Shizuoka Prefecture forest public-function report (1,102 stands)

Forest Effect on Water Yield

+14hundred million t/yr

Bare baseline 390 M t → Current forest 1,800 M t
Forest delivers 3.7× the water of bare ground.

1. Prefecture-wide summary

Stands processed

1,102stands

Forest area

161,182ha

Water yield

1.8B m³/yr

Bare-ground baseline

0.39B m³/yr

Forest effect

+1.41B m³/yr

+366% (≈19.4 M household-equivalents)

CO₂ absorption

1.55M t-CO₂/yr

What this means: If the 161,182 ha of Shizuoka forest in this report were converted to bare ground (clear-cut and unreplanted), annual water yield would drop from 1.8 B m³ to 0.39 B m³ — a loss of about 1.41 B m³ (≈19.4 million household-equivalents). The public-good function of keeping these forests intact is exactly this delta, quantified.

2. Per-municipality breakdown

Sorted by forest area. This dataset covers the Hamamatsu / Kosai forest planning zone (internal codes in Shizuoka's Forest Cloud). We resolve municipality names via the GSI Japan reverse-geocoding API.

Municipality	Stands	Forest area (ha)	Water yield (m³/yr)	Bare baseline (m³/yr)	Forest effect	CO₂ (t/yr)

3. Calculation method

Per stand:

Stand polygon area (SHAPE_AREA) pulled from Shizuoka Forest Cloud vector tiles
Climate (NASA POWER), elevation (GSI Japan), and geology (AIST Seamless Geological Map) sampled at the stand centroid
Forestry Agency Simplified Evaluation Method Ver.1.0 applied for water yield (evergreen conifer assumed)
Bare-ground baseline: water yield = precipitation × 10% (per the official manual)
CO₂ absorption: IPCC AFOLU Tier 2 (9.62 t-CO₂/ha/yr) × stand area

4. Structural error compression

The Forestry Agency simplified method is originally targeted at stands under 100 ha. We apply it at the stand level (median ≈ 100 ha), which is already a significant accuracy improvement over AOI-wide aggregation. To compress error structurally further:

20 m mesh subdivision for stands >100 ha (Forestry Agency LiDAR integration: Tochigi, Hyogo, Kochi already public)
Replace defaults with measured values for species, age, and density (cross-reference local forest ledgers)
Multi-temporal NDVI consensus to stabilize the forest mask
Integrate AMeDAS for finer climate resolution (50 km → 17 km, monthly → 10-minute)
Move to Tier 3 to compress uncertainty from ±30% to ±10-15%

Each of these is on the implementation roadmap rather than just a disclaimer.

5. Data sources

Stand polygons: Shizuoka Forest Cloud public system (MAGIS.RINPAN vector tiles)
Climate: NASA POWER monthly API (2020-2024 mean)
Elevation: GSI Japan 5 m DEM API
Geology: AIST Seamless Geological Map v2 API
Water-yield formula: Forestry Agency of Japan "Simplified Evaluation Method for Forest Water Yield" Ver.1.0 (March 2026)
CO₂ conversion: IPCC AFOLU 2006 Tier 2 + Forestry Agency yield-prediction tables

※ This report is a third-party estimate aligned with the Forestry Agency of Japan's official formula. It is not an official certification. All numerical values are estimates and do not constitute commercial guarantees.