Water accounting - Water Resource Management

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Runoff Coefficient Calculation

The runoff coefficient is a dimensionless parameter that represents the fraction of rainfall that becomes surface runoff. It is calculated based on the land use composition within the dam's watershed using OpenStreetMap data.

Quick Navigation

💧 What is Runoff Coefficient? 📊 Calculation Method 🌍 Land Use Types 🔧 How to Use

💧 What is Runoff Coefficient?

Definition

The runoff coefficient (C) is a dimensionless number between 0 and 1 that represents the proportion of rainfall that becomes surface runoff rather than infiltrating into the soil or being evaporated.

Interpretation

C = 0.0: All rainfall infiltrates (e.g., dense forest)
C = 0.5: Half the rainfall becomes runoff (e.g., mixed land use)
C = 1.0: All rainfall becomes runoff (e.g., impervious surfaces)

Why It Matters

The runoff coefficient is essential for:
• Estimating peak discharge during rainfall events
• Designing dam spillways and flood management systems
• Calculating water availability for irrigation and supply
• Assessing watershed response to land use changes

📊 Calculation Method

Weighted Average Approach

$C_{watershed} = \frac{\sum_{i=1}^{n} (C_i \times A_i)}{A_{total}}$

Where:
• $C_i$ = Runoff coefficient for land use type i
• $A_i$ = Area of land use type i within the watershed
• $A_{total}$ = Total watershed area
• $n$ = Number of different land use types

Data Source

Land use data is obtained from OpenStreetMap (OSM) using the Overpass API. The system queries the watershed boundary polygon and extracts all tagged features with landuse, natural, and building attributes.

Processing Steps

Retrieve watershed boundary from DamWatershed model
Query OpenStreetMap for land use features within the watershed
Clip land use polygons to watershed boundary
Calculate area of each land use type
Apply runoff coefficient for each land use type
Calculate weighted average runoff coefficient

🌍 Land Use Types and Coefficients

The following table shows typical runoff coefficients for different land use types:

Land Use Type	Coefficient	Description
Forest / Wood	0.10 - 0.15	Dense vegetation, high infiltration
Grassland / Meadow	0.15 - 0.25	Moderate infiltration
Farmland / Agricultural	0.30 - 0.45	Cultivated land with variable infiltration
Residential (Low Density)	0.40 - 0.50	Scattered buildings with green space
Residential (High Density)	0.60 - 0.70	Dense urban development
Commercial / Retail	0.80 - 0.90	Mostly impervious surfaces
Industrial	0.70 - 0.80	Factories and warehouses
Wetland / Water	0.05	High infiltration and storage

Note

If a land use type is not found in the watershed, a default coefficient of 0.50 is used. The final watershed runoff coefficient is the area-weighted average of all identified land use types.

🔧 How to Use

Step 1: Download Watershed

First, download the watershed boundary for your dam using the 'Download Watershed' button in the Watershed Information section. This delineates the drainage area that contributes runoff to your dam.

Step 2: Calculate Runoff Coefficient

Click the calculator button next to the 'Runoff Coefficient' field. The system will:
• Query OpenStreetMap for land use data within the watershed
• Calculate the area of each land use type
• Compute the weighted average runoff coefficient
• Automatically populate the field with the calculated value

Step 3: Review Results

A success notification will show the calculated coefficient and the dominant land use type. The browser console will display a detailed breakdown of all land use types found in the watershed.

Step 4: Manual Adjustment (Optional)

You can manually adjust the runoff coefficient if you have local knowledge or more detailed land use data. The calculated value serves as a good starting point based on OSM data.

💡 Key Insights

Urbanized watersheds have higher runoff coefficients (more impervious surfaces)
Forested watersheds have lower runoff coefficients (more infiltration)
The runoff coefficient affects peak discharge calculations in the Rational Method
Land use changes (e.g., deforestation) will increase the runoff coefficient
OSM data quality varies by region; verify results with local knowledge
The calculation uses the Rational Method formula: Q = C × I × A

References

Runoff coefficients are based on standard hydrological references and vary by soil type, slope, and vegetation. The values used here are typical for the Rational Method and may need adjustment based on local conditions. For more information, consult hydrological design manuals or local water resource agencies.

Dam Water Balance Calculation

The water balance calculation determines how water flows through the dam system, accounting for inflows, losses, and outputs. It helps predict dam storage levels, spillway discharge, and water availability for supply.

Quick Navigation

💧 Inflows 💨 Losses ⚖️ Balance & Outputs 📊 Calculation Method

💧 Inflows

Total Inflow (Mm³)

$Q_{inflow} = Q_{rainfall} + Q_{runoff} + Q_{allocated}$

Where:
• $Q_{rainfall}$ = Direct rainfall on dam surface (Mm³)
• $Q_{runoff}$ = Runoff from watershed (Mm³)
• $Q_{allocated}$ = Water allocated to dam from other sources (Mm³)

This is the total water entering the dam system during the turn.

Rainfall Inflow Calculation

$Q_{rainfall} = (P \times A_{surface}) / 1000$

Where:
• $P$ = Annual precipitation (mm)
• $A_{surface}$ = Dam surface area (km²)
• 1000 = Conversion factor (mm to m, km² to Mm³)

Direct rainfall falling on the dam water surface.

Runoff Inflow Calculation

$Q_{runoff} = (P \times A_{watershed} \times C) / 1000$

Where:
• $P$ = Annual precipitation (mm)
• $A_{watershed}$ = Watershed area (km²)
• $C$ = Runoff coefficient (0-1)
• 1000 = Conversion factor

Runoff generated from rainfall over the watershed, adjusted by the runoff coefficient based on land use.

💨 Losses

Evaporation Loss (Mm³)

$Q_{evap} = (E \times A_{surface} \times 365) / 1000000$

Where:
• $E$ = Daily evaporation rate (mm/day)
• $A_{surface}$ = Dam surface area (km²)
• 365 = Days per year
• 1000000 = Conversion to Mm³

Water lost to evaporation from the dam surface. Higher in arid climates and during hot seasons.

Seepage Loss (incl. Infiltration) (Mm³)

$Q_{seepage} = (S \times A_{surface} \times 365) / 1000000$

Where:
• $S$ = Daily seepage rate (mm/day)
• $A_{surface}$ = Dam surface area (km²)
• 365 = Days per year
• 1000000 = Conversion to Mm³

Water lost through seepage through dam walls and infiltration into surrounding soil. Depends on dam construction quality and soil permeability.

Total Losses (Mm³)

$Q_{losses} = Q_{evap} + Q_{seepage}$

Sum of all water losses from the dam system.

⚖️ Balance & Outputs

Net Inflow (Mm³)

$Q_{net} = Q_{inflow} - Q_{losses}$

Water available after accounting for losses. This is the net water that can be stored or released from the dam.

Spillway Discharge (Mm³)

$Q_{spillway} = \max(0, V_{current} + Q_{net} - V_{capacity})$

Where:
• $V_{current}$ = Current dam volume (Mm³)
• $Q_{net}$ = Net inflow (Mm³)
• $V_{capacity}$ = Total dam capacity (Mm³)

Water that must be released through spillways when the dam reaches capacity. Prevents overflow and dam failure.

Storage % (Percentage)

$Storage\% = \frac{V_{current} + Q_{net} - Q_{spillway}}{V_{capacity}} \times 100$

Percentage of dam capacity filled after accounting for inflows, losses, and spillway discharge. Indicates dam fullness level.

Water Supply (Mm³)

$Q_{supply} = \min(Q_{available}, Q_{demand})$

Where:
• $Q_{available}$ = Available volume for allocation (Mm³)
• $Q_{demand}$ = Total water demand from allocations (Mm³)

Water that can be supplied to users. Limited by available volume and total demand.

Hydropower Generation (MWh)

$E = Q_{discharge} \times H \times \rho \times g \times \eta / 3600000$

Where:
• $Q_{discharge}$ = Water discharge through turbines (m³)
• $H$ = Gross head (m)
• $\rho$ = Water density (1000 kg/m³)
• $g$ = Gravitational acceleration (9.81 m/s²)
• $\eta$ = Turbine efficiency (0-1)
• 3600000 = Conversion to MWh

Electrical energy generated from water flowing through turbines. Only calculated if hydropower is enabled.

📊 Calculation Method

Runoff Calculation Methods

The system supports two methods for calculating runoff from precipitation:

SCS Curve Number Method: Uses curve number (CN) based on soil type and land use. More complex but more accurate for different soil conditions.
Rational Method: Uses runoff coefficient (C) directly. Simpler and faster, suitable for small watersheds.

SCS Curve Number Method

$Q = \frac{(P - I_a)^2}{P - I_a + S}$

Where:
• $P$ = Precipitation (mm)
• $I_a$ = Initial abstraction (mm) = 0.2 × S
• $S$ = Maximum potential retention (mm) = (25400/CN) - 254
• $CN$ = Curve number (30-100)

More accurate for varying soil and land use conditions.

Rational Method

$Q = C \times I \times A$

Where:
• $C$ = Runoff coefficient (0-1)
• $I$ = Rainfall intensity (mm/time)
• $A$ = Watershed area (km²)

Simpler method, suitable for small watersheds and quick estimates.

💡 Key Insights

Water balance is calculated annually based on input parameters
Evaporation and seepage are significant losses in arid climates
Spillway discharge prevents dam overflow and ensures safety
Storage percentage indicates dam fullness and water availability
Hydropower generation depends on discharge volume and head height
Water supply is limited by available volume and user demand
Runoff coefficient significantly affects inflow calculations
All calculations assume steady-state conditions over the year

⚠️ Important Notes

These calculations are simplified and assume uniform conditions throughout the year
Actual water balance may vary seasonally and require more detailed modeling
Evaporation and seepage rates should be calibrated with local data
Runoff coefficient can be calculated automatically from watershed land use
Water supply is constrained by available volume and cannot exceed capacity
Hydropower generation requires both discharge and head to be positive

Runoff Calculation

Runoff is the portion of precipitation that flows over the land surface into streams and rivers. The calculated runoff depends on the selected calculation method and watershed characteristics.

Quick Navigation

💧 What is Runoff? 📊 SCS Method 📈 Rational Method 🔧 Affecting Factors

💧 What is Runoff?

Definition

Runoff is the water that flows over the land surface after precipitation. It includes direct runoff from rainfall and baseflow from groundwater. The amount of runoff depends on precipitation, watershed characteristics, soil type, land use, and antecedent moisture conditions.

Runoff Components

Direct Runoff: Water flowing directly over the surface during and immediately after rainfall
Interflow: Water moving laterally through the soil
Baseflow: Groundwater contribution to streamflow

📊 SCS Curve Number Method

Formula

$Q = \frac{(P - I_a)^2}{P - I_a + S}$

Where:
• $Q$ = Direct runoff (mm)
• $P$ = Precipitation (mm)
• $I_a$ = Initial abstraction (mm) = 0.2 × S
• $S$ = Maximum potential retention (mm) = (25400/CN) - 254
• $CN$ = Curve Number (30-100)

Conversion to Mm³

$Q_{Mm^3} = \frac{Q_{mm} \times A_{km^2}}{1000}$

• $Q_{mm}$ = Runoff in millimeters
• $A_{km^2}$ = Watershed area in square kilometers
• 1000 = Conversion factor to Mm³

Curve Number (CN) Values

CN depends on soil type and land use:
• Low CN (30-50): Forests, grasslands, sandy soils
• Medium CN (50-75): Agricultural land, mixed soil types
• High CN (75-100): Urban areas, clay soils, impervious surfaces

📈 Rational Method

Formula

$Q = C \times (P - ET) \times A$

Where:
• $Q$ = Runoff (Mm³)
• $C$ = Runoff coefficient (0-1)
• $P$ = Annual precipitation (mm)
• $ET$ = Evapotranspiration during rainfall season (mm)
• $A$ = Watershed area (km²)

Conversion to Mm³

$Q_{Mm^3} = \frac{C \times (P - ET) \times A}{1000}$

• $C$ = Runoff coefficient (0-1)
• $P$ = Annual precipitation (mm)
• $ET$ = Evapotranspiration (mm)
• $A$ = Watershed area (km²)
• 1000 = Conversion factor to Mm³

Note: The evapotranspiration is subtracted from precipitation to account for water losses due to evaporation and plant transpiration during the rainfall season. Only the remaining water can become runoff.

Runoff Coefficient (C) Values

C depends on land use and soil permeability:
• Low C (0.05-0.20): Forests, wetlands, sandy soils
• Medium C (0.20-0.50): Grasslands, agricultural land
• High C (0.50-1.00): Urban areas, impervious surfaces

🔧 Factors Affecting Runoff

Precipitation

Higher precipitation increases runoff. The relationship is non-linear due to initial abstraction and infiltration.

Soil Type

Soil infiltration capacity affects runoff. Clay soils have low infiltration (high runoff), while sandy soils have high infiltration (low runoff).

Land Use

Vegetation and surface cover affect runoff. Forests and grasslands reduce runoff, while urban areas and impervious surfaces increase it.

Watershed Slope

Steeper slopes increase runoff velocity and reduce infiltration time, resulting in higher runoff.

Antecedent Moisture

Soil moisture before rainfall affects infiltration capacity. Wet soils have less infiltration capacity, resulting in higher runoff.

💡 Key Insights

SCS method is more accurate for design storms and accounts for soil-vegetation interactions
Rational method is simpler and suitable for small watersheds and quick estimates
Runoff increases with watershed area and precipitation
Urbanization increases runoff by reducing infiltration
The calculated runoff is used to estimate dam inflow

Note

The calculated runoff is automatically updated when you change the precipitation, watershed area, calculation method, curve number, or runoff coefficient. This value represents the annual runoff from the watershed that contributes to dam inflow.

Pumping Station Data Configuration

Year: Loading year information...

Allocated Water

Water Allocation

Available Volume for Allocation (Mm³):

Total Allocated: 0 Mm³

Available for Allocation: 0 Mm³

Pumping Station Metrics

Total pumped water (Mm³):

Total energy consumption (mWh):

Total energy cost (million money):

Total exported salts (tons):

Pumping Station Design

Basic Information

Configuration Name:

Pump Type:

Power Source:

Control System:

Pumping Capacity

Design Capacity (m³/day):

Current Pumping Rate (m³/day):

Maximum Pumping Rate (m³/day):

Total Dynamic Head (m):

Static Head (m):

Friction Losses (m):

Water Salinity (mg/l):

Pump Configuration

Number of Pumps:

Pumps in Operation:

Standby Pumps:

Pump Efficiency (%):

Motor Efficiency (%):

Energy price (money/kWh):

Operating Hours/Day:

Power and Energy

Installed Power (kW):

Operating Power (kW):

Energy Consumption (kWh/day):

Pumping Station Performance

Performance Metrics

Operational Status:

Capacity Utilization (%):

Availability (%):

Reliability Score:

Automation Level (%):

Renewable Energy (%):

Financial Performance

Annual Operating Cost:

Annual Revenue:

Cost per m³ Pumped:

Jobs Created:

Wastewater Asset Editor

Wastewater Treatment Plant Data

Turn-aware

Review treatment capacity, water quality, resource recovery, and financial performance using the same compact interface language as the main game form.

Plant Configuration

Edit wastewater treatment assumptions

Keep annual data, allocation logic, treatment performance, and calculated outcomes in one modal without changing the existing save and load workflow.

Water allocation Treatment metrics Financial results

Water Allocation

Available Volume: Mm³

Total Allocated: 0.0 Mm³

Available For Allocation: 0.0 Mm³

Configuration Name

Treatment Level

Treatment Technology

Operational Status

Drinking Water Treatment Plant Data

Year: Select the year for this data

Allocated Water

Water Allocation

Available Volume for Allocation (Mm³):

Total Allocated: 0 Mm³

Available for Allocation: 0 Mm³

Configuration Name

Treatment Level

Primary Treatment Technology

Water Source

Operational Status

Water Quality Rating

Drinking Water Network Data

Year: Select the year for this data

Allocated Water

Water Allocation

Available Volume for Allocation (Mm³):

Total Allocated: 0 Mm³

Available for Allocation: 0 Mm³

Network Name

Network Type

Total Length (km)

Average Pipe Diameter (mm)

Pipe Material

Average Pipe Age (years)

Design Capacity (m³/day)

Current Flow (m³/day)

Peak Demand (m³/day)

Average Pressure (bar)

Minimum Pressure (bar)

Maximum Pressure (bar)

Desalination Plant Data

Year: Select the year for this data

Allocated Water

Water Allocation

Available Volume for Allocation (Mm³):

Total Allocated: 0 Mm³

Available for Allocation: 0 Mm³

Configuration Name

Desalination Technology

Feed Water Source

Operational Status

Product Water Quality Rating

Asset Lifespan (years)

Transfer Data

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Allocated Water

Water Allocation

Available Volume for Allocation (Mm³):

Total Allocated: 0 Mm³

Available for Allocation: 45.0 Mm³

Configuration Name

Transfer Type

Water Source

Operational Status

Transfer Distance (km)

Elevation Gain (m)

Irrigated Perimeter Controls

Edit agricultural production assumptions

Keep water allocations, crop-level parameters, irrigation methods, productivity targets, and future interventions aligned without changing the existing data workflow.

Water allocation aware Cropping systems WEFE indicators

Allocated Water

Water Allocation Summary

Total Water Allocated: 0.0 Mm³

Number of Sources: 0

Average per Source: 0.0 Mm³

Turn: 1

Water Strategy: Water allocations include formal allocations from dams, resource nodes, and other water infrastructure assets. Each cropping system can specify water sources based on availability and crop requirements.

🌾 Water-Food Nexus: Agriculture consumes 70% of global freshwater. Efficient irrigation systems and crop selection optimize water productivity. Virtual water content varies by crop type: cereals (1,000-3,000 L/kg), vegetables (200-400 L/kg), fruits (500-1,000 L/kg).

Irrigation system metrics

Total Cultivated Area (ha): 0

Water Requirement (Mm³): 0 Mm³

Water Demand (Mm³): 0 Mm³

Water consumption (m³/ha): 0.00

Water Demande staristaction (%): 0.00

Rainfall inflow (Mm³): 0.000 Mm³

Energy Demand (GWh): 0 GWh

Energy consumption (kWh/ha): 0.00

Energy Use Efficiency (KWh/m³): 0.00

Mechanization energy consumption (GWh): 0 GWh

Average Water Productivity (money/m³): 0.00

Groundwater recharge (Mm³): 0.000

Recycled Water (Mm³): 0.000

Part of infiltration (0-1): Aquifer:

Part of runoff (0-1): River:

Part of evaporation (0-1):

Crop Water Cost (M): 0

Crop Energy Cost (M): 0

Crop Labour Cost (M): 0

Crop Mechanization Cost (M): 0

Crop Seeds Cost (M): 0

Nitrogen Cost (M): 0

Fertilizer Cost (M): 0

Pesticide Cost (M): 0

Other Production Cost (M): 0

Total Crop Cost (M): 0

Total Revenue (M): 0

Total Gross Profit (M): 0

Exported Salts (M kg): 0

Imported Salts (M kg): 0

Nitrate Pollution (M kg): 0

Pesticide Pollution (M kg): 0

Total CO₂ Emissions (M kg CO₂): 0

Total Carbon Footprint (M kg CO₂e): 0

Number of Systems: 0

Water Demand Satisfaction

Allocate total water demand satisfaction by source. Specify how the total perimeter water demand will be met from different water sources.

Select Dam Asset: Dam Volume (Mm³):

Select Transfer Asset: Transfer Volume (Mm³):

Select Aquifer Resource: Aquifer Volume (Mm³):

Select River Resource: River Volume (Mm³):

Select Wastewater Asset: Wastewater Volume (Mm³):

Select Desalination Asset: Desalination Volume (Mm³):

Select Rain Harvest Asset: Rain Harvest Volume (Mm³):

Total Allocated: 0.000 Mm³

Total Required: 0.000 Mm³

Not Satisfied

Irrigation System Data

🌾 Area & Water Demand

Total Area (ha):

Irrigated Area (ha):

Water Demand (m³/ha/year):

Rainfall (mm/year):

Cropping Systems

No cropping systems added yet. Click 'Add Cropping System' to start.

Download Satellite Data

Download satellite data for your asset including rainfall, temperature, evapotranspiration, land cover, productivity, and soil moisture data from various sources like NASA, CHIRPS, and WAPOR.

📊 Available Data Types

💧 Rainfall

Download precipitation data from multiple sources:

NASA: Global Precipitation Measurement (GPM) data
CHIRPS: Climate Hazards Group InfraRed Precipitation with Station data
WAPOR: FAO WaPOR precipitation data

🌡️ Temperature

NASA temperature data including minimum, maximum, and average temperatures.

💨 Evapotranspiration

WAPOR evapotranspiration data:

AETI: Actual Evapotranspiration and Interception
RET: Reference Evapotranspiration

🗺️ Land Cover Classification

Land cover classification data from WAPOR and Copernicus sources.

🌾 Productivity

WAPOR productivity indicators:

NPP: Net Primary Production
GBWP: Gross Biomass Water Productivity

🌱 Soil Moisture

WAPOR Relative Soil Moisture (RSM) data.

📝 How to Download Data

Select Date Range: Choose the start and end dates for your data download.
Choose Data Category: Select from Rainfall, Temperature, Evapotranspiration, Land Cover, Productivity, or Soil Moisture.
Select Specific Data Type: Choose the specific data source (e.g., NASA, CHIRPS, WAPOR).
Optional - Download TIF: Check this option to also download the raw GeoTIFF files.
Click Download: The data will be processed and downloaded as a CSV file with time series data.

📄 Output Format

Downloaded data is provided in CSV format with the following columns:

Date: The date of the observation
Value: The measured value (units depend on data type)
Source: The data source (NASA, CHIRPS, WAPOR, etc.)

Tips

Larger date ranges may take longer to process
TIF files are large - only download if you need the raw geospatial data
Some data types may not be available for all date ranges
Data is automatically aggregated for your asset's geographic boundary

Water Requirements Calculator

Rainfall Data Source:

Asset time series Nearest weather station

Select Calculation Period

Reference ET0 Start Year:

Reference ET0 End Year:

Rainfall Start Year:

Rainfall End Year:

ET0 Data Source

Info: Select the ET0 data source for scenario time series rainfall calculations.

ET0 calculated using:

Crop Information

Selected Crop:

-

Reduction Coefficient:

-

Monthly Crop Coefficients (Kc):

Jan: -

Feb: -

Mar: -

Apr: -

May: -

Jun: -

Jul: -

Aug: -

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Nov: -

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Calculation Results

Calculated Water Requirement: -

(ET0 × Kc) mm/year

Calculated irrigation demand: -

(ET0 × Kc - Effective Rainfall) mm/year

Data Sources Used

ET0 Source: -

Rainfall Source: -

Monthly Average ET0 Values (mm/month):

Jan: -

Feb: -

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Average Annual ET0: 0 mm/year

Monthly Average Rainfall Values (mm/month):

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Annual Rainfall Total: 0 mm/year

Monthly Effective Rainfall Values (mm/month): (Rainfall × Effective Rainfall Coefficient)

Jan: -

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Annual Effective Rainfall Total: 0 mm/year

Water Requirements Calculator - All Cropping Systems

Rainfall Data Source:

Asset time series Nearest weather station

Select Calculation Period

Reference ET0 Start Year:

Reference ET0 End Year:

Rainfall Start Year:

Rainfall End Year:

View Results by Cropping System and Year

Select Cropping System:

Select Year (Turn):

Select a cropping system and year to view calculated water requirements for that specific turn.

Crop Information

Selected Crop:

-

Reduction Coefficient:

-

Monthly Crop Coefficients (Kc):

Jan: -

Feb: -

Mar: -

Apr: -

May: -

Jun: -

Jul: -

Aug: -

Sep: -

Oct: -

Nov: -

Dec: -

Calculation Results

Calculated Water Requirement: -

(ET0 × Kc) mm/year

Calculated irrigation demand: -

(ET0 × Kc - Effective Rainfall) mm/year

Monthly Average ET0 Values (mm/month):

Jan: -

Feb: -

Mar: -

Apr: -

May: -

Jun: -

Jul: -

Aug: -

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Average Annual ET0: 0 mm/year

Monthly Average Rainfall Values (mm/month):

Jan: -

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Annual Rainfall Total: 0 mm/year

Monthly Effective Rainfall Values (mm/month):

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Annual Effective Rainfall Total: 0 mm/year

How Water Requirements Are Calculated

Water requirements for irrigation are calculated using the FAO Penman-Monteith method, which considers crop water needs, evapotranspiration, rainfall, and irrigation efficiency.

Main Formula

$$WR = \frac{ET_c - P_e}{IE}$$

Where:

$WR$ = Water Requirement (mm/year)
$ET_c$ = Crop Evapotranspiration (mm/year)
$P_e$ = Effective Rainfall (mm/year)
$IE$ = Irrigation Efficiency (decimal)

Calculation Steps

Step 1: Calculate Reference Evapotranspiration ($ET_0$)

ET0 represents the evapotranspiration rate from a reference surface (grass). It is calculated using meteorological data including temperature, humidity, wind speed, and solar radiation. The system uses data from NASA POWER or WaPOR sources.

Step 2: Calculate Crop Evapotranspiration ($ET_c$)

ETc is calculated by multiplying ET0 by the crop coefficient (Kc) for each month:

$$ET_c = ET_0 \times K_c \times K_{red}$$

Kc varies by crop type and growth stage. K_red is the reduction coefficient accounting for partial ground cover or stress conditions.

Step 3: Calculate Effective Rainfall ($P_e$)

Not all rainfall is available for crop use. Effective rainfall accounts for losses due to runoff and deep percolation:

$$P_e = P \times C_{eff}$$

The effective rainfall coefficient typically ranges from 0.6 to 0.8, depending on soil type, slope, and rainfall intensity. ($C_{eff} = 0.6 - 0.8$)

Step 4: Calculate Net Irrigation Requirement

The net irrigation requirement is the difference between crop water needs and effective rainfall:

$$NIR = ET_c - P_e$$

If Pe exceeds ETc in any month, the net irrigation requirement for that month is zero. ($NIR = \max(0, ET_c - P_e)$)

Additional Factors

Irrigation Efficiency ($IE$)

Accounts for water losses during conveyance and application. Typical values: Drip irrigation (0.85-0.95), Sprinkler (0.70-0.85), Surface irrigation (0.50-0.70).

Data Sources

ET0 data from NASA POWER or WaPOR. Rainfall data from observed stations, NASA, CHIRPS, or WaPOR. The calculator uses multi-year averages for more reliable estimates.

Monthly Aggregation

Calculations are performed monthly and then summed to provide annual water requirements. This accounts for seasonal variations in crop water needs and rainfall patterns.

Reference

This methodology follows FAO Irrigation and Drainage Paper No. 56: 'Crop Evapotranspiration - Guidelines for computing crop water requirements' (Allen et al., 1998).

Understanding Irrigation Efficiency

{% trans "Irrigation efficiency measures how effectively water is delivered from the source to the crop root zone. It accounts for losses during conveyance, distribution, and application." %}

Definition

$$IE = \frac{\text{Water Used by Crop}}{\text{Water Supplied}} \times 100\%$$

Typical Efficiency Values

💧 Drip Irrigation: 85-95%

{% trans "Water is delivered directly to the root zone through emitters. Minimal evaporation and runoff losses. Best for high-value crops and water-scarce regions." %}

🌧️ Sprinkler Irrigation: 70-85%

{% trans "Water is sprayed over the crop canopy. Some losses due to evaporation and wind drift. Suitable for most field crops and uniform water distribution." %}

🌊 Surface Irrigation: 50-70%

{% trans "Water flows over the field surface by gravity. Higher losses due to deep percolation, runoff, and evaporation. Traditional method, lower initial cost but less efficient." %}

Factors Affecting Efficiency

Conveyance Losses

{% trans "Water lost during transport from source to field through canals, pipes, or ditches. Seepage and evaporation are main causes." %}

Application Uniformity

{% trans "How evenly water is distributed across the field. Poor uniformity leads to over-irrigation in some areas and under-irrigation in others." %}

System Maintenance

{% trans "Well-maintained systems operate more efficiently. Clogged emitters, leaking pipes, and damaged equipment reduce efficiency." %}

Soil Type

{% trans "Sandy soils have higher infiltration rates leading to deep percolation losses. Clay soils may cause runoff if application rate exceeds infiltration." %}

Climate Conditions

{% trans "High temperatures, low humidity, and strong winds increase evaporation losses, especially for sprinkler and surface irrigation." %}

How to Improve Efficiency

{% trans "Upgrade to more efficient irrigation systems (drip or micro-sprinklers)" %}
{% trans "Line canals with concrete or use piped conveyance systems" %}
{% trans "Install soil moisture sensors for precision irrigation scheduling" %}
{% trans "Regular maintenance and repair of irrigation equipment" %}
{% trans "Level fields to improve water distribution uniformity" %}
{% trans "Irrigate during cooler hours (early morning or evening) to reduce evaporation" %}
Use mulching to reduce soil evaporation
{% trans "Train operators on proper irrigation management practices" %}

Impact on Water Requirements

{% trans "Irrigation efficiency directly affects the total water needed:" %}

$$\text{Total Water} = \frac{\text{Net Irrigation Requirement}}{IE}$$

{% trans "Example: If a crop needs 500 mm of water and irrigation efficiency is 70%, the total water to be supplied is 500 / 0.70 = 714 mm." %}

$$\text{Total Water} = \frac{500 \text{ mm}}{0.70} = 714 \text{ mm}$$

References

{% trans "FAO Irrigation and Drainage Paper No. 33: 'Yield Response to Water' and No. 56: 'Crop Evapotranspiration'. USDA Natural Resources Conservation Service: 'Irrigation Water Management'." %}

Understanding Irrigation Network Efficiency

Irrigation network efficiency measures how effectively water is transported and distributed from the source (dam, well, treatment plant) to the field level through the conveyance infrastructure (canals, pipes, pumping stations).

Definition

$$\eta_{network} = \frac{\text{Water Delivered to Fields}}{\text{Water Supplied to Network}} \times 100\%$$

This represents the percentage of water that successfully reaches the field level after accounting for all conveyance losses in the distribution network.

Network vs Field Efficiency

🚰 Network Efficiency (Conveyance)

Losses during water transport from source to field through canals, pipes, and pumping stations. Includes seepage, evaporation, and leakage in the distribution infrastructure.

Typical values: 70-90%

💧 Field Efficiency (Application)

Losses during water application at the field level. Depends on irrigation method (drip, sprinkler, surface) and how effectively water reaches the crop root zone.

Typical values: 50-95% (varies by method)

Overall System Efficiency

The total irrigation system efficiency combines both network and field efficiencies:

$$\eta_{total} = \eta_{network} \times \eta_{field}$$

Example: If network efficiency is 85% and field efficiency is 70%, the overall system efficiency is 0.85 × 0.70 = 0.595 or 59.5%.

Factors Affecting Network Efficiency

Canal Seepage

Water lost through unlined or poorly maintained canals. Earthen canals can lose 20-50% of water through seepage into the ground.

Evaporation Losses

Water lost to evaporation from open canals and reservoirs, especially in hot, dry climates. Can account for 5-15% of losses.

Pipe Leakage

Leaks in pressurized pipe networks due to aging infrastructure, poor joints, or damage. Modern piped systems typically have 5-10% losses.

Operational Spills

Water wasted during system operation, maintenance, or due to poor water management practices at distribution points.

Network Length & Complexity

Longer distribution networks and more complex systems with multiple branches have higher cumulative losses.

Typical Network Efficiency Values

Earthen Canals (unlined) 50-70%

Lined Canals (concrete) 75-85%

Piped Networks (modern) 85-95%

Impact on Total Water Needs

Network efficiency affects the total water that must be supplied to the system:

$$Q_{source} = \frac{Q_{field}}{\eta_{network}}$$

Where:

$Q_{source}$ = Water needed from source (dam, well)
$Q_{field}$ = Water needed at field level
$\eta_{network}$ = Network efficiency (0-1)

Example: $Q_{source} = \frac{1000 \text{ m}^3}{0.85} = 1176 \text{ m}^3$

References

FAO Irrigation and Drainage Paper No. 45: 'Guidelines for Designing and Evaluating Surface Irrigation Systems'. ICID (International Commission on Irrigation and Drainage): 'Irrigation Efficiency and Water Conveyance'.

Cropping System Calculations

This guide explains how each calculated variable in the cropping system is computed based on your input parameters.

Important: Most calculations use an 'Effective Area' which is the Area Cultivated multiplied by the Crop Density Factor. This factor accounts for crop density variations (e.g., double cropping, intercropping, or sparse planting).

Quick Navigation

💧 Water Calculations ⚡ Energy Calculations 💰 Cost Calculations 📊 Economic Indicators 🌱 Environmental Indicators 🌍 Carbon Emissions

💧 Water Calculations

Crop Water Requirements (m³)

$$Q_{requirement} = \frac{WR_{req} \times A \times D_{crop} \times 10}{1000}$$

Where:
• $WR_{req}$ = Water Requirement field (mm/year) - from ET0 × Kc
• $A$ = Area Cultivated (ha)
• $D_{crop}$ = Crop Density Factor (0-1)
• 10 = Conversion factor (ha to m²)
• 1000 = Conversion from mm to m
Represents the theoretical water needed by crops without efficiency adjustments.

Crop Water Demand (m³)

$$Q_{crop} = \frac{NWD \times A \times D_{crop} \times 10}{K_{red} \times IE} \times (1 + LR)$$

Where:
• $NWD$ = Net Water Demand field (mm/year) - from (ET0 × Kc - Rainfall)
• $A$ = Area Cultivated (ha)
• $D_{crop}$ = Crop Density Factor (0-1)
• $K_{red}$ = Reduction Coefficient
• $IE$ = Irrigation Efficiency
• $LR$ = Leaching Requirement Ratio
Represents the actual water needed at field level, adjusted for irrigation efficiency and leaching requirements.

Recycled Water (Mm³)

$$Q_{recycled} = (1 - IE) \times Q_{crop} / 1000000$$

Water not used by crops that returns to the system through deep percolation and runoff.

Groundwater Recharge (m³)

$$Q_{recharge} = IR \times Q_{crop}$$

Where: $IR$ = Infiltration Rate (portion of water that percolates to groundwater)

Virtual Water (m³/kg)

$$VW = \frac{Q_{crop}}{Y_{total}}$$

Where: $Y_{total}$ = Total Yield (kg) = Yield per ha × Area Cultivated × Crop Density Factor

⚡ Energy Calculations

Crop Energy Demand (kWh)

📌 Note: This calculation accounts for multiple energy sources with different efficiency factors, plus mechanization fuel consumption.

Total Energy:

$$E_{total} = E_{pumping} + E_{pressurization} + E_{mechanization}$$

1. Pumping Energy (by source):

$$E_{pump} = \sum_{source} \frac{9.81 \times H_{pump} \times Q_{crop} \times P_{source} \times 1000}{3.6 \times 10^6 \times \eta_{source} \times D_{source}}$$

Where:
• $H_{pump}$ = Pumping Head (m) - lifting water to surface/tank
• $Q_{crop}$ = Crop Water Demand (m³)
• $P_{source}$ = Part of energy source (0-1): Grid, Fuel, Gas, Solar, Wind
• $\eta_{source}$ = Motor Pump Yield by source (efficiency, 0-1):
— Grid/Solar/Wind: Electric Motor Pump Yield (default 0.85)
— Fuel: Fuel Motor Pump Yield (default 0.75)
— Gas: Gas Motor Pump Yield (default 0.80)
• $D_{source}$ = Energy density factor:
— Fuel (Diesel): 0.85
— Gas: 0.90
— Grid/Solar/Wind: 1.0
• 9.81 = Gravitational acceleration (m/s²)

2. Pressurization Energy (by source):

$$E_{press} = \sum_{source} \frac{9.81 \times H_{press} \times Q_{crop} \times P_{source} \times 1000}{3.6 \times 10^6 \times \eta_{source} \times D_{source}}$$

Where:
• $H_{press}$ = Pressurization Head (m) - pressure needed for irrigation system
• $\eta_{source}$ = Source-specific motor pump yield (same as pumping energy)
• Other variables same as pumping energy

3. Mechanization Energy:

$$E_{mech} = F_{consumption} \times N_{mech} \times A \times D_{crop} \times 10$$

Where:
• $F_{consumption}$ = Engines fuel consumption (l/day)
• $N_{mech}$ = Number of mechanization days
• $A$ = Area Cultivated (ha)
• $D_{crop}$ = Crop Density Factor
• 10 = Diesel energy content (~10 kWh/liter)

💡 Key Points:
• Energy is calculated separately for each source (Grid, Fuel, Gas, Solar, Wind) then summed
• Different energy sources have different efficiency factors
• Electric motors (Grid, Solar, Wind) use Electric Motor Pump Yield
• Fuel motors use Fuel Motor Pump Yield (typically lower efficiency)
• Gas motors use Gas Motor Pump Yield
• Fossil fuels (Diesel, Gas) have lower energy density factors due to conversion losses
• Pumping energy lifts water from source (well, river) to surface/tank
• Pressurization energy creates pressure needed for irrigation system operation
• Mechanization energy is based on diesel fuel consumption of farm machinery

Mechanization Energy Consumption (kWh)

$$E_{mech} = F_{consumption} \times N_{mech} \times A \times D_{crop} \times 10$$

Where:
• $F_{consumption}$ = Engines fuel consumption (l/day)
• $N_{mech}$ = Number of mechanization days
• $A$ = Area Cultivated (ha)
• $D_{crop}$ = Crop Density Factor
• 10 = Diesel energy content (~10 kWh/liter)

Note: This energy is already included in the total Crop Energy Demand above.

💰 Cost Calculations

Crop Water Cost (money)

$$C_{water} = Q_{crop} \times P_{water}$$

Where: $P_{water}$ = Water Price (money/m³)

Crop Energy Cost (money)

📌 Note: Energy cost is calculated separately for each energy source with proper unit conversions.

Total Cost Formula:

$$C_{energy} = C_{grid} + C_{fuel} + C_{gas} + C_{solar} + C_{wind}$$

By Energy Source:

Grid, Solar, Wind (electric):
$$C_{electric} = E_{source} \times P_{electric}$$ • $E_{source}$ = Energy in kWh
• $P_{electric}$ = Cost per kWh (money/kWh)

Fuel (diesel):
$$C_{fuel} = \frac{E_{fuel}}{10} \times P_{fuel}$$ • $E_{fuel}$ = Energy in kWh
• $10$ = Diesel energy content (kWh/L)
• $P_{fuel}$ = Fuel cost (money/L)
• Division converts kWh to liters

Gas (natural gas):
$$C_{gas} = \frac{E_{gas}}{13.9} \times P_{gas}$$ • $E_{gas}$ = Energy in kWh
• $13.9$ = Natural gas energy content (kWh/kg)
• $P_{gas}$ = Gas cost (money/kg)
• Division converts kWh to kilograms

💡 Key Points:
• Grid, Solar, Wind costs are in money/kWh (direct multiplication)
• Fuel cost is in money/liter, so kWh must be converted to liters first
• Gas cost is in money/kg, so kWh must be converted to kg first
• Total energy per source includes pumping + pressurization energy
• Mechanization energy (diesel) is added to fuel energy total

Crop Labour Cost (money)

$$C_{labour} = N_{labour} \times P_{labour} \times A \times D_{crop}$$

Where:
• $N_{labour}$ = Number of labour days
• $P_{labour}$ = Labour cost per day (money/ha/day)
• $A$ = Area Cultivated (ha)
• $D_{crop}$ = Crop Density Factor

Crop Mechanization Cost (money)

$$C_{mech} = N_{mech} \times P_{mech} \times A \times D_{crop}$$

Where:
• $N_{mech}$ = Number of mechanization days
• $P_{mech}$ = Mechanization cost per day (money/ha/day)
• $D_{crop}$ = Crop Density Factor

Crop Seeds Cost (money)

$$C_{seeds} = Q_{seeds} \times P_{seeds} \times A \times D_{crop}$$

Where:
• $Q_{seeds}$ = Seeds quantity (kg/ha)
• $P_{seeds}$ = Seeds price (money/kg)
• $D_{crop}$ = Crop Density Factor

Nitrogen Cost (money)

$$C_{N} = Q_{N} \times P_{N} \times A \times D_{crop}$$

Where:
• $Q_{N}$ = Nitrogen quantity (kg/ha)
• $P_{N}$ = Nitrogen price (money/kg)
• $D_{crop}$ = Crop Density Factor

Fertilizer Cost (money)

$$C_{fert} = (Q_{P} \times P_{P} + Q_{K} \times P_{K}) \times A \times D_{crop}$$

Where:
• $Q_{P}$, $Q_{K}$ = Phosphorus and Potassium quantities (kg/ha)
• $P_{P}$, $P_{K}$ = Phosphorus and Potassium prices (money/kg)
• $D_{crop}$ = Crop Density Factor

Pesticide Cost (money)

$$C_{pest} = Q_{pest} \times P_{pest} \times A \times D_{crop}$$

Where:
• $Q_{pest}$ = Pesticide quantity (kg/ha)
• $P_{pest}$ = Pesticide price (money/kg)
• $D_{crop}$ = Crop Density Factor

Other Production Cost (money)

$$C_{other} = C_{other/ha} \times A \times D_{crop}$$

Includes miscellaneous costs like packaging, storage, transport, etc.

Total Crop Cost (money)

$$C_{total} = C_{water} + C_{energy} + C_{labour} + C_{mech} + C_{seeds} + C_{N} + C_{fert} + C_{pest} + C_{other}$$

Sum of all production costs for the cropping system.

📊 Economic Indicators

Total Revenue (money)

$$R_{total} = Y_{total} \times P_{crop}$$

Where:
• $Y_{total}$ = Total Yield (kg) = Yield per ha × Area × Crop Density
• $P_{crop}$ = Crop Price (money/kg)

Gross Profit (money)

$$GP = R_{total} - C_{total}$$

Net income after deducting all production costs from total revenue.

Water Productivity - Economic (money/m³)

$$WP_{econ} = \frac{R_{total}}{Q_{crop}}$$

Revenue generated per cubic meter of water used. Higher values indicate more efficient water use economically.

Water Productivity - Physical (kg/m³)

$$WP_{phys} = \frac{Y_{total}}{Q_{crop}}$$

Crop yield produced per cubic meter of water used. Measures physical efficiency of water use.

🌱 Environmental Indicators

Exported Salts (kg)

$$S_{export} = A \times D_{crop} \times 25$$

Estimated salt removal through drainage water. Value of 25 kg/ha is a typical estimate for irrigated agriculture.

Nitrate Pollution (kg)

$$N_{pollution} = Q_{N} \times A \times D_{crop} \times (1 - E_{N})$$

Where:
• $Q_{N}$ = Nitrogen applied (kg/ha)
• $E_{N}$ = Nitrogen efficiency (typically 0.6-0.7)
• $D_{crop}$ = Crop Density Factor
Represents nitrogen not absorbed by crops that may leach to groundwater or runoff.

Pesticide Pollution (kg)

$$P_{pollution} = Q_{pest} \times A \times D_{crop} \times (1 - E_{pest})$$

Where:
• $Q_{pest}$ = Pesticide applied (kg/ha)
• $E_{pest}$ = Pesticide efficiency (typically 0.7-0.8)
• $D_{crop}$ = Crop Density Factor
Represents pesticide residues that may contaminate water or soil.

🌍 Carbon Emissions & Sequestration

Three-Tier Carbon Accounting System

Tier 1: CO₂ Emissions (Energy Only) - Direct emissions from irrigation energy sources (grid, fuel, gas, solar, wind)
Tier 2: Carbon Footprint Base - CO₂ + Agricultural GHG (N₂O from nitrogen, emissions from fertilizer production)
Tier 3: Net Carbon Footprint - Base emissions - Carbon sequestration offset (agroecology systems only)

Agricultural Inputs Reduction Factor (Agroecology Systems)

$$K_{reduce} = \frac{100 - ae\_inputs\_decrease}{100}$$
Where:
• $ae\_inputs\_decrease$ = Agroecology agricultural inputs decrease impact (%, typically 20-30)
• $K_{reduce}$ = Reduction factor applied to nitrogen, phosphorus, potassium, and pesticides
• Example: 20% decrease → $K_{reduce}$ = (100-20)/100 = 0.8

This factor affects:
• Nitrogen inputs applied → Reduces N₂O emissions
• Phosphorus & Potassium inputs → Reduces fertilizer production emissions
• Pesticide application → Reduces pesticide pollution and application costs

CO₂ Emissions - Energy Only (kg CO₂)

$$CO_2 = E_{grid} \cdot f_{grid} + E_{fuel} \cdot f_{fuel} + E_{gas} \cdot f_{gas} + E_{solar} \cdot f_{solar} + E_{wind} \cdot f_{wind}$$
Where:
• $E_{grid}$ = Grid electricity consumption (kWh)
• $E_{fuel}$ = Diesel fuel consumption (L) = $\frac{Energy_{fuel}}{10}$ (kWh ÷ 10 kWh/L)
• $E_{gas}$ = Natural gas consumption (kg) = $\frac{Energy_{gas}}{13.9}$ (kWh ÷ 13.9 kWh/kg)
• $E_{solar}$ = Solar energy consumption (kWh)
• $E_{wind}$ = Wind energy consumption (kWh)

Emission Factors:
• $f_{grid}$ = 0.0543 kg CO₂/kWh (average grid mix)
• $f_{fuel}$ = 3.15 kg CO₂/L (diesel combustion)
• $f_{gas}$ = 2.75 kg CO₂/kg (natural gas combustion)
• $f_{solar}$ = 0.05 kg CO₂/kWh (lifecycle emissions from panel production)
• $f_{wind}$ = 0.01 kg CO₂/kWh (lifecycle emissions from turbine production)

Represents: Direct CO₂ emissions from all energy sources used for irrigation, independent of agricultural inputs.

Carbon Footprint Base - All GHG Emissions (kg CO₂e)

$$CF_{base} = CO_2 + N_2O_{emissions} + Fert_{emissions}$$
Component 1: Energy-Related CO₂
$$CO_2 = \text{(See above formula)}$$
Component 2: N₂O Emissions from Nitrogen Fertilizer
$$N_2O_{emissions} = A_{eff} \times N \times K_{reduce} \times 1.325$$
Where:
• $N$ = Nitrogen application rate (kg/ha) - user input
• $K_{reduce}$ = Agroecology inputs reduction factor (see above)
• $A_{eff}$ = Effective Area = Area Cultivated × Crop Density Factor (ha)
• 1.325 = N₂O GWP emission factor (kg CO₂e per kg N)
• N₂O is 298× more potent than CO₂ as a greenhouse gas

Component 3: Fertilizer Production Emissions (P & K)
$$Fert_{emissions} = A_{eff} \times (P + K) \times K_{reduce} \times 0.5$$
Where:
• $P$ = Phosphorus application rate (kg/ha) - user input
• $K$ = Potassium application rate (kg/ha) - user input
• $K_{reduce}$ = Agroecology inputs reduction factor
• 0.5 = Fertilizer production emission factor (kg CO₂e per kg P+K)
• Manufacturing synthetic fertilizers is energy-intensive

Impact of Agroecology: When agroecology system is active with inputs decrease = 20%, the applied nitrogen, phosphorus, and potassium are reduced by 20%, proportionally reducing N₂O and fertilizer production emissions.

Carbon Sequestration Offset (kg CO₂e offset)

$$C_{seq} = S_{rate} \times 3.67 \times 1000 \times A_{eff}$$
Where:
• $S_{rate}$ = Carbon sequestration rate from ActionImpact (tC/ha/yr)
• 3.67 = Conversion factor: Molecular weight of CO₂ (44) ÷ Atomic weight of C (12)
• 1000 = Conversion from metric tons (tC) to kilograms
• $A_{eff}$ = Effective Area (ha)

Example Calculation:
• Agroecology sequestration: 2 tC/ha/yr
• Effective area: 100 ha
• $C_{seq}$ = 2 × 3.67 × 1000 × 100 = 734,000 kg CO₂e

For Non-Agroecology Systems: $C_{seq}$ = 0 (no sequestration offset applied)
Interpretation: Only agroecology cropping systems (with ae_carbon_sequestration ActionImpact) receive a carbon sequestration offset.

NET Carbon Footprint (kg CO₂e)

$$CF_{net} = CF_{base} - C_{seq}$$
$$CF_{net} = (CO_2 + N_2O_{emissions} + Fert_{emissions}) - C_{seq}$$
Interpretation:
• Regular Systems: $CF_{net}$ = $CF_{base}$ (no sequestration offset)
• Agroecology Systems: $CF_{net}$ = $CF_{base}$ - $C_{seq}$ (can be negative if sequestration > emissions)
• Negative Footprint: System removes more CO₂ from atmosphere than it emits (carbon negative)
• Positive Footprint: System still emits more than it sequesters (carbon positive)

Nitrate Pollution (affected by inputs reduction)

$$N_{pollution} = A_{eff} \times N \times K_{reduce} \times (1 - E_{N}) \times 4.43$$
Where:
• $N$ = Nitrogen applied (kg/ha)
• $K_{reduce}$ = Agroecology inputs reduction factor (0.8 for 20% decrease)
• $E_{N}$ = Nitrogen use efficiency (typically 0.6-0.7)
• 4.43 = Conversion factor from NO₃-N to NO₃ (molecular weight ratio)
• Agroecology systems reduce nitrogen applied, thus reducing nitrate pollution

Pesticide Pollution (affected by inputs reduction)

$$P_{pollution} = A_{eff} \times Q_{pest} \times K_{reduce} \times (1 - E_{pest})$$
Where:
• $Q_{pest}$ = Pesticide quantity applied (kg/ha)
• $K_{reduce}$ = Agroecology inputs reduction factor (0.8 for 20% decrease)
• $E_{pest}$ = Pesticide efficiency (typically 0.7-0.8)
• Agroecology systems reduce phytosanitary treatments, thus reducing pesticide pollution

Impact Summary: Agroecology vs Regular Systems

Metric	Agroecology	Regular
CO₂ Emissions	Unchanged	Unchanged
Nitrogen Applied	↓ 20-30%	100%
N₂O Emissions	↓ 20-30%	100%
Fertilizer Production Emissions	↓ 20-30%	100%
Nitrate Pollution	↓ 20-30%	100%
Pesticide Pollution	↓ 20-30%	100%
Carbon Sequestration	↑ 1-3 tC/ha/yr	0

💡 Strategies to Reduce Carbon Footprint

Immediate Actions:
• Switch to agroecology system to reduce N inputs and capture sequestration
• Switch to renewable energy (solar, wind) for irrigation pumping
• Use high-efficiency electric motors instead of diesel engines

Medium-Term Strategies:
• Apply nitrogen fertilizer based on soil testing (precision application)
• Use slow-release or controlled-release fertilizers to reduce N₂O
• Optimize timing of fertilizer application
• Implement drip irrigation to improve irrigation efficiency

Long-Term Strategies:
• Transition to agroforestry (trees + crops) for maximum sequestration
• Build soil organic matter through composting and residue incorporation
• Implement conservation agriculture (reduced tillage, cover crops)

References

Calculations based on FAO guidelines, standard agricultural engineering formulas, and water-energy-food nexus principles. Specific coefficients may vary by region and crop type.

Latitude	Jan	Feb	Mar	Apr	May	Jun
0°	0.27	0.27	0.27	0.27	0.27	0.27
30°	0.24	0.25	0.27	0.29	0.31	0.32
40°	0.22	0.24	0.27	0.30	0.32	0.34

Future Interventions

The Future Interventions section allows you to plan long-term changes in irrigated area for a cropping system. This is essential for strategic water resource planning and scenario analysis.

Key Feature: The system automatically calculates linear interpolation between the current state and your target, making it easy to model gradual agricultural expansion or contraction over time.

🎯 When to Use Future Interventions

🌾

Agricultural Expansion Planning

Model scenarios where irrigated areas will gradually increase over time, such as land development projects or infrastructure improvements.

💧

Water Conservation Programs

Plan for reduction in irrigated area due to water scarcity, drought management, or shift to more efficient cropping patterns.

📊

Policy Impact Assessment

Evaluate the long-term water resource impacts of agricultural policies, subsidies, or regulatory changes that affect cultivation areas.

🔄

Scenario Comparison

Compare different growth trajectories to understand their implications on water demand, energy consumption, and economic outcomes.

⚙️ How It Works

1 Define Your Target

Enter the projected irrigated area (in hectares) you want to achieve and the target year. The current area is automatically read from the 'Area Cultivated' field in the cropping system.

Example: Current area: 100 ha → Projected area: 150 ha by year 2030

2 Linear Interpolation Calculation

The system calculates intermediate values for all years between the current state and target year using linear interpolation:

$$A_{turn} = A_{current} + \frac{(A_{target} - A_{current})}{n_{steps}} \times (turn - turn_{start})$$

Where:
• $A_{turn}$ = Area for a specific turn
• $A_{current}$ = Current area (Turn 1)
• $A_{target}$ = Projected target area
• $n_{steps}$ = Number of turns from current to target
• $turn$ = Turn number being calculated

Example: 100 ha → 150 ha over 5 turns = +10 ha per turn (110, 120, 130, 140, 150)

3 Post-Target Years

For all years after the target year, the system maintains the projected area constant. This assumes that once the target is reached, it remains stable.

Example: If target is 150 ha by 2030, years 2031-2035 will all use 150 ha

⚠️ Important Considerations

Save First, Project Later

You must save the cropping system data in Turn 1 before calculating projections. The system needs a baseline to work from.

Only Area is Projected

The projection feature only updates the 'Area Cultivated' field. All other parameters (crop density, water requirements, yields, costs, etc.) remain as defined in Turn 1 unless manually adjusted.

Review Projected Data

After calculating projections, navigate through the turns to review the interpolated areas. You can manually adjust any turn if needed.

Recalculation Overwrites

Running the projection calculation again will overwrite any previous projections for this cropping system. Manual edits to future turns will be replaced.

📋 Typical Workflow

Define baseline: In Turn 1, enter all cropping system parameters including current area cultivated
Save data: Click 'Save Agricultural Consumption Data' to store the baseline
Set target: In the Future Interventions section, enter projected area and target year
Calculate: Click 'Calculate Projections' to apply linear interpolation
Review: Navigate through turns to verify the interpolated values
Adjust: Make manual adjustments to specific turns if needed
Analyze: Use the projection data to assess long-term water demand and impacts

✨ Benefits of Using Future Interventions

⏱️

Time Saving

Automatically populate multiple turns instead of manual entry

📈

Consistency

Ensure smooth, logical transitions between years

🔍

Transparency

Clear mathematical approach to future projections

🎯

Strategic Planning

Visualize long-term impacts of interventions

Technical Note: Client-Side Calculation

The projection calculation is performed entirely in your browser (client-side), which means it can handle any number of game turns without backend limitations. The interpolated values are then saved to each turn individually, ensuring data integrity and allowing for manual adjustments if needed.

Irrigation System Metrics

These metrics aggregate data from all cropping systems in the irrigated perimeter, providing a comprehensive overview of water use, energy consumption, costs, revenue, and environmental impacts.

Quick Navigation

📊 Basic Aggregates 💧 Water Metrics ⚡ Energy Metrics 💰 Cost Aggregates 📈 Economic Indicators 🌱 Environmental & Carbon

📊 Basic Aggregates

Cultivated Area (ha)

$$A_{total} = \sum_{i=1}^{n} (A_i \times D_{crop,i})$$

Where:
• $A_i$ = Area Cultivated of each system (ha)
• $D_{crop,i}$ = Crop Density Factor of each system (0-1)
Sum of effective cultivated areas (Area × Crop Density Factor) across all cropping systems in the perimeter.

Number of Systems

Total count of active cropping systems in the irrigated perimeter.

💧 Water Metrics

Water Requirement (Mm³)

$$Q_{requirement} = \sum_{i=1}^{n} Q_{requirement,i}$$

Where:
• $Q_{requirement,i}$ = Crop Water Requirements of each system (m³)
Total water requirement calculated from ET0 × Kc without efficiency adjustment. Represents the theoretical water needed by crops.

Water Demand (Mm³)

$$Q_{total} = \frac{\sum_{i=1}^{n} Q_{crop,i}}{\eta_{network}}$$

Where:
• $Q_{crop,i}$ = Crop Water Demand of each cropping system (m³)
• $\eta_{network}$ = Irrigation network efficiency
Adjusted for irrigation efficiency and network losses to determine total water needed at source.

Rainfall Inflow (Mm³)

$$R_{inflow} = \sum_{i=1}^{n} (P_i \times A_i \times 10) / 1000000$$

Where:
• $P_i$ = Rainfall for each system (mm/year)
• $A_i$ = Area of each system (ha)
• 10 = Conversion factor (ha to m²)
• 1000000 = Conversion to Mm³

Recycled Water (Mm³)

$$Q_{recycled} = \sum_{i=1}^{n} Q_{recycled,i}$$

Sum of recycled water from all systems. Can be allocated to aquifer (infiltration), river (runoff), or evaporation.

Groundwater Recharge (Mm³)

$$Q_{recharge} = \sum_{i=1}^{n} Q_{recharge,i} / 1000000$$

Total water percolating to groundwater from all cropping systems.

Average Water Productivity (money/m³)

$$WP_{avg} = \frac{\sum_{i=1}^{n} R_i}{\sum_{i=1}^{n} Q_{crop,i}}$$

Total revenue divided by total water consumption. Indicates overall economic efficiency of water use across the perimeter.

⚡ Energy Metrics

Energy Demand (kWh)

$$E_{total} = \sum_{i=1}^{n} E_{crop,i}$$

Total energy required for pumping water across all cropping systems.

Mechanization Energy Consumption (kWh)

$$E_{mech,total} = \sum_{i=1}^{n} E_{mech,i}$$

Total energy consumed by agricultural machinery across all systems.

💰 Cost Aggregates

All cost metrics are simple sums across all cropping systems:

Individual Cost Components

Crop Water Cost: $\sum C_{water,i}$
Crop Energy Cost: $\sum C_{energy,i}$
Crop Labour Cost: $\sum C_{labour,i}$
Crop Mechanization Cost: $\sum C_{mech,i}$
Crop Seeds Cost: $\sum C_{seeds,i}$
Nitrogen Cost: $\sum C_{N,i}$
Fertilizer Cost: $\sum C_{fert,i}$
Pesticide Cost: $\sum C_{pest,i}$
Other Production Cost: $\sum C_{other,i}$

Total Crop Cost (money)

$$C_{total} = \sum_{i=1}^{n} C_{total,i}$$

Sum of all production costs across all cropping systems in the perimeter.

📈 Economic Indicators

Total Revenue (money)

$$R_{total} = \sum_{i=1}^{n} R_i$$

Sum of revenue from all cropping systems. Represents total income from crop sales.

Total Gross Profit (money)

$$GP_{total} = R_{total} - C_{total}$$

Net income for the entire irrigated perimeter after deducting all production costs.

🌱 Environmental Impact & Carbon Emissions

Exported Salts (kg)

$$S_{export} = \sum_{i=1}^{n} S_{export,i}$$

Total salt removal through drainage water from all systems.

Imported Salts (kg)

$$S_{import} = Q_{total} \times 1000000 \times S_{water}$$

Where:
• $Q_{total}$ = Total water demand (Mm³)
• $S_{water}$ = Water salinity (g/L)
Salts brought into the system through irrigation water.

Nitrate Pollution (kg)

$$N_{pollution} = \sum_{i=1}^{n} N_{pollution,i}$$

Total nitrogen not absorbed by crops that may leach to groundwater or runoff.

Pesticide Pollution (kg)

$$P_{pollution} = \sum_{i=1}^{n} P_{pollution,i}$$

Total pesticide residues that may contaminate water or soil.

CO₂ Emissions (kg CO₂)

$$CO_2 = \sum_{i=1}^{n} CO_{2,i}$$

Where:
$$CO_{2,i} = E_{grid,i} \times 0.5 + E_{fuel,i} \times 2.68 + E_{gas,i} \times 2.75 + E_{solar,i} \times 0.05 + E_{wind,i} \times 0.01$$
Total carbon dioxide emissions from energy consumption across all cropping systems. Accounts for different emission factors per energy source:
• Grid: 0.5 kg CO₂/kWh
• Diesel fuel: 2.68 kg CO₂/L
• Natural gas: 2.75 kg CO₂/kg
• Solar: 0.05 kg CO₂/kWh (lifecycle)
• Wind: 0.01 kg CO₂/kWh (lifecycle)

Carbon Footprint (kg CO₂e)

$$CF_{total} = \sum_{i=1}^{n} CF_i$$

Where:
$$CF_i = CO_{2,i} + (N_i \times 1.325) + ((P_i + K_i) \times 0.5)$$
Total carbon footprint including:
• Direct CO₂ emissions from energy
• N₂O emissions from nitrogen fertilizer (1.325 kg CO₂e/kg N)
• Fertilizer production emissions (0.5 kg CO₂e/kg P+K)

This comprehensive metric captures the full climate impact of agricultural activities across the entire irrigated perimeter.

💡 Key Insights

These metrics provide a holistic view of the entire irrigated perimeter's performance
Water demand is adjusted for network efficiency to show total water needed at source
Economic indicators help assess overall profitability and water productivity
Environmental metrics track the perimeter's ecological footprint including carbon emissions
Carbon footprint accounts for direct energy emissions plus fertilizer-related greenhouse gases
Use these aggregates for decision-making, reporting, sustainability assessment, and optimization

Note

All metrics are automatically calculated and updated when cropping system data changes. Values represent the sum or weighted average of individual system calculations.

Allocated Water

This section displays the water allocations from various sources (dams, resource nodes, water infrastructure) that have been formally allocated to this irrigated perimeter for the current turn.

What is Allocated Water?

Allocated water represents the formal water rights or allocations granted to the irrigated perimeter from various water sources. These allocations are typically:

Granted by water authorities or basin management agencies
Based on water availability and priority rights
May vary by season or year depending on water availability
Represent the maximum water that can be withdrawn from each source

Water Sources

🏔️ Dams

Surface water stored in reservoirs. Allocations depend on reservoir levels and release schedules.

💧 Resource Nodes

Groundwater wells, springs, or other water sources. Allocations based on sustainable yield and pumping capacity.

🏭 Water Infrastructure

Treatment plants, desalination facilities, or water transfer systems. Allocations based on infrastructure capacity.

Allocation Information Displayed

Source Name: Name of the water source (dam, well, etc.)
Volume (Mm³): Amount of water allocated for this turn
Location: Geographic location of the source
Status: Active/Inactive status of the allocation
Allocation Date: When the allocation was granted

Water Balance

The water balance shows:

Total Allocated: Sum of all water allocations
Number of Sources: Count of different water sources
Average per Source: Mean allocation across sources

📊 Sankey Diagram

Click the Sankey diagram button to visualize:

Water flows from sources to the irrigated perimeter
Relative contribution of each source
Water distribution to cropping systems
Water losses and recycling

⚠️ Important Notes

Allocations are managed by water authorities, not directly editable here
Actual water use may be less than allocated amount
Allocations may change between turns based on water availability
Multiple sources provide flexibility and water security

Irrigation System Data

This section contains perimeter-level parameters that apply to all cropping systems. These values affect calculations across the entire irrigated perimeter.

Parameter Categories

💰 Water Economics & Quality

Water Price: Cost per m³ of water (money/m³)
Water Salinity: Salt content in irrigation water (g/L)

⚡ Energy Parameters

Pumping Head: Vertical lift height for water (m)
Motor Pump Yield: Pump efficiency (0-1)
Energy Cost: Electricity price (money/kWh)

🔌 Energy Source Distribution

Part of Grid: Proportion of energy from electrical grid (0-1)
Part of Fuel: Proportion of energy from diesel/petrol (0-1)
Part of Gas: Proportion of energy from natural gas (0-1)
Part of Solar Energy: Proportion of energy from solar panels (0-1)
Part of Wind Energy: Proportion of energy from wind turbines (0-1)

Note: The sum of all energy source parts should equal 1.0 to represent 100% of energy supply. For example: Grid 0.6 + Fuel 0.3 + Solar 0.1 = 1.0

🚰 Infrastructure & Efficiency

Irrigation Network Efficiency: Overall conveyance efficiency from water source to field (0-1). Accounts for water losses during transport through canals and pipes.
Drip Irrigation Efficiency: Water application efficiency for drip systems (0-1). Typically 0.85-0.95 due to precise water delivery.
Surface Irrigation Efficiency: Water application efficiency for surface/flood irrigation (0-1). Typically 0.45-0.70 due to higher losses.
Sprinkler Irrigation Efficiency: Water application efficiency for sprinkler systems (0-1). Typically 0.70-0.85 with moderate losses from wind and evaporation.
Maintenance Cost: Annual maintenance expenses per hectare (money/ha/year). Includes repairs, equipment upkeep, and infrastructure maintenance.
Operational Cost: Annual operational expenses per hectare (money/ha/year). Includes labor, administration, and day-to-day operations.
Leaching Requirement Ratio: Additional water fraction needed to leach salts from root zone (0-0.5). Higher values needed for saline soils or poor drainage.

Note: Efficiency values directly impact water demand calculations. Higher efficiency means less water is needed for the same crop requirements. Leaching ratio increases total water application to prevent salt buildup.

💵 Additional Cost Considerations

Maintenance and operational costs are combined with water and energy costs to calculate total irrigation system expenses. These costs vary by infrastructure age, system complexity, and management intensity.

🌾 Soil & Environmental

Effective Rainfall Coefficient: Fraction of rainfall effectively used by crops (0-1). Accounts for runoff, deep percolation, and evaporation losses.

Why These Parameters Matter

Applied uniformly to all cropping systems in the perimeter
Affect water demand, energy consumption, and cost calculations
Represent infrastructure and environmental conditions
Changes here impact all system-level metrics
Energy source distribution helps track renewable vs. fossil fuel usage for sustainability analysis

How to Use

Enter values based on actual perimeter conditions
Use measured data when available (pump efficiency, water salinity)
Consult engineering specifications for infrastructure parameters
Update values when conditions change (e.g., new pumps, water quality)
Save data to apply parameters to all cropping systems

💡 Tips

Default values are provided but should be adjusted to match reality
Network efficiency significantly impacts total water demand
Pumping head and energy cost determine irrigation energy expenses
Different irrigation methods have different efficiencies: Drip (90%) > Sprinkler (75%) > Surface (60%)
Leaching requirement depends on soil salinity and crop tolerance - use 0.1-0.2 for moderate salinity, 0.2-0.3 for high salinity
Maintenance costs are typically 1-2% of initial infrastructure investment annually
Energy source distribution values must sum to 1.0 (e.g., 70% grid + 20% solar + 10% fuel = 1.0)
Track renewable energy adoption by increasing solar/wind proportions over time

Cropping Systems

Cropping systems represent the different crop types, irrigation methods, and agricultural practices used in the irrigated perimeter. Each system has its own water requirements, costs, and yields.

What is a Cropping System?

A cropping system defines:

Crop Type: What is grown (wheat, tomatoes, olives, etc.)
Irrigation Method: How water is applied (drip, sprinkler, surface)
Area: How much land is cultivated (hectares)
Inputs: Water, energy, labor, seeds, fertilizers, pesticides
Outputs: Crop yield and revenue

Managing Cropping Systems

➕ Add Cropping System

Click the 'Add Cropping System' button to create a new system. Fill in crop details, area, irrigation method, and input costs.

✏️ Edit System

Modify any parameter in a cropping system card. Changes are calculated in real-time and shown in the metrics section.

🗑️ Delete System

Click the delete button on a system card to remove it. Metrics will update automatically.

Key Features

Real-time Calculations: Water demand, costs, and revenue calculated automatically
Water Source Allocation: Specify which water sources supply each system
Calculated Variables: View water demand, energy use, costs, profit, and environmental impacts
Aggregate Metrics: See totals across all systems in the metrics section

Tools Available

🌾 Soil Occupation

Generate cropping systems automatically from statistical data about typical crop distributions in your region.

📊 Pie Charts

Visualize the distribution of area, water demand, costs, or revenue across all cropping systems.

💡 Tips

Start with major crops that occupy the most area
Use realistic yield and cost data for accurate economic analysis
Allocate water sources to match actual infrastructure connections
Review calculated metrics to optimize water use and profitability
Save your data regularly to preserve changes

Soil Occupation

The Soil Occupation tool automatically generates cropping systems based on statistical data about typical crop distributions in your region. This saves time when setting up a new irrigated perimeter.

How It Works

Click the 'Soil occupation' button
A form appears with crop statistics for your region
Enter the total area to be distributed
Adjust crop percentages if needed (must sum to 100%)
Click 'Generate Systems' to create cropping systems automatically
Systems are created with default parameters that you can then customize

Data Sources

Soil occupation statistics come from:

Agricultural census data
Regional crop distribution surveys
Historical land use patterns
Ministry of Agriculture statistics

Benefits

⚡ Quick setup - generate multiple systems at once
📊 Realistic distribution - based on actual regional data
🎯 Accurate baseline - good starting point for analysis
✏️ Customizable - adjust generated systems as needed

When to Use

Setting up a new irrigated perimeter
Creating a baseline scenario for comparison
When you don't have detailed crop data yet
To quickly populate systems for testing

⚠️ Important Notes

Generated systems use default parameters - review and adjust them
Crop percentages must sum to 100%
You can modify or delete generated systems
Statistics may not perfectly match your specific perimeter

Rainfed Agriculture Data Manager

Tun (Year): Select the year for this data

Rainfed System Metrics

Total Cultivated Area (ha): 0

Total Water Demand (Mm³): 0.000 Mm³

Effective Rainfall (Mm³): 0.000 Mm³

Water Deficit (Mm³): 0.000 Mm³

Total Labour Cost (Million): 0

Mechanization Cost (Million): 0

Mechanization Energy (kWh): 0

Seeds Cost (Million): 0

Nitrogen Cost (Million): 0

Fertilizer Cost (Million): 0

Pesticide Cost (Million): 0

Other Production Cost (Million): 0

Total Crop Cost (Million): 0

Total Revenue (Million): 0

Total Gross Profit (Million): 0

Nitrate Pollution (Million kg): 0

Pesticide Pollution (Million kg): 0

Carbon Footprint (Million kg CO₂e): 0

Total Carbon Sequestration (Million kg CO₂e): 0

Average Water Productivity (money/m³): 0.0000

Number of Systems: 0

Rainfed Agricultural Data

Total Area (ha):

Cultivated Area (ha):

Annual Rainfall (mm):

Effective Rainfall Coefficient (0-1):

Rainfall Variability (0-1):

Soil Health Factor (0.7-1.3):

Soil Water Retention (mm):

Infiltration Rate (0-1):

Maintenance Cost (money/ha/year):

Operational Cost (money/ha/year):

Erosion Risk Factor (0-1):

Conservation Practices Efficiency (0-1):

Cropping Systems

No cropping systems added yet. Click 'Add Cropping System' to start.

Rainfed Cropping System Calculations

This guide explains how each calculated variable in the rainfed cropping system is computed based on your input parameters and rainfall data.

Important: Rainfed agriculture calculations focus on effective rainfall utilization and water deficit analysis, rather than irrigation efficiency.

Quick Navigation

💧 Water Calculations 💰 Cost Calculations 📊 Economic Indicators 🌱 Environmental Indicators

💧 Water Calculations

Water Demand (m³)

$$Q_{demand} = A \times WR \times 10 \times CSF$$

Where:
• $A$ = Area Cultivated (ha)
• $WR$ = Water Requirement (mm/season)
• $CSF$ = Climate Stress Factor (accounts for drought/heat stress)
• $10$ = Conversion factor from mm·ha to m³

Effective Rainfall (m³)

$$Q_{rainfall} = A \times AR \times ERC \times 10$$

Where:
• $AR$ = Annual Rainfall (mm) - from Rainfed Agricultural Data section
• $ERC$ = Effective Rainfall Coefficient (0.0-1.0) - portion of rainfall available to crops

Note: Not all rainfall is available to crops due to runoff, deep percolation, and evaporation.

Water Deficit (m³)

$$Deficit = \max(0, Q_{demand} - Q_{rainfall})$$

If positive, indicates water stress - crop water requirements exceed available rainfall.
If zero, rainfall is sufficient to meet crop water needs.

Virtual Water (m³/kg)

$$VW = \frac{Q_{demand}}{Y_{total} \times 1000}$$

Where: $Y_{total}$ = Total Production (tons) = Area Cultivated × Yield per Hectare

💰 Cost Calculations

Labour Cost

$$C_{labour} = A \times LD \times LC$$

• $LD$ = Labour Days (days/ha)
• $LC$ = Labour Cost (money/day)

Mechanization Cost

$$C_{mech} = A \times MD \times MC$$

• $MD$ = Mechanization Days (days/ha)
• $MC$ = Mechanization Cost (money/day)

Seeds Cost

$$C_{seeds} = A \times SN \times SP$$

• $SN$ = Seed Needs (kg/ha)
• $SP$ = Seed Price (money/kg)

Nitrogen Cost

$$C_{N} = A \times N \times NP$$

• $N$ = Nitrogen Application (kg/ha)
• $NP$ = Nitrogen Price (money/kg)

Fertilizer Cost (P)

$$C_{P} = A \times P \times FP$$

• $P$ = Phosphorus Application (kg/ha)
• $FP$ = Fertilizer Price (money/kg)

Pesticide Cost

$$C_{pest} = A \times PT \times PP$$

• $PT$ = Phytosanitary Treatment (kg/ha)
• $PP$ = Pesticide Price (money/L)

Other Production Cost

$$C_{other} = Y_{total} \times OC$$

• $OC$ = Other Production Cost per Ton (money/ton)
• $Y_{total}$ = Total Production (tons)

Total Crop Cost

$$C_{total} = C_{labour} + C_{mech} + C_{seeds} + C_{N} + C_{P} + C_{pest} + C_{other}$$

📊 Economic Indicators

Total Revenue

$$R_{total} = Y_{total} \times EP$$

• $EP$ = Expected Product Price (money/ton)

Gross Profit

$$GP = R_{total} - C_{total}$$

Positive values indicate profitable operation, negative values indicate losses.

Water Productivity (Economic)

$$WP_{econ} = \frac{GP}{Q_{demand}}$$

Gross profit earned per cubic meter of water demanded (money/m³).

Water Productivity (Physical)

$$WP_{phys} = \frac{Y_{total} \times 1000}{Q_{demand}}$$

Kilograms of product produced per cubic meter of water demanded (kg/m³).

🌱 Environmental Indicators

Nitrate Pollution (kg)

$$NP = A \times N \times (1 - NUE) \times 1.5$$

• $NUE$ = Nitrogen Use Efficiency (default 0.8 = 80%)
• $1.5$ = Conversion factor for nitrate formation

Pesticide Pollution (kg)

$$PP = A \times PT \times (1 - PE)$$

• $PE$ = Pesticide Efficiency (default 0.8 = 80%)

Carbon Footprint (kg CO₂e)

$$CF = E_{N2O} + E_{fert} + E_{mech}$$

Components:
• $E_{N2O} = A \times N \times 1.325$ (N₂O emissions from nitrogen)
• $E_{fert} = A \times (P + K) \times 0.5$ (fertilizer production)
• $E_{mech} = MD \times A \times 10 \times 2.68$ (mechanization, assuming 10L diesel/day)

Carbon Sequestration (kg CO₂e)

$$CS = A \times Y \times CSF$$

Where:
• $A$ = Area Cultivated (ha)
• $Y$ = Yield per Hectare (t/ha)
• $CSF$ = Carbon Sequestration Factor (kg CO₂e/t, typical: 200-400 for crops)

Note: Carbon sequestration represents CO₂ absorbed by plants during photosynthesis and stored in biomass and soil organic matter.

💡 Key Concepts for Rainfed Agriculture

Water Deficit Analysis

Unlike irrigated agriculture, rainfed systems depend on natural rainfall. Water deficit indicates when supplementary irrigation or drought-resistant varieties may be needed.

Effective Rainfall Coefficient

Typical values: 0.5-0.8 depending on soil type, slope, and conservation practices. Higher values indicate better rainfall retention.

Climate Stress Factor

Increases water requirements during drought or heat stress conditions. Values >1.0 indicate stress conditions that increase crop water needs.

Rainfed System Metrics

These metrics aggregate data from all cropping systems in the rainfed agriculture area, providing a comprehensive overview of water availability, water deficit, costs, revenue, and environmental impacts specific to rainfed farming.

Quick Navigation

📊 Basic Aggregates 💧 Water Metrics 💰 Cost Aggregates 📈 Economic Indicators 🌱 Environmental Impact

📊 Basic Aggregates

Total Cultivated Area (ha)

Sum of cultivated areas across all cropping systems in the rainfed agriculture area.

Number of Systems

Total count of active cropping systems in the rainfed agriculture area.

💧 Water Metrics

Total Water Demand (Mm³)

$$Q_{demand} = \sum_{i=1}^{n} (A_i \times WR_i \times 10) / 1,000,000$$

Where:
• $A_i$ = Cultivated area of each crop (ha)
• $WR_i$ = Water requirement of each crop (mm)
• 10 = Conversion factor (1 ha = 10,000 m², 1 mm = 0.001 m, so 1 mm×ha = 10 m³)
• 1,000,000 = Conversion from m³ to Mm³
Sum of water needed for all cropping systems during the growing season.

Effective Rainfall (Mm³)

$$R_{eff} = (P \times A \times C_e \times 10) / 1,000,000$$

Where:
• $P$ = Annual rainfall (mm)
• $A$ = Total cultivated area (ha)
• $C_e$ = Effective rainfall coefficient (0-1)
• 10 = Conversion factor (ha to m²)
• 1,000,000 = Conversion to Mm³
The portion of rainfall that is actually available for crop use after accounting for runoff and other losses.

Water Deficit (Mm³)

$$D_{water} = \max(0, Q_{demand} - R_{eff})$$

The gap between water demand and effective rainfall. If negative, sufficient rainfall meets crop needs. Positive values indicate supplementary irrigation or water stress.

💰 Cost Aggregates

💡 Note: For saved systems, the metrics use the precise calculated values from the database. For new/unsaved systems, costs are estimated using per-hectare input values multiplied by cultivated area.

Labour Cost

Sum of labour costs from all cropping systems. For saved systems, uses calculated values (Area × Days × Cost/Day). For new systems, uses Area × Labour Cost Per Hectare.

Mechanization, Nitrogen, Pesticide & Other Costs

Each cost component is summed across all systems. Saved systems use their detailed calculations based on actual input quantities and prices. New systems use per-hectare cost inputs.

Total Crop Cost

$$C_{total} = C_{labour} + C_{mech} + C_{seeds} + C_{nitrogen} + C_{fert} + C_{pest} + C_{other}$$

Sum of all production costs including labour, mechanization, inputs, and other expenses.

Total Revenue

$$R_{total} = \sum_{i=1}^{n} (Y_i \times A_i \times P_i)$$

Where:
• $Y_i$ = Yield of each crop (t/ha)
• $A_i$ = Area of each crop (ha)
• $P_i$ = Price per unit (money/t)
Total income from crop sales across all systems.

📈 Economic Indicators

Gross Profit

$$Profit = R_{total} - C_{total}$$

Total revenue minus total production costs. Indicates overall economic viability of the rainfed agriculture system.

Average Water Productivity

$$WP = R_{total} / (Q_{demand} \times 1,000,000)$$

Economic return per cubic meter of water used. Higher values indicate more efficient water use.

🌱 Environmental Impact

Nitrate Pollution (kg)

$$N_{poll} = \sum_{i=1}^{n} (A_i \times N_i \times (1 - E_n) \times R_n)$$

Where:
• $A_i$ = Cultivated area (ha)
• $N_i$ = Nitrogen application (kg/ha)
• $E_n$ = Nitrogen use efficiency (default 0.8)
• $R_n$ = Nitrification rate (default 0.3)
For saved systems, uses calculated values based on actual nitrogen inputs. For new systems, estimates based on nitrogen cost.

Pesticide Pollution (kg)

$$P_{poll} = \sum_{i=1}^{n} (A_i \times P_i \times (1 - E_p))$$

Where:
• $A_i$ = Cultivated area (ha)
• $P_i$ = Pesticide application (kg/ha)
• $E_p$ = Pesticide treatment efficiency (default 0.8)
For saved systems, uses calculated values. For new systems, estimates based on pesticide cost.

Carbon Footprint (kg CO₂e)

$$CF_{saved} = \sum_{i=1}^{n} [A_i \times (N_i \times 5.5 + P_i \times 1.2 + K_i \times 0.6 + Pest_i \times 10 + Labour_i \times 2 + Mech_i \times 50)]$$

$$CF_{new} = \sum_{i=1}^{n} (A_i \times 100)$$

For saved systems, uses detailed calculation based on actual inputs (nitrogen, phosphorus, potassium, pesticides, labour, mechanization). For new systems, uses simplified estimate of 100 kg CO₂e per hectare. Total greenhouse gas emissions from all rainfed agriculture activities.

🌱 Carbon Sequestration (kg CO₂e)

$CS = \sum_{i=1}^{n} (A_i \times Y_i \times F_i)$

Where:
• $A_i$ = Cultivated area of each crop (ha)
• $Y_i$ = Yield per hectare (t/ha)
• $F_i$ = Carbon sequestration factor (kg CO₂e/t)
Total carbon dioxide equivalent sequestered by crops through photosynthesis and biomass production. This represents the positive environmental impact of crop growth in capturing atmospheric carbon.

💡 Note: The carbon sequestration factor varies by crop type and farming practices. Typical values range from 200-400 kg CO₂e per ton of crop production. Higher values indicate crops with greater carbon capture potential.

⚠️ Important Notes

Metrics are recalculated automatically whenever you modify cropping system data or rainfed agriculture parameters.
All metrics are aggregated at the rainfed agriculture asset level and saved when you click Save.
Dual Calculation Approach: For saved cropping systems, metrics use precise calculated values from the database (based on detailed input quantities and prices). For new/unsaved systems, metrics are estimated using per-hectare cost fields.
Each cropping system now has input fields for per-hectare costs (labour, mechanization, nitrogen, fertilizer, seeds, pesticide, and other costs) for simplified data entry.
Water deficit may indicate the need for supplementary irrigation or improved water management practices.
Water demand conversion: 1 mm of water over 1 hectare = 10 m³. The formula correctly accounts for this conversion.
Environmental impact metrics (pollution, carbon footprint) use detailed calculations for saved systems and simplified estimates for new systems.
Carbon sequestration factor is customizable per crop and typically ranges from 200-400 kg CO₂e per ton of crop production.

Rainfed Agricultural Data Fields

These fields define the general characteristics of your rainfed agriculture area. They provide the environmental, soil, and economic context that applies to all cropping systems within this rainfed area.

Quick Navigation

📐 Area Parameters 🌧️ Rainfall Parameters 🌱 Soil Parameters 💰 Economic Parameters 🛡️ Conservation Parameters

📐 Area Parameters

Total Area (ha)

The total land area designated for rainfed agriculture, measured in hectares. This includes both cultivated and fallow land.

💡 Typical Range: 10-10,000 ha depending on farm size and region

Cultivated Area (ha)

The portion of the total area that is actively cultivated with crops. This should be less than or equal to the total area.

💡 Note: The difference between total and cultivated area represents fallow land, infrastructure, or buffer zones.

🌧️ Rainfall Parameters

Annual Rainfall (mm)

The average annual precipitation in millimeters for your location. This is the primary water source for rainfed agriculture.

🌍 Global Context:
• Arid: <250 mm/year
• Semi-arid: 250-500 mm/year
• Sub-humid: 500-1000 mm/year
• Humid: >1000 mm/year

Effective Rainfall Coefficient (0-1)

The fraction of total rainfall that is actually available for crop use. Accounts for losses due to runoff, deep percolation, and evaporation.

$$R_{eff} = R_{total} \times C_{eff}$$

📊 Typical Values:
• Sandy soil: 0.5-0.6
• Loamy soil: 0.7-0.8
• Clay soil: 0.6-0.7
• With conservation practices: 0.8-0.9

Rainfall Variability (0-1)

The coefficient of variation of annual rainfall. Higher values indicate greater year-to-year unpredictability, increasing production risk.

⚠️ Risk Levels:
• Low variability: <0.2
• Moderate: 0.2-0.3
• High: 0.3-0.5
• Very high: >0.5

🌱 Soil Parameters

Soil Health Factor (0.7-1.3)

A multiplier representing overall soil fertility and health. Affects crop productivity. Values >1.0 indicate above-average soil quality, <1.0 indicate degraded soils.

🎯 Interpretation:
• Degraded: 0.7-0.85
• Average: 0.85-1.15
• Good: 1.15-1.25
• Excellent: 1.25-1.3

Soil Water Retention (mm)

The total depth of plant-available water that can be stored in the soil profile. Critical for crop survival during dry spells between rainfall events.

$$WHC = (FC - PWP) \times D_{root}$$

Where:
• $FC$ = Field capacity
• $PWP$ = Permanent wilting point
• $D_{root}$ = Root zone depth

📏 By Soil Type:
• Sandy: 80-120 mm
• Loamy: 150-200 mm
• Clay: 180-250 mm

Infiltration Rate (0-1)

The fraction of rainfall that infiltrates into the soil rather than running off. Higher values mean more water enters the soil.

🌊 Factors Affecting:
• Soil texture and structure
• Slope steepness
• Vegetation cover
• Conservation practices

💰 Economic Parameters

Maintenance Cost (money/ha/year)

Annual cost per hectare for maintaining rainfed agriculture infrastructure and general land maintenance. Includes terraces, contour bunds, access roads, etc.

Operational Cost (money/ha/year)

Annual operational expenses per hectare not directly related to crop production. Includes land taxes, insurance, general farm overhead, administrative costs.

🛡️ Conservation Parameters

Erosion Risk Factor (0-1)

The inherent risk of soil erosion based on topography, soil type, and climate. Higher values indicate greater erosion susceptibility.

⚠️ Risk Categories:
• Low: <0.2 (flat, well-vegetated)
• Moderate: 0.2-0.4 (gentle slopes)
• High: 0.4-0.6 (steep slopes)
• Very high: >0.6 (very steep, bare soil)

Conservation Practices Efficiency (0-1)

The effectiveness of implemented soil and water conservation practices in reducing erosion and improving water retention. Higher values indicate better conservation.

🌾 Practice Examples:
• Contour farming: 0.5-0.6
• Terracing: 0.7-0.8
• Mulching + cover crops: 0.8-0.9
• Integrated conservation: 0.9-1.0

🔄 How These Fields Are Used

Rainfall parameters calculate the effective water available to all crops in the area
Soil parameters affect crop yields and water use efficiency across all cropping systems
Economic parameters are added to crop-specific costs for total farm profitability analysis
Conservation parameters influence environmental sustainability indicators
All values are applied at the rainfed area level and affect system-wide metrics

⚠️ Important Notes

These parameters represent area-wide conditions and should be based on average or representative values.
Rainfall data should preferably be based on 10-20 years of historical records for accuracy.
Soil parameters can be obtained from soil surveys, field measurements, or local agricultural extension services.
Conservation practice efficiency should reflect actual implemented practices, not theoretical maximum values.
All fields are required for accurate system metrics calculation.
Changes to these fields will affect all cropping systems in this rainfed area.

Rainfed Water Requirements Calculator

Rainfall Data Source:

Scenario time series rainfall Nearest weather station

ET0 Data Source:

Select Calculation Period

Start Year:

End Year:

Crop Information

Selected Crop:

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Monthly Crop Coefficients (Kc):

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Calculation Results

Calculated Water Requirement: -

mm/year

Data Sources Used

ET0 Source: -

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Monthly Average ET0 Values (mm/month):

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Annual Rainfall Total: 0 mm/year

Rainfed Water Requirements - All Systems & Turns

Rainfall Data Source:

Scenario time series rainfall Nearest weather station

ET0 Data Source:

Select Calculation Period

Start Year:

End Year:

Note: These years define the historical climate baseline. Future turns automatically use climate projection data.

View Results

Cropping System:

Turn (Year):

After calculation, select a system and turn to preview results.

Crop Information

Selected Crop:

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Reduction Coefficient:

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Monthly Crop Coefficients (Kc):

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Calculation Results

Calculated Water Requirement: -

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Data Sources Used

ET0: -

Rainfall: -

Monthly Average ET0 (mm/month):

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Annual Rainfall Total: 0 mm/year

Rainfed System Metrics

These metrics aggregate data from all cropping systems in the rainfed agriculture area, providing a comprehensive overview of water availability, water deficit, costs, revenue, and environmental impacts specific to rainfed farming.

Quick Navigation

📊 Basic Aggregates 💧 Water Metrics 💰 Cost Aggregates 📈 Economic Indicators 🌱 Environmental Impact

📊 Basic Aggregates

Total Cultivated Area (ha)

Sum of cultivated areas across all cropping systems in the rainfed agriculture area.

Number of Systems

Total count of active cropping systems in the rainfed agriculture area.

💧 Water Metrics

Total Water Demand (Mm³)

$$Q_{demand} = \sum_{i=1}^{n} (A_i \times WR_i \times 10) / 1,000,000$$

Where:
• $A_i$ = Cultivated area of each crop (ha)
• $WR_i$ = Water requirement of each crop (mm)
• 10 = Conversion factor (1 ha = 10,000 m², 1 mm = 0.001 m, so 1 mm×ha = 10 m³)
• 1,000,000 = Conversion from m³ to Mm³
Sum of water needed for all cropping systems during the growing season.

Effective Rainfall (Mm³)

$$R_{eff} = (P \times A \times C_e \times 10) / 1,000,000$$

Where:
• $P$ = Annual rainfall (mm)
• $A$ = Total cultivated area (ha)
• $C_e$ = Effective rainfall coefficient (0-1)
• 10 = Conversion factor (ha to m²)
• 1,000,000 = Conversion to Mm³
The portion of rainfall that is actually available for crop use after accounting for runoff and other losses.

Water Deficit (Mm³)

$$D_{water} = \max(0, Q_{demand} - R_{eff})$$

The gap between water demand and effective rainfall. If negative, sufficient rainfall meets crop needs. Positive values indicate supplementary irrigation or water stress.

💰 Cost Aggregates

💡 Note: For saved systems, the metrics use the precise calculated values from the database. For new/unsaved systems, costs are estimated using per-hectare input values multiplied by cultivated area.

Labour Cost

Sum of labour costs from all cropping systems. For saved systems, uses calculated values (Area × Days × Cost/Day). For new systems, uses Area × Labour Cost Per Hectare.

Mechanization, Nitrogen, Pesticide & Other Costs

Each cost component is summed across all systems. Saved systems use their detailed calculations based on actual input quantities and prices. New systems use per-hectare cost inputs.

Total Crop Cost

$$C_{total} = C_{labour} + C_{mech} + C_{seeds} + C_{nitrogen} + C_{fert} + C_{pest} + C_{other}$$

Sum of all production costs including labour, mechanization, inputs, and other expenses.

Total Revenue

$$R_{total} = \sum_{i=1}^{n} (Y_i \times A_i \times P_i)$$

Where:
• $Y_i$ = Yield of each crop (t/ha)
• $A_i$ = Area of each crop (ha)
• $P_i$ = Price per unit (money/t)
Total income from crop sales across all systems.

📈 Economic Indicators

Gross Profit

$$Profit = R_{total} - C_{total}$$

Total revenue minus total production costs. Indicates overall economic viability of the rainfed agriculture system.

Average Water Productivity

$$WP = R_{total} / (Q_{demand} \times 1,000,000)$$

Economic return per cubic meter of water used. Higher values indicate more efficient water use.

🌱 Environmental Impact

Nitrate Pollution (kg)

$$N_{poll} = \sum_{i=1}^{n} (A_i \times N_i \times (1 - E_n) \times R_n)$$

Where:
• $A_i$ = Cultivated area (ha)
• $N_i$ = Nitrogen application (kg/ha)
• $E_n$ = Nitrogen use efficiency (default 0.8)
• $R_n$ = Nitrification rate (default 0.3)
For saved systems, uses calculated values based on actual nitrogen inputs. For new systems, estimates based on nitrogen cost.

Pesticide Pollution (kg)

$$P_{poll} = \sum_{i=1}^{n} (A_i \times P_i \times (1 - E_p))$$

Where:
• $A_i$ = Cultivated area (ha)
• $P_i$ = Pesticide application (kg/ha)
• $E_p$ = Pesticide treatment efficiency (default 0.8)
For saved systems, uses calculated values. For new systems, estimates based on pesticide cost.

Carbon Footprint (kg CO₂e)

$$CF_{saved} = \sum_{i=1}^{n} [A_i \times (N_i \times 5.5 + P_i \times 1.2 + K_i \times 0.6 + Pest_i \times 10 + Labour_i \times 2 + Mech_i \times 50)]$$

$$CF_{new} = \sum_{i=1}^{n} (A_i \times 100)$$

For saved systems, uses detailed calculation based on actual inputs (nitrogen, phosphorus, potassium, pesticides, labour, mechanization). For new systems, uses simplified estimate of 100 kg CO₂e per hectare. Total greenhouse gas emissions from all rainfed agriculture activities.

🌱 Carbon Sequestration (kg CO₂e)

$CS = \sum_{i=1}^{n} (A_i \times Y_i \times F_i)$

Where:
• $A_i$ = Cultivated area of each crop (ha)
• $Y_i$ = Yield per hectare (t/ha)
• $F_i$ = Carbon sequestration factor (kg CO₂e/t)
Total carbon dioxide equivalent sequestered by crops through photosynthesis and biomass production. This represents the positive environmental impact of crop growth in capturing atmospheric carbon.

💡 Note: The carbon sequestration factor varies by crop type and farming practices. Typical values range from 200-400 kg CO₂e per ton of crop production. Higher values indicate crops with greater carbon capture potential.

⚠️ Important Notes

Metrics are recalculated automatically whenever you modify cropping system data or rainfed agriculture parameters.
All metrics are aggregated at the rainfed agriculture asset level and saved when you click Save.
Dual Calculation Approach: For saved cropping systems, metrics use precise calculated values from the database (based on detailed input quantities and prices). For new/unsaved systems, metrics are estimated using per-hectare cost fields.
Each cropping system now has input fields for per-hectare costs (labour, mechanization, nitrogen, fertilizer, seeds, pesticide, and other costs) for simplified data entry.
Water deficit may indicate the need for supplementary irrigation or improved water management practices.
Water demand conversion: 1 mm of water over 1 hectare = 10 m³. The formula correctly accounts for this conversion.
Environmental impact metrics (pollution, carbon footprint) use detailed calculations for saved systems and simplified estimates for new systems.
Carbon sequestration factor is customizable per crop and typically ranges from 200-400 kg CO₂e per ton of crop production.

Drought Indices Calculation Guide

Overview

Drought indices are quantitative measures used to assess the severity and extent of drought conditions in a specific region. These indices combine meteorological and vegetation data to provide a comprehensive understanding of drought status. They are essential tools for water resource management, agricultural planning, and climate monitoring.

Drought Indices Explained

SPI - Standardized Precipitation Index

Definition: The SPI measures the deviation of precipitation from the long-term average, standardized to account for the variability of precipitation at different time scales.

Calculation: SPI = (Precipitation - Mean) / Standard Deviation

Range: -3 to +3

Interpretation:

SPI ≥ 2.0: Extremely wet
1.5 to 1.99: Very wet
1.0 to 1.49: Moderately wet
-0.99 to 0.99: Near normal
-1.49 to -1.0: Moderately dry
-1.99 to -1.5: Very dry
≤ -2.0: Extremely dry

Use Case: Ideal for assessing precipitation-based drought conditions at various time scales (1, 3, 6, 12 months)

SPEI - Standardized Precipitation-Evapotranspiration Index

Definition: The SPEI extends the SPI by incorporating both precipitation and temperature (through evapotranspiration), providing a more comprehensive drought assessment that accounts for water demand.

Calculation: SPEI = (Precipitation - Potential Evapotranspiration) standardized

Range: -3 to +3

Interpretation: Same as SPI, but accounts for temperature effects on water availability

Use Case: Better for regions with significant temperature variations and for assessing agricultural drought

NDVI - Normalized Difference Vegetation Index

Definition: NDVI measures vegetation greenness and health by comparing red and near-infrared light reflected by vegetation.

Calculation: NDVI = (NIR - Red) / (NIR + Red)

Range: -1 to +1

Interpretation:

NDVI > 0.5: Dense vegetation
0.3 to 0.5: Moderate vegetation
0.1 to 0.3: Sparse vegetation
< 0.1: Bare soil or water

Use Case: Direct indicator of vegetation stress and drought impact on crops and natural vegetation

VCI - Vegetation Condition Index

Definition: VCI normalizes NDVI values relative to historical minimum and maximum values, providing a relative measure of vegetation condition.

Calculation: VCI = (NDVI - NDVImin) / (NDVImax - NDVImin) × 100

Range: 0-100%

Interpretation:

VCI > 50%: Good vegetation condition
30-50%: Moderate vegetation condition
< 30%: Poor vegetation condition (drought stress)

Use Case: Identifies vegetation stress relative to historical norms, useful for early drought detection

TCI - Temperature Condition Index

Definition: TCI measures temperature stress on vegetation by normalizing land surface temperature relative to historical extremes.

Calculation: TCI = (TSTmax - TST) / (TSTmax - TSTmin) × 100

Range: 0-100%

Interpretation:

TCI > 50%: Cool/favorable temperatures
30-50%: Moderate temperature stress
< 30%: High temperature stress

Use Case: Identifies heat stress on vegetation, important for assessing drought severity in hot regions

VHI - Vegetation Health Index

Definition: VHI combines VCI and TCI to provide a comprehensive vegetation health assessment that accounts for both moisture and temperature stress.

Calculation: VHI = 0.1 × VCI + 0.9 × TCI

Range: 0-100%

Interpretation:

VHI > 50%: Good vegetation health
30-50%: Moderate vegetation stress
< 30%: Severe vegetation stress (drought)

Use Case: Comprehensive drought indicator combining moisture and temperature effects, best for overall drought assessment

Data Requirements

Minimum Data Period: At least 12 months of historical data is recommended for accurate calculations

Data Sources:

Precipitation & Temperature: NASA POWER API
Vegetation Data: MODIS/Sentinel satellites
Land Surface Temperature: MODIS thermal bands

Temporal Resolution: Monthly aggregated data for consistency and reliability

Data Storage & Calculation

Database Model: DamWatershedTimeSeriesData

Key Columns Used:

date: The date field stores the month and year of the measurement
data_type: Specifies the type of data (e.g., 'rainfall_nasa', 'temperature_nasa_power', 'npp_wapor')
value: The numeric measurement value stored as a float

Data Types Used for Calculations:

SPI: Uses 'rainfall_nasa' or 'rainfall_chirps' values
SPEI: Uses 'rainfall_*' and 'temperature_*' values to calculate water balance
NDVI: Calculated from satellite vegetation indices (derived from MODIS data)
VCI: Derived from NDVI values relative to historical min/max
TCI: Uses land surface temperature data from satellite thermal bands
VHI: Combines VCI and TCI values (0.1×VCI + 0.9×TCI)

Spatial Coverage

NDVI & Vegetation Indices:

NDVI and related vegetation indices (VCI, TCI, VHI) are calculated at the watershed centroid location. The centroid represents the geographic center of the watershed area and is used as the representative point for extracting satellite vegetation data.

Why Centroid?

Provides a single representative value for the entire watershed
Reduces computational complexity for large watershed areas
Ensures consistency in time series analysis
Satellite data is typically available at 250m-1km resolution, making centroid extraction practical

Precipitation & Temperature: These indices use point-based data extracted at the watershed centroid from global meteorological datasets (NASA POWER API).

How to Interpret Results

Compare multiple indices for a comprehensive drought assessment
SPI and SPEI indicate meteorological drought conditions
NDVI, VCI, TCI, and VHI indicate vegetation and agricultural drought
Negative SPI/SPEI values and low VCI/TCI/VHI values indicate drought conditions
Monitor trends over time to identify emerging or worsening drought situations
Use results to inform water management and agricultural planning decisions

Important Notes

Calculations may take a few moments depending on data availability and time period
Data quality depends on the availability of satellite and meteorological data for your location
Results are most reliable when using at least 5 years of historical data
Different indices may show different drought signals - use multiple indices for validation
Consult with water resource and agricultural experts for decision-making based on these indices

Download Rainfall Data

Date Range

Start Date

End Date

Select API Source

NASA

NASA POWER

Global meteorological data

CHIRPS

Climate Hazards Group data

Data will be used to calculate annual average precipitation

Download Temperature Data

Date Range

Start Date

End Date

Select API Source

OM

Open-Meteo

Free historical weather data

ClimateServ

Climate temperature data

Temperature Type

Minimum

Daily min temp

Maximum

Daily max temp

Average

Daily avg temp

Data will be used to calculate average temperature values

Download Satellite Data

Download satellite data for your asset including rainfall, temperature, evapotranspiration, land cover, productivity, and soil moisture data from various sources like NASA, CHIRPS, and WAPOR.

📊 Available Data Types

💧 Rainfall

Download precipitation data from multiple sources:

NASA: Global Precipitation Measurement (GPM) data
CHIRPS: Climate Hazards Group InfraRed Precipitation with Station data
WAPOR: FAO WaPOR precipitation data

🌡️ Temperature

NASA temperature data including minimum, maximum, and average temperatures.

💨 Evapotranspiration

WAPOR evapotranspiration data:

AETI: Actual Evapotranspiration and Interception
RET: Reference Evapotranspiration

🗺️ Land Cover Classification

Land cover classification data from WAPOR and Copernicus sources.

🌾 Productivity

WAPOR productivity indicators:

NPP: Net Primary Production
GBWP: Gross Biomass Water Productivity

🌱 Soil Moisture

WAPOR Relative Soil Moisture (RSM) data.

📝 How to Download Data

Select Date Range: Choose the start and end dates for your data download.
Choose Data Category: Select from Rainfall, Temperature, Evapotranspiration, Land Cover, Productivity, or Soil Moisture.
Select Specific Data Type: Choose the specific data source (e.g., NASA, CHIRPS, WAPOR).
Optional - Download TIF: Check this option to also download the raw GeoTIFF files.
Click Download: The data will be processed and downloaded as a CSV file with time series data.

📄 Output Format

Downloaded data is provided in CSV format with the following columns:

Date: The date of the observation
Value: The measured value (units depend on data type)
Source: The data source (NASA, CHIRPS, WAPOR, etc.)

Tips

Larger date ranges may take longer to process
TIF files are large - only download if you need the raw geospatial data
Some data types may not be available for all date ranges
Data is automatically aggregated for your asset's geographic boundary

Loading time series data...

Data Types

Start Year

End Year

Time Scale

Monthly Yearly

Data Summary

Total Records: -

Data Types: -

Year Range: -

Asset Type: -

Loading time series data...

Game Session Configuration

Configure your game session with basic information, scenario development parameters, and game turns. These settings define the context and progression of the WEFE Nexus simulation.

Quick Navigation

📋 Basic Information 💰 Economic Parameters ⚠️ Climate Risk 🌡️ Climate Change 🔄 Game Turns

📋 Basic Information

Game Name

A descriptive name for your game session that helps identify it in the list of sessions. Choose a name that reflects the scenario or region being simulated.

Description

Optional detailed description of the game session, including objectives, context, or notes for participants.

Scenario

Select the geographic scenario that provides the map boundaries, water resources, and initial assets for the simulation.

💰 Economic Scenario Parameters

Economic Growth Rate (%/year)

Default: 2.5% per year

The annual rate of economic growth that affects resource prices, demand, and player revenues. Higher growth rates increase economic activity but may stress water-energy-food resources.

💡 Tip: Typical values range from 1-5%. Use lower values for stable economies, higher values for developing regions.

⚠️ Climate Risk Parameters

Drought Probability (%/year)

Default: 10% chance per year

The annual probability of a drought event occurring, which reduces water availability and may trigger water restrictions or crop failures.

⚠️ Impact: Drought events reduce water resources, increase irrigation costs, and can damage crops and ecosystems.

Flood Probability (%/year)

Default: 10% chance per year

The annual probability of a flood event occurring, which can damage infrastructure, contaminate water supplies, and disrupt agricultural activities.

⚠️ Impact: Flood events damage assets, reduce water quality, and can cause economic losses.

🌡️ Climate Change Projections

Temperature Increase (°C/year)

Default: 0.02°C per year

The annual rate of temperature increase due to climate change. This affects evapotranspiration rates, crop water requirements, and ecosystem health.

🌡️ Context: IPCC projections suggest 0.015-0.03°C/year depending on emissions scenario. Over 20 years, this means 0.3-0.6°C total warming.

Precipitation Decrease (mm/year)

Default: 0.5 mm per year

The annual decrease in precipitation due to climate change. This directly reduces water availability for agriculture, ecosystems, and urban water supplies.

💧 Impact: Combined with temperature increase, this creates water stress. Over 20 years: 10mm less rain + higher evaporation = significant water deficit.

🔄 Game Turns

What are Game Turns?

Each game turn represents one year in the simulation. During each turn, players make decisions about resource allocation, infrastructure development, and policy implementation. The system then calculates the impacts on the WEFE Nexus.

Turn Number

The sequence number of the turn (1, 2, 3, ...). This determines the order in which turns are played.

Year

The calendar year represented by this turn (e.g., 2024, 2025, 2026). This helps contextualize the simulation timeline.

💡 Managing Turns

Use 'Add Turn' to create a new year in the simulation
Use 'Copy from Previous Year' to duplicate data when editing
Turns must be sequential - you cannot skip years
Climate change effects accumulate across turns

WEFE Nexus Integration

These scenario parameters work together to simulate the complex relationships in the Water-Energy-Food-Ecosystem (WEFE) Nexus:

Economic growth increases demand for water, energy, and food
Temperature increase raises crop water requirements and energy for cooling
Reduced precipitation stresses all sectors simultaneously
Extreme events (drought/flood) test system resilience
Trade-offs between sectors become more pronounced over time

Field	Symbol	Unit	Default	Description
Discharge	\(Q\)	l/s	from CWR	Peak pumping flow rate (auto-filled from CWR peak month)
Total Manometric Head	\(H\)	m	25	Static head + friction losses in the pipeline
Motor-Pump Efficiency	\(\eta_{mp}\)	—	0.8	Combined efficiency of motor and pump (0–1)
Daily Operating Hours	\(h_{op}\)	h/day	10	Number of hours the pump operates per day
Performance Ratio	\(PR\)	—	0.75	Overall system losses: wiring, soiling, temperature, inverter (0–1)
Panel Area	\(A_{panel}\)	m²	1	Active area of one PV panel
Panel Efficiency	\(\eta_{panel}\)	%	20	Conversion efficiency at STC (Standard Test Conditions)
Water Density	\(\rho\)	kg/m³	1000	Density of water (adjust for saline/warm water)
Temp. Coefficient	\(\gamma\)	/°C	0.004	Power loss per °C above 25 °C — typical crystalline Si: 0.004/°C
Startup Safety Margin	\(f_s\)	%	20	Extra capacity (20–25 %) to overcome static friction and ensure reliable early-morning start

Loss Component	Symbol	Typical Range	Default	Notes
DC wiring losses	\(L_{wiring}\)	1–5 %	3 %	Resistive losses in cables from panels to controller
Inverter / MPPT controller	\(L_{inv}\)	3–12 %	7 %	Variable-speed drive or inverter efficiency losses
Soiling / dust	\(L_{soil}\)	5–15 %	10 %	Major factor in arid Morocco — depends on cleaning frequency (1–2 × / month recommended)

\(R_{ratio}\)	Assessment	Implication
< 1.05	⚠️ Undersized	Array may not start pump reliably or sustain rated flow
1.10 – 1.30	✅ Optimal	Good balance — surplus accounts for temperature derating and safety margin
> 1.35	⚠️ Oversized	Unnecessary cost; consider adding a storage tank instead

Symbol	Name	Unit	Notes
\(Q\)	Design discharge	l/s (then m³/s)	From CWR peak month continuous-flow equivalent
\(H\)	Total Manometric Head	m	Static head + friction losses (HMT)
\(\rho\)	Water density	kg/m³	Typically 1000 (pure water at 4 °C)
\(g\)	Gravitational acceleration	m/s²	9.81 m/s²
\(\eta_{mp}\)	Motor-pump efficiency	—	Combined motor × pump (0–1)
\(h_{op}\)	Daily operating hours	h/day	Pump run time per day
\(G_{daily}\)	Daily solar radiation	MJ/m²/day	From MoroccoWeatherDataGrid (IDW-interpolated)
\(PSH\)	Peak Solar Hours	kWh/m²/day	\(G_{daily}/3.6\)
\(PSH_{design}\)	Design-month PSH	kWh/m²/day	PSH of peak irrigation month
\(PR\)	Performance Ratio	—	System losses factor (typical 0.70–0.85)
\(L_{wiring}\)	Wiring losses	—	Typical 0.01–0.05; part of PR breakdown
\(L_{inv}\)	Inverter/controller losses	—	Typical 0.03–0.12; part of PR breakdown
\(L_{soil}\)	Soiling losses	—	Typical 0.05–0.15 in Morocco; part of PR breakdown
\(P_{hyd}\)	Hydraulic power	kW	\(\rho g Q H / 1000\)
\(P_{abs}\)	Absorbed power	kW	\(P_{hyd} / \eta_{mp}\)
\(E_{day}\)	Daily energy	kWh/day	\(P_{abs} \times h_{op}\)
\(P_{solar}\)	Required solar power	kWp	\(E_{day} / (PSH_{design} \times PR)\)
\(f_s\)	Startup safety margin	—	Fractional extra capacity (0.20–0.25) for reliable pump start
\(\gamma\)	Temperature coefficient	/°C	Typical 0.004/°C (crystalline Si); power loss per °C above 25 °C
\(T_{cell}\)	Cell temperature	°C	\(T_{amb,max} + 25\) (NOCT approx.)
\(P_{solar,\,temp}\)	Temp-derated power	kWp	\(P_{solar} / [1 - \gamma(T_{cell}-25)]\)
\(R_{ratio}\)	Array-to-motor ratio	—	\(P_{installed} / P_{abs}\); ideal 1.10–1.30
\(A_{panel}\)	Panel area	m²	Physical aperture area of one module
\(\eta_{panel}\)	Panel efficiency	—	At STC (1000 W/m², 25 °C)
\(P_{panel}\)	Panel peak power	Wp	\(A_{panel} \times \eta_{panel} \times 1000\)
\(N\)	Number of panels	—	\(\lceil P_{solar}/(P_{panel}/1000) \rceil\)
\(P_{installed}\)	Installed capacity	kWp	\(N \times A_{panel} \times \eta_{panel}\)
\(S_{total}\)	Total panel area	m²	\(N \times A_{panel}\)
\(\beta_{opt}\)	Optimal tilt angle	°	\(\approx \|\varphi\|\); adj. ±15° for seasonal opt.
\(Y_{spec}\)	Specific yield	kWh/kWp/year	\(PSH_{annual} \times PR \times 365\)

Field	Symbol	Default	Description
Start / End year	—	current year	Filters climate records to the selected period; multi-year data are averaged.
Value chain	—	—	Crop family (e.g. cereals, vegetables); average Kc of all member crops is used.
Crop	—	optional	If specified, overrides value-chain Kc with the individual crop's monthly Kc values.
ET0 method	—	Blaney-Criddle	Algorithm used to compute reference evapotranspiration (see sections below).
Irrigation efficiency	\(\eta_{irr}\)	0.70	Fraction of delivered water that reaches the root zone (drip ≈ 0.90, sprinkler ≈ 0.75, surface ≈ 0.55).
Reduction coefficient	\(K_{red}\)	1.00	Multiplier applied to Kc; used to model deficit irrigation or stressed conditions.
Leaching requirement	\(LR\)	0.00	Extra water fraction needed to leach salts below the root zone; added on top of CWR.
Irrigated area	\(A\)	1 ha	Area used to convert depth-based demand (mm) to volumetric demand (Mm³) and sizing discharge (l/s).
Effective rainfall coeff.	\(\alpha_{rain}\)	0.70	Fraction of rainfall that is effectively stored in the root zone (varies by rainfall intensity, soil, slope).

Intermediate variable	Formula	Notes
Saturation vapour pressure \(e_s\)	\(e_s = 0.6108\,\exp\!\left(\tfrac{17.27\,T}{T+237.3}\right)\)	kPa; \(T\) in °C
Actual vapour pressure \(e_a\)	\(e_a = e_s \times RH/100\)	kPa; \(RH\) in %
Vapour pressure deficit \(\delta e\)	\(\delta e = e_s - e_a\)	kPa
Slope of SVP curve \(\Delta\)	\(\Delta = \dfrac{4098\,e_s}{(T+237.3)^2}\)	kPa/°C
Psychrometric constant \(\gamma\)	\(\gamma = 0.000665 \times P_{atm}\)	kPa/°C; \(P_{atm}\) in kPa
Net radiation \(R_n\)	\(R_n \approx 0.77 \times R_s\)	Simplified; albedo α = 0.23 → \(1-\alpha = 0.77\)
Soil heat flux \(G\)	\(G \approx 0\)	Negligible at daily time step

Symbol	Name	Unit	Notes
\(P_m\)	Monthly rainfall	mm/month	IDW-interpolated from 6 nearest stations
\(\alpha_{rain}\)	Effective rainfall coeff.	—	User input, default 0.70
\(P_{eff,m}\)	Effective monthly rainfall	mm/month	\(\alpha_{rain} \times P_m\)
\(ET_{0,m}\)	Reference ET (monthly)	mm/month	BC, PM or WaPOR method
\(K_{c,m}\)	Crop coefficient	—	FAO-56 based, per month
\(K_{red}\)	Reduction coefficient	—	1.0 = full ET; < 1 = deficit
\(ET_{c,m}\)	Crop ET (monthly)	mm/month	\(ET_{0,m} \times K_{c,m} \times K_{red}\)
\(CWR_m\)	Crop water requirement	mm/month	\(\max(0, ET_{c,m} - P_{eff,m})\)
\(\eta_{irr}\)	Irrigation efficiency	—	User input, default 0.70
\(LR\)	Leaching requirement	—	User input, default 0.0
\(IWD_m\)	Irrigation water demand (monthly)	mm/month	\(CWR_m / \eta_{irr} \times (1+LR)\)
\(A\)	Irrigated area	ha	User input
\(IWD_{Mm^3}\)	Annual volumetric demand	Mm³/year	\(\sum IWD_m \times A \times 10 / 10^6\)
\(m^*\)	Peak month	—	Month with max IWD
\(Q_{design}\)	Sizing discharge	l/s	Continuous-flow equiv. for peak month
\(T\)	Mean daily temperature	°C	BC and PM input
\(R_s\)	Solar radiation	MJ/m²/day	BC with radiation
\(R_n\)	Net radiation	MJ/m²/day	\(0.77 R_s\) (PM simplification)
\(\Delta\)	SVP curve slope	kPa/°C	PM formula
\(\gamma\)	Psychrometric constant	kPa/°C	\(0.000665 \times P_{atm}\)
\(\delta e\)	Vapour pressure deficit	kPa	\(e_s - e_a\)
\(u_2\)	Wind speed at 2 m	m/s	PM input
\(RH\)	Relative humidity	%	PM input
\(P_{atm}\)	Atmospheric pressure	kPa	PM input

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