Enhance documentation with detailed findings from analysis report

- Add clustered vs isolated facility comparison to README
- Expand infrastructure insights with hyperscaler energy strategies
- Document additional database tables (opposition cases, IM3 projections, utility rates)
- Enhance research ideas with specific watershed names and grid saturation data
- Add data quality notes about EIA longitude corrections
- Reference loaded but unused tables for future analysis

research-ideas.md

@@ -61,6 +61,8 @@ canonical_map = {
 ### 3. Water Stress Overlay
 **Status**: 257 HUC8 watersheds contain data centers; 15 watersheds hold 50% of facilities
 
+**Priority**: HIGH - Critical for environmental impact analysis
+
 **Approach**:
 - Join to USGS WaterWatch streamflow data
 - Add USGS Drought Watch indicators by HUC8
@@ -69,10 +71,18 @@ canonical_map = {
   - Surface water withdrawal permits
   - Drought frequency/severity (USDM historical data)
 
+**Key Watersheds for Focus**:
+- **Middle Potomac-Catoctin** (HUC8 02070008): 235 DCs (12.8% of US total) - Loudoun/Ashburn
+- **Middle Potomac-Anacostia-Occoquan** (02070010): 111 DCs - Fairfax/inner Loudoun
+- **Coyote** (18050003): 88 DCs - Silicon Valley
+- **Upper Scioto** (05060001): 73 DCs - Columbus OH
+- **Umatilla** (17070103): 29 DCs - AWS-exclusive watershed
+
 **Research Questions**:
 - Are data centers sited in water-stressed watersheds?
 - Do high-density clusters (Loudoun County, Columbus OH) face water constraints?
 - Compare water stress in hyperscaler non-metro sites (Columbia River corridor) vs. metro clusters
+- Does single-operator watershed capture (Umatilla = AWS only) correlate with water availability?
 
 **Tables to Create**:
 - `watershed_water_stress` - HUC8-level water stress indicators
@@ -83,27 +93,38 @@ canonical_map = {
 ---
 
 ### 4. Opposition Cases Overlay
-**Status**: Anecdotal evidence of community opposition to new data centers
+**Status**: 18 geocoded opposition cases in `opposition_cases_geocoded` table (loaded but unused)
 
 **Approach**:
-- Compile cases of rejected/delayed data center proposals (news archive scraping)
-- Geocode opposition cases, join to demographics/hazards
+- Expand dataset: Compile additional cases of rejected/delayed data center proposals from news archives
+- Geocode all opposition cases, join to demographics/hazards
 - Test hypotheses:
   - Do wealthier/more educated communities successfully block projects?
   - Are opposition cases more common in water-stressed or drought-prone areas?
   - Do smaller non-metro communities have less bargaining power?
+  - Does clustered vs. isolated location predict opposition likelihood?
 
 **Research Questions**:
 - What predicts opposition success?
 - Are opposition cases spatially clustered?
 - Do demographics differ between accepted vs. rejected sites?
+- Correlation with FEMA hazard exposure scores?
+
+**Analysis Plan**:
+```sql
+-- Join opposition cases to demographics
+SELECT o.*, ct.median_household_income, ct.bachelors_or_higher_pct
+FROM opposition_cases_geocoded o
+JOIN _dc_census_tract_acs_2024 ct 
+  ON ST_Contains(ct.geom, o.geom);
+```
 
 **Output**: `opposition_cases_analysis.md`
 
 ---
 
 ### 5. IM3 Forward Projection Integration
-**Status**: IM3 model includes projected data center demand growth
+**Status**: IM3 model data loaded in `im3_state_projected_moderate_50` (328 rows) and `im3_projected_state_demand_summary` (31 rows)
 
 **Approach**:
 - Load IM3 projected demand scenarios (2030, 2040, 2050)
@@ -113,10 +134,34 @@ canonical_map = {
   - Land availability (zoned industrial parcels)
 - Identify regions where projected demand may exceed infrastructure capacity
 
+**Grid Saturation Context** (from current analysis):
+- **New Jersey**: 83% of grid within 50 km of DC
+- **Nevada**: 75%
+- **Tennessee**: 70%
+- **Oregon**: 68%
+- **Arizona**: 56%
+- **Virginia**: 50%
+
 **Research Questions**:
 - Which states face grid saturation from data center growth?
 - Are projected sites in water-stressed watersheds?
 - Does IM3 assume spatial distribution patterns consistent with current siting?
+- Can states with >50% grid saturation accommodate projected demand?
+
+**Implementation**:
+```sql
+-- Compare current saturation to IM3 projected demand
+SELECT 
+  current.state,
+  current.dc_count,
+  current.pct_grid_saturated,
+  proj.facility_count AS projected_new_facilities,
+  proj.total_it_mw AS projected_new_mw
+FROM state_grid_saturation current
+JOIN im3_projected_state_demand_summary proj ON current.state = proj.state
+WHERE current.pct_grid_saturated > 50
+ORDER BY current.pct_grid_saturated DESC;
+```
 
 **Notebook**: `im3_projection_overlay.ipynb`