\" aria-sort=\"none\"><button type=\"button\" data-fk-sort=\"c1\">Unit<\/button><\/th><th scope=\"col\" data-col=\"c2\" aria-sort=\"none\"><button type=\"button\" data-fk-sort=\"c2\">Cadence<\/button><\/th><th scope=\"col\" data-col=\"c3\" aria-sort=\"none\"><button type=\"button\" data-fk-sort=\"c3\">Label<\/button><\/th><th scope=\"col\" data-col=\"c4\" aria-sort=\"none\"><button type=\"button\" data-fk-sort=\"c4\">Passport<\/button><\/th><\/tr><\/thead><tbody><tr data-fk-key=\"cx-systems-evidence-register:r0-0\" tabindex=\"0\" role=\"row\" aria-selected=\"false\"><td>Models in library<\/td><td>models<\/td><td>monthly<\/td><td><span class=\"nx-fk-pill\" data-state=\"info\"><i aria-hidden=\"true\"><\/i>OFFICIAL<\/span><\/td><td>SP-9504<\/td><\/tr><tr data-fk-key=\"cx-systems-evidence-register:r0-1\" tabindex=\"0\" role=\"row\" aria-selected=\"false\" aria-current=\"true\" data-cur=\"true\"><td>Models with validation record<\/td><td data-sv=\"0\"> of models<\/td><td>monthly<\/td><td><span class=\"nx-fk-pill\" data-state=\"info\"><i aria-hidden=\"true\"><\/i>DERIVED<\/span><\/td><td>SP-6894<\/td><\/tr><tr data-fk-key=\"cx-systems-evidence-register:r0-2\" tabindex=\"0\" role=\"row\" aria-selected=\"false\"><td>Coupled runs completed<\/td><td>runs<\/td><td>weekly<\/td><td><span class=\"nx-fk-pill\" data-state=\"info\"><i aria-hidden=\"true\"><\/i>OBSERVED<\/span><\/td><td>SP-0370<\/td><\/tr><tr data-fk-key=\"cx-systems-evidence-register:r0-3\" tabindex=\"0\" role=\"row\" aria-selected=\"false\"><td>Reuse across platforms<\/td><td>uses<\/td><td>quarterly<\/td><td><span class=\"nx-fk-pill\" data-state=\"info\"><i aria-hidden=\"true\"><\/i>DERIVED<\/span><\/td><td>SP-3045<\/td><\/tr><\/tbody><\/table><\/div><\/div><div class=\"nx-fk-panel nx-cx-p\" data-w=\"2\" data-t=\"kv\"><div class=\"nx-fk-panel-head\"><div><h4 class=\"nx-fk-panel-title\">Source passport<\/h4><\/div><\/div><dl class=\"nx-fk-dl\"><div><dt>Source<\/dt><dd>Model library<\/dd><\/div><div><dt>Licence<\/dt><dd>open \u00b7 attribution<\/dd><\/div><div><dt>Steward<\/dt><dd>Research partner<\/dd><\/div><div><dt>Coverage<\/dt><dd>94 pct of places<\/dd><\/div><div><dt>Known limits<\/dt><dd>sparse in uplands<\/dd><\/div><\/dl><\/div><div class=\"nx-fk-panel nx-cx-p\" data-w=\"6\" data-t=\"chart\"><div class=\"nx-fk-panel-head\"><div><h4 class=\"nx-fk-panel-title\">Coverage by place<\/h4><\/div><\/div><svg class=\"nx-fk-svg\" viewBox=\"0 0 520 210\" width=\"520\" height=\"210\" role=\"img\" focusable=\"false\" preserveAspectRatio=\"xMidYMid meet\" aria-label=\"Coverage by place\" data-fk-chart=\"cx-systems-evidence-register-c2\" data-nx-z=\"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\"><\/svg><\/div><\/div><div class=\"nx-fk-tip\" aria-hidden=\"true\" hidden><\/div><\/figure><\/div><\/div><p class=\"nx-caption\"><strong>Systems Science and Modelling \u00b7 Evidence register<\/strong><span>Evidence register, in outline: domain structure with placeholder names and illustrative values, not a record.<\/span><\/p><\/div><\/div><\/div><\/section> <nav class=\"nx-index-strip\" data-nx-spy=\"true\" aria-label=\"On this page\"><div class=\"nx-container\"><a href=\"#nx-sec-brief-answer\"><span>01<\/span>The short answer<\/a><a href=\"#nx-s-3-sec\"><span>02<\/span>Draft to published version<\/a><a href=\"#nx-sec-field\"><span>03<\/span>Hazards and exposure in North America<\/a><a href=\"#nx-sec-methods\"><span>04<\/span>The methods in use<\/a><a href=\"#nx-sec-pg-method-register\"><span>05<\/span>Each method, its role in this field\u2026<\/a><a href=\"#nx-sec-pg-uncertainty\"><span>06<\/span>Where uncertainty in systems\u2026<\/a><a href=\"#nx-sec-uncertainty\"><span>07<\/span>How uncertainty is reported<\/a><a href=\"#nx-sec-terms\"><span>08<\/span>Terms used on this page<\/a><\/div><\/nav> <section id=\"nx-sec-brief-answer\" class=\"nx-section\" data-hue=\"project\" data-variant=\"inset\" aria-labelledby=\"nx-s-2\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">01<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">In brief<\/span><\/div><h2 id=\"nx-s-2\" class=\"nx-section-title\">The short answer.<\/h2><p class=\"nx-lede\">The Systems Science and Modelling methods page sets out the methods the platform relies on, among them systems engineering, probability and statistics, and uncertainty quantification and model validation, with their assumptions, validation and limits. Each analysis lists its assumptions and data, reports ranges and confidence beside central estimates, is checked against observations or other models, and states what it cannot show.<\/p><\/div><\/div><\/section><div class=\"nx-live-slot\" data-nxf-slot=\"search\" data-nxf-kind=\"search\" data-nxf-resource=\"nexus:\/\/gcri\/G-P19\/research\/methods\/#search\" data-nxf-title=\"Search publications\" data-nxf-height=\"520\" hidden><\/div><section id=\"nx-s-3-sec\" class=\"nx-section\" data-hue=\"risk\" data-tone=\"alt\" aria-labelledby=\"nx-s-3\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">02<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Canvas<\/span><\/div><h2 id=\"nx-s-3\" class=\"nx-section-title\">Draft to published version.<\/h2><\/div><div class=\"nx-section-body\"><div class=\"nx-canvas-wrap\"><div class=\"nx-plate\" data-wide=\"true\"><div class=\"nx-plate-label\"><span class=\"nx-eyebrow\"><strong>Canvas<\/strong> \u00b7 draft to published version<\/span><span class=\"nx-eyebrow\">Design, not a record<\/span><\/div><div class=\"nx-figure-frame\" data-scene=\"true\"><svg class=\"nx-figure nx-ui nx-dag\" viewBox=\"0 0 1200 564\" data-nx-dag=\"true\" data-w=\"1200\" data-h=\"564\" role=\"img\" aria-labelledby=\"nx-dag-g-p19-research-methods-prisma-t nx-dag-g-p19-research-methods-prisma-d\" data-nx-z=\"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\"><title id=\"nx-dag-g-p19-research-methods-prisma-t\">Methods and uncertainty: systematic evidence synthesis<\/title><desc id=\"nx-dag-g-p19-research-methods-prisma-d\">A question is framed with its owner and a protocol registered; records are searched, screened and checked for eligibility by two reviewers; data are extracted, synthesised and graded for certainty before a brief is written. Design of the process, not a record of a run.<\/desc><\/svg><\/div><\/div><p class=\"nx-caption\"><strong>Fig.<\/strong><span>How a finding is reviewed before it is published. Design, not a record.<\/span><\/p><\/div><\/div><\/div><\/section><section id=\"nx-sec-field\" class=\"nx-section\" data-hue=\"project\" aria-labelledby=\"nx-s-4\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">03<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Geography<\/span><\/div><h2 id=\"nx-s-4\" class=\"nx-section-title\">Hazards and exposure in North America.<\/h2><p class=\"nx-lede\">For methods and uncertainty, in GCRI's spatial-intelligence reading, the map opens on true-colour imagery and land cover with relief in 3D and true colour from NASA GIBS, framed on North America; every other NASA layer, live feed and forecast waits in the layer list.<\/p><\/div><div class=\"nx-section-body\"><div class=\"nx-canvas-wrap\"><div class=\"nx-cmap-field\" data-nx-map=\"ctx-field\" data-cmap=\"north-america:risk\" data-ml-src=\"risk\" data-ml-plan=\"p-7ca00f4b\" data-ml-relief=\"1.3\"><div class=\"nx-wm\" data-nx-water=\"ctx-risk\" data-wm-domain=\"ctx-risk\" data-wm-tiles=\"on\" data-wm-flat=\"on\" data-wm-focus=\"-170,7,-52,72\" data-ws-live=\"off\" data-claim=\"INTEGRATED\" data-wm-panel=\"closed\" data-wm-mode=\"2d\"><div class=\"nx-wm-stage\" tabindex=\"0\" role=\"application\" aria-roledescription=\"interactive map\" aria-label=\"Hazards and exposure, North America: satellite and model layers from NASA on a 3D terrain of ASTER GDEM elevation. Arrow keys move; with Shift they turn and tilt in 3D; plus and minus zoom, 0 resets; I inspects, question mark lists the keys.\" aria-describedby=\"nx-wm-help\"><canvas class=\"nx-wm-canvas\" aria-hidden=\"true\"><\/canvas><p class=\"nx-wm-noscript\">The interactive map needs JavaScript; the layer list and sources are below.<\/p><div class=\"nx-wm-presets\" role=\"group\" aria-label=\"Quick views\"><button type=\"button\" class=\"nx-wm-preset\" data-wm-preset=\"true||||\" aria-pressed=\"false\">True colour<\/button><button type=\"button\" class=\"nx-wm-preset\" data-wm-preset=\"cover||||\" aria-pressed=\"false\">Land cover<\/button><button type=\"button\" class=\"nx-wm-preset\" data-wm-preset=\"flood||||\" aria-pressed=\"false\">Floods this week<\/button><button type=\"button\" class=\"nx-wm-preset\" data-wm-preset=\"ntl||||\" aria-pressed=\"false\">Night lights<\/button><\/div><div class=\"nx-wm-panel\" id=\"nx-wm-panel\" role=\"region\" aria-label=\"Map layers\"><div class=\"nx-wm-panel-head\"><p class=\"nx-wm-panel-title\">Layers <span class=\"nx-wm-count\">2<\/span><\/p><button type=\"button\" class=\"nx-wm-icon nx-wm-panel-close\" data-wm-act=\"panel\" aria-label=\"Close the layer list\"><svg viewBox=\"0 0 16 16\" aria-hidden=\"true\" focusable=\"false\"><path d=\"M3.5 3.5l9 9M12.5 3.5l-9 9\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/button><\/div><div class=\"nx-wm-panel-body\"><div class=\"nx-wm-group\"><p class=\"nx-wm-group-title\">Hazards and exposure, for this page<\/p><button type=\"button\" class=\"nx-wm-layer\" data-wm-toggle=\"true\" aria-pressed=\"true\" data-wm-z=\"20\" data-wm-lag=\"1\" data-wm-prov=\"NASA LANCE\" data-wm-kind=\"Satellite image\"><span class=\"nx-wm-check\" aria-hidden=\"true\"><\/span><span class=\"nx-wm-layer-text\"><span class=\"nx-wm-layer-name\">True colour<\/span><span class=\"nx-wm-layer-src\">NASA LANCE VIIRS NOAA-20 corrected reflectance \u00b7 <span data-wm-date=\"true\">13 Oct 2026<\/span><\/span><\/span><\/button><div class=\"nx-wm-tools\" data-wm-tools=\"true\" hidden><\/div><button type=\"button\" class=\"nx-wm-layer\" data-wm-toggle=\"cover\" aria-pressed=\"true\" data-wm-z=\"21\" data-wm-lag=\"0\" data-wm-time=\"latest\" data-wm-op=\"0.7\" data-wm-short=\"Land cover\" data-wm-prov=\"NASA LP DAAC\" data-wm-kind=\"Satellite classification; latest year GIBS publishes\"><span class=\"nx-wm-check\" aria-hidden=\"true\"><\/span><span class=\"nx-wm-layer-text\"><span class=\"nx-wm-layer-name\">Land cover type (IGBP), yearly<\/span><span class=\"nx-wm-layer-src\">NASA LP DAAC MODIS Terra and Aqua land cover (MCD12Q1) \u00b7 <span data-wm-date=\"cover\">2024<\/span><\/span><\/span><\/button><div class=\"nx-wm-tools\" data-wm-tools=\"cover\" hidden><\/div><button type=\"button\" class=\"nx-wm-layer\" data-wm-toggle=\"flood\" aria-pressed=\"false\" data-wm-z=\"22\" data-wm-lag=\"0\" data-wm-short=\"Flood water\" data-wm-prov=\"NASA LANCE\" data-wm-kind=\"Satellite detection; clouds leave gaps\"><span class=\"nx-wm-check\" aria-hidden=\"true\"><\/span><span class=\"nx-wm-layer-text\"><span class=\"nx-wm-layer-name\">Flood water, 3-day composite<\/span><span class=\"nx-wm-layer-src\">NASA LANCE VIIRS Global Flood Product \u00b7 <span data-wm-date=\"flood\">14 Oct 2026<\/span><\/span><\/span><\/button><div class=\"nx-wm-tools\" data-wm-tools=\"flood\" hidden><\/div><button type=\"button\" class=\"nx-wm-layer\" data-wm-toggle=\"ntl\" aria-pressed=\"false\" data-wm-z=\"23\" data-wm-lag=\"0\" data-wm-op=\"0.9\" data-wm-short=\"Night lights\" data-wm-prov=\"NASA LAADS DAAC\" data-wm-kind=\"Satellite radiance, corrected for moonlight and atmosphere\"><span class=\"nx-wm-check\" aria-hidden=\"true\"><\/span><span class=\"nx-wm-layer-text\"><span class=\"nx-wm-layer-name\">Night-time lights, daily<\/span><span class=\"nx-wm-layer-src\">NASA LAADS DAAC VIIRS Black Marble (VNP46A2) \u00b7 <span data-wm-date=\"ntl\">12 Oct 2026<\/span><\/span><\/span><\/button><div class=\"nx-wm-tools\" data-wm-tools=\"ntl\" hidden><\/div><button type=\"button\" class=\"nx-wm-layer\" data-wm-toggle=\"people\" aria-pressed=\"false\" data-wm-z=\"24\" data-wm-lag=\"0\" data-wm-op=\"0.8\" data-wm-short=\"Population density\" data-wm-prov=\"NASA SEDAC (CIESIN, Columbia University)\" data-wm-kind=\"Census-based estimate, static (2020)\"><span class=\"nx-wm-check\" aria-hidden=\"true\"><\/span><span class=\"nx-wm-layer-text\"><span class=\"nx-wm-layer-name\">Population density, 2020<\/span><span class=\"nx-wm-layer-src\">NASA SEDAC (CIESIN, Columbia University) Gridded Population of the World v4.11 \u00b7 <span data-wm-date=\"people\">static<\/span><\/span><\/span><\/button><div class=\"nx-wm-tools\" data-wm-tools=\"people\" hidden><\/div><button type=\"button\" class=\"nx-wm-layer\" data-wm-toggle=\"imerg\" aria-pressed=\"false\" data-wm-z=\"25\" data-wm-lag=\"0\" data-wm-short=\"Precipitation\" data-wm-prov=\"NASA GES DISC\" data-wm-kind=\"Satellite estimate, near real time\"><span class=\"nx-wm-check\" aria-hidden=\"true\"><\/span><span class=\"nx-wm-layer-text\"><span class=\"nx-wm-layer-name\">Precipitation rate, daily mean<\/span><span class=\"nx-wm-layer-src\">NASA GES DISC GPM IMERG \u00b7 <span data-wm-date=\"imerg\">12 Oct 2026<\/span><\/span><\/span><\/button><div class=\"nx-wm-tools\" data-wm-tools=\"imerg\" hidden><\/div><\/div><\/div><\/div><div class=\"nx-wm-rail\" role=\"toolbar\" aria-orientation=\"vertical\" aria-label=\"Map controls\"><button type=\"button\" class=\"nx-wm-icon nx-wm-open\" data-wm-act=\"panel\" aria-controls=\"nx-wm-panel\" aria-expanded=\"false\" aria-label=\"Layers\" title=\"Layers\"><svg viewBox=\"0 0 16 16\" aria-hidden=\"true\" focusable=\"false\"><path d=\"M8 2.5l-6.5 3.5 6.5 3.5 6.5-3.5zm-6.5 6.5 6.5 3.5 6.5-3.5m-13 2.8 6.5 3.5 6.5-3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/button><button type=\"button\" class=\"nx-wm-icon\" data-wm-act=\"tools\" aria-controls=\"nx-wm-menu\" aria-expanded=\"false\" aria-label=\"Expert tools\" title=\"Expert tools\"><svg viewBox=\"0 0 16 16\" aria-hidden=\"true\" focusable=\"false\"><path d=\"M3 4.5l10 0m-10 3.5 10 0m-10 3.5 10 0m-7.5-8.5 0 3m5 .5 0 3m-3.5.5 0 3\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/button><span class=\"nx-wm-sep\" aria-hidden=\"true\"><\/span><button type=\"button\" class=\"nx-wm-icon\" data-wm-act=\"in\" aria-label=\"Zoom in\" title=\"Zoom in\"><svg viewBox=\"0 0 16 16\" aria-hidden=\"true\" focusable=\"false\"><path d=\"M8 3v10M3 8h10\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/button><button type=\"button\" class=\"nx-wm-icon\" data-wm-act=\"out\" aria-label=\"Zoom out\" title=\"Zoom out\"><svg viewBox=\"0 0 16 16\" aria-hidden=\"true\" focusable=\"false\"><path d=\"M3 8h10\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/button><button type=\"button\" class=\"nx-wm-icon\" data-wm-act=\"reset\" aria-label=\"Reset the view\" title=\"Reset the view\"><svg viewBox=\"0 0 16 16\" aria-hidden=\"true\" focusable=\"false\"><path d=\"M3.2 8a4.8 4.8 0 1 0 1.5-3.5M3.2 2.6v2.6h2.6\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/button><button type=\"button\" class=\"nx-wm-icon\" data-wm-act=\"full\" aria-label=\"Full screen\" title=\"Full screen\"><svg viewBox=\"0 0 16 16\" aria-hidden=\"true\" focusable=\"false\"><path d=\"M2.5 6l0-3.5 3.5 0m7.5 3.5 0-3.5-3.5 0m-7.5 7.5 0 3.5 3.5 0m7.5-3.5 0 3.5-3.5 0\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/button><\/div><div class=\"nx-wm-menu\" id=\"nx-wm-menu\" role=\"menu\" aria-label=\"Expert tools\" hidden><button type=\"button\" class=\"nx-wm-menu-item\" role=\"menuitemcheckbox\" aria-checked=\"false\" data-wm-tool=\"inspect\">Inspect a point<kbd>I<\/kbd><\/button><button type=\"button\" class=\"nx-wm-menu-item\" role=\"menuitemcheckbox\" aria-checked=\"false\" data-wm-tool=\"measure\">Measure distance<kbd>M<\/kbd><\/button><button type=\"button\" class=\"nx-wm-menu-item\" role=\"menuitemcheckbox\" aria-checked=\"false\" data-wm-tool=\"compare\">Compare two dates<kbd>C<\/kbd><\/button><button type=\"button\" class=\"nx-wm-menu-item\" role=\"menuitem\" data-wm-tool=\"share\">Copy a link to this view<\/button><button type=\"button\" class=\"nx-wm-menu-item\" role=\"menuitem\" data-wm-tool=\"png\">Export as PNG with credits<\/button><button type=\"button\" class=\"nx-wm-menu-item\" role=\"menuitem\" data-wm-tool=\"xt\" data-wm-xt=\"6oPh6EhWj+gDMzpLLT8H\/wVfxJakWdyAB8snze2Nado=\">More expert tools<\/button><button type=\"button\" class=\"nx-wm-menu-item\" role=\"menuitem\" data-wm-tool=\"keys\">Keyboard shortcuts<kbd>?<\/kbd><\/button><\/div><div class=\"nx-wm-keys\" role=\"dialog\" aria-label=\"Keyboard shortcuts\" hidden><p class=\"nx-wm-keys-title\">Keyboard, with the map focused<\/p><dl class=\"nx-wm-keys-list\"><\/dl><button type=\"button\" class=\"nx-wm-icon nx-wm-keys-close\" data-wm-tool=\"keys\" aria-label=\"Close the shortcuts\"><svg viewBox=\"0 0 16 16\" aria-hidden=\"true\" focusable=\"false\"><path d=\"M3.5 3.5l9 9M12.5 3.5l-9 9\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/button><\/div><p class=\"nx-wm-hint\" hidden>Hold Ctrl or \u2318 and scroll to zoom<\/p><p class=\"nx-wm-toolbar\" role=\"status\" hidden><\/p><div class=\"nx-wm-tip\" role=\"tooltip\" hidden><\/div><div class=\"nx-wm-pin\" hidden><div class=\"nx-wm-pin-head\"><p class=\"nx-wm-pin-title\"><\/p><button type=\"button\" class=\"nx-wm-icon\" data-wm-act=\"unpin\" aria-label=\"Close the card\"><svg viewBox=\"0 0 16 16\" aria-hidden=\"true\" focusable=\"false\"><path d=\"M3.5 3.5l9 9M12.5 3.5l-9 9\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/button><\/div><div class=\"nx-wm-pin-chart\"><\/div><div class=\"nx-wm-pin-body\"><\/div><\/div><div class=\"nx-wm-dock\"><div class=\"nx-wm-time\" role=\"group\" aria-label=\"Imagery date\"><button type=\"button\" class=\"nx-wm-icon\" data-wm-step=\"prev\" aria-label=\"One day earlier\">\u2039<\/button><p class=\"nx-wm-time-label\">Latest available<\/p><button type=\"button\" class=\"nx-wm-icon\" data-wm-step=\"next\" aria-label=\"One day later\">\u203a<\/button><span class=\"nx-wm-track\" role=\"slider\" tabindex=\"0\" aria-label=\"Imagery date, up to 30 days back\"><\/span><button type=\"button\" class=\"nx-wm-latest\" data-wm-step=\"latest\" aria-pressed=\"true\">Latest<\/button><\/div><div class=\"nx-wm-chips\" role=\"group\" aria-label=\"Legends\"><\/div><p class=\"nx-wm-attrib\">NASA GIBS \/ EOSDIS \u00b7 ASTER GDEM (METI, NASA) \u00b7 Blue Marble (NASA) \u00b7 \u00a9 OpenStreetMap contributors (ODbL) \u00b7 Natural Earth<\/p><div class=\"nx-wm-legends\" aria-live=\"polite\" hidden><\/div><\/div><\/div><div class=\"nx-container nx-wm-below\"><p class=\"nx-wm-status\" role=\"status\">Loading the latest NASA imagery.<\/p><p id=\"nx-wm-help\" class=\"nx-wm-help\">Drag to move. Ctrl or \u2318 and scroll, pinch or the buttons to zoom; hover for the values under the pointer; reset returns to the region.<\/p><p class=\"nx-caption\"><span>For methods and uncertainty, in GCRI's spatial-intelligence reading, the map opens on true-colour imagery and land cover with relief in 3D and true colour from NASA GIBS, framed on North America; every other NASA layer, live feed and forecast waits in the layer list.<\/span><span data-honesty=\"true\">Satellite and model products as NASA publishes them, each with its own date; indicators, not assessments of any place; claim ceiling INTEGRATED.<\/span><\/p><details class=\"nx-wm-credits\"><summary><span class=\"nx-wm-credits-line\">Data: NASA GIBS \u00b7 ASTER GDEM \u00b7 Blue Marble \u00b7 \u00a9 OpenStreetMap contributors \u00b7 Natural Earth \u00b7 Copernicus Sentinel-2 L2A \u00b7 NASA HLS S30<\/span><span class=\"nx-wm-credits-more\">Sources and licences<\/span><\/summary><p class=\"nx-wm-credit\"><ul class=\"nx-wm-credit-list\"><li data-wm-credit=\"nasa.gibs.field-layers\">We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). <a class=\"nx-link\" href=\"https:\/\/www.earthdata.nasa.gov\/engage\/open-data-services-software-policies\" rel=\"noopener\" target=\"_blank\">NASA open data<\/a><\/li><li data-wm-credit=\"nasa.gibs.water-layers\">We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). <a class=\"nx-link\" href=\"https:\/\/www.earthdata.nasa.gov\/engage\/open-data-services-software-policies\" rel=\"noopener\" target=\"_blank\">NASA open data<\/a><\/li><li data-wm-credit=\"nasa.lance.viirs-water\">VIIRS near-real-time products (flood, land surface temperature, snow cover, corrected reflectance), NASA LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). <a class=\"nx-link\" href=\"https:\/\/www.earthdata.nasa.gov\/engage\/open-data-services-software-policies\" rel=\"noopener\" target=\"_blank\">NASA open data<\/a><\/li><li data-wm-credit=\"nasa.modis-viirs.land\">MODIS land products (vegetation indices, gross primary production, land cover), NASA LP DAAC and LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). <a class=\"nx-link\" href=\"https:\/\/www.earthdata.nasa.gov\/engage\/open-data-services-software-policies\" rel=\"noopener\" target=\"_blank\">NASA open data<\/a><\/li><li data-wm-credit=\"nasa.laads.black-marble\">VIIRS Black Marble night-time lights, NASA Goddard Space Flight Center; distributed by the NASA Level-1 and Atmosphere Archive and Distribution System (LAADS DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). <a class=\"nx-link\" href=\"https:\/\/www.earthdata.nasa.gov\/engage\/open-data-services-software-policies\" rel=\"noopener\" target=\"_blank\">NASA open data<\/a><\/li><li data-wm-credit=\"sedac.gpw-v4\">Center for International Earth Science Information Network (CIESIN), Columbia University. 2018. Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 11. NASA Socioeconomic Data and Applications Center (SEDAC). Licensed under CC BY 4.0. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). <a class=\"nx-link\" href=\"https:\/\/creativecommons.org\/licenses\/by\/4.0\/\" rel=\"noopener\" target=\"_blank\">CC BY 4.0<\/a><\/li><li data-wm-credit=\"nasa.gpm.imerg\">GPM IMERG precipitation, NASA Precipitation Processing System; distributed by the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). <a class=\"nx-link\" href=\"https:\/\/www.earthdata.nasa.gov\/engage\/open-data-services-software-policies\" rel=\"noopener\" target=\"_blank\">NASA open data<\/a><\/li><li data-wm-credit=\"nasa-meti.aster-gdem-v3\">ASTER GDEM is a product of METI and NASA (ASTER Global Digital Elevation Model V003, NASA LP DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). <a class=\"nx-link\" href=\"https:\/\/www.earthdata.nasa.gov\/engage\/open-data-services-software-policies\" rel=\"noopener\" target=\"_blank\">NASA open data<\/a><\/li><li data-wm-credit=\"naturalearth.all-scales\">Made with Natural Earth. Free vector and raster map data @ naturalearthdata.com. <a class=\"nx-link\" href=\"https:\/\/www.naturalearthdata.com\/about\/terms-of-use\/\" rel=\"noopener\" target=\"_blank\">Public domain<\/a><\/li><li data-wm-credit=\"nasa.gibs.reference-osm\">\u00a9 OpenStreetMap contributors (ODbL), via NASA GIBS (coastlines, boundaries, roads and place names). Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). <a class=\"nx-link\" href=\"https:\/\/www.openstreetmap.org\/copyright\" rel=\"noopener\" target=\"_blank\">ODbL<\/a><\/li><li data-wm-credit=\"nasa.earth-observatory.blue-marble\">Blue Marble, NASA Earth Observatory; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). <a class=\"nx-link\" href=\"https:\/\/www.earthdata.nasa.gov\/engage\/open-data-services-software-policies\" rel=\"noopener\" target=\"_blank\">NASA open data<\/a><\/li><li>Context on the globe and flat map: coastlines, boundaries, roads and place names from NASA GIBS reference layers (OpenStreetMap data, ODbL, \u00a9 OpenStreetMap contributors); Blue Marble imagery as an optional base; 3D terrain and the elevation read-out from the ASTER GDEM elevation colour index (5 m to 200 m classes, exaggerated for legibility). Boundaries are drawn as published and imply no position on any territory.<\/li><li>Globe: MapLibre GL JS 6.9.1, BSD-3-Clause, \u00a9 MapLibre contributors.<\/li><li>Observed (EO): Copernicus Sentinel-2 L2A (contains modified Copernicus Sentinel data 2026), Microsoft Planetary Computer<\/li><li>Observed (EO): NASA HLS S30 (contains modified Copernicus Sentinel data 2026). We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS).<\/li><li>Optional layers (35 sources in the layer list: live, forecast, observed and context) print their provider credit on the map and here when switched on; forecasts are model output and derived indices are estimates.<\/li><\/ul><p class=\"nx-wm-credit\"><strong>Layers and dates<\/strong><\/p><ul class=\"nx-wm-credit-list\"><li>True colour: VIIRS NOAA-20 corrected reflectance, NASA LANCE \u00b7 <span data-wm-date=\"true\">13 Oct 2026<\/span><\/li><li>Land cover type (IGBP), yearly: MODIS Terra and Aqua land cover (MCD12Q1), NASA LP DAAC \u00b7 <span data-wm-date=\"cover\">2024<\/span><\/li><li>Flood water, 3-day composite: VIIRS Global Flood Product, NASA LANCE \u00b7 <span data-wm-date=\"flood\">14 Oct 2026<\/span><\/li><li>Night-time lights, daily: VIIRS Black Marble (VNP46A2), NASA LAADS DAAC \u00b7 <span data-wm-date=\"ntl\">12 Oct 2026<\/span><\/li><li>Population density, 2020: Population: CIESIN, Columbia University, Gridded Population of the World v4.11 (2018), NASA SEDAC, CC BY 4.0 \u00b7 <span data-wm-date=\"people\">static<\/span><\/li><li>Precipitation rate, daily mean: GPM IMERG, NASA GES DISC \u00b7 <span data-wm-date=\"imerg\">12 Oct 2026<\/span><\/li><\/ul><\/p><\/details><\/div><\/div><div class=\"nx-live-slot nx-live-slot--map\" data-nxf-slot=\"map\" data-nxf-kind=\"map\" data-nxf-resource=\"nexus:\/\/gcri\/G-P19\/research\/methods\/#map\" data-nxf-title=\"Systems Science and Modelling live map\" data-nxf-height=\"560\" hidden><\/div><\/div><\/div><\/div><\/div><\/section><section id=\"nx-sec-methods\" class=\"nx-section\" data-hue=\"risk\" data-tone=\"alt\" aria-labelledby=\"nx-s-5\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">04<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Methods<\/span><\/div><h2 id=\"nx-s-5\" class=\"nx-section-title\">The methods in use.<\/h2><\/div><div class=\"nx-section-body\"><div class=\"nx-methods\"><ol class=\"nx-mledger\" aria-label=\"Methods\"><li><a class=\"nx-mledger-main\" href=\"https:\/\/therisk.global\/systems-modelling\/stem\/systems-engineering\/\"><span class=\"nx-mledger-n\" aria-hidden=\"true\">01<\/span><span class=\"nx-mledger-body\"><span class=\"nx-mledger-name\">Systems engineering<\/span><span class=\"nx-mledger-role\">Requirements for decision models \u00b7 Interface control for coupled models<\/span><\/span><span class=\"nx-mledger-go\"><span class=\"nx-mledger-go-label\">Applied here<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/span><\/a><div class=\"nx-mledger-aside\"><a class=\"nx-mledger-canon\" href=\"https:\/\/therisk.global\/stem\/engineering\/systems-engineering\/\" aria-label=\"Systems engineering: canonical page on the STEM Commons\">Canonical \u00b7 STEM Commons <span aria-hidden=\"true\">\u2197<\/span><\/a><\/div><\/li><li><a class=\"nx-mledger-main\" href=\"https:\/\/therisk.global\/systems-modelling\/stem\/probability-statistics\/\"><span class=\"nx-mledger-n\" aria-hidden=\"true\">02<\/span><span class=\"nx-mledger-body\"><span class=\"nx-mledger-name\">Probability and statistics<\/span><span class=\"nx-mledger-role\">Bayesian calibration \u00b7 Proper scoring of predictions \u00b7 Ensemble statistics<\/span><\/span><span class=\"nx-mledger-go\"><span class=\"nx-mledger-go-label\">Applied here<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/span><\/a><div class=\"nx-mledger-aside\"><a class=\"nx-mledger-canon\" href=\"https:\/\/therisk.global\/stem\/mathematics\/probability-statistics\/\" aria-label=\"Probability and statistics: canonical page on the STEM Commons\">Canonical \u00b7 STEM Commons <span aria-hidden=\"true\">\u2197<\/span><\/a><\/div><\/li><li><a class=\"nx-mledger-main\" href=\"https:\/\/therisk.global\/systems-modelling\/stem\/uncertainty-quantification\/\"><span class=\"nx-mledger-n\" aria-hidden=\"true\">03<\/span><span class=\"nx-mledger-body\"><span class=\"nx-mledger-name\">Uncertainty quantification and model validation<\/span><span class=\"nx-mledger-role\">Uncertainty budgets \u00b7 Surrogate models for expensive simulations \u00b7 Credibility assessment<\/span><\/span><span class=\"nx-mledger-go\"><span class=\"nx-mledger-go-label\">Applied here<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/span><\/a><div class=\"nx-mledger-aside\"><a class=\"nx-mledger-canon\" href=\"https:\/\/therisk.global\/stem\/mathematics\/uncertainty-quantification\/\" aria-label=\"Uncertainty quantification and model validation: canonical page on the STEM Commons\">Canonical \u00b7 STEM Commons <span aria-hidden=\"true\">\u2197<\/span><\/a><\/div><\/li><li><a class=\"nx-mledger-main\" href=\"https:\/\/therisk.global\/systems-modelling\/stem\/network-science\/\"><span class=\"nx-mledger-n\" aria-hidden=\"true\">04<\/span><span class=\"nx-mledger-body\"><span class=\"nx-mledger-name\">Network science and contagion<\/span><span class=\"nx-mledger-role\">Common network representations \u00b7 Contagion model comparison \u00b7 Multilayer analysis<\/span><\/span><span class=\"nx-mledger-go\"><span class=\"nx-mledger-go-label\">Applied here<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/span><\/a><div class=\"nx-mledger-aside\"><a class=\"nx-mledger-canon\" href=\"https:\/\/therisk.global\/stem\/mathematics\/network-science\/\" aria-label=\"Network science and contagion: canonical page on the STEM Commons\">Canonical \u00b7 STEM Commons <span aria-hidden=\"true\">\u2197<\/span><\/a><\/div><\/li><li><a class=\"nx-mledger-main\" href=\"https:\/\/therisk.global\/systems-modelling\/stem\/complex-systems\/\"><span class=\"nx-mledger-n\" aria-hidden=\"true\">05<\/span><span class=\"nx-mledger-body\"><span class=\"nx-mledger-name\">Complex systems and agent-based modelling<\/span><span class=\"nx-mledger-role\">Agent-based model standards \u00b7 Feedback and tipping point analysis \u00b7 Early warning indicators<\/span><\/span><span class=\"nx-mledger-go\"><span class=\"nx-mledger-go-label\">Applied here<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/span><\/a><div class=\"nx-mledger-aside\"><a class=\"nx-mledger-canon\" href=\"https:\/\/therisk.global\/stem\/mathematics\/complex-systems\/\" aria-label=\"Complex systems and agent-based modelling: canonical page on the STEM Commons\">Canonical \u00b7 STEM Commons <span aria-hidden=\"true\">\u2197<\/span><\/a><\/div><\/li><li><a class=\"nx-mledger-main\" href=\"https:\/\/therisk.global\/systems-modelling\/stem\/optimization\/\"><span class=\"nx-mledger-n\" aria-hidden=\"true\">06<\/span><span class=\"nx-mledger-body\"><span class=\"nx-mledger-name\">Optimization and operations research<\/span><span class=\"nx-mledger-role\">Problem formulation guidance \u00b7 Robust and stochastic comparisons \u00b7 Solver benchmarking<\/span><\/span><span class=\"nx-mledger-go\"><span class=\"nx-mledger-go-label\">Applied here<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/span><\/a><div class=\"nx-mledger-aside\"><a class=\"nx-mledger-canon\" href=\"https:\/\/therisk.global\/stem\/mathematics\/optimization\/\" aria-label=\"Optimization and operations research: canonical page on the STEM Commons\">Canonical \u00b7 STEM Commons <span aria-hidden=\"true\">\u2197<\/span><\/a><\/div><\/li><li><a class=\"nx-mledger-main\" href=\"https:\/\/therisk.global\/systems-modelling\/stem\/decision-analysis\/\"><span class=\"nx-mledger-n\" aria-hidden=\"true\">07<\/span><span class=\"nx-mledger-body\"><span class=\"nx-mledger-name\">Decision analysis under uncertainty<\/span><span class=\"nx-mledger-role\">Framing the decision before the model \u00b7 Value of information for models<\/span><\/span><span class=\"nx-mledger-go\"><span class=\"nx-mledger-go-label\">Applied here<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/span><\/a><div class=\"nx-mledger-aside\"><a class=\"nx-mledger-canon\" href=\"https:\/\/therisk.global\/stem\/mathematics\/decision-analysis\/\" aria-label=\"Decision analysis under uncertainty: canonical page on the STEM Commons\">Canonical \u00b7 STEM Commons <span aria-hidden=\"true\">\u2197<\/span><\/a><\/div><\/li><li><a class=\"nx-mledger-main\" href=\"https:\/\/therisk.global\/systems-modelling\/stem\/computing\/\"><span class=\"nx-mledger-n\" aria-hidden=\"true\">08<\/span><span class=\"nx-mledger-body\"><span class=\"nx-mledger-name\">High-performance, cloud and edge computing<\/span><span class=\"nx-mledger-role\">Ensemble design within budgets \u00b7 Workflow orchestration \u00b7 Reproducible environments<\/span><\/span><span class=\"nx-mledger-go\"><span class=\"nx-mledger-go-label\">Applied here<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/span><\/a><div class=\"nx-mledger-aside\"><a class=\"nx-mledger-canon\" href=\"https:\/\/therisk.global\/stem\/technology\/computing\/\" aria-label=\"High-performance, cloud and edge computing: canonical page on the STEM Commons\">Canonical \u00b7 STEM Commons <span aria-hidden=\"true\">\u2197<\/span><\/a><\/div><\/li><\/ol><\/div><\/div><\/div><\/section><div class=\"nx-live-slot\" data-nxf-slot=\"evidence\" data-nxf-kind=\"evidence\" data-nxf-resource=\"nexus:\/\/gcri\/G-P19\/research\/methods\/#evidence\" data-nxf-title=\"Evidence records\" data-nxf-height=\"520\" hidden><\/div><section id=\"nx-sec-pg-method-register\" class=\"nx-section\" data-hue=\"project\" data-variant=\"split\" aria-labelledby=\"nx-s-6\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">05<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Method register<\/span><\/div><h2 id=\"nx-s-6\" class=\"nx-section-title\">Each method, its role in this field and how it is checked.<\/h2><\/div><div class=\"nx-section-body\"><div class=\"nx-table-wrap\"><ul class=\"nx-dir\" data-cols=\"3\" aria-label=\"Method\"><li><a class=\"nx-dir-row\" href=\"https:\/\/therisk.global\/systems-modelling\/stem\/systems-engineering\/\"><span class=\"nx-dir-name\">Systems engineering<\/span><span class=\"nx-dir-fact\"><span class=\"nx-dir-k\">Role here<\/span><span class=\"nx-dir-v\">Systems engineering is the method this platform stewards for the network.<\/span><\/span><span class=\"nx-dir-fact\"><span class=\"nx-dir-k\">Checks applied<\/span><span class=\"nx-dir-v\">Requirements traceability; Interface review; Change impact analysis<\/span><\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/li><li><a class=\"nx-dir-row\" href=\"https:\/\/therisk.global\/systems-modelling\/stem\/probability-statistics\/\"><span class=\"nx-dir-name\">Probability statistics<\/span><span class=\"nx-dir-fact\"><span class=\"nx-dir-k\">Role here<\/span><span class=\"nx-dir-v\">Probability and statistics are the language of uncertainty in modelling.<\/span><\/span><span class=\"nx-dir-fact\"><span class=\"nx-dir-k\">Checks applied<\/span><span class=\"nx-dir-v\">Posterior predictive checks; Prior sensitivity; Scoring on held-out data<\/span><\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/li><li><a class=\"nx-dir-row\" href=\"https:\/\/therisk.global\/systems-modelling\/stem\/uncertainty-quantification\/\"><span class=\"nx-dir-name\">Uncertainty quantification<\/span><span class=\"nx-dir-fact\"><span class=\"nx-dir-k\">Role here<\/span><span class=\"nx-dir-v\">Uncertainty quantification and model validation is a method this platform stewards.<\/span><\/span><span class=\"nx-dir-fact\"><span class=\"nx-dir-k\">Checks applied<\/span><span class=\"nx-dir-v\">Emulator validation; Interval coverage; Structural comparison<\/span><\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/li><li><a class=\"nx-dir-row\" href=\"https:\/\/therisk.global\/systems-modelling\/stem\/network-science\/\"><span class=\"nx-dir-name\">Network science<\/span><span class=\"nx-dir-fact\"><span class=\"nx-dir-k\">Role here<\/span><span class=\"nx-dir-v\">Network science and contagion is a method this platform stewards for the network.<\/span><\/span><span class=\"nx-dir-fact\"><span class=\"nx-dir-k\">Checks applied<\/span><span class=\"nx-dir-v\">Missing link sensitivity; Model comparison; Event validation<\/span><\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/li><li><a class=\"nx-dir-row\" href=\"https:\/\/therisk.global\/systems-modelling\/stem\/complex-systems\/\"><span class=\"nx-dir-name\">Complex systems<\/span><span class=\"nx-dir-fact\"><span class=\"nx-dir-k\">Role here<\/span><span class=\"nx-dir-v\">Complex systems and agent-based modelling is a method this platform stewards.<\/span><\/span><span class=\"nx-dir-fact\"><span class=\"nx-dir-k\">Checks applied<\/span><span class=\"nx-dir-v\">Pattern-oriented validation; Robustness of tipping points; False alarm assessment<\/span><\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/li><li><a class=\"nx-dir-row\" href=\"https:\/\/therisk.global\/systems-modelling\/stem\/optimization\/\"><span class=\"nx-dir-name\">Optimization<\/span><span class=\"nx-dir-fact\"><span class=\"nx-dir-k\">Role here<\/span><span class=\"nx-dir-v\">Optimization and operations research is a method this platform stewards.<\/span><\/span><span class=\"nx-dir-fact\"><span class=\"nx-dir-k\">Checks applied<\/span><span class=\"nx-dir-v\">Formulation review; Solution verification; Out-of-sample testing<\/span><\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/li><li><a class=\"nx-dir-row\" href=\"https:\/\/therisk.global\/systems-modelling\/stem\/decision-analysis\/\"><span class=\"nx-dir-name\">Decision analysis<\/span><span class=\"nx-dir-fact\"><span class=\"nx-dir-k\">Role here<\/span><span class=\"nx-dir-v\">Decision analysis under uncertainty connects models to choices.<\/span><\/span><span class=\"nx-dir-fact\"><span class=\"nx-dir-k\">Checks applied<\/span><span class=\"nx-dir-v\">Decision relevance review; Sensitivity of choice; Communication testing<\/span><\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/li><li><a class=\"nx-dir-row\" href=\"https:\/\/therisk.global\/systems-modelling\/stem\/computing\/\"><span class=\"nx-dir-name\">Computing<\/span><span class=\"nx-dir-fact\"><span class=\"nx-dir-k\">Role here<\/span><span class=\"nx-dir-v\">High-performance, cloud and edge computing determine which models can be run, how many ensemble members and scenarios are feasible, and whether results can be reproduced.<\/span><\/span><span class=\"nx-dir-fact\"><span class=\"nx-dir-k\">Checks applied<\/span><span class=\"nx-dir-v\">Cross-platform reruns; Resource accounting; Failure recovery testing<\/span><\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/li><\/ul><\/div><\/div><\/div><\/section><section id=\"nx-sec-pg-uncertainty\" class=\"nx-section\" data-hue=\"risk\" data-tone=\"alt\" data-variant=\"inset\" aria-labelledby=\"nx-s-7\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">06<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Uncertainty<\/span><\/div><h2 id=\"nx-s-7\" class=\"nx-section-title\">Where uncertainty in systems modelling analysis comes from, and how it is shown.<\/h2><\/div><div class=\"nx-section-body\"><div class=\"nx-table-wrap\"><table class=\"nx-table\" data-stack=\"true\"><thead><tr><th>Source<\/th><th>Why it matters here<\/th><th>How it is reported<\/th><\/tr><\/thead><tbody><tr><td data-label=\"Source\">Coupling<\/td><td data-label=\"Why it matters here\">Interfaces between models introduce inconsistencies<\/td><td data-label=\"How it is reported\">Interface assumptions documented<\/td><\/tr><tr><td data-label=\"Source\">Structural<\/td><td data-label=\"Why it matters here\">Different models disagree<\/td><td data-label=\"How it is reported\">Intercomparison<\/td><\/tr><tr><td data-label=\"Source\">Parameters<\/td><td data-label=\"Why it matters here\">Many are poorly constrained<\/td><td data-label=\"How it is reported\">Sensitivity analysis<\/td><\/tr><tr><td data-label=\"Source\">Scenarios<\/td><td data-label=\"Why it matters here\">Deep uncertainty<\/td><td data-label=\"How it is reported\">Scenario discovery<\/td><\/tr><\/tbody><\/table><\/div><\/div><\/div><\/section><section id=\"nx-sec-uncertainty\" class=\"nx-section\" data-hue=\"project\" data-tone=\"alt\" data-variant=\"split\" aria-labelledby=\"nx-s-8\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">07<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Uncertainty<\/span><\/div><h2 id=\"nx-s-8\" class=\"nx-section-title\">How uncertainty is reported.<\/h2><\/div><div class=\"nx-section-body\"><ol class=\"nx-rows\"><li><span class=\"nx-eyebrow nx-index\">01<\/span><div><h3 class=\"nx-h4\">State assumptions<\/h3><p class=\"nx-p nx-mt-1\">Each analysis lists its assumptions and the data it depends on.<\/p><\/div><\/li><li><span class=\"nx-eyebrow nx-index\">02<\/span><div><h3 class=\"nx-h4\">Quantify where possible<\/h3><p class=\"nx-p nx-mt-1\">Ranges and confidence are reported alongside central estimates.<\/p><\/div><\/li><li><span class=\"nx-eyebrow nx-index\">03<\/span><div><h3 class=\"nx-h4\">Validate and compare<\/h3><p class=\"nx-p nx-mt-1\">Models are checked against observations and, where possible, against other models.<\/p><\/div><\/li><li><span class=\"nx-eyebrow nx-index\">04<\/span><div><h3 class=\"nx-h4\">Publish limits<\/h3><p class=\"nx-p nx-mt-1\">What an analysis cannot show is stated beside what it can.<\/p><\/div><\/li><\/ol><\/div><\/div><\/section><section id=\"nx-sec-terms\" class=\"nx-section\" data-hue=\"risk\" data-tone=\"alt\" data-variant=\"split\" aria-labelledby=\"nx-s-9\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">08<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Key terms<\/span><\/div><h2 id=\"nx-s-9\" class=\"nx-section-title\">Terms used on this page.<\/h2><p class=\"nx-lede\">Each term as this page uses it. Where a standard-setting body defines the term, the wording follows that body.<\/p><\/div><div class=\"nx-section-body\"><div class=\"nx-table-wrap\"><table class=\"nx-table\" data-stack=\"true\"><thead><tr><th scope=\"col\">Term<\/th><th scope=\"col\">Definition<\/th><\/tr><\/thead><tbody><tr><td data-label=\"Term\">Uncertainty quantification<\/td><td data-label=\"Definition\">Characterising and propagating the uncertainties in a model to state confidence in its outputs.<\/td><\/tr><tr><td data-label=\"Term\">Sensitivity analysis<\/td><td data-label=\"Definition\">Repeating an analysis under different assumptions to show how much the result depends on them.<\/td><\/tr><tr><td data-label=\"Term\">Model validation<\/td><td data-label=\"Definition\">Comparing model predictions with independent observations to judge fitness for a stated use.<\/td><\/tr><tr><td data-label=\"Term\">Systems engineering<\/td><td data-label=\"Definition\">Systems engineering is an interdisciplinary approach to designing and managing complex systems over their life cycle.<\/td><\/tr><\/tbody><\/table><\/div><\/div><\/div><\/section><section id=\"nx-sec-pg-sources\" class=\"nx-section\" data-hue=\"project\" data-variant=\"inset\" aria-labelledby=\"nx-s-10\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">09<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Sources<\/span><\/div><h2 id=\"nx-s-10\" class=\"nx-section-title\">Where this page's references lead.<\/h2><p class=\"nx-lede\">The bodies and documents this page is read against. Status and editions change; each link goes to the issuing body.<\/p><\/div><div class=\"nx-section-body\"><ul class=\"nx-list\" data-nav=\"true\"><li><a class=\"nx-link\" href=\"https:\/\/www.isimip.org\/\" target=\"_blank\" rel=\"noopener\"><span>ISIMIP Inter-Sectoral Impact Model Intercomparison Project<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/li><li><a class=\"nx-link\" href=\"https:\/\/www.jasss.org\/23\/2\/7.html\" target=\"_blank\" rel=\"noopener\"><span>ODD protocol for describing agent-based models (Grimm et al.)<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/li><li><a class=\"nx-link\" href=\"https:\/\/www.iso.org\/standard\/72140.html\" target=\"_blank\" rel=\"noopener\"><span>IEC 31010:2019 Risk assessment techniques (ISO\/IEC)<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/li><li><a class=\"nx-link\" href=\"https:\/\/www.nature.com\/articles\/sdata201618\" target=\"_blank\" rel=\"noopener\"><span>FAIR Guiding Principles for scientific data management (Wilkinson et al., Scientific Data)<\/span><svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/li><\/ul><\/div><\/div><\/section><section id=\"nx-s-11-sec\" class=\"nx-section\" data-hue=\"risk\" data-tone=\"alt\" aria-labelledby=\"nx-s-11\"><div class=\"nx-container\"><div class=\"nx-section-head\"><div class=\"nx-eyebrow-row\"><span class=\"nx-eyebrow\">10<\/span><span class=\"nx-rule\" aria-hidden=\"true\"><\/span><span class=\"nx-eyebrow\">Questions<\/span><\/div><h2 id=\"nx-s-11\" class=\"nx-section-title\">Questions and answers.<\/h2><\/div><div class=\"nx-section-body\"><div class=\"nx-faq\"><details><summary>Are the methods open?<\/summary><div class=\"nx-answer\">Method descriptions are public on the STEM Commons. Code and data follow their own licences and access terms, listed in the source register.<\/div><\/details><\/div><\/div><\/div><\/section><section class=\"nx-section\" data-tone=\"alt\" aria-labelledby=\"nx-rel-12\"><div class=\"nx-container\"><span class=\"nx-eyebrow\">Related<\/span><h2 id=\"nx-rel-12\" class=\"nx-h3 nx-mt-2\">Around Systems Science and Modelling.<\/h2><nav class=\"nx-related nx-mt-3\" aria-label=\"Related\"><a href=\"https:\/\/therisk.global\/systems-modelling\/research\/sources\/\">Source and data register <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a href=\"https:\/\/therisk.global\/systems-modelling\/\">Systems Science and Modelling home <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a href=\"https:\/\/therisk.global\/systems-modelling\/counterparts\/\">Counterparts across the Consortium <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a href=\"https:\/\/therisk.global\/\">The Global Centre for Risk and Innovation home <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a href=\"https:\/\/therisk.global\/trust\/\">GCRI governance and trust <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/nav><\/div><\/section><section class=\"nx-closing\" aria-labelledby=\"nx-close-13\"><div class=\"nx-container\"><span class=\"nx-eyebrow\">Systems Science and Modelling<\/span><h2 id=\"nx-close-13\" class=\"nx-section-title\">Bring your expertise to this field.<\/h2><p class=\"nx-lede\">The current service level is R0: information and enquiries. An enquiry receives a reference and names the next step; applications, payments, compute allocations and registrations open only when their team, terms and review capacity exist.<\/p><div class=\"nx-actions\"><a class=\"nx-btn\" data-variant=\"primary\" href=\"mailto:contact@therisk.global?subject=Systems%20Science%20and%20Modelling%3A%20Methods%20and%20uncertainty\">Write to the team <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a class=\"nx-btn\" data-variant=\"secondary\" href=\"https:\/\/therisk.global\/systems-modelling\/contact\/\">See all contact routes<\/a><\/div><\/div><\/section><\/div><\/div><script class=\"_iub_cs_skip\">window.__nxMount ? window.__nxMount(document.currentScript) : null;<\/script>\n\n\n<script type=\"application\/ld+json\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"FAQPage\",\"@id\":\"https:\/\/therisk.global\/systems-modelling\/research\/methods\/#faq\",\"isPartOf\":{\"@id\":\"https:\/\/therisk.global\/systems-modelling\/research\/methods\/#webpage\"},\"inLanguage\":\"en\",\"mainEntity\":[{\"@type\":\"Question\",\"name\":\"Are the methods open?\",\"acceptedAnswer\":{\"@type\":\"Answer\",\"text\":\"Method descriptions are public on the STEM Commons. 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