Spatial Feasibility Analysis of Vietnam's Water-Saving Agricultural Policy in Japan
Vietnam's Alternative Wet Drying (AWD) is an effective water-saving irrigation practice. Can this policy be transported to Japan? What biophysical and institutional constraints determine feasibility?
AWD is a water-saving practice that allows rice paddies to periodically dry between growing stages, reducing irrigation water demand while maintaining yields. It works well in Vietnam due to humid monsoons and established farmer networks. However, traditional water balance models does not account for biophysical constraints. When we add biophysical constraints (slope, soil drainage, pH), suitable area drops from 62% to 18%.
classified as suitable
AWD suitability depends on whether water deficits occur frequently enough to allow safe drying cycles without crop stress. The water balance equation is:
The overestimation problem: The Nelson–Sander model counts dekads (10-day periods) with precipitation deficit, treating all deficits equally. A −5 mm deficit counts the same as a −150 mm deficit, which is not realistic since major precipitation deficits push fields past critical soil-moisture thresholds, flipping them from AWD-suitable into extreme AWD conditions where crop stress and yield loss occur. This leads to inflated suitability estimates that misguide policy decisions.
Rather than counting dekads with any level of precipitation deficit, we implement a threshold-based approach. Areas are suitable only when water deficits does not exceed the safe threshold (−50 mm) that doesn't trigger stress-free drying cycles.
The final AWD suitability map integrates both water balance and biophysical factors. Only areas that are BOTH water-deficit AND biophysically favorable are classified as suitable.
Suitability Reduction: Japan's biophysical constraints (terrain, soil properties, latitude-driven climate) limit suitable area to 18% compared to Vietnam's 45%. Additionally, suitable paddies are far more dispersed, making coordinated extension and farmer networks harder to implement—a critical institutional feasibility issue.
Biophysical suitability is not uniform. Kanto and Tohoku plains (flat, clay-rich soils, moderate moisture) are highly suitable. Southwestern regions (high percolation, poor drainage) and elevated areas (rapid drying, moisture stress) are poorly suited.
Implication: Unlike Vietnam's uniform delta, Japan's rice system spans distinct agroecological zones. Extension strategy cannot be one-size-fits-all. High-suitability zones (Kanto, parts of Tohoku) are good targets; scattered suitable paddies in unfavorable regions should be deprioritized.
Policy transportability fails not because of biophysical impossibility, but because institutional capacity is mismatched to geography. The barriers differ by region:
Critical insight: Institutional barriers are not uniform. High-suitability zones are institutionally feasible with training + pilot programs. Low-suitability zones require structural policy change (subsidies, risk insurance) that extension alone cannot solve. Forcing AWD in fragmented, unsuitable regions wastes resources and erodes farmer trust.
Transportability assessment: AWD is technically feasible in 18% of Japan's paddies, concentrated in Kanto and Tohoku. However, success requires strategic sequencing and institutional alignment.
Target: Kanto Plain + northern Tohoku (≈6% of national rice area)
Regions: Southwest (Kyushu, Shikoku), scattered upland areas (≈12% of national rice area)
| Metric | Phase 1 Impact |
| Area under AWD | 180,000–220,000 ha |
| CH₄ emissions avoided | 0.8–1.2 Mt CO₂eq/year |
| Water savings | 25–35% in target regions |
| Extension cost per hectare | $150–200 (3–5 year amortized) |
Demonstrates how threshold-based water balance models improve suitability assessment, correcting 3.4× overestimation of traditional approaches.
Operationalizes policy transportability concept using composite suitability mapping integrating biophysical and institutional factors.
Informs Japanese Ministry of Agriculture on realistic AWD implementation scope and geographic prioritization for climate adaptation.
Integrates satellite data (slope, soil), climate data (CHIRPS precipitation), and soil properties into unified suitability framework.