Earth and Space Science · California Grade 7

MS-ESS3-2

Analyze and interpret data on natural hazards to forecast future catastrophic events and inform the development of technologies to mitigate their effects.

Clarification statement: Emphasis is on how some natural hazards, such as volcanic eruptions and severe weather, are preceded by phenomena that allow for reliable predictions, but others, such as earthquakes, occur suddenly and with no notice, and thus are not yet predictable. Examples of natural hazards can be taken from interior processes (such as earthquakes and volcanic eruptions), surface processes (such as mass wasting and tsunamis), or severe weather events (such as hurricanes, tornadoes, and floods). Examples of data can include the locations, magnitudes, and frequencies of the natural hazards. Examples of technologies can be global (such as satellite systems to monitor hurricanes or forest fires) or local (such as building basements in tornado-prone regions or reservoirs to mitigate droughts).

Source: California Department of Education, NGSS Preferred Integrated Course Model, Grade 7 (accessed 2026-10-18)

Chapters

Chapter 11: Scales of Change on Earth's Surfacesupports

Landslides, flash floods and eruptions appear here as fast changes whose conditions build slowly. Forecasting those hazards and designing mitigation, which is what MS-ESS3-2 assesses, belongs to Lessons 25 and 26; here students only learn why the events are sudden and what they do to the surface.

Chapter 25: Volcanic Eruptions and Earthquakesassesses

This is the lesson's performance expectation. Lab 1 asks students to forecast which towns face which hazards from mapped event data, and Lab 3 has them rank bridge sites from frequency, magnitude and ground data and choose a mitigation plan. The deck keeps the clarification statement's contrast front and center: eruptions are often preceded by measurable precursors, while earthquakes strike without reliable warning.

Chapter 26: Mass Wasting, Tsunamis, and Floodsassesses

Lab 3 is the main evidence: students compute tsunami arrival times from distance and depth, use a record of past earthquakes and seafloor-sensor readings to set warning thresholds, and test their procedure against that record. Lab 1 and Lab 2 add model data and a simulated flood record that inform slope protection and a bridge's design flood. The deck keeps the clarification statement's contrast in view: atmospheric-river floods and distant tsunamis can be forecast hours to days ahead, while local tsunamis and most landslides give little or no notice.

Worksheets (20)

Chapter	Worksheet	Role	How it connects
Ch. 25	W1 · Fifteen Seconds and Fifty-Nine Days: Two Hazards, Two Kinds of Warning Phenomenon exploration	supports	The two cases set up the contrast in the PE's clarification statement: volcanic eruptions are often preceded by measurable signs, while earthquakes strike without notice. Students raise the questions the chapter's data work will answer; nothing here is assessed yet.
Ch. 25	W2 · Twelve Words for Restless Ground: Sorting, Linking and Using Hazard Terms Vocabulary in action	supports	Precursor event, frequency, magnitude, forecast and mitigate are the words the PE's data analysis depends on. Sorting and linking them, and separating forecast from prediction, prepares students to interpret hazard data in W5 and W6.
Ch. 25	W3 · Forecasting a Fault: How California Plans for Quakes No One Can Predict Reading with evidence	practice	Students read how scientists turn data on the locations, magnitudes and frequencies of past earthquakes into a probability forecast, and how that forecast shaped California's building rules and warning technology. They interpret the reasoning in the text rather than analyzing a dataset themselves, so this sheet practices the PE; W5 and W6 assess it.
Ch. 25	W4 · California's Restless Edge: Modeling Where Magma and Earthquakes Come From Diagrams and models	practice	The disciplinary core idea for this PE says that mapping past hazards together with an understanding of the related geologic forces helps forecast where future events are likely. Students model those forces for California's plate settings, which builds toward forecasting locations; the sheet does not ask them to analyze hazard data.
Ch. 25	W5 · Counting Quakes: Frequency, Magnitude and a 30-Year Forecast Data and graphing	assesses	Students analyze the magnitudes, frequencies and timing of past earthquakes, the kinds of data the clarification statement names, to forecast future large quakes as a likelihood over a time window and to recommend a mitigation. The forecast they write in q10 is direct evidence toward the PE.
Ch. 25	W6 · Is Mount Corva Waking Up? A Claim-Evidence-Reasoning Case Claim, evidence, reasoning	assesses	The clarification statement names volcanic eruptions as hazards preceded by phenomena that allow reliable forecasts. Students analyze three precursor signals and a volcanic history to forecast that an eruption is becoming more likely, choose an alert level, and justify mitigation for a town, which is direct evidence toward the PE.
Ch. 25	W7 · Fixing Marisol's Hazard Report: Ten Claims, Eight Errors Error analysis	practice	Students correct faulty reasoning about magnitude, frequency, forecasts and early warning, which are the ideas needed to interpret hazard data for this PE. Diagnosing errors practices the reasoning; it does not ask students to analyze a new dataset.
Ch. 25	W8 · California Hazard Briefing: A Twelve-Card Jigsaw Collaborative investigation	practice	Groups sort real evidence about California's volcanoes and faults into what allows short-term eruption forecasts, what supports long-term earthquake forecasts, and which technologies reduce harm. They reason with hazard data but do not analyze a dataset themselves, so the sheet practices the PE.
Ch. 25	W9 · Listening to Silver Basin: Design a Volcano Monitoring and Alert Plan Transfer and design	assesses	Students use what precursor data reveal about rising magma to design a monitoring technology and an alert rule that would let officials forecast an eruption and act before it. Choosing which signals to measure, and how many must change before raising the alert, is evidence toward the mitigation half of the PE.
Ch. 25	W10 · Volcanic Eruptions and Earthquakes: Mastery Check Retrieval and mastery check	assesses	The forecasting items and the synthesis ask students to interpret precursor and frequency data, express a forecast as a likelihood over time rather than a date, and connect forecasts to mitigation, which is evidence toward the PE as written.
Ch. 26	W1 · One County, Three Hazards: Del Norte's Tsunamis, Floods and Sliding Highway Phenomenon exploration	supports	Students notice that one stretch of coast faces three hazards, that different hazards cluster in different landscapes, and that tsunamis arrive hours after distant earthquakes. Those location, frequency and timing patterns are the kind of hazard data the PE asks students to analyze; this sheet raises the questions, and later sheets do the analysis and forecasting.
Ch. 26	W2 · Trigger, Event or Defense? Sorting the Language of Hazards Vocabulary in action	supports	Students separate the causes of hazards, the hazard events themselves and the ways people forecast and reduce harm, and they distinguish a forecast from an exact prediction. That language is background the PE's data analysis depends on.
Ch. 26	W3 · What Holds a Hillside Up? Slope, Water and Earth Material Reading with evidence	practice	Students use the passage to identify the data that forecast where slopes fail (steepness, material, old slides, shaking, rainfall intensity after fire) and to match mitigation to each cause. This builds the reasoning the PE asks for; students are not yet analyzing a dataset themselves.
Ch. 26	W4 · From Trench to Beach: Modeling a Tsunami and the Sensor That Catches It Diagrams and models	practice	Students model why a tsunami is low and fast in deep water but slow and tall near shore, and how the DART system turns a deep-ocean pressure change into a warning. That model explains why tsunami arrival can be forecast once the triggering earthquake has happened and why the sensors sit where they do, which prepares students for the PE's data analysis in W6.
Ch. 26	W5 · Is the Big Flood Due? Ranking 24 Years of River Peaks Data and graphing	assesses	Students analyze the magnitudes and frequencies of past floods, the kinds of data the clarification statement names, to forecast the yearly chance of floods of different sizes and to recommend how high a new building should sit. The forecast and recommendation they write in q7 and q8 are direct evidence toward the PE. The data are simulated, so the sheet assesses the reasoning, not real-world conclusions.
Ch. 26	W6 · Racing Across the Ocean: Does Depth Set a Tsunami's Speed? Claim, evidence, reasoning	assesses	Students analyze distances, travel times and wave heights from past tsunamis to establish that ocean depth sets speed, then forecast arrival times for two towns and explain what each forecast means for warnings and mitigation. This matches the clarification's emphasis on hazards whose timing can be forecast once a triggering event is detected. The data are simulated.
Ch. 26	W7 · Fixing Jordan's Hazard Fact Sheet: Tidal Waves, Due Floods and Soggy Slopes Error analysis	practice	Students correct claims about what causes tsunamis and controls their speed and height, what a flood recurrence interval means and how water and fire change slopes. Accurate versions of these ideas are what students need to forecast hazards and choose mitigation, so the sheet builds toward the PE rather than assessing it.
Ch. 26	W8 · Forecast Desk Jigsaw: How Much Warning Does Each Hazard Give? Collaborative investigation	practice	The clarification statement stresses that some hazards are preceded by phenomena that allow reliable forecasts while others, such as earthquakes, strike without notice. Groups sort real monitoring tools and California cases by warning time and match mitigation to each. The cards give descriptions rather than datasets, so the sheet builds the PE's reasoning without fully assessing it.
Ch. 26	W9 · After the Fire: Choosing Debris-Flow Defenses for Sycamore Canyon Transfer and design	assesses	Students interpret a post-fire hazard assessment (chance of a debris flow, expected volume and the rainfall burst that would trigger it) and use it to choose and combine structures and a rainfall-based warning. That is the PE's second half, informing the development of technologies to mitigate a hazard. The assessment values are simulated, so the sheet assesses the reasoning rather than conclusions about a real place.
Ch. 26	W10 · Mass Wasting, Tsunamis and Floods: Mastery Check Retrieval and mastery check	assesses	Items 4, 7, 9 and 11 ask students to calculate arrival times and flood chances and to tell a forecast from an exact prediction, and the synthesis asks them to name the data that forecast two hazards and match mitigation to each hazard's warning time. Together these give direct evidence toward the PE.

Labs (6)

Chapter	Lab	Role	How it connects
Ch. 25	Lab 1 · The Unlabeled Map: Find the Hidden Plate Boundaries Evidence-based mystery	assesses	Students analyze simulated hazard data (locations, magnitudes, depths) to rank four towns by earthquake hazard, identify which face volcanic hazards, and recommend mitigation (q8, q9, q12). This produces direct evidence toward the forecasting part of the PE; Lab 3 adds the frequency data and the technology choice.
Ch. 25	Lab 2 · Shake Table Bridge Challenge: Define, Build, Shake, Improve Engineering design challenge	practice	Earthquake-resistant structures are one of the mitigation technologies the PE refers to. The shaking levels stand for frequent, rare and very rare earthquakes, but students analyze test data from a model rather than data on real hazards, so this is practice.
Ch. 25	Lab 3 · Three Crossings, One Bridge: Rank the Sites by Hazard Risk Data-driven decision	assesses	Students compute earthquake frequencies from a catalog, compare magnitudes, weigh the chances of rare great earthquakes, mudflows and tsunamis, rank three sites, and choose a site and mitigation measures within a budget (q1 to q6). The data are simulated, but the task is the analysis-and-mitigation reasoning the PE describes.
Ch. 26	Lab 1 · Tilt, Soak, Slide: When Does a Model Hillside Fail? Physical model	practice	Students analyze pooled failure-angle data and rain-to-failure counts to identify the conditions that make slopes fail, then use them to judge which mitigation works and what a landslide watch should monitor. The data come from a model, not from records of real hazards, so this builds toward the PE rather than assessing it.
Ch. 26	Lab 2 · Clear the Flood: Design, Test and Combine a Model Bridge Engineering design challenge	practice	Students turn a simulated record of yearly peak flows into yearly chances and expected numbers of floods over a bridge's life, and use them to choose which flood the bridge must survive. This uses hazard frequency data to inform a technology, but the record is simulated and short, so the role is practice.
Ch. 26	Lab 3 · Four Hours or Twenty Minutes: Write a Tsunami Warning Procedure Data-driven decision	assesses	Students analyze magnitudes, depths, fault motion and DART readings from past events, calculate arrival times from depth and distance, and use the results to set thresholds in a warning procedure, a mitigation technology. The local-source calculation shows the clarification statement's point that some hazards cannot be forecast with enough notice. The task produces direct evidence toward the PE.