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<meta name="author" content="Greg Harrison">
<title>Using Gradient-Boosted Machine Learning Models to Forecast Lake Water Quality</title>
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</head>
<body class="quarto-light">
<div class="reveal">
<div class="slides">
<section id="title-slide" class="quarto-title-block center">
<h1 class="title">Using Gradient-Boosted Machine Learning Models to Forecast Lake Water Quality</h1>
<div class="quarto-title-authors">
<div class="quarto-title-author">
<div class="quarto-title-author-name">
Greg Harrison
</div>
</div>
</div>
</section>
<section id="neon-forecasting-challenge" class="slide level2">
<h2>NEON Forecasting Challenge</h2>
<ul>
<li>Ecological forecasting could improve natural resource management and advance predictive theory.</li>
<li>The Ecological Forecasting Initiative is hosting a data science challenge to accurately forecast observations at NEON sites across the U.S.</li>
<li>Focused on aquatics theme, generating 1- to 30-day ahead forecasts of water temperature, dissolved oxygen, and chlorophyll-a at 24 lakes and streams.</li>
<li>Contributes to a growing set of automated forecasting models that will be used to quantify the boundaries prediction in ecology.</li>
</ul>
</section>
<section id="neon-workflow" class="slide level2">
<h2>NEON Workflow</h2>
<img data-src="Images/NeonWorkflow.jpeg" class="r-stretch quarto-figure-center"><p>Figure from <span class="citation" data-cites="thomas2023">(<a href="#/references" role="doc-biblioref" onclick="">Thomas et al. 2023</a>)</span></p>
</section>
<section id="what-is-xgboost" class="slide level2">
<h2>What is XGBoost?</h2>
<ul>
<li><strong>XGBoost</strong> (Extreme Gradient Boosting): Ensemble model based on decisions trees that utilizes Gradient Boosting and is optimized to run fast</li>
<li><strong>Ensemble</strong>: Combines multiple models together for enhanced performance</li>
<li><strong>Gradient Boosting</strong>: Each new model learns to correct for previous models shortcomings</li>
<li><strong>Extreme</strong>: Can use parallelization and GPUs to speed up training</li>
</ul>
</section>
<section id="xgboost-diagram" class="slide level2">
<h2>XGBoost Diagram</h2>
<img data-src="Images/xgboostpicture.webp" class="r-stretch quarto-figure-center"><p>Figure from <span class="citation" data-cites="xgboost">(<a href="#/references" role="doc-biblioref" onclick="">Pal 2020</a>)</span></p>
</section>
<section id="where-has-xgboost-been-used-before" class="slide level2">
<h2>Where has XGBoost been used before?</h2>
<ul>
<li><p>Predicting groundwater levels in Selangor, Malaysia, outperforming both ANNs and SVMs <span class="citation" data-cites="ibrahemahmedosman2021">(<a href="#/references" role="doc-biblioref" onclick="">Ibrahem Ahmed Osman et al. 2021</a>)</span></p></li>
<li><p>Predicting changes in ICU Covid-19 patients’ sequential organ failure assessment scores <span class="citation" data-cites="montomoli2021">(<a href="#/references" role="doc-biblioref" onclick="">Montomoli et al. 2021</a>)</span></p></li>
<li><p>Predicting heart disease in clinic patients with around 91.8% accuracy <span class="citation" data-cites="budholiya2022">(<a href="#/references" role="doc-biblioref" onclick="">Budholiya, Shrivastava, and Sharma 2022</a>)</span></p></li>
</ul>
</section>
<section id="questions" class="slide level2">
<h2>Questions</h2>
<ul>
<li>How well does XGBoost perform in forecasting temperature, oxygen, and chlorophyll-a compare to baseline models such as Climatology and Persistence?</li>
<li>Do oxygen and chlorophyll-a forecasts benefit from using forecasted water temperature?</li>
</ul>
</section>
<section id="methods" class="slide level2">
<h2>Methods</h2>
<ul>
<li>R script to train XGBoost models on historical data, used day of year and forecasted air temperatures as inputs.</li>
<li>Reserved random 20% of data to evaluate model performance.</li>
<li>Forecast distribution due to combination of ensemble variance and random noise added based on model performance on testing data.</li>
<li>Two main families of models, parallel where each variable was predicted independently of the others, and sequential, where predicted water temperature was used as an input for Dissolved Oxygen and Chlorophyll-a</li>
</ul>
</section>
<section id="parallel-model" class="slide level2">
<h2>Parallel Model</h2>
<img data-src="Images/ParallelModel.png" class="r-stretch quarto-figure-center"></section>
<section id="sequential-model" class="slide level2">
<h2>Sequential Model</h2>
<img data-src="Images/SequentialModel.png" class="r-stretch quarto-figure-center"></section>
<section id="methods-1" class="slide level2">
<h2>Methods</h2>
<ul>
<li>Using Github actions produce a reproducible workflow that produces daily forecasts.</li>
<li>Every day a new XGBoost model is trained for each NEON site and target variable, and then uses NOAA forecasts to predict values 30 days into the future and submits.</li>
<li>Forecasting since February 14, 2023 (65 Days)</li>
</ul>
</section>
<section id="focal-analysis-sites" class="slide level2">
<h2>Focal Analysis Sites</h2>
<!--Our results will focus on Lake Suggs and Lake Barco, two similar lakes in northern Florida.-->
<img data-src="Images/SUGG_BARC.png" class="r-stretch quarto-figure-center"><div class="cell">
</div>
<div class="cell">
</div>
<div class="cell">
</div>
</section>
<section id="example-forecast" class="slide level2">
<h2>Example Forecast</h2>
<img data-src="PresentationSP23_files/figure-revealjs/unnamed-chunk-4-1.png" width="960" class="r-stretch"></section>
<section>
<section id="results" class="title-slide slide level1 center">
<h1>Results</h1>
<div class="cell">
</div>
<div class="cell">
</div>
</section>
<section id="temperature" class="slide level2">
<h2>Temperature</h2>
<img data-src="PresentationSP23_files/figure-revealjs/unnamed-chunk-7-1.png" width="960" class="r-stretch"></section>
<section id="oxygen" class="slide level2">
<h2>Oxygen</h2>
<img data-src="PresentationSP23_files/figure-revealjs/unnamed-chunk-8-1.png" width="960" class="r-stretch"></section>
<section id="chlorphyll-a" class="slide level2">
<h2>Chlorphyll-a</h2>
<img data-src="PresentationSP23_files/figure-revealjs/unnamed-chunk-9-1.png" width="960" class="r-stretch"></section>
<section id="performance-of-parallel-xgboost-relative-to-climatology" class="slide level2">
<h2>Performance of Parallel XGBoost Relative to Climatology</h2>
<!--y axis: delta log off of climatology x axis: horizon, $delta$ log $2^{\Delta \log differnce}$ log probability with climatology add negative if its worse and positive if its better-->
<div class="cell">
</div>
<img data-src="PresentationSP23_files/figure-revealjs/unnamed-chunk-11-1.png" width="960" class="r-stretch"></section></section>
<section>
<section id="other-themes" class="title-slide slide level1 center">
<h1>Other Themes</h1>
</section>
<section id="mountain-lake-biological-station" class="slide level2">
<h2>Mountain Lake Biological Station</h2>
<div class="cell">
</div>
<div class="cell">
</div>
<img data-src="PresentationSP23_files/figure-revealjs/unnamed-chunk-14-1.png" width="960" class="r-stretch"></section>
<section id="conclusion" class="slide level2">
<h2>Conclusion</h2>
<ul>
<li>XGBoost showed potential for strong forecasting capabilities with limited model inputs</li>
<li>On average outperformed climatology on Temperature and Oxygen variables across all horizons and better than climatology on the first 18 days</li>
<li>Water temperature as a predictor for oxygen and chlorophyll-a did not improve predictions as currently designed</li>
<li>Further exploration into refining our application of this model to ecological forecasting could be beneficial</li>
</ul>
</section>
<section id="references" class="slide level2 smaller scrollable">
<h2>References</h2>
<div class="footer footer-default">
</div>
<div id="refs" class="references csl-bib-body hanging-indent" role="doc-bibliography">
<div id="ref-budholiya2022" class="csl-entry" role="doc-biblioentry">
Budholiya, Kartik, Shailendra Kumar Shrivastava, and Vivek Sharma. 2022. <span>“An Optimized XGBoost Based Diagnostic System for Effective Prediction of Heart Disease.”</span> <em>Journal of King Saud University - Computer and Information Sciences</em> 34 (7): 4514–23. <a href="https://doi.org/10.1016/j.jksuci.2020.10.013">https://doi.org/10.1016/j.jksuci.2020.10.013</a>.
</div>
<div id="ref-ibrahemahmedosman2021" class="csl-entry" role="doc-biblioentry">
Ibrahem Ahmed Osman, Ahmedbahaaaldin, Ali Najah Ahmed, Ming Fai Chow, Yuk Feng Huang, and Ahmed El-Shafie. 2021. <span>“Extreme Gradient Boosting (Xgboost) Model to Predict the Groundwater Levels in Selangor Malaysia.”</span> <em>Ain Shams Engineering Journal</em> 12 (2): 1545–56. <a href="https://doi.org/10.1016/j.asej.2020.11.011">https://doi.org/10.1016/j.asej.2020.11.011</a>.
</div>
<div id="ref-montomoli2021" class="csl-entry" role="doc-biblioentry">
Montomoli, Jonathan, Luca Romeo, Sara Moccia, Michele Bernardini, Lucia Migliorelli, Daniele Berardini, Abele Donati, et al. 2021. <span>“Machine Learning Using the Extreme Gradient Boosting (XGBoost) Algorithm Predicts 5-Day Delta of SOFA Score at ICU Admission in COVID-19 Patients.”</span> <em>Journal of Intensive Medicine</em> 1 (2): 110–16. <a href="https://doi.org/10.1016/j.jointm.2021.09.002">https://doi.org/10.1016/j.jointm.2021.09.002</a>.
</div>
<div id="ref-xgboost" class="csl-entry" role="doc-biblioentry">
Pal, Aratrika. 2020. <span>“Gradient Boosting Trees for Classification: A Beginner’s Guide,”</span> October. <a href="https://medium.com/swlh/gradient-boosting-trees-for-classification-a-beginners-guide-596b594a14ea">https://medium.com/swlh/gradient-boosting-trees-for-classification-a-beginners-guide-596b594a14ea</a>.
</div>
<div id="ref-thomas2023" class="csl-entry" role="doc-biblioentry">
Thomas, R Quinn, Carl Boettiger, Cayelan C Carey, Michael C Dietze, Leah R Johnson, Melissa A Kenney, Jason S McLachlan, et al. 2023. <span>“The NEON Ecological Forecasting Challenge.”</span> <em>Frontiers in Ecology and the Environment</em> 21 (3): 112–13. <a href="https://doi.org/10.1002/fee.2616">https://doi.org/10.1002/fee.2616</a>.
</div>
</div>
</section></section>
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'menu': {"side":"left","useTextContentForMissingTitles":true,"markers":false,"loadIcons":false,"custom":[{"title":"Tools","icon":"<i class=\"fas fa-gear\"></i>","content":"<ul class=\"slide-menu-items\">\n<li class=\"slide-tool-item active\" data-item=\"0\"><a href=\"#\" onclick=\"RevealMenuToolHandlers.fullscreen(event)\"><kbd>f</kbd> Fullscreen</a></li>\n<li class=\"slide-tool-item\" data-item=\"1\"><a href=\"#\" onclick=\"RevealMenuToolHandlers.speakerMode(event)\"><kbd>s</kbd> Speaker View</a></li>\n<li class=\"slide-tool-item\" data-item=\"2\"><a href=\"#\" onclick=\"RevealMenuToolHandlers.overview(event)\"><kbd>o</kbd> Slide Overview</a></li>\n<li class=\"slide-tool-item\" data-item=\"3\"><a href=\"#\" onclick=\"RevealMenuToolHandlers.overview(event)\"><kbd>e</kbd> PDF Export Mode</a></li>\n<li class=\"slide-tool-item\" data-item=\"4\"><a href=\"#\" onclick=\"RevealMenuToolHandlers.keyboardHelp(event)\"><kbd>?</kbd> Keyboard Help</a></li>\n</ul>"}],"openButton":true},
'smaller': false,
// Display controls in the bottom right corner
controls: false,
// Help the user learn the controls by providing hints, for example by
// bouncing the down arrow when they first encounter a vertical slide
controlsTutorial: false,
// Determines where controls appear, "edges" or "bottom-right"
controlsLayout: 'edges',
// Visibility rule for backwards navigation arrows; "faded", "hidden"
// or "visible"
controlsBackArrows: 'faded',
// Display a presentation progress bar
progress: true,
// Display the page number of the current slide
slideNumber: false,
// 'all', 'print', or 'speaker'
showSlideNumber: 'all',
// Add the current slide number to the URL hash so that reloading the
// page/copying the URL will return you to the same slide
hash: true,
// Start with 1 for the hash rather than 0
hashOneBasedIndex: false,
// Flags if we should monitor the hash and change slides accordingly
respondToHashChanges: true,
// Push each slide change to the browser history
history: true,
// Enable keyboard shortcuts for navigation
keyboard: true,
// Enable the slide overview mode
overview: true,
// Disables the default reveal.js slide layout (scaling and centering)
// so that you can use custom CSS layout
disableLayout: false,
// Vertical centering of slides
center: false,
// Enables touch navigation on devices with touch input
touch: true,
// Loop the presentation
loop: false,
// Change the presentation direction to be RTL
rtl: false,
// see https://revealjs.com/vertical-slides/#navigation-mode
navigationMode: 'linear',
// Randomizes the order of slides each time the presentation loads
shuffle: false,
// Turns fragments on and off globally
fragments: true,
// Flags whether to include the current fragment in the URL,
// so that reloading brings you to the same fragment position
fragmentInURL: false,
// Flags if the presentation is running in an embedded mode,
// i.e. contained within a limited portion of the screen
embedded: false,
// Flags if we should show a help overlay when the questionmark
// key is pressed
help: true,
// Flags if it should be possible to pause the presentation (blackout)
pause: true,
// Flags if speaker notes should be visible to all viewers
showNotes: false,
// Global override for autoplaying embedded media (null/true/false)
autoPlayMedia: null,
// Global override for preloading lazy-loaded iframes (null/true/false)
preloadIframes: null,
// Number of milliseconds between automatically proceeding to the
// next slide, disabled when set to 0, this value can be overwritten
// by using a data-autoslide attribute on your slides
autoSlide: 0,
// Stop auto-sliding after user input
autoSlideStoppable: true,
// Use this method for navigation when auto-sliding
autoSlideMethod: null,
// Specify the average time in seconds that you think you will spend
// presenting each slide. This is used to show a pacing timer in the
// speaker view
defaultTiming: null,
// Enable slide navigation via mouse wheel
mouseWheel: false,
// The display mode that will be used to show slides
display: 'block',
// Hide cursor if inactive
hideInactiveCursor: true,
// Time before the cursor is hidden (in ms)
hideCursorTime: 5000,
// Opens links in an iframe preview overlay
previewLinks: false,
// Transition style (none/fade/slide/convex/concave/zoom)
transition: 'none',
// Transition speed (default/fast/slow)
transitionSpeed: 'default',
// Transition style for full page slide backgrounds
// (none/fade/slide/convex/concave/zoom)
backgroundTransition: 'none',
// Number of slides away from the current that are visible
viewDistance: 3,
// Number of slides away from the current that are visible on mobile
// devices. It is advisable to set this to a lower number than
// viewDistance in order to save resources.
mobileViewDistance: 2,
// The "normal" size of the presentation, aspect ratio will be preserved
// when the presentation is scaled to fit different resolutions. Can be
// specified using percentage units.
width: 1050,
height: 700,
// Factor of the display size that should remain empty around the content
margin: 0.1,
math: {
mathjax: 'https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.0/MathJax.js',
config: 'TeX-AMS_HTML-full',
tex2jax: {
inlineMath: [['\\(','\\)']],
displayMath: [['\\[','\\]']],
balanceBraces: true,
processEscapes: false,
processRefs: true,
processEnvironments: true,
preview: 'TeX',
skipTags: ['script','noscript','style','textarea','pre','code'],
ignoreClass: 'tex2jax_ignore',
processClass: 'tex2jax_process'
},
},
// reveal.js plugins
plugins: [QuartoLineHighlight, PdfExport, RevealMenu, QuartoSupport,
RevealMath,
RevealNotes,
RevealSearch,
RevealZoom
]
});
</script>
<script>
// htmlwidgets need to know to resize themselves when slides are shown/hidden.
// Fire the "slideenter" event (handled by htmlwidgets.js) when the current
// slide changes (different for each slide format).
(function () {
// dispatch for htmlwidgets
function fireSlideEnter() {
const event = window.document.createEvent("Event");
event.initEvent("slideenter", true, true);
window.document.dispatchEvent(event);
}
function fireSlideChanged(previousSlide, currentSlide) {
fireSlideEnter();
// dispatch for shiny
if (window.jQuery) {
if (previousSlide) {
window.jQuery(previousSlide).trigger("hidden");
}
if (currentSlide) {
window.jQuery(currentSlide).trigger("shown");
}
}
}
// hookup for slidy
if (window.w3c_slidy) {
window.w3c_slidy.add_observer(function (slide_num) {
// slide_num starts at position 1
fireSlideChanged(null, w3c_slidy.slides[slide_num - 1]);
});
}
})();
</script>
<script id="quarto-html-after-body" type="application/javascript">
window.document.addEventListener("DOMContentLoaded", function (event) {
const toggleBodyColorMode = (bsSheetEl) => {
const mode = bsSheetEl.getAttribute("data-mode");
const bodyEl = window.document.querySelector("body");
if (mode === "dark") {
bodyEl.classList.add("quarto-dark");
bodyEl.classList.remove("quarto-light");
} else {
bodyEl.classList.add("quarto-light");
bodyEl.classList.remove("quarto-dark");
}
}
const toggleBodyColorPrimary = () => {
const bsSheetEl = window.document.querySelector("link#quarto-bootstrap");
if (bsSheetEl) {
toggleBodyColorMode(bsSheetEl);
}
}
toggleBodyColorPrimary();
const tabsets = window.document.querySelectorAll(".panel-tabset-tabby")
tabsets.forEach(function(tabset) {
const tabby = new Tabby('#' + tabset.id);
});
const clipboard = new window.ClipboardJS('.code-copy-button', {
target: function(trigger) {
return trigger.previousElementSibling;
}
});
clipboard.on('success', function(e) {
// button target
const button = e.trigger;
// don't keep focus
button.blur();
// flash "checked"
button.classList.add('code-copy-button-checked');
var currentTitle = button.getAttribute("title");
button.setAttribute("title", "Copied!");
let tooltip;
if (window.bootstrap) {
button.setAttribute("data-bs-toggle", "tooltip");
button.setAttribute("data-bs-placement", "left");
button.setAttribute("data-bs-title", "Copied!");
tooltip = new bootstrap.Tooltip(button,
{ trigger: "manual",
customClass: "code-copy-button-tooltip",
offset: [0, -8]});
tooltip.show();
}
setTimeout(function() {
if (tooltip) {
tooltip.hide();
button.removeAttribute("data-bs-title");
button.removeAttribute("data-bs-toggle");
button.removeAttribute("data-bs-placement");
}
button.setAttribute("title", currentTitle);
button.classList.remove('code-copy-button-checked');
}, 1000);
// clear code selection
e.clearSelection();
});
function tippyHover(el, contentFn) {
const config = {
allowHTML: true,
content: contentFn,
maxWidth: 500,
delay: 100,
arrow: false,
appendTo: function(el) {
return el.closest('section.slide') || el.parentElement;
},
interactive: true,
interactiveBorder: 10,
theme: 'quarto-reveal',
placement: 'bottom-start'
};
config['offset'] = [0,0];
config['maxWidth'] = 700;
window.tippy(el, config);
}
const noterefs = window.document.querySelectorAll('a[role="doc-noteref"]');
for (var i=0; i<noterefs.length; i++) {
const ref = noterefs[i];
tippyHover(ref, function() {
// use id or data attribute instead here
let href = ref.getAttribute('data-footnote-href') || ref.getAttribute('href');
try { href = new URL(href).hash; } catch {}
const id = href.replace(/^#\/?/, "");
const note = window.document.getElementById(id);
return note.innerHTML;
});
}
const findCites = (el) => {
const parentEl = el.parentElement;
if (parentEl) {
const cites = parentEl.dataset.cites;
if (cites) {
return {
el,
cites: cites.split(' ')
};
} else {
return findCites(el.parentElement)
}
} else {
return undefined;
}
};
var bibliorefs = window.document.querySelectorAll('a[role="doc-biblioref"]');
for (var i=0; i<bibliorefs.length; i++) {
const ref = bibliorefs[i];
const citeInfo = findCites(ref);
if (citeInfo) {
tippyHover(citeInfo.el, function() {
var popup = window.document.createElement('div');
citeInfo.cites.forEach(function(cite) {
var citeDiv = window.document.createElement('div');
citeDiv.classList.add('hanging-indent');
citeDiv.classList.add('csl-entry');
var biblioDiv = window.document.getElementById('ref-' + cite);
if (biblioDiv) {
citeDiv.innerHTML = biblioDiv.innerHTML;
}
popup.appendChild(citeDiv);
});
return popup.innerHTML;
});
}
}
});
</script>
</body></html>