Title:	Economic Analysis of Soil and Water Conservation Measures in Watersheds
Version:	0.1.0
Description:	Provides functions and benchmark datasets for the economic appraisal of soil and water conservation (SWC) measures in watershed development projects. Implements benefit-cost ratio (BCR), net present value (NPV), internal rate of return (IRR) via the bisection method of Brent (1973, ISBN:9780130223715), modified BCR, marginal rate of return using the CIMMYT (1988, ISBN:9686127127) method, payback period, soil loss economic valuation via the Universal Soil Loss Equation of Wischmeier and Smith (1978, ISBN:0160016258), groundwater recharge valuation, employment generation ratio, sensitivity analysis, switching value analysis, and Monte Carlo simulation. Six datasets are included: state-wise BCR benchmarks from NABARD (2019) watershed evaluations, USLE erodibility parameters for Indian soil orders from NBSS and LUP, rainfall erosivity for twenty Indian districts from IMD data, SWC unit cost norms from PMKSY-WDC (GoI 2015), and two hypothetical datasets for illustration. Methods follow Gittinger (1982, ISBN:9780801825439) and Squire and van der Tak (1975, ISBN:9780801816697).
License:	GPL (≥ 3)
Encoding:	UTF-8
Language:	en-US
LazyData:	true
RoxygenNote:	7.3.3
Depends:	R (≥ 4.1.0)
Imports:	stats, graphics, grDevices, utils
Suggests:	testthat (≥ 3.0.0), knitr, rmarkdown, covr
VignetteBuilder:	knitr
Config/testthat/edition:	3
NeedsCompilation:	no
Packaged:	2026-04-13 05:18:42 UTC; acer
Author:	Sadikul Islam [aut, cre]
Maintainer:	Sadikul Islam <sadikul.islamiasri@gmail.com>
Repository:	CRAN
Date/Publication:	2026-04-16 20:10:02 UTC

swcEcon: Economic Analysis of Soil and Water Conservation Measures

Description

Provides functions and benchmark datasets for the economic appraisal of soil and water conservation (SWC) measures in watershed development projects. Functions cover financial appraisal (BCR, NPV, IRR, PBP, MRR), soil loss valuation (USLE), water resource valuation, employment generation, sensitivity analysis, switching value, Monte Carlo simulation, a full pipeline runner, and automated HTML report generation.

Author(s)

Maintainer: Sadikul Islam sadikul.islamiasri@gmail.com (ORCID)

References

Brent, R.P. (1973). Algorithms for Minimization Without Derivatives. Prentice-Hall. ISBN: 9780130223715.

CIMMYT (1988). From Agronomic Data to Farmer Recommendations. CIMMYT, Mexico DF. ISBN: 9686127127.

Gittinger, J.P. (1982). Economic Analysis of Agricultural Projects, 2nd ed. Johns Hopkins University Press. ISBN: 9780801825439.

GoI (2015). Common Guidelines for Watershed Development Projects under PMKSY-WDC. Ministry of Rural Development, New Delhi.

Joshi, P.K., Jha, A.K., Wani, S.P., Joshi, L. and Shiyani, R.L. (2005). Meta-Analysis to Assess Impact of Watershed Program and People's Participation. IWMI Research Report 8. ISBN: 9290906677.

NABARD (2019). Operational Guidelines: Watershed Development Fund. National Bank for Agriculture and Rural Development, Mumbai.

Squire, L. and van der Tak, H.G. (1975). Economic Analysis of Projects. Johns Hopkins University Press. ISBN: 9780801816697.

Wischmeier, W.H. and Smith, D.D. (1978). Predicting Rainfall Erosion Losses. USDA Agriculture Handbook No. 537. ISBN: 0160016258.

Benefit-cost ratio for SWC watershed projects

Description

Computes the discounted Benefit-Cost Ratio (BCR) for a SWC project. BCR is the ratio of present value of benefits to present value of costs.

Usage

calc_bcr(
  investment,
  annual_benefit,
  annual_omc = 0,
  life = 20L,
  discount_rate = 0.12,
  residual_value = 0,
  benefit_lag = 0L
)

Arguments

Details

BCR = \frac{\sum_{t=1}^{n} B_t/(1+r)^t + S/(1+r)^n}{ I_0 + \sum_{t=1}^{n} C_t/(1+r)^t}

Decision rules (Gittinger 1982; GoI 2008): BCR > 1.0 is viable; BCR >= 1.5 meets NABARD threshold for watershed funding (NABARD 2019); BCR < 1.0 is not viable at the chosen discount rate.

Value

A named list of class "swcEcon_bcr" with elements: bcr, pv_benefits, pv_costs, verdict, and inputs.

References

Gittinger, J.P. (1982). Economic Analysis of Agricultural Projects, 2nd ed. Johns Hopkins University Press. ISBN: 9780801825439.

GoI (2008). Guidelines for Economic Analysis of Projects. Planning Commission of India, New Delhi.

NABARD (2019). Operational Guidelines: Watershed Development Fund. National Bank for Agriculture and Rural Development, Mumbai.

Examples

calc_bcr(investment = 20, annual_benefit = 6,
         annual_omc = 0.8, life = 20, discount_rate = 0.12)

# With 2-year gestation period
calc_bcr(investment = 35, annual_benefit = 9, annual_omc = 1.2,
         life = 20, discount_rate = 0.12, benefit_lag = 2)

Employment generation ratio for SWC projects

Description

Computes the Employment Generation Ratio (EGR) and checks compliance with the MGNREGS 60 per cent labour norm.

Usage

calc_employment(employment_days, investment_lakh, wages_per_day = 250)

Arguments

Details

EGR = \frac{\text{Person-days}}{\text{Investment (INR lakh)}}

Value

A named list with egr_days_per_lakh, total_wage_bill_inr, labour_share_pct, and mgnregs_60pct_norm.

References

GoI (2023). Mahatma Gandhi National Rural Employment Guarantee Scheme: Operational Guidelines, 4th ed. Ministry of Rural Development, New Delhi.

NABARD (2019). Operational Guidelines: Watershed Development Fund. National Bank for Agriculture and Rural Development, Mumbai.

Examples

calc_employment(employment_days = 45000, investment_lakh = 50,
                wages_per_day = 250)

Internal rate of return for SWC watershed projects

Description

Computes the IRR – the discount rate at which NPV equals zero – using the bisection algorithm of Brent (1973).

Usage

calc_irr(
  investment,
  annual_benefit,
  annual_omc = 0,
  life = 20L,
  lower = 0,
  upper = 2
)

Arguments

Details

Benchmarks: 12 per cent (Planning Commission, GoI 2008); 12–15 per cent (NABARD 2019); 10–15 per cent (World Bank 1998).

Value

A list of class "swcEcon_irr" with irr, irr_pct, converged, and benchmark comparisons.

References

Brent, R.P. (1973). Algorithms for Minimization Without Derivatives. Prentice-Hall. ISBN: 9780130223715.

GoI (2008). Guidelines for Economic Analysis of Projects. Planning Commission of India, New Delhi.

NABARD (2019). Operational Guidelines: Watershed Development Fund. National Bank for Agriculture and Rural Development, Mumbai.

Examples

calc_irr(investment = 20, annual_benefit = 6,
         annual_omc = 0.8, life = 20)

Additional crop income from SWC-enabled irrigation

Description

Additional crop income from SWC-enabled irrigation

Usage

calc_irrigation_benefit(
  irrig_area_ha,
  yield_increase_t_ha,
  crop_price_inr_t,
  input_cost_inr_ha = 8000
)

Arguments

Value

A named list with gross, additional cost, and net benefit.

References

Joshi, P.K., Jha, A.K., Wani, S.P., Joshi, L. and Shiyani, R.L. (2005). Meta-Analysis to Assess Impact of Watershed Program and People's Participation. IWMI Research Report 8. ISBN: 9290906677.

Examples

calc_irrigation_benefit(irrig_area_ha = 80, yield_increase_t_ha = 1.6,
                         crop_price_inr_t = 18000, input_cost_inr_ha = 8000)

Modified benefit-cost ratio

Description

Computes the Modified BCR: MBCR = (TB - OC) / CC (Gittinger 1982).

Usage

calc_mbcr(total_benefit, operating_cost, capital_cost)

Arguments

Value

A list of class "swcEcon_mbcr" with mbcr and interpretation.

References

Gittinger, J.P. (1982). Economic Analysis of Agricultural Projects, 2nd ed. Johns Hopkins University Press. ISBN: 9780801825439.

Examples

calc_mbcr(total_benefit = 80, operating_cost = 12, capital_cost = 20)

Marginal rate of return (CIMMYT method)

Description

Computes MRR following CIMMYT (1988): the return per unit of additional investment when switching from current practice to a SWC technology.

Usage

calc_mrr(nb_with, nb_without, cost_with, cost_without, min_mrr = 100)

Arguments

Details

MRR = \frac{NB_{with} - NB_{without}}{C_{with} - C_{without}} \times 100

A minimum acceptable MRR of 100 per cent is recommended by CIMMYT (1988).

Value

A list of class "swcEcon_mrr" with mrr, marginal_benefit, marginal_cost, and recommendation.

References

CIMMYT (1988). From Agronomic Data to Farmer Recommendations. CIMMYT, Mexico DF. ISBN: 9686127127.

Byerlee, D. and Collinson, M. (1980). Planning Technologies Appropriate to Farmers. CIMMYT, Mexico DF.

Examples

calc_mrr(nb_with = 18000, nb_without = 11000,
         cost_with = 16000, cost_without = 11500)

Net present value for SWC watershed projects

Description

Computes the Net Present Value (NPV) by discounting annual net benefits.

Usage

calc_npv(
  investment,
  annual_benefit,
  annual_omc = 0,
  life = 20L,
  discount_rate = 0.12,
  residual_value = 0
)

Arguments

Details

NPV = \sum_{t=1}^{n}\frac{B_t - C_t}{(1+r)^t} + \frac{S}{(1+r)^n} - I_0

Value

A list of class "swcEcon_npv" with npv, cashflows (data frame), and decision.

References

Gittinger, J.P. (1982). Economic Analysis of Agricultural Projects, 2nd ed. Johns Hopkins University Press. ISBN: 9780801825439.

Squire, L. and van der Tak, H.G. (1975). Economic Analysis of Projects. Johns Hopkins University Press. ISBN: 9780801816697.

Examples

r <- calc_npv(investment = 20, annual_benefit = 6,
              annual_omc = 0.8, life = 20, discount_rate = 0.12)
print(r)
head(r$cashflows)

Nutrient replacement cost from soil erosion

Description

Estimates the annual economic cost of NPK nutrients lost through soil erosion based on soil nutrient content and fertiliser prices.

Usage

calc_nutrient_cost(
  soil_loss_t_ha,
  area_ha,
  n_kg_per_t = 0.5,
  p_kg_per_t = 0.08,
  k_kg_per_t = 1.2,
  n_price = 20,
  p_price = 50,
  k_price = 25
)

Arguments

Value

A named list with nutrient quantities lost and replacement costs.

References

Katyal, J.C. and Sharma, B.D. (1991). Nutrients in soil fertility. Fertiliser News, 36(4), 13–24.

Examples

data(usle_india_soils)
s <- usle_india_soils[usle_india_soils$soil_series == "Alfisols", ]
calc_nutrient_cost(soil_loss_t_ha = 12, area_ha = 200,
                   n_kg_per_t = s$n_kg_per_t,
                   p_kg_per_t = s$p_kg_per_t,
                   k_kg_per_t = s$k_kg_per_t)

Payback period for SWC projects

Description

Computes simple and discounted payback periods and assesses adoption likelihood. PBP is the strongest predictor of voluntary SWC uptake among smallholders in rainfed India (Joshi et al. 2005).

Usage

calc_pbp(
  investment,
  annual_benefit,
  annual_omc = 0,
  life = 20L,
  discount_rate = 0.12
)

Arguments

Value

A list of class "swcEcon_pbp" with simple_pbp, discounted_pbp, and adoption.

References

Joshi, P.K., Jha, A.K., Wani, S.P., Joshi, L. and Shiyani, R.L. (2005). Meta-Analysis to Assess Impact of Watershed Program and People's Participation. IWMI Research Report 8. ISBN: 9290906677.

Singh, A.J., Lal, P. and Sharma, S.K. (2006). Economics of adoption of improved technologies in rainfed farming systems. Indian Journal of Agricultural Economics, 61(3), 420–435.

Examples

calc_pbp(investment = 20, annual_benefit = 6, annual_omc = 0.8)

Economic cost of soil loss using the USLE

Description

Estimates annual economic cost of soil loss using the Universal Soil Loss Equation (Wischmeier and Smith 1978) and converts the reduction achieved by a SWC measure to monetary value.

Usage

calc_soil_loss_cost(
  R,
  K,
  LS,
  C_pre,
  C_post,
  P_pre = 1,
  P_post = 0.5,
  area_ha = 1,
  nutrient_cost_per_t = 1000,
  years = 1
)

Arguments

Details

A = R \cdot K \cdot LS \cdot C \cdot P \quad (t/ha/yr)

The annual economic benefit = (A_pre - A_post) x area x nutrient cost.

Value

A list of class "swcEcon_soil" with soil_loss_pre, soil_loss_post, soil_saved_ha, soil_saved_total, annual_benefit_inr, and pct_reduction.

References

Wischmeier, W.H. and Smith, D.D. (1978). Predicting Rainfall Erosion Losses. USDA Agriculture Handbook No. 537. ISBN: 0160016258.

Singh, G., Babu, R., Narain, P., Bhushan, L.S. and Abrol, I.P. (1992). Soil erosion rates in India. Journal of Soil and Water Conservation, 47(1), 97–99.

Katyal, J.C. and Sharma, B.D. (1991). Nutrients in soil fertility. Fertiliser News, 36(4), 13–24.

Examples

data(usle_india_soils)
K <- usle_india_soils[usle_india_soils$soil_series == "Vertisols", "k_mean"]
calc_soil_loss_cost(R = 720, K = K, LS = 4.2,
                    C_pre = 0.35, C_post = 0.18,
                    P_pre = 1.0, P_post = 0.5, area_ha = 500)

Switching value analysis for SWC projects

Description

Computes how much costs can rise (or benefits fall) before BCR = 1.0. A higher switching value indicates greater robustness to estimation error (Gittinger 1982; World Bank 1998).

Usage

calc_switching_value(
  investment,
  annual_benefit,
  annual_omc = 0,
  life = 20L,
  discount_rate = 0.12
)

Arguments

Value

A list of class "swcEcon_sv" with switching values and interpretations.

References

Gittinger, J.P. (1982). Economic Analysis of Agricultural Projects, 2nd ed. Johns Hopkins University Press. ISBN: 9780801825439.

World Bank (1998). Handbook on Economic Analysis of Investment Operations. World Bank, Washington DC.

Examples

calc_switching_value(investment = 20, annual_benefit = 6,
                      annual_omc = 0.8, life = 20,
                      discount_rate = 0.12)

Groundwater recharge and runoff harvesting value

Description

Estimates annual economic value of water benefits from a SWC watershed intervention.

Usage

calc_water_value(
  area_ha,
  rainfall_mm,
  rc_pre = 0.35,
  rc_post = 0.2,
  harvest_pct = 45,
  gw_recharge_pct = 20,
  water_value_m3 = 3.5
)

Arguments

Details

Runoff volume (m3/yr) = RC x P x A x 10. Annual water benefit = (Q_harvest + Q_recharge) x water_value.

Value

A list of class "swcEcon_water" with runoff volumes and annual_benefit_inr.

References

Joshi, P.K., Jha, A.K., Wani, S.P., Joshi, L. and Shiyani, R.L. (2005). Meta-Analysis to Assess Impact of Watershed Program and People's Participation. IWMI Research Report 8. ISBN: 9290906677.

Examples

data(rainfall_erosivity_india)
rf <- rainfall_erosivity_india[
  rainfall_erosivity_india$district == "Pune", "annual_rf_mm"]
calc_water_value(area_ha = 500, rainfall_mm = rf,
                 rc_pre = 0.35, rc_post = 0.20)

Simulated farm-level SWC adoption survey dataset

Description

A hypothetically generated survey of 120 farm households from four Indian states. SWC adoption modelled via logistic regression. Not real survey data.

Usage

data(farmer_adoption)

Format

A data frame with 120 rows and 10 variables:

farmer_id

Character. Farmer identifier.

state

Character. State (Maharashtra, Rajasthan, Karnataka, MP).

farm_size_ha

Numeric. Farm area (ha).

education_yrs

Integer. Years of formal education.

annual_income_lakh

Numeric. Annual household income (INR lakh).

credit_access

Character. Institutional credit access (Yes/No).

extension_visits

Integer. Extension agent visits per year.

yield_pre_kharif

Numeric. Kharif yield before SWC (t/ha).

adopted_swc

Integer. Adoption: 1 = adopted, 0 = not adopted.

yield_post_kharif

Numeric. Kharif yield after SWC (t/ha); NA for non-adopters.

Details

Data status: HYPOTHETICALLY GENERATED. Not real survey data.

Adoption logit model:

logit(p) = -1.2 + 0.15 \cdot size + 0.08 \cdot edu + 0.20 \cdot income + 0.60 \cdot credit + 0.18 \cdot extension

Simulated adoption rate approx. 63 per cent. set.seed(2025).

Source

Hypothetical. See data-raw/generate_all_datasets.R.

References

Joshi, P.K., Jha, A.K., Wani, S.P., Joshi, L. and Shiyani, R.L. (2005). Meta-Analysis to Assess Impact of Watershed Program and People's Participation. IWMI Research Report 8. ISBN: 9290906677.

Singh, A.J., Lal, P. and Sharma, S.K. (2006). Economics of adoption of improved technologies in rainfed farming systems. Indian Journal of Agricultural Economics, 61(3), 420–435.

Examples

data(farmer_adoption)
mean(farmer_adoption$adopted_swc)
aggregate(adopted_swc ~ state, data = farmer_adoption, FUN = mean)

Generate an automated HTML economic appraisal report

Description

Produces a self-contained HTML report from a run_swc_pipeline result, formatted for NABARD and PMKSY-WDC project proposals.

Usage

generate_swc_report(
  pipeline,
  output_file = "swcEcon_report.html",
  title = "SWC Economic Appraisal Report",
  author = "swcEcon",
  organisation = ""
)

Arguments

Value

Invisibly returns the path to the HTML file.

References

GoI (2015). Common Guidelines for Watershed Development Projects under PMKSY-WDC. Ministry of Rural Development, New Delhi.

NABARD (2019). Operational Guidelines: Watershed Development Fund. National Bank for Agriculture and Rural Development, Mumbai.

Examples

pl  <- run_swc_pipeline(investment = 20, annual_benefit = 6,
                         annual_omc = 0.8, include_sensitivity = FALSE)
tmp <- tempfile(fileext = ".html")
generate_swc_report(pl, output_file = tmp, author = "Researcher")

Monte Carlo simulation for SWC project risk analysis

Description

Stochastic simulation of BCR and NPV distributions. Investment, benefit, and O&M costs are sampled from truncated Normal distributions; project life from a discrete Uniform; discount rate from a continuous Uniform. Follows Pouliquen (1970) as recommended by World Bank (1998).

Usage

monte_carlo_swc(
  inv_mean = 20,
  inv_cv = 0.1,
  ben_mean = 6,
  ben_cv = 0.15,
  omc_mean = 0,
  omc_cv = 0.2,
  life_min = 15L,
  life_max = 25L,
  r_min = 0.1,
  r_max = 0.14,
  n_sim = 5000L,
  seed = 42L
)

Arguments

Value

A list of class "swcEcon_mc" with simulated BCR and NPV vectors, probability estimates, and summary statistics.

References

ADB (2017). Guidelines for the Economic Analysis of Projects. Asian Development Bank, Manila. https://www.adb.org/documents/guidelines-economic-analysis-projects

Pouliquen, L.Y. (1970). Risk Analysis in Project Appraisal. World Bank Occasional Papers No. 11. Johns Hopkins University Press.

World Bank (1998). Handbook on Economic Analysis of Investment Operations. World Bank, Washington DC.

Examples

mc <- monte_carlo_swc(inv_mean = 20, ben_mean = 6, omc_mean = 0.8,
                       n_sim = 1000, seed = 42)
print(mc)

Print a swcEcon_result object

Description

Print a swcEcon_result object

Usage

## S3 method for class 'swcEcon_result'
print(x, ...)

Arguments

Value

Invisibly returns x.

Rainfall erosivity (R-factor) for 20 Indian watershed districts

Description

USLE R-factor and climatological parameters for 20 representative watershed districts across major Indian agro-ecological zones.

Usage

data(rainfall_erosivity_india)

Format

A data frame with 20 rows and 8 variables:

district

Character. District headquarters name.

state

Character. State name.

lat

Numeric. Latitude, decimal degrees (WGS84).

lon

Numeric. Longitude, decimal degrees (WGS84).

annual_rf_mm

Numeric. Mean annual rainfall (mm), 1981–2010.

r_factor

Numeric. USLE R-factor (MJ mm / ha hr yr).

kharif_pct

Numeric. June–September rainfall (per cent).

mean_temp_c

Numeric. Mean annual temperature (degrees C).

Details

Data status: Real – derived from public domain data using published peer-reviewed formulae.

R-factor computed using Modified Fournier Index (MFI) and the regression: R = 38.46 + 3.48 x MFI (Bhattacharyya et al. 2010). Rainfall normals from IMD 0.25-degree gridded dataset, 1981–2010.

Source

IMD 0.25-degree gridded rainfall, 1981–2010. India Meteorological Department, Pune (public domain). https://imdpune.gov.in

References

Bhattacharyya, T., Pal, D.K., Mandal, C. and others (2010). Soils of India: Historical perspective, classification and recent advances. Current Science, 98(9), 1248–1257.

Pai, D.S. and others (2014). Development of a new high spatial resolution long period daily gridded rainfall data set over India. Mausam, 65(1), 1–18.

Examples

data(rainfall_erosivity_india)
rainfall_erosivity_india[rainfall_erosivity_india$r_factor > 900,
  c("district", "state", "r_factor")]

Run the complete swcEcon economic appraisal pipeline

Description

Runs BCR, NPV, IRR, payback period, switching value, and optionally sensitivity analysis and Monte Carlo simulation in a single call.

Usage

run_swc_pipeline(
  investment,
  annual_benefit,
  annual_omc = 0,
  life = 20L,
  discount_rate = 0.12,
  project_name = "SWC Project",
  include_sensitivity = TRUE,
  include_monte_carlo = FALSE,
  n_sim = 2000L,
  ...
)

Arguments

Value

A list of class "swcEcon_pipeline" with steps (sub-module results), summary (data frame), and metadata.

Examples

pl <- run_swc_pipeline(
  investment     = 20,
  annual_benefit = 6,
  annual_omc     = 0.8,
  project_name   = "Hypothetical Check Dam Project",
  include_sensitivity  = FALSE,
  include_monte_carlo  = FALSE
)
print(pl)

Sensitivity analysis for SWC project appraisal

Description

Performs one-at-a-time (OAT) sensitivity analysis varying costs, benefits, and discount rate by specified ranges. Returns an 8-scenario table suitable for a tornado diagram.

Usage

sensitivity_analysis(
  investment,
  annual_benefit,
  annual_omc = 0,
  life = 20L,
  discount_rate = 0.12,
  cost_range_pct = 20,
  benefit_range_pct = 20,
  rate_range_pct = 3
)

Arguments

Details

Required by NABARD (2019) for watershed project appraisal and recommended by World Bank (1998) for agricultural investment projects.

Value

A list of class "swcEcon_sens" with scenarios (data frame), base_bcr, base_npv, and summary.

References

NABARD (2019). Operational Guidelines: Watershed Development Fund. National Bank for Agriculture and Rural Development, Mumbai.

World Bank (1998). Handbook on Economic Analysis of Investment Operations. World Bank, Washington DC.

Examples

sensitivity_analysis(investment = 20, annual_benefit = 6,
                      annual_omc = 0.8, life = 20,
                      discount_rate = 0.12)

State-wise SWC watershed economic benchmarks for India

Description

Typical ranges of BCR, IRR, unit cost, employment generation ratio, and payback period for watershed SWC projects across ten major Indian states. Compiled from published government evaluation reports.

Usage

data(swc_benchmarks)

Format

A data frame with 10 rows and 10 variables:

state

Character. State name.

agro_zone

Character. Agro-ecological zone.

annual_rainfall_mm

Numeric. Mean annual rainfall (mm).

bcr_min

Numeric. Minimum BCR from evaluated projects.

bcr_max

Numeric. Maximum BCR.

bcr_typical

Numeric. Median BCR across evaluations.

irr_pct

Numeric. Typical IRR (per cent).

cost_per_ha

Numeric. Investment cost per ha (INR).

egr_person_days_per_lakh

Numeric. Person-days per INR lakh.

pbp_years

Numeric. Typical payback period (years).

Details

Data status: Real – public domain government documents.

Compiled from NABARD WDF Annual Reports 2010–2022 (National Bank for Agriculture and Rural Development), PMKSY-WDC Progress Reports (https://dolr.gov.in), and CRIDA Technical Bulletins (ICAR). All BCR values computed at 12 per cent discount rate.

Source

NABARD WDF Annual Reports 2010–2022 (public domain). PMKSY-WDC Progress Reports, GoI (public domain).

References

NABARD (2019). Operational Guidelines: Watershed Development Fund. National Bank for Agriculture and Rural Development, Mumbai.

GoI (2015). Common Guidelines for Watershed Development Projects under PMKSY-WDC. Ministry of Rural Development, New Delhi.

Examples

data(swc_benchmarks)
swc_benchmarks[swc_benchmarks$bcr_typical >= 2.0,
               c("state", "bcr_typical", "irr_pct")]

SWC measure unit cost norms (PMKSY-WDC 2015, updated to 2024)

Description

Standard unit costs for 18 common SWC structures from PMKSY-WDC Common Guidelines (GoI 2015), updated to 2024 using RBI CPI.

Usage

data(swc_cost_norms)

Format

A data frame with 18 rows and 7 variables:

measure

Character. SWC measure name.

unit

Character. Cost basis: per unit or per ha.

norm_2015_inr

Numeric. PMKSY-WDC 2015 unit cost (INR).

norm_2024_inr

Numeric. Estimated 2024 unit cost (INR).

design_life_yr

Numeric. Expected design life (years).

omc_pct_capital

Numeric. Annual O&M as per cent of capital.

labour_pct

Numeric. Labour as per cent of total cost.

Details

Data status: Real – public domain Government of India guidelines.

Unit costs from PMKSY-WDC Common Guidelines (GoI 2015), available at https://dolr.gov.in. The 2024 estimates apply a CPI inflation factor of 1.65 (RBI CPI April 2015 to April 2024).

Source

GoI (2015). Common Guidelines for Watershed Development Projects under PMKSY-WDC. Ministry of Rural Development, New Delhi. Available at https://dolr.gov.in.

References

GoI (2015). Common Guidelines for Watershed Development Projects under PMKSY-WDC. Ministry of Rural Development, New Delhi.

CSWCRTI (2019). Technical Manual on Soil and Water Conservation Structures. ICAR, Dehradun (public domain).

Examples

data(swc_cost_norms)
swc_cost_norms[swc_cost_norms$design_life_yr >= 20,
               c("measure", "norm_2024_inr", "design_life_yr")]

USLE erodibility and nutrient parameters for Indian soil orders

Description

Soil erodibility K-factor ranges and NPK nutrient content for eight major soil orders in Indian watersheds.

Usage

data(usle_india_soils)

Format

A data frame with 8 rows and 11 variables:

soil_series

Character. Soil order (USDA classification).

soil_order

Character. Common Indian name.

states_typical

Character. States where order predominates.

k_min

Numeric. Minimum K-factor (t ha hr / ha MJ mm).

k_max

Numeric. Maximum K-factor.

k_mean

Numeric. Mean K-factor for use when site data unavailable.

oc_pct

Numeric. Typical organic carbon (per cent).

t_value

Numeric. Permissible soil loss (t/ha/yr).

n_kg_per_t

Numeric. N per tonne of soil (kg/t).

p_kg_per_t

Numeric. P per tonne (kg/t).

k_kg_per_t

Numeric. K per tonne (kg/t).

Details

Data status: Real – public domain scientific literature.

K-factor values from NBSS and LUP Technical Bulletin No. 132 (ICAR) and Singh et al. (1992). Nutrient content from Katyal and Sharma (1991).

Source

NBSS and LUP (2002). Soil Erodibility (K Factor) of Different Soils of India. Technical Bulletin 132. ICAR, Nagpur.

References

Wischmeier, W.H. and Smith, D.D. (1978). Predicting Rainfall Erosion Losses. USDA Agriculture Handbook No. 537. ISBN: 0160016258.

Singh, G., Babu, R., Narain, P., Bhushan, L.S. and Abrol, I.P. (1992). Soil erosion rates in India. Journal of Soil and Water Conservation, 47(1), 97–99.

Katyal, J.C. and Sharma, B.D. (1991). Nutrients in soil fertility. Fertiliser News, 36(4), 13–24.

Examples

data(usle_india_soils)
usle_india_soils[usle_india_soils$soil_series == "Vertisols", ]

Simulated watershed SWC project evaluation dataset

Description

A hypothetically generated dataset of 50 simulated SWC project evaluations for package illustration. Not real project data.

Usage

data(watershed_projects)

Format

A data frame with 50 rows and 18 variables:

project_id

Character. Identifier (WS001–WS050).

state

Character. Simulated state name.

swc_measure

Character. Primary SWC measure.

area_ha

Numeric. Watershed area (ha).

investment_lakh

Numeric. Capital investment (INR lakh).

annual_benefit_lakh

Numeric. Annual gross benefit (INR lakh).

annual_omc_lakh

Numeric. Annual O&M cost (INR lakh).

discount_rate_pct

Numeric. Discount rate (per cent).

project_life

Numeric. Design life (years).

soil_loss_pre

Numeric. Pre-SWC soil loss (t/ha/yr).

soil_loss_post

Numeric. Post-SWC soil loss (t/ha/yr).

gw_level_change_m

Numeric. Groundwater level change (m).

irrig_area_added_ha

Numeric. Additional irrigated area (ha).

employment_days

Numeric. Employment generated (person-days).

hh_benefited

Numeric. Beneficiary households.

bcr

Numeric. Computed benefit-cost ratio.

npv_lakh

Numeric. Net present value (INR lakh).

pbp_years

Numeric. Simple payback period (years).

Details

Data status: HYPOTHETICALLY GENERATED. Not real project data.

Generated with set.seed(2025). Parameter distributions calibrated to NABARD WDF project characteristics (Joshi et al. 2005). See data-raw/generate_all_datasets.R.

Source

Hypothetical. See data-raw/generate_all_datasets.R.

References

Joshi, P.K., Jha, A.K., Wani, S.P., Joshi, L. and Shiyani, R.L. (2005). Meta-Analysis to Assess Impact of Watershed Program and People's Participation. IWMI Research Report 8. ISBN: 9290906677.

Examples

data(watershed_projects)
summary(watershed_projects$bcr)
aggregate(bcr ~ swc_measure, data = watershed_projects, FUN = mean)