VM0042 Carbon Model — Turkish Drip Irrigation Programme

Verra VCS VM0042 v2.2 · IPCC 2019 Tier 1 N₂O · IPCC 2006 SOC · Ex-ante scenario analysis

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WATER SYSTEM DECISION FRAMEWORK — VM0042 Turkish Drip Irrigation Programme

Four water delivery system types are modelled. Each system has a different baseline irrigation practice, pressurization requirement, water tariff structure, energy cost profile, and eligibility for the government electricity subsidy (50% discount when converting to drip). Select the active system in the top control bar to update all cost-benefit calculations.

Attribute Open System
Gravity (Cazibe)		 Open System
Motor Pump (Motopomplu)		 Closed Canal System
Kapalı Basınçlı		 Self-Owned Well
Kuyu / Sondaj
Baseline Irrigation Flood / Furrow
Salma sulama — gravity-fed, no pump		 Sprinkler
Yağmurlama — pump already in place		 Flood / FurrowSprinkler
Either possible (pressurized canal)		 Sprinkler
Well pump powers baseline system
Transition Scenarios Flood → Surface Drip
Flood → SDI		 Sprinkler → Surface Drip
Sprinkler → SDI		 Flood/Spr → Surface Drip
Flood/Spr → SDI		 Sprinkler → Surface Drip
Sprinkler → SDI
Pump / Pressurization New pump required
161,864 TL one-time CAPEX — needed to pressurize drip system		 Check capacity
Existing pump may be reused — verify flow rate for drip		 Not required
Canal already pressurized — connects directly to drip header		 Check capacity
Existing well pump may be reused at different pressure
Baseline Energy Cost Zero
No pump in flood/gravity baseline → 0 kWh/ha		 Normal (1.0×)
Sprinkler pump: water × 0.75 MJ/m³ ÷ 3.6 kWh		 Zero
Pressurized canal provides head — no separate pump energy		 High (1.5×)
Well pump lifts groundwater — 1.5× surface energy
Project Energy Cost (Drip) Extra cost
Starts paying drip pump energy (was 0) — but 50% subsidy applies		 Saving
Drip uses less water → lower energy, plus 50% subsidy		 Zero
Canal pressure unchanged — no pump energy in any scenario		 Saving
Drip uses less water — but no subsidy applies
Electricity Subsidy (50%) ✓ Eligible
Government subsidy on drip pump electricity — open canal systems		 ✓ Eligible
Open canal system — 50% subsidy on project energy applies		 ✗ Not eligible
Closed/pressurized canal — subsidy only for open canal systems		 ✗ Not eligible
Self-owned well — no electricity subsidy
Water Tariff (Baseline) 6,300 TL/ha/yr
Seasonal flat rate — DSİ/sulama birliği		 5,900 TL/ha/yr
Well electricity covers pumping (no water tariff per se)		 6,300 TL/ha/yr
Volumetric hidrant tariff (Netafim data)		 Zero
Farmer owns groundwater — no water fee
Water Tariff (Drip) 4,400 TL/ha/yr
Reduced tariff for drip systems		 4,400 TL/ha/yr
Netafim 2024 drip tariff data		 4,400 TL/ha/yr
Netafim 2024 drip tariff data		 Zero
No water tariff regardless of system type
Water Saving (Flood→Drip) +1,900 TL/ha/yr
≈ $42/ha/yr at 45.43 TL/USD		 +1,500 TL/ha/yr
≈ $33/ha/yr (sprinkler baseline)		 +1,900 TL/ha/yr
≈ $42/ha/yr at 45.43 TL/USD		 Zero
No tariff in any scenario
Surface Drip Lifetime 1 year
Annual tape replacement (open canal sediment)		 1 year
Annual tape replacement		 5 years
Clean pressurized water → longer tape life		 5 years
Clean groundwater → longer tape life
SDI Lifetime 15 years 15 years 15 years 15 years
TKDK Subsidy (Drip CAPEX) Surface Drip: 50%
SDI: 70%		 Surface Drip: 50%
SDI: 70%		 Surface Drip: 50%
SDI: 70%		 Surface Drip: 50%
SDI: 70%
SOC Credit Eligibility Scen A (SD + tillage)Scen C (SDI) Scen A (SD + tillage)Scen C (SDI) Scen AScen C Scen AScen C
Open System — Gravity
Best for: Flood-irrigated fields connected to open canal (DSİ gravity)
Key constraint: Must purchase pump for drip (CAPEX hit)
Energy: Goes from 0 → pays drip pump (partly offset by 50% subsidy)
Water quality: Canal sediment → annual tape replacement
Open System — Motor Pump
Best for: Farms already running sprinkler from open canal
Key constraint: Pump capacity check needed
Energy: Saves energy (less water × 50% subsidy on drip)
Water quality: Canal → annual tape replacement
Closed Canal System
Best for: Farms on pressurized hidrant networks
Key constraint: No pump needed — simplest transition
Energy: Zero in all scenarios (canal pressure)
Water quality: Clean → 5-year tape lifetime
Self-Owned Well
Best for: Farms with private groundwater well
Key constraint: High baseline energy (1.5× factor)
Energy: Saves energy (less water pumped) but no subsidy
Water quality: Clean groundwater → 5-year tape lifetime
IPCC 2019 Tier 1 Parameters — Editable Inputs
Corn — Baseline Fertilizer


Wheat — Baseline Fertilizer


N Reduction Rate (Project)


FracLEACH


Corn — N₂O Calculation Chain (IPCC Tier 1)
Step / ParameterBaselineABCUnit
Wheat — N₂O Calculation Chain (IPCC Tier 1)
Step / ParameterBaselineABCUnit
N₂O Emission Reductions — Scenario Comparison
N₂O Emissions (tCO₂e/ha/yr) — Corn & Wheat by Scenario
Emission Reduction vs Baseline (tCO₂e/ha/yr)
MetricCornWheatRotation Avg

IPCC 2019 Tier 1 Formula:
N₂O-N = N×EF₁ + N_urea×FracGASF_urea×EF₄ + N_dap×FracGASF_dap×EF₄ + N×FracLEACH×EF₅
N₂O (kg/ha) = N₂O-N × 44/28 · tCO₂e/ha = N₂O_kg × GWP/1000
EF₁=0.005 · EF₄=0.01 · EF₅=0.011 · FracGASF_urea=0.15 · FracGASF_dap=0.08 · GWP=273 (AR6)

N₂O Emission Modeling Methodology

Direct and indirect N₂O is modeled under different water and fertilization regimes, following Approach 3 in the VM0042 protocol. The transition from flood to drip reduces waterlogging frequency, shifting production from denitrification-dominated to nitrification-dominated pathways, generally lowering total emissions [1]. In this study, the switch from flood/furrow/sprinkler to surface drip irrigation and sub-surface drip irrigation (SDI) were modeled under various rotation scenarios.

Although the literature provides more precise emission factors (EFs) for flood-irrigated maize [2] and comparative analyses across irrigation systems and crop types [3], no study has explicitly evaluated EFs across comparable drip- and flood-irrigated maize scenarios. To ensure methodological consistency and avoid double counting, the IPCC default EF for all N inputs in dry climates [4], set at 0.005, is applied uniformly across all scenarios.

Indirect N₂O emission factors for atmospheric deposition (EF₄ = 0.010 kg N₂O-N kg⁻¹ NH₃-N) and leaching (EF₅ = 0.011 kg N₂O-N kg⁻¹ N leached) were adopted from IPCC (2019) Tier 1 defaults and held constant across all irrigation scenarios [4]. These factors represent biogeochemical processes occurring after reactive nitrogen leaves the field boundary — atmospheric redeposition and denitrification in receiving water bodies, respectively — and are therefore independent of on-farm irrigation management. Therefore, no scenario-specific adjustment was applied.

For the FracLEACH parameter, the IPCC default value of 0.24 [4] is applied in the baseline scenario. Empirical evidence from maize production systems under semi-arid conditions indicates that drip irrigation reduces nitrogen losses via leaching by approximately 33% compared to flood irrigation [5]. This reduction factor is therefore applied, resulting in an assumed FracLEACH value of 0.16 for drip irrigation. Due to the lack of differentiated data, the same value is also used for the SDI scenario. Furthermore, as the referenced study reports no significant difference in NH₃ volatilization between irrigation methods, FracGASF,urea and FracGASF,DAP are assumed to remain at their IPCC default values of 0.15 and 0.08, respectively, across all scenarios.

References

[1] Gültekin, R., Avağ, K., Görgiişen, C., Öztürk, Ö., Yeter, T. & Bahçeci Alsan, P. (2023). Effect of deficit irrigation practices on greenhouse gas emissions in drip irrigation. Scientia Horticulturae, 310, 111757.

[2] Franco-Luesma, S., Lafuente, V., Alonso-Ayuso, M., Bielsa, A., Kouchami-Sardoo, I., Arrúe, J.L. & Álvaro-Fuentes, J. (2022). Maize diversification and nitrogen fertilization effects on soil nitrous oxide emissions in irrigated Mediterranean conditions. Frontiers in Environmental Science, 10, 914851.

[3] Cayuela, M.L. et al. (2017). Direct nitrous oxide emissions in Mediterranean climate cropping systems: Emission factors based on a meta-analysis of available measurement data. Agriculture, Ecosystems & Environment, 238, 25–35.

[4] Baasansuren, J. et al. (2019). 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories. IPCC, Switzerland.

[5] Di, Y., Gao, Y., Yang, H., Yan, D., Tang, Y., Zhang, W., Hu, Y. & Li, F. (2024). Cutting carbon and nitrogen footprints of maize production by optimizing nitrogen management under different irrigation methods. Frontiers in Plant Science, 15, 1476710.

SOC Reference — SoilGrids (ISRIC) Data for Turkish Agricultural Regions

Click a region to set SOC_REF. Values = OCS 0–30 cm (t C/ha) from SoilGrids REST API (ISRIC, 2024).

Selected: —  |  SOC_REF = 30 t C/ha  
IPCC 2006 Tier 1 — Land Management Factors
FactorValueNote
FLU — Land use (annual cropland)1.00Cropland remaining cropland [IPCC 2006, Table 5.4]
FI_baseline — Input factor (flood)1.00Medium residue, no manure [Table 5.6, warm dry]
FI_project — Input factor (drip)1.11High residue (optimised fertigation → better yield → more residue) [Table 5.6]
FMG_baseline — Full tillage (flood)1.00Full tillage = 1.00 [Table 5.5, warm dry]
FMG_ScenA — Surface drip1.00No tillage change with surface drip lines
FMG_ScenC — SDI (no-till)1.10SDI buried lines → no-till feasible → FMG_no-till [Table 5.5]
Transition period20 yrDefault: 20 years to new SOC equilibrium [IPCC 2006 §2.3.3.1]
C→CO₂ conversion44/12 = 3.667Molecular weight ratio CO₂/C
SOC Stock Calculation Results
ParameterBaselineABCUnit
SOC Accumulation Over 20-Year Transition Period
Cumulative SOC Stock (t C/ha) — IPCC Linear Accumulation
Annual ΔSOC Carbon Credit (tCO₂e/ha/yr)
NPV/ha — Scen A
—
Surface Drip + N₂O + SOC
NPV/ha — Scen B
—
Surface Drip + N₂O only
NPV/ha — Scen C
—
SDI + N₂O + SOC
Programme Carbon Revenue
—
Total USD (all farms, best scenario)
Annual Benefits & Costs Breakdown (USD/ha/yr)
Carbon Revenue Breakdown (per ha/yr)
ComponentScen AScen BScen CUnit
NPV Sensitivity to Carbon Price (per ha)
Cumulative Cash Flow per Farmer (full programme duration)
Year-by-Year Farmer Cash Flow (per ha) — Corn–Wheat Rotation
All values in USD/ha. Odd years = corn, even years = wheat. Carbon revenue starts Y2. Tape replacement and TKDK subsidy schedule depends on selected water system. Scroll right for full 20-year view.
MRV Design Impact on Farmer Cash Flow — Surface Drip & SDI × All 4 MRV Designs
Both irrigation scenarios × 4 MRV designs. SOC App1 = annual credits; App2 = Y6/11/16/21 lump sum. N₂O App1 = measured (×EF ratio×0.95); App3 = IPCC default. Solid = SDI, Dashed = Surface Drip.
Programme Totals (all farms × farm size × duration)
MetricScen AScen BScen CUnit
Turkey Funding Structure — TKDK Subsidy & Ziraat Bank Credit
Government grant covers 50% (surface drip) or 70% (SDI) of system CAPEX. Tape replacement at Y7/Y14 is also subsidized at the same TKDK rate. Farmer can reapply every 5 years for new or expanded systems only. Tillage equipment (direct seeder / min-till planter) is a one-time upfront cost for Scen A & C — not currently subsidized.
Ziraat Bankası 0% nominal credit is more widely used than the grant. At 30% inflation, 0% nominal ≈ −23% real interest — significant hidden subsidy. Equal nominal installments decline in real value each year. Farmer must repay before receiving a new credit for expansion.
Carbon Credits Generated Over Programme Duration (tCO₂e/ha/yr)
Annual Credits per ha — corn/wheat year variation + SOC
Credits Summary
MetricScen AScen BScen C
Total Carbon Revenue — All Farms, Cumulative (USD)
Implementer / Programme Operator Revenue
Cumulative implementer net revenue (after costs)
MRV Operations — Netafim
Certification — Virridy / Verra
Revenue Summary & Partner Viability
Implementer LCCA — Year-by-Year Cash Flow (Netafim & Virridy)
Annual cost and revenue breakdown per partner. Netafim earns from drip equipment sales (shown separately) and its share of carbon revenue. Virridy covers Verra/VVB certification and earns its carbon revenue share. Verra levy applied at each verification event. All values in USD.
Dynamic Enrollment Model — Growth Over Time
Starting from — farms × — ha. Each new cohort starts at base farm size and grows independently.
Total enrolled farms & area over time
Cumulative farmer carbon revenue — dynamic enrollment (Scenario A / B / C)
Implementer cumulative net revenue — dynamic enrollment (Scenario A / B / C)
Implementer Economics × MRV Design — SDI Programme · All 4 Designs
Cumulative implementer net revenue after full MRV costs (from MRV tab parameters) + annual expenses. Irrigation = SDI. Carbon = implementer's share per year. Verification lag applied.
Phased Regional Enrollment Simulator — Cohort SOC Clock

Each region's SOC measurement clock starts from its own enrollment year. Farmers joining later do not inherit existing SOC stock — the 20-year SOC transition process starts from zero.

Region / Phase Start Year Initial Farms ha/farm₀ +Farms/yr Max Farms ha Growth %/yr Max ha/farm
Enrolled area by year — by region (ha)
Cohort-based SOC credit output (tCO₂e/yr) — each region on its own clock
Implementer cumulative net revenue — phased enrollment vs flat baseline (MRV C, SDI)
MRV Cost & Measurement Parameters
SOC Sampling — VM0042 §8.2.1.3
N₂O Sampling
Costs — Lab & Field
Costs — Programme-Level (VM0042 v2.2 CC)
MRV Scenario Comparison — Total Program · 20-Year Horizon
VM0042 v2.2 Corrections & Clarifications (11 Jun 2026) applied: ● Clar. 9 (back-modeling) — App1 t0 SOC cost reduced: only the direct-sampling fraction (100% − back-modeled %) needs physical t0 sampling; rest are estimated from the first 5-yr remeasurement campaign. ● Clar. 9 (MVR true-up) — App1 (Designs A/C) must resubmit MVR to IME after each 5-yr remeasurement; MVR revalidation cost charged ×4 over 20 yr. ● Clar. 8 (App2 remeasurement) — App2 (Designs B/D) must remeasure both project sites and permanent baseline control sites every 5 yr; baseline control site cost added to setup and periodic. ● Clar. 3/5 (EA documentation) — one-time baseline scenario + common-practice desk study per eligibility area (province). Lab distance updated to Ankara TGSKMAE (~600 km from Adana) per Clar. 7.
Scenario A Scenario B Scenario C Scenario D
SOC / N₂O approach App 1 + App 1 App 2 + App 1 App 1 + App 3 App 2 + App 3
Cumulative Net Revenue After MRV Cost
SOC Sampling Optimisation — Net Value vs. Sample Size
Net SOC credit revenue minus SOC-specific sampling cost · total program
Year-by-Year MRV Cost — All 4 Scenarios
Optimal Sample Size by MRV Design — Net Value Analysis
App1 (SOC model, Designs A & C): SE has a model-error floor — more samples help less at high n. MC/sample = 4 events × strata × lab cost × 2 sub-samples.
App2 (direct sampling, Designs B & D): SE is sampling-only, no model floor — more samples always help. MC/sample = 15 events-equivalent × strata × lab cost × 2.
Net value = total SOC credit revenue − SOC-specific sampling & monitoring cost over program horizon. Optimal n* = peak of the net value curve.
Net SOC value vs. samples per stratum — App1 (Designs A, C) and App2 (Designs B, D)
Per-Design Summary at Optimal n*
MRV Economics With Adoption Trajectory — 20-Year Horizon
Revenue and cost are recalculated year-by-year using the enrolled area from Adoption Dynamics (Bass diffusion). The bar chart shows annual carbon revenue vs. total MRV + overhead cost for the best design at the selected year. Why is cumulative NPV negative early on? Fixed overhead costs (VVB $20k/yr, IME/model $8k/yr, chamber lab $14k+/yr) are incurred from Y1, while carbon revenue only starts at Y2 and scales with enrolled area. Programmes stay cash-negative until enrolled area is large enough for revenue to exceed costs. Design D (App3 N₂O, no chambers) has the lowest fixed costs and earliest break-even.
Cumulative implementer NPV — 4 MRV designs (selected farmer scenario)
Annual: carbon revenue vs. total MRV cost (selected design at selected year)
MRV Design × Programme Scale — Implementer NPV Heatmap
Pareto Frontier — Farmer NPV/ha vs Implementer NPV (all design × scale combinations)
Farmer Adoption & Area Expansion — System Dynamics Model
Scen A — Flood → Surface Drip
N₂O + SOC · tillage change required
Verim kaybı korkusu
Geleneksel alışkanlık + yabancı ot sorunu
Scen B — Flood → Surface Drip
N₂O only · programme tillage gerektirmiyor
Verim kaybı korkusu
Programme tillage require etmiyor
Scen C — Flood → SDI
N₂O + SOC · SDI doğal olarak derin sürümü azaltıyor
Verim kaybı korkusu
SDI yeraltı boru → derin sürüm zaten azalıyor
Cumulative adopting farmers — Scenarios A, B, C (Bass diffusion S-curve)
Total enrolled area (ha) — extensive margin × intensive margin
Programme covers yield loss from practice changes → reduces effective δ_fert and δ_till barriers proportionally. Kalitatif bulgular: "en önemli programme design mekanizması" (46 refs, 27 kaynak). Programme bu taahhüdü karşılayacak fonu bulmalı.
Extensive margin: dF/dt = (p + q·F)·(1−F)·N·P_adopt  |  P_adopt_i = σ(β·NPV_i) × (1−δ_fert_i·(1−yg)·%ΔN_i) × (1−δ_till_i·(1−yg))
Intensive margin: ha(age) = ha₀·(1+expand%)^max(0,age−Ziraat_term) ≤ maxHa/farm  |  Dropout: each cohort shrinks by dropout%/yr
Scen A = Flood → Surface Drip + reduced tillage + SOC  ·  Scen B = Flood → Surface Drip, no tillage req.  ·  Scen C = Flood → SDI + SOC
Carbon Credits per Scenario — N₂O & SOC, Timing by MRV Design
Credits are calculated from enrolled area (above) × per-ha emission reductions. MRV design (global selector) sets verification timing: A/C = annual VVB · B = biennial · D = 5-yr lump sum. SOC: App1 (Designs A,C) = annual crediting · App2 (Designs B,D) = lump at Y6/11/16/21.
N₂O credits from enrolled area (tCO₂e) — verification timing per design
SOC credits from enrolled area (tCO₂e) — App1 annual / App2 5-yr lump
Total annual credits — N₂O + SOC combined (tCO₂e/yr), all 3 scenarios
N₂O & SOC Sampling — Optimal n as Programme Scales
n* = total soil cores for the entire programme (not per farm, not per ha). Each extra core reduces sampling uncertainty, unlocking more SOC credits. Marginal revenue (MR) per core scales with enrolled area; optimal n* is where MR = MC. App1 MC = $640/core (4 sampling events); App2 MC = $2,400/core (15 events over 20yr). CV% here = variability of the SOC change (not the absolute stock) — at low CV, the SOC change is measured precisely with few cores; at high CV many more are needed.
40%
Enrolled area @ Y20
Scen A: —
Scen B: —
Scen C: —
App1 opt n* (Scen A): —
App2 opt n* (Scen A): —
Optimal n* vs total enrolled area — App1 (Designs A,C) and App2 (Designs B,D) · stars = Scen A/B/C @ Y20
N₂O Flux Chambers — Designs A & B (App1) only · Power-Analysis Minimum vs Economic Optimum
Designs C/D use IPCC App3 — no flux chambers needed. For App1 (Designs A/B): the VM0042 §8.2.1.3 formula sets a regulatory minimum chamber count based on statistical power; the marginal-revenue analysis finds the economic optimum where the last chamber just pays for itself. The gap between these two lines shows why App1 N₂O is costly: chamber MC often exceeds MR at typical Turkish programme scales, meaning App3 may dominate unless scale is very large.
80%
20%
N₂O optimal chambers vs enrolled area — VM0042 power min (red dashed) vs economic opt (orange) · stars = Scen A/B/C @ Y20
Program Implementer Economics — MRV Cost–Revenue Optimization
Implementer Inputs
—%
MRV costs (VVB, IME, lab) from MRV Design tab settings.
At selected scenario Y20:
① Implementer net value vs sample size n — all 4 MRV designs (at selected scenario Y20 area)
② Implementer NPV vs programme scale (ha) — each design at its optimal n*
③ Optimal MRV design by enrolled area — highest implementer NPV at each scale
④ Annual carbon revenue vs MRV cost — 20-yr trajectory using adoption dynamics (selected scenario, all 4 designs)