Rainfed_Wheat_Barley_Emergy_Dataset
Description
This dataset supports the findings of the study "Emergy-based sustainability and climate resilience assessment of rain-fed wheat and barley production systems: A multi-regional analysis in Iran" published in Cleaner Environmental Systems. The dataset comprises comprehensive emergy accounting data for rain-fed wheat and barley production systems across ten major Iranian provinces: Kurdistan, East Azerbaijan, Hamadan, Kermanshah, West Azerbaijan, Zanjan, Ardabil, Lorestan, Markazi, and Khuzestan. Data were collected through 450 field questionnaires during the 2023–2024 cropping seasons and supplemented with official statistics from the Iranian Ministry of Jihad-e-Agriculture, the Iran Meteorological Organization, and the Environmental Protection Organization. Soil erosion was estimated using the Revised Universal Soil Loss Equation (RUSLE) model with locally calibrated factors. The dataset includes: 1. Raw input data for wheat (Wheat.csv) and barley (Barley.csv) including solar radiation, wind kinetic energy, rainfall chemical energy, soil organic matter loss, mineral loss from erosion, labor, seeds, machinery, nitrogen fertilizer, phosphorus fertilizer, potash fertilizer, micronutrients, manure, herbicides, fungicides, insecticides, electricity, fuel, and crop yield for each province. 2. Calculated emergy indicators including Transformity (sej/J), Specific Emergy (sej/g), Percent Renewable Emergy (%), Emergy Yield Ratio (EYR), Emergy Investment Ratio (EIR), Environmental Loading Ratio (ELR), Emergy Sustainability Index (ESI), and Emergy Index of Product Safety (EIPS). 3. RUSLE soil erosion factors (R, K, LS, C, P) and estimated soil loss (ton/ha) for each province. 4. Sensitivity analysis results under three climate scenarios: Optimistic (+5% rainfall), Medium (-10% rainfall), and Pessimistic (-20% rainfall), including changes in EYR, ELR, and ESI. 5. Composite Resilience Index (CIR) calculations for each province under drought stress. All emergy calculations follow the standard framework of Odum (1996) and Brown & Ulgiati (2004) using the 12.0E+24 sej/yr global emergy baseline. Unit Emergy Values (UEVs) were sourced from standard references including Brown (2002), Brown & Ulgiati (2004), and Wang et al. (2024). This dataset enables full reproducibility of the study and facilitates comparative emergy assessments of rain-fed cereal systems in other semi-arid regions worldwide. Researchers can use this data to validate emergy models, conduct meta-analyses, or develop sustainable agricultural policies. The data are provided in CSV and Excel formats with a complete Data Dictionary (Data_Dictionary.xlsx) and a README.md file explaining variable definitions, units, and methodological notes. This work was financially supported by the University of Zabol under Grant No. IR-UOZ-GR-6673.
Files
Steps to reproduce
This section provides step-by-step instructions to reproduce all emergy calculations and indicators reported in the study. STEP 1: DATA COLLECTION - Obtain field data from 450 questionnaires distributed across ten provinces (see manuscript Table 1 for province selection criteria). Questionnaires captured input quantities including seed (kg/ha), labor (hours/ha), machinery (hours/ha), chemical fertilizers (kg/ha), manure (kg/ha), pesticides (L/ha), electricity (kWh/ha), and fuel (L/ha). - Collect provincial climate data (solar radiation, wind speed, rainfall) from the Iran Meteorological Organization. - Obtain official crop yield statistics from the Iranian Ministry of Jihad-e-Agriculture (5-year average 2019-2023). - Collect soil property data (texture, organic matter, structure, permeability) from the Environmental Protection Organization. STEP 2: SOIL EROSION ESTIMATION (RUSLE MODEL) - Calculate rainfall erosivity (R factor) using long-term rainfall data from provincial meteorological stations. - Determine soil erodibility (K factor) from soil texture and organic matter content (Walkley-Black wet oxidation method). - Derive slope length and steepness (LS factor) from a 30m resolution Digital Elevation Model (DEM). - Assign cover management (C factor) based on crop type (wheat/barley) and regional management practices. - Assign support practice (P factor) based on conservation practices (e.g., contour farming). - Compute annual soil loss (ton/ha) using: A = R × K × LS × C × P. STEP 3: EMERGY CONVERSION - Convert all physical inputs to solar emergy (sej) using Unit Emergy Values (UEVs) provided in manuscript Table 2. - Classify inputs into four categories: * R: Environmental renewable (solar, wind, rainfall chemical energy) * N: Environmental non-renewable (soil organic matter loss, mineral loss from erosion) * FR: Purchased renewable (10% labor, 20% seeds, 20% manure) * FN: Purchased non-renewable (90% labor, 80% seeds, 80% manure, all chemical fertilizers, pesticides, fuel, electricity, machinery) - Calculate total emergy input (sej/ha/yr) as: Total = R + N + FR + FN. STEP 4: CALCULATE EMERGY INDICATORS - Transformity (Tr) = Total emergy ÷ Output energy (J/ha) - Specific Emergy (SpE) = Total emergy ÷ Output mass (g/ha) - Percent Renewable (%R) = (R ÷ Total) × 100 - Emergy Yield Ratio (EYR) = Total ÷ (FR + FN) - Emergy Investment Ratio (EIR) = (FR + FN) ÷ (R + N) - Environmental Loading Ratio (ELR) = (N + FN + FR) ÷ R - Modified ELR (ELR*) = (N + FN) ÷ (R + FR) - Emergy Sustainability Index (ESI) = EYR ÷ ELR - Modified ESI (ESI*) = EYR ÷ ELR* - Emergy Index of Product Safety (EIPS) = Output emergy ÷ Chemical input emergy
Institutions
- Zabol UniversitySistan and Baluchestan, Zabol