================== Quality Assessment ================== Understand the quality scoring system and how to filter events by quality metrics for reliable seismological analysis. -------- Overview -------- The platform implements a comprehensive quality assessment system that evaluates earthquake locations based on multiple factors. Events are graded from **A+** (excellent) to **F** (poor), based on international standards (Bondár, 2004; Bormann, 2012) and regional quantitative assessments of the GeoNet network performance in New Zealand (Warren-Smith et al., 2025). This grading helps you identify the most reliable data for your analysis. Quick Reference =============== .. list-table:: :header-rows: 1 :widths: 15 85 * - Grade - Recommended Use * - **A+/A** - Precision studies, location-dependent analysis, publications * - **B+/B** - General research, statistical analysis, most applications * - **C** - Completeness studies, broad pattern analysis * - **D/F** - Avoid for location-dependent analysis; review for errors **Key Principle:** Higher grades mean more reliable locations and magnitudes. Always filter by quality appropriate to your research question. -------------- Quality Grades -------------- Grade Definitions ================= .. list-table:: :header-rows: 1 :widths: 10 20 70 * - Grade - Score Range - Description * - A+ - 95-100 - Excellent quality with minimal uncertainties * - A - 90-94 - Very good quality, reliable parameters * - B+ - 85-89 - Good quality, suitable for most analyses * - B - 80-84 - Good quality with moderate uncertainties * - C - 70-79 - Fair quality, use with caution * - D - 60-69 - Poor quality, significant uncertainties * - F - 0-59 - Very poor quality, unreliable parameters ----------------- Quality Components ----------------- The overall quality score is calculated from four weighted components: 1. Location Quality (35%) ========================== Based on horizontal and vertical uncertainties: **Horizontal Uncertainty:** * Excellent: < 1 km * Good: 1-5 km * Fair: 5-10 km * Poor: > 10 km **Vertical Uncertainty (Depth):** * Excellent: < 2 km * Good: 2-10 km * Fair: 10-20 km * Poor: > 20 km 2. Network Geometry (25%) ========================== Based on azimuthal gap and station distribution: **Azimuthal Gap:** * Excellent: < 90° * Good: 90-180° * Fair: 180-270° * Poor: > 270° **Station Distribution:** * Well-distributed stations around event * Adequate depth control * Sufficient near-source stations These criteria follow the network geometry recommendations of Bondár (2004). 3. Solution Quality (15%) ========================== Based on phase counts and residuals: **Used Phase Count:** * Excellent: > 30 phases * Good: 20-30 phases * Fair: 10-20 phases * Poor: < 10 phases **Used Station Count:** * Excellent: > 15 stations * Good: 10-15 stations * Fair: 5-10 stations * Poor: < 5 stations **Standard Error (RMS):** * Excellent: < 0.3 s * Good: 0.3-0.5 s * Fair: 0.5-1.0 s * Poor: > 1.0 s These thresholds align with the International Seismological Centre (ISC) standards for high-quality locations (Bondár & Storchak, 2011). 4. Magnitude Quality (15%) =========================== Based on station count and uncertainty: **Magnitude Station Count:** * Excellent: > 10 stations * Good: 5-10 stations * Fair: 3-5 stations * Poor: < 3 stations **Magnitude Uncertainty:** * Excellent: < 0.1 * Good: 0.1-0.2 * Fair: 0.2-0.3 * Poor: > 0.3 Magnitude type preference (Mw > Ms > mb > ML) is based on the ISC-GEM standards for magnitude reliability (Storchak et al., 2013). 5. Evaluation Status (10%) =========================== Based on the review status of the origin and magnitude solution: * **Final / Reviewed**: Full points — solution has been manually verified. * **Confirmed**: Partial points — solution has passed automated checks. * **Preliminary**: Minimal points — automatic solution, not yet reviewed. * **Rejected / Unknown**: No points. ----------------- Quality Filtering ----------------- Filter by Quality Grade ======================== On the Analytics or Catalogues page: 1. Click **Filters** 2. Select **Minimum Quality Grade** 3. Choose grade (e.g., B or better) 4. Apply filter **Common filters:** * **A or better:** High-quality events for precise analysis * **B or better:** Good quality for most research * **C or better:** Include fair quality events Filter by Specific Metrics =========================== Apply custom thresholds: **Location Uncertainty:** .. code-block:: text Max Horizontal Uncertainty: 5 km Max Depth Uncertainty: 10 km **Network Geometry:** .. code-block:: text Max Azimuthal Gap: 180° Min Station Count: 10 **Solution Quality:** .. code-block:: text Min Phase Count: 15 Max RMS: 0.5 s ----------------- Quality Visualization ----------------- Quality Score Distribution ========================== View distribution of quality grades: * Bar chart showing event counts per grade * Percentage of high-quality events * Identify quality issues in catalogue Quality on Map ============== Events color-coded by quality: * Green: A+, A (excellent/very good) * Yellow: B+, B (good) * Orange: C (fair) * Red: D, F (poor/very poor) Quality Trends ============== Analyze quality over time: * Time series of average quality score * Identify periods of poor network coverage * Track improvements in monitoring ----------------- Improving Quality ----------------- For Data Uploads ================ To improve quality of uploaded data: 1. Include uncertainty values 2. Provide phase counts and station counts 3. Add azimuthal gap information 4. Include RMS residuals 5. Specify evaluation status For GeoNet Imports ================== Import high-quality events: .. code-block:: text Minimum Magnitude: 3.0 (Larger events generally better located) Enable "Update Existing Events" to get revised parameters. For Merged Catalogues ===================== Use quality-aware merging: 1. Prioritize high-quality catalogues 2. Use "Most Complete" strategy 3. Filter low-quality events before merging ----------------- Quality Metrics Reference ----------------- Azimuthal Gap ============= **Definition:** Largest angle between adjacent stations as seen from the epicenter. **Interpretation:** * Small gap (< 90°): Good azimuthal coverage * Large gap (> 180°): Poor coverage, elongated uncertainty * Gap > 270°: Very poor coverage, unreliable location **Impact:** Affects horizontal location uncertainty and reliability. Phase Count =========== **Definition:** Number of seismic phases (P-waves, S-waves) used in location. **Interpretation:** * More phases = better constrained location * Minimum 8 phases for reliable location * 20+ phases for high-quality location **Impact:** Affects all uncertainty estimates. Station Count ============= **Definition:** Number of seismic stations contributing to location. **Interpretation:** * More stations = better coverage * Minimum 8 stations for reliable location in sparse regions (Warren-Smith et al., 2025) * 10+ stations for good quality globally * 30+ stations for high-precision studies **Impact:** Affects network geometry and solution stability. RMS Residual ============ **Definition:** Root mean square of travel time residuals. **Interpretation:** * Low RMS (< 0.3 s): Good fit to data * High RMS (> 1.0 s): Poor fit, possible errors **Impact:** Indicates solution quality and data consistency. ----------------- Best Practices ----------------- For Analysis ============ * Use A or B grade events for precise studies * Include C grade for completeness analysis * Exclude D and F grades for location-dependent studies For Visualization ================= * Color-code by quality on maps * Show uncertainty ellipses for context * Filter low-quality events for clarity For Export ========== * Include quality grades in exports * Document quality thresholds used * Preserve all quality metrics For Reporting ============= * Report percentage of high-quality events * Document quality filtering applied * Include quality distribution statistics ---------- Next Steps ---------- * :doc:`visualization` - Visualize quality metrics * :doc:`exporting-data` - Export with quality filters * :doc:`../data-validation` - Data validation guide ---------- References ---------- The quality assessment metrics and scoring system in this platform are based on established seismological literature: * **Warren-Smith, E., et al. (2025).** *A quantitative assessment of GeoNet earthquake location quality in Aotearoa New Zealand.* New Zealand Journal of Geology and Geophysics. (Specific assessment of regional network performance and station thresholds). * **Bondár, I. (2004).** *Epicentre Accuracy Based on Seismic Network Criteria.* Geophysical Journal International. (Network geometry and station count requirements). * **Bondár, I., & Storchak, D. A. (2011).** *Improved Location Procedures at the International Seismological Centre.* Geophysical Journal International. (Quality scoring and azimuthal gap/RMS thresholds). * **Bormann, P., Ed. (2012).** *IASPEI New Manual of Seismological Observatory Practice (NMSOP-2).* Deutsches GeoForschungsZentrum GFZ. (Standardized quality metrics and reporting). * **Storchak, D. A., et al. (2013).** *Public Release of the ISC-GEM Global Instrumental Earthquake Catalogue (1900-2009).* Seismological Research Letters. (Parameter selection and magnitude hierarchy). * **Woessner, J., et al. (2016).** *Seismicity Catalogs.* Community Online Resource for Statistical Seismicity Analysis (CORSSA). (Best practices for catalog quality assessment).