{"id":92265,"date":"2026-04-14T07:00:11","date_gmt":"2026-04-14T07:00:11","guid":{"rendered":"https:\/\/gaeatech.com\/knowledge-center\/?p=92265"},"modified":"2026-04-13T22:55:14","modified_gmt":"2026-04-13T22:55:14","slug":"pollutev10-example-20-sensitivity-analysis-leachate-system","status":"publish","type":"post","link":"https:\/\/gaeatech.com\/knowledge-center\/pollutev10-example-20-sensitivity-analysis-leachate-system\/","title":{"rendered":"POLLUTEv10 Example 20: Sensitivity Analysis of Primary Leachate Collection System Failure"},"content":{"rendered":"\n<h2 class=\"wp-block-heading\" id=\"h-introduction\">Introduction<\/h2>\n\n\n\n<p>POLLUTEv10 Example 20 introduces <strong>Sensitivity Analysis<\/strong> as a powerful tool to evaluate how uncertainty in system performance impacts contaminant transport. In this case, the focus is on the <strong>service life of a Primary Leachate Collection System (PLCS)<\/strong> and how variations in its failure timing influence contaminant migration.<\/p>\n\n\n\n<p>Building on the framework established in <strong>Examples 15 and 16<\/strong>, this model incorporates both:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Variable Properties<\/strong><\/li>\n\n\n\n<li><strong>Passive Sink<\/strong><\/li>\n<\/ul>\n\n\n\n<p>to simulate changing hydraulic conditions as the leachate collection system degrades over time.<\/p>\n\n\n\n<blockquote class=\"wp-block-quote is-layout-flow wp-block-quote-is-layout-flow\">\n<p class=\"has-small-font-size\">\u26a0\ufe0f <em>Important Note:<\/em> This is a hypothetical example intended for instructional purposes only. It should not be used directly for real-world landfill design or risk assessment without expert guidance.<\/p>\n<\/blockquote>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-conceptual-model-overview\">Conceptual Model Overview<\/h2>\n\n\n\n<p>The modeled system consists of:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>A <strong>landfill source<\/strong> with constant contaminant concentration<\/li>\n\n\n\n<li>A <strong>Primary Leachate Collection System (PLCS)<\/strong> subject to failure over time<\/li>\n\n\n\n<li>Multiple subsurface layers<\/li>\n\n\n\n<li>An underlying <strong>aquifer system<\/strong><\/li>\n<\/ul>\n\n\n\n<p>The key variable is the <strong>time at which the PLCS begins to fail<\/strong>, which directly affects flow and contaminant migration.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-objective-of-the-sensitivity-analysis\">Objective of the Sensitivity Analysis<\/h2>\n\n\n\n<p>The purpose of this example is to evaluate how uncertainty in <strong>PLCS failure timing<\/strong> impacts:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Contaminant breakthrough timing<\/li>\n\n\n\n<li>Concentration levels in the aquifer<\/li>\n\n\n\n<li>Long-term system performance<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-failure-time-range\">Failure Time Range<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Minimum failure start time:<\/strong> 15 years<\/li>\n\n\n\n<li><strong>Maximum failure start time:<\/strong> 50 years<\/li>\n<\/ul>\n\n\n\n<p>By varying this parameter, the model generates a range of possible outcomes, helping quantify risk and uncertainty.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-key-input-parameters\">Key Input Parameters<\/h2>\n\n\n\n<p>The model uses the same parameters as <strong>Example 15<\/strong>, with the addition of sensitivity analysis variables.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-transport-and-material-properties\">Transport and Material Properties<\/h3>\n\n\n\n<figure class=\"wp-block-table\"><table><tbody><tr><th>Property<\/th><th>Symbol<\/th><th>Value<\/th><th>Units<\/th><\/tr><tr><td>Diffusion Coefficient<\/td><td>D<\/td><td>0.02<\/td><td>m\u00b2\/a<\/td><\/tr><tr><td>Dispersivity<\/td><td>\u03b1<\/td><td>0.4<\/td><td>m<\/td><\/tr><tr><td>Distribution Coefficient<\/td><td>K<\/td><td>0<\/td><td>cm\u00b3\/g<\/td><\/tr><tr><td>Soil Porosity<\/td><td>n<\/td><td>0.3<\/td><td>\u2013<\/td><\/tr><tr><td>Granular Layer Porosity<\/td><td>n<\/td><td>0.3<\/td><td>\u2013<\/td><\/tr><tr><td>Dry Density<\/td><td>\u03c1d<\/td><td>1.5<\/td><td>g\/cm\u00b3<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-geometric-parameters\">Geometric Parameters<\/h3>\n\n\n\n<figure class=\"wp-block-table\"><table><tbody><tr><td>Layer<\/td><td>Thickness<\/td><\/tr><tr><td>Layer 1<\/td><td>1 m<\/td><\/tr><tr><td>Layer 2<\/td><td>0.3 m<\/td><\/tr><tr><td>Layer 3<\/td><td>2 m<\/td><\/tr><tr><td>Aquifer Thickness<\/td><td>1 m<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-source-and-system-properties\">Source and System Properties<\/h3>\n\n\n\n<figure class=\"wp-block-table\"><table><tbody><tr><td>Parameter<\/td><td>Symbol<\/td><td>Value<\/td><\/tr><tr><td>Source Concentration<\/td><td>c\u2080<\/td><td>1000 mg\/L<\/td><\/tr><tr><td>Reference Height of Leachate<\/td><td>Hr<\/td><td>7.5 cm\u00b3\/g<\/td><\/tr><tr><td>Landfill Length<\/td><td>L<\/td><td>200 m<\/td><\/tr><tr><td>Landfill Width<\/td><td>W<\/td><td>1 m<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-flow-parameters-variable\">Flow Parameters (Variable)<\/h3>\n\n\n\n<figure class=\"wp-block-table\"><table><tbody><tr><td>Parameter<\/td><td>Symbol<\/td><td>Description<\/td><\/tr><tr><td>Darcy Velocity<\/td><td>va<\/td><td>Varies with PLCS performance<\/td><\/tr><tr><td>Sink Outflow Velocity<\/td><td>vs<\/td><td>Varies with system degradation<\/td><\/tr><tr><td>Leachate Collection Rate<\/td><td>Qc<\/td><td>Variable<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-aquifer-properties\">Aquifer Properties<\/h3>\n\n\n\n<figure class=\"wp-block-table\"><table><tbody><tr><td>Parameter<\/td><td>Symbol<\/td><td>Value<\/td><\/tr><tr><td>Aquifer Porosity<\/td><td>nb<\/td><td>0.3<\/td><\/tr><tr><td>Aquifer Velocity<\/td><td>vb<\/td><td>4 m\/a<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-modeling-approach-in-pollutev10\">Modeling Approach in POLLUTEv10<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-step-1-base-model-setup\">Step 1: Base Model Setup<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Use the configuration from <strong>Example 15<\/strong><\/li>\n\n\n\n<li>Ensure Variable Properties and Passive Sink features are enabled<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-step-2-define-sensitivity-parameter\">Step 2: Define Sensitivity Parameter<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Set <strong>failure start time<\/strong> as the variable parameter<\/li>\n\n\n\n<li>Define range: <strong>15 to 50 years<\/strong><\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-step-3-link-failure-to-system-behavior\">Step 3: Link Failure to System Behavior<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Adjust:\n<ul class=\"wp-block-list\">\n<li>Darcy velocity (va)<\/li>\n\n\n\n<li>Sink outflow velocity (vs)<\/li>\n\n\n\n<li>Leachate collection rate (Qc)<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n\n\n\n<p>These parameters evolve as the PLCS degrades.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-step-4-run-multiple-simulations\">Step 4: Run Multiple Simulations<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li>POLLUTE automatically evaluates scenarios across the defined range<\/li>\n\n\n\n<li>Results represent a spectrum of possible outcomes<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-graphical-output-probability-vs-concentration\">Graphical Output: Probability vs Concentration<\/h2>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"1007\" height=\"910\" src=\"https:\/\/gaeatech.com\/knowledge-center\/wp-content\/uploads\/2026\/04\/image-31.jpg\" alt=\"\" class=\"wp-image-92266\" srcset=\"https:\/\/gaeatech.com\/knowledge-center\/wp-content\/uploads\/2026\/04\/image-31.jpg 1007w, https:\/\/gaeatech.com\/knowledge-center\/wp-content\/uploads\/2026\/04\/image-31-300x271.jpg 300w, https:\/\/gaeatech.com\/knowledge-center\/wp-content\/uploads\/2026\/04\/image-31-768x694.jpg 768w\" sizes=\"auto, (max-width: 1007px) 100vw, 1007px\" \/><\/figure>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-pdf-report\">PDF Report<\/h2>\n\n\n<div class=\"ead-preview\"><div class=\"ead-document\" style=\"position: relative;padding-top: 90%\"><div class=\"ead-iframe-wrapper\"><iframe src=\"\/\/docs.google.com\/viewer?url=https%3A%2F%2Fgaeatech.com%2Fknowledge-center%2Fwp-content%2Fuploads%2F2026%2F04%2Fpollute-example20.pdf&amp;embedded=true&amp;hl=en\" title=\"Embedded Document\" class=\"ead-iframe\" style=\"width: 100%;height: 100%;border: none;position: absolute;left: 0;top: 0;visibility: hidden;\"><\/iframe><\/div>\t\t\t<div class=\"ead-document-loading\" 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loading=\"lazy\" decoding=\"async\" src=\"https:\/\/gaeatech.com\/knowledge-center\/wp-content\/plugins\/embed-any-document\/images\/reload.svg\" alt=\"Reload\" width=\"12\" height=\"12\"\/> Reload document\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<span>|<\/span>\n\t\t\t\t\t\t\t<a href=\"https:\/\/gaeatech.com\/knowledge-center\/wp-content\/uploads\/2026\/04\/pollute-example20.pdf\" class=\"ead-document-btn\" target=\"_blank\">\n\t\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/gaeatech.com\/knowledge-center\/wp-content\/plugins\/embed-any-document\/images\/open.svg\" alt=\"Open\" width=\"12\" height=\"12\"\/> Open in new tab\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t<\/div><\/div>\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-why-sensitivity-analysis-matters\">Why Sensitivity Analysis Matters<\/h2>\n\n\n\n<p>Sensitivity analysis is critical in environmental modeling because:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Real-world systems involve <strong>uncertainty<\/strong><\/li>\n\n\n\n<li>Material degradation is <strong>time-dependent<\/strong><\/li>\n\n\n\n<li>Field conditions are <strong>rarely uniform<\/strong><\/li>\n<\/ul>\n\n\n\n<p>This approach helps:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Identify <strong>critical parameters<\/strong><\/li>\n\n\n\n<li>Quantify <strong>risk ranges<\/strong><\/li>\n\n\n\n<li>Support <strong>decision-making and design optimization<\/strong><\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-key-takeaways\">Key Takeaways<\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>The <strong>service life of leachate systems<\/strong> is a critical control on contaminant migration<\/li>\n\n\n\n<li>POLLUTEv10 enables robust <strong>uncertainty analysis<\/strong> through sensitivity tools<\/li>\n\n\n\n<li>Combining <strong>Variable Properties<\/strong> and <strong>Passive Sink<\/strong> features allows realistic system degradation modeling<\/li>\n\n\n\n<li>Sensitivity analysis provides insight into <strong>best-case and worst-case scenarios<\/strong><\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-final-thoughts\">Final Thoughts<\/h2>\n\n\n\n<p>Example 20 highlights the importance of moving beyond single deterministic simulations toward <strong>probabilistic and sensitivity-based approaches<\/strong>. By evaluating a range of failure scenarios, engineers can better understand the <strong>risk envelope<\/strong> associated with landfill performance.<\/p>\n\n\n\n<p>However, applying these tools in practice requires:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Strong hydrogeologic understanding<\/li>\n\n\n\n<li>Careful parameter selection<\/li>\n\n\n\n<li>Validation against field or monitoring data<\/li>\n<\/ul>\n\n\n\n<p>These advanced features should only be used by qualified professionals, particularly for projects with regulatory or environmental significance.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p>.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Introduction POLLUTEv10 Example 20 introduces Sensitivity Analysis as a powerful tool to evaluate how uncertainty in system performance impacts contaminant transport. In this case, the focus is on the service life of a Primary Leachate Collection System (PLCS) and how variations in its failure timing influence contaminant migration. Building on the framework established in Examples [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":92268,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[858,1632],"tags":[501,24,821,675,1672,1627,552],"class_list":["post-92265","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-contaminant-transport-modeling","category-pollute-examples","tag-contaminant-transport","tag-environmental-engineering","tag-hydrogeology","tag-landfill-modeling","tag-leachate-collection-system","tag-pollutev10","tag-sensitivity-analysis"],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v27.4 (Yoast SEO v27.4) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>POLLUTEv10 Example 20 Sensitivity Analysis Model Overview - Knowledge Center<\/title>\n<meta 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