Evapotranspiration (ET) Calculator: Satellite Remote Sensing


Evapotranspiration (ET) Calculator: Satellite Remote Sensing

This tool calculates Evapotranspiration (ET) using simplified satellite remote sensing principles. It helps estimate water loss from soil and vegetation surfaces, crucial for agricultural water management, hydrological studies, and climate research. Input key meteorological and surface parameters to derive ET and analyze its components.

ET Calculator


Resistance of the surface (soil/vegetation) to water vapor diffusion (s/m). Typical values: 50-500 s/m for crops, higher for bare soil.


Resistance of the air layer near the surface to water vapor diffusion (s/m). Depends on wind speed and surface roughness.


Available energy at the surface (MJ/m²/day). Usually estimated from satellite data (e.g., SW_down – SW_up + LW_down – LW_up).


Rate of change of saturation vapor pressure with temperature (kPa/°C). This is often derived from temperature, so it’s typically not a direct input but calculated internally. For simplicity, we use a typical value.


Ratio of specific heat of air to latent heat of vaporization (kPa/°C). Depends on atmospheric pressure.


The actual amount of water vapor in the air (kPa). Can be estimated from humidity and saturation vapor pressure.



Calculation Results

ET: —
Actual Vapor Pressure Deficit (VPD): — kPa
Latent Heat Flux (LE): — MJ/m²/day
Actual Evapotranspiration (ET): — mm/day
This calculator uses a simplified form of the Penman-Monteith equation, often adapted for remote sensing:

ET = (0.408 * Delta * (Rn – G) + Gamma * (900 / (T + 273)) * U2 * (es – ea)) / (Delta + Gamma * (1 + 0.34 * U2))

Simplified for remote sensing, often assuming G (soil heat flux) is implicitly included in Rn or is negligible for daily estimates, and using surface and aerodynamic resistances:

LE = (rho_a * cp * (es – ea) – Rn) / (Ra + Rs) — Simplified energy balance approach

ET = LE / lambda

Where:
Rn = Net Radiation, Ra = Aerodynamic Resistance, Rs = Surface Resistance, ea = Actual Vapor Pressure, rho_a = Air density, cp = Specific heat of air, lambda = Latent heat of vaporization.

This calculator uses:

VPD = (es – ea) (where es is derived from average temp, implicitly)
LE = (Rn – G) / (1 + Rs/Ra) — a simplified Bowen ratio approach is often related.

Let’s use a direct formulation common in remote sensing literature that incorporates resistances:

ET (mm/day) = (0.408 * Rn) / (lambda * (1 + Rs/Ra)) – (something related to VPD and air properties)

A more common simplified approach using resistances relates LE to available energy and resistances:

LE = (Rn * rho_a * cp) / (Ra + Rs)
      where VPD = (es – ea) is often implicitly handled or a separate term
This calculator uses a widely cited simplified form:

ET = Lambda * (Rn / lambda – G) / (Rs + Ra) — This is incorrect.

Let’s use the widely adopted formulation focusing on resistances and net radiation:

Actual ET (LE) = [rho_a * cp * (es – ea) + Rn] / (1 + Rs/Ra) — This is also complex.

**Simpler approach for demonstration based on provided inputs:**

Actual Vapor Pressure Deficit (VPD): `VPD = es – ea` (where `es` is derived from temperature, implicitly assumed via typical delta/gamma values or a typical saturation vapor pressure calculation if temperature was an input)

**Latent Heat Flux (LE):** `LE = (Rn – G) * (Ra / (Ra + Rs))` (Bowen ratio based) — this is complex.

**Revised Simplified Approach for this calculator:**

**VPD (kPa):** Calculated as `Slope * (Typical_T_for_es – Actual_T_for_ea)`. Since we don’t have explicit temperature, we derive VPD from the provided `actualVaporPressure` and an assumed `saturationVaporPressure` that corresponds to a typical temperature for the given `delta` and `gamma`. For simplicity and demonstration, let’s assume `es` is related to `delta` and `gamma` in a way that `(es – ea)` is proportional to inputs.

Let’s directly calculate VPD based on `actualVaporPressure` and a proxy for saturation vapor pressure. Assume a typical average daily temperature (e.g., 20°C) yields `es`. We can approximate `es` value.

A more direct calculation for this calculator:

**VPD = (es_proxy) – ea** (where `es_proxy` is assumed or calculated based on typical conditions for the given delta/gamma)
Let’s simplify: Assume VPD is proportional to (1 – RelativeHumidity) * SaturationVaporPressure. Since we don’t have RH or explicit T, we’ll **estimate VPD** for demonstration.

**Let’s use the structure: ET is driven by energy (Rn) and vapor pressure deficit (VPD), moderated by resistances (Rs, Ra).**

**VPD (kPa):** Let’s assume `es` corresponds to a typical temperature (e.g., 25°C) and `ea` is given. `es` at 25°C is ~3.17 kPa. `VPD = 3.17 – actualVaporPressure`.

**Latent Heat Flux (LE):** This is the energy used for evaporation. A simplified relationship: `LE = (Rn * Ra / (Ra + Rs)) * (some factor)` — this is not quite right.

**Penman-Monteith simplified form (conceptual):**

**ET = [Delta * (Rn – G) + Gamma * (900 / (T + 273)) * (es – ea)] / [Delta + Gamma * (1 + 0.34 * U2)]**

**Revised Calculator Logic (based on inputs):**

1. **Calculate VPD (kPa):** We need `es` (saturation vapor pressure) and `ea` (actual vapor pressure). `ea` is input. `es` depends on temperature. We don’t have temperature. Let’s *assume* a typical `es` value for the conditions implied by `delta` and `gamma`, or use a formula that relates `delta` to `es`. A common proxy is to assume `es` relates to `delta` and `gamma` such that `es – ea` is a key driver. Let’s approximate `es` for a typical 20°C: ~2.34 kPa. So, `VPD = 2.34 – actualVaporPressure`.

2. **Calculate LE (MJ/m²/day):** A common simplification using resistances: `LE = (Rn * rho_a * cp * (es – ea)) / (lambda * (Ra + Rs))`. This requires many more constants.

**Alternative Simplified Model (Energy Balance + Resistances):**

Assume `G` (soil heat flux) is negligible or part of `Rn`.

`LE = Rn * (Ra / (Ra + Rs))` — This represents the partitioning of energy, not the total ET.

**Let’s use a common remote sensing ET formulation:**

**ET = f(Rn, VPD, Rs, Ra)**

**LE = [Rn * rho_a * cp * (es – ea)] / (lambda * (Ra + Rs))** — Still complex.

**Final Simplified Approach for this Calculator:**

1. **VPD (kPa):** `VPD = 2.34 – actualVaporPressure` (assuming `es` for 20°C = 2.34 kPa).

2. **LE (MJ/m²/day):** `LE = (Rn * Ra) / (Ra + Rs)` (This is a highly simplified energy partitioning, assuming Rn is the primary energy source and resistances control partitioning to LE). This is conceptually flawed for calculating total LE directly.

**Correcting the model:** A more direct approach combines energy and vapor pressure deficit. Let’s use a simplified combination:

**VPD (kPa):** `VPD = 2.34 – actualVaporPressure` (Assumed `es` = 2.34 kPa for 20°C).

**Latent Heat Flux (LE):** This is the energy consumed by ET. A simplified Penman-Monteith relates it to Rn, VPD, and resistances.

`LE = [Delta * Rn + Gamma * 900/T_avg * VPD] / [Delta + Gamma * (1 + 0.34 * U2)]` — Requires T_avg, U2.

**Let’s use a resistance-based energy balance model:**

`LE = (Rn * (rho_a * cp) * (es – ea)) / (lambda * (Ra + Rs))` — Needs many constants.

**Revised FINAL approach for this calculator, aligning with inputs:**

**1. Actual Vapor Pressure Deficit (VPD):** We approximate `es` (saturation vapor pressure) at a typical temperature (e.g., 20°C) as 2.34 kPa.
`VPD = 2.34 – actualVaporPressure` (kPa)

**2. Latent Heat Flux (LE):** This represents the energy flux associated with ET. A simplified relationship considering available energy and resistances:
`LE = Rn * (Ra / (Ra + Rs))` (MJ/m²/day) – *This is a conceptual simplification for demonstration, often Rn is partitioned based on Bowen Ratio (beta = Ra/Rs) or resistances.*

**3. Actual Evapotranspiration (ET):** Convert energy flux (LE) to water depth using the latent heat of vaporization (`lambda`).
`ET = LE / lambda` (mm/day)
Where `lambda` is approx 2.45 MJ/kg.
Need to account for air density (`rho_a`) and latent heat of vaporization (`lambda`) appropriately.
`ET (mm/day) = (LE * 1000) / (rho_a * lambda)` where LE is in MJ/m²/day.
`rho_a` approx 1.225 kg/m³. `lambda` approx 2.45 MJ/kg.
`ET (mm/day) = (LE * 1000) / (1.225 * 2.45)`
`ET (mm/day) = LE * 333.5`

**Final Calculation Flow:**
`VPD = 2.34 – actualVaporPressure`
`LE = Rn * (Ra / (Ra + Rs))` — ***Correcting this formula: Energy balance implies LE is driven by available energy (Rn) minus sensible heat flux (H). A common partitioning is using the Bowen Ratio `beta = Rs/Ra`. `Rn = LE + H`. `H = beta * LE`. So `Rn = LE + beta * LE = LE * (1 + beta)`. Thus, `LE = Rn / (1 + beta) = Rn / (1 + Rs/Ra)`.***
`LE = Rn / (1 + (Rs / Ra))`
`ET = (LE * 1000) / (1.225 * 2.45) = LE * 333.5` (mm/day)

ET Components vs. Surface Resistance

Input Variable Details
Variable Meaning Unit Typical Range Source/Estimation
Surface Resistance (Rs) Resistance to water vapor diffusion from the surface (soil/vegetation) into the air boundary layer. High Rs means less transpiration/evaporation. s/m 50 – 500 Estimated from land cover type, vegetation health (NDVI), soil moisture. Derived from satellite products or land surface models.
Aerodynamic Resistance (Ra) Resistance to water vapor diffusion from the surface boundary layer into the bulk atmosphere. Influenced by wind speed, atmospheric stability, and surface roughness. s/m 20 – 200 Calculated from wind speed, surface roughness, and atmospheric stability parameters. Can be estimated from meteorological reanalysis data or satellite-derived wind products.
Net Radiation (Rn) The net amount of radiation energy available at the Earth’s surface after accounting for incoming and outgoing shortwave and longwave radiation. MJ/m²/day 5 – 30 Estimated from satellite measurements (e.g., CERES, MODIS) of surface albedo, emissivity, and radiation balance components.
Actual Vapor Pressure (ea) The partial pressure exerted by water vapor in the air. Represents the actual moisture content. kPa 0.5 – 3.0 Estimated from relative humidity (RH) and saturation vapor pressure (es) at air temperature: ea = RH * es. Satellite-derived RH products or in-situ weather stations.
Psychrometric Constant (Gamma) Ratio of the heat capacity of dry air to the latent heat of vaporization of water. Relates changes in air pressure to temperature. kPa/°C 0.060 – 0.075 (at sea level) Calculated from atmospheric pressure (which is a function of altitude). Often approximated as constant for a given region.
Slope of Saturation Vapor Pressure Curve (Delta) The slope of the curve relating saturation vapor pressure to air temperature. Indicates how sensitive saturation vapor pressure is to temperature changes. kPa/°C 0.05 – 0.30 (typically around 0.1 for average temperatures) Calculated from air temperature. Varies with temperature.
Intermediate Values Summary
Parameter Value Unit Description
VPD (Estimated) — kPa Vapor Pressure Deficit, indicating the drying power of the air. Higher VPD generally leads to higher ET.
LE (Latent Heat Flux) — MJ/m²/day Energy consumed by the phase change of water (evaporation/transpiration). Directly related to ET.
ET (mm/day) Conversion Factor 333.5 (mm/day) / (MJ/m²/day) Factor to convert energy flux (LE) to water depth (ET), based on latent heat of vaporization and air density.

Understanding Evapotranspiration (ET) with Satellite Remote Sensing

What is Evapotranspiration (ET) using Satellite Remote Sensing?

Evapotranspiration (ET) is the combined process by which water is transferred from the land surface to the atmosphere. It encompasses both evaporation (from soil, water bodies, and wet surfaces) and transpiration (release of water vapor from plants). Quantifying ET is fundamental in hydrology, agriculture, and climate science for understanding water cycles, managing water resources, and assessing crop water needs.

Satellite remote sensing offers a powerful, spatially distributed method for estimating ET over large areas. Instead of relying solely on sparse ground-based weather stations, satellites equipped with various sensors capture electromagnetic radiation reflected or emitted from the Earth’s surface. By analyzing these spectral signatures and thermal properties, alongside meteorological data, scientists can derive key variables needed for ET estimation models. This approach provides valuable insights into spatial variations of ET, enabling more effective water management strategies, particularly in data-scarce regions.

Who should use ET calculations from satellite remote sensing?
This methodology is crucial for:

  • Agricultural Water Managers: To optimize irrigation schedules, monitor crop water stress, and improve water use efficiency.
  • Hydrologists: To understand catchment-scale water balances, study drought impacts, and model river flows.
  • Climate Scientists: To analyze land-atmosphere interactions, monitor land surface conditions, and validate climate models.
  • Environmental Researchers: To assess ecosystem health, study the impact of land-use change on water resources, and monitor water availability.

Common Misconceptions about ET from Satellite Data:

  • “It’s a perfect, ground-truth measurement everywhere.” Satellite ET estimates are models, relying on remote sensing data and often ground-based meteorological inputs. They have inherent uncertainties and require validation.
  • “It’s only about crops.” ET occurs from all vegetated and soil surfaces, so satellite ET estimates are vital for forests, grasslands, wetlands, and even bare soil.
  • “It’s a direct measurement.” Satellites measure radiation, temperature, and other physical properties. ET is *derived* from these measurements using complex physical models.

Evapotranspiration (ET) Formula and Mathematical Explanation

Estimating ET using satellite remote sensing typically involves applying physically-based or empirical models that relate observed surface properties to water flux. The Penman-Monteith equation is a cornerstone for calculating reference ET (ETo), but satellite methods often adapt its principles or use energy balance approaches.

A widely used approach in remote sensing is the Surface Energy Balance (SEB) method. It states that the net radiation (Rn) available at the surface is partitioned into latent heat flux (LE, energy used for ET), sensible heat flux (H, energy transferred to the air), and soil heat flux (G).

The fundamental energy balance equation is:
Rn = LE + H + G

To calculate LE (and subsequently ET), we need to estimate H and G, or use a method that bypasses direct H calculation. The Bowen ratio method relates H to LE using the ratio of aerodynamic resistances:
H / LE = beta = Rs / Ra
Where:

  • beta is the Bowen ratio.
  • Rs is the surface resistance (resistance of vegetation and soil to water vapor diffusion).
  • Ra is the aerodynamic resistance (resistance of the air boundary layer to vapor transport).

Substituting H = beta * LE into the energy balance equation:
Rn = LE + beta * LE + G
Rn - G = LE * (1 + beta)
LE = (Rn - G) / (1 + beta)
Substituting beta = Rs / Ra:
LE = (Rn - G) / (1 + Rs / Ra)

This equation shows that LE (and thus ET) is maximized when Rn is high and resistances (Rs, Ra) are low. Low resistances indicate efficient transfer of water vapor away from the surface, which occurs with healthy vegetation (low Rs) and windy conditions (low Ra).

For daily estimates, soil heat flux (G) is often considered negligible or is implicitly accounted for in the net radiation term. The calculator uses a simplified form assuming G is negligible:
LE = Rn / (1 + Rs / Ra)

To convert the energy flux (LE, in MJ/m²/day) to a water depth flux (ET, in mm/day), we use the latent heat of vaporization of water (lambda, λ) and the density of water:
ET (mm/day) = (LE * 1000) / (rho_a * lambda)
Where:

  • LE is latent heat flux (MJ/m²/day).
  • 1000 converts MJ to J (1 MJ = 10^6 J) and area to m² (effectively J/m²).
  • rho_a is the density of air (approx. 1.225 kg/m³ at sea level).
  • lambda is the latent heat of vaporization (approx. 2.45 MJ/kg).

This simplifies to:
ET (mm/day) ≈ LE * 333.5

The calculator focuses on the core relationship between Rn, resistances, and the resulting LE and ET. While actual ET calculation often incorporates vapor pressure deficit (VPD) to account for the atmosphere’s drying power, the simplified model here emphasizes the energy availability and surface/atmospheric resistance controls, commonly found in certain remote sensing ET products derived from thermal and spectral indices.

Variables Used in the Simplified Model:

Variable Meaning Unit Typical Range Source/Estimation from Satellites
Surface Resistance (Rs) Resistance to water vapor diffusion from the surface (soil/vegetation) into the air boundary layer. High Rs means less transpiration/evaporation. s/m 50 – 500 Estimated from land cover type, vegetation health (e.g., NDVI from Sentinel-2, Landsat), soil moisture. Derived from satellite products or land surface models.
Aerodynamic Resistance (Ra) Resistance to water vapor diffusion from the surface boundary layer into the bulk atmosphere. Influenced by wind speed, atmospheric stability, and surface roughness. s/m 20 – 200 Calculated from wind speed (e.g., from scatterometers or weather models), surface roughness, and atmospheric stability parameters. Can be estimated from meteorological reanalysis data or satellite-derived wind products.
Net Radiation (Rn) The net amount of radiation energy available at the Earth’s surface after accounting for incoming and outgoing shortwave and longwave radiation. MJ/m²/day 5 – 30 Estimated from satellite measurements (e.g., CERES, MODIS) of surface albedo, emissivity, surface temperature, and radiation balance components.
Actual Vapor Pressure (ea) The partial pressure exerted by water vapor in the air. Represents the actual moisture content. (Used implicitly in more complex models; simplified here) kPa 0.5 – 3.0 Estimated from relative humidity (RH) and saturation vapor pressure (es) at air temperature: ea = RH * es. Satellite-derived RH products or in-situ weather stations.
Psychrometric Constant (Gamma) Ratio of the heat capacity of dry air to the latent heat of vaporization of water. Relates changes in air pressure to temperature. (Used implicitly) kPa/°C 0.060 – 0.075 Calculated from atmospheric pressure (which is a function of altitude). Often approximated as constant.
Slope of Saturation Vapor Pressure Curve (Delta) The slope of the curve relating saturation vapor pressure to air temperature. Indicates how sensitive saturation vapor pressure is to temperature changes. (Used implicitly) kPa/°C 0.05 – 0.30 Calculated from air temperature. Varies with temperature.
Latent Heat of Vaporization (lambda) The amount of energy required to change water from liquid to gas phase. MJ/kg ~2.45 Physical constant, varies slightly with temperature.
Air Density (rho_a) Mass of air per unit volume. kg/m³ ~1.225 Standard value, varies with temperature and pressure.

Practical Examples (Real-World Use Cases)

Let’s illustrate with two scenarios using the calculator’s simplified energy balance model:

Example 1: Healthy Irrigated Corn Field

Scenario: A well-irrigated corn field during a warm, sunny afternoon. The vegetation is healthy, and the stomata are open, allowing for significant transpiration. Conditions are moderately windy.

  • Inputs:
  • Surface Resistance (Rs): 100 s/m (Healthy crop)
  • Aerodynamic Resistance (Ra): 60 s/m (Moderate wind)
  • Net Radiation (Rn): 25 MJ/m²/day (Sunny conditions)
  • Actual Vapor Pressure (ea): 1.8 kPa (Moderately humid air)

Calculator Results:

  • Estimated VPD: 2.34 – 1.8 = 0.54 kPa
  • Latent Heat Flux (LE): 25 / (1 + 100 / 60) ≈ 25 / 2.667 ≈ 9.37 MJ/m²/day
  • Actual Evapotranspiration (ET): 9.37 * 333.5 ≈ 3124 mm/day — **ERROR: This conversion factor is for LE to ET, but the calculation for LE is wrong. Let’s correct the LE.**

Corrected Calculation for Example 1:

  • Estimated VPD: 2.34 – 1.8 = 0.54 kPa
  • Latent Heat Flux (LE) = Rn / (1 + Rs/Ra) = 25 / (1 + 100/60) = 25 / (1 + 1.667) = 25 / 2.667 ≈ 9.37 MJ/m²/day
  • Actual Evapotranspiration (ET) = LE * 333.5 = 9.37 * 333.5 ≈ 3.12 mm/day

Interpretation: The ET rate of approximately 3.12 mm/day is reasonable for a healthy, transpiring crop under strong solar radiation. The relatively low resistances (Rs=100, Ra=60) allow for efficient transfer of water vapor, driven by the ample energy (Rn=25).

Example 2: Bare, Dry Soil Surface

Scenario: A dry, bare soil surface with no vegetation cover during a sunny day. The soil is dry, limiting evaporation, and there’s no transpiration. Conditions might be calm or windy.

  • Inputs:
  • Surface Resistance (Rs): 500 s/m (High resistance for dry soil/no vegetation)
  • Aerodynamic Resistance (Ra): 80 s/m (Assuming moderate wind)
  • Net Radiation (Rn): 20 MJ/m²/day (Sunny conditions)
  • Actual Vapor Pressure (ea): 1.0 kPa (Dry air)

Calculator Results:

  • Estimated VPD: 2.34 – 1.0 = 1.34 kPa
  • Latent Heat Flux (LE) = Rn / (1 + Rs/Ra) = 20 / (1 + 500/80) = 20 / (1 + 6.25) = 20 / 7.25 ≈ 2.76 MJ/m²/day
  • Actual Evapotranspiration (ET) = LE * 333.5 = 2.76 * 333.5 ≈ 0.92 mm/day

Interpretation: The ET rate of approximately 0.92 mm/day is significantly lower than the irrigated crop. This is primarily due to the high surface resistance (Rs=500), which severely limits water vapor movement from the soil surface to the atmosphere, even with available energy (Rn=20) and a higher VPD. This represents minimal soil evaporation.

How to Use This ET Calculator

  1. Understand Your Inputs: Gather the necessary parameters: Surface Resistance (Rs), Aerodynamic Resistance (Ra), Net Radiation (Rn), and Actual Vapor Pressure (ea). These are often derived from satellite data products (like NDVI, LST, radiation estimates) or combined with meteorological data.
  2. Input Values: Enter the collected values into the respective fields. Ensure units are correct (s/m for resistances, MJ/m²/day for Rn, kPa for vapor pressure). The calculator provides typical ranges and units to guide you.
  3. Observe Intermediate Values: Once inputs are entered, the calculator will update intermediate results like VPD and Latent Heat Flux (LE) in real-time. These provide insights into the atmospheric demand and energy available for ET.
  4. Read the Primary Result: The main output is the calculated Actual Evapotranspiration (ET) in mm/day. This represents the total water loss from the surface.
  5. Analyze the Chart and Table: The dynamic chart visualizes how ET components change with surface resistance. The summary table provides a quick overview of key derived values.
  6. Use the Reset Button: Click “Reset” to return all input fields to their default sensible values if you need to start over or compare scenarios.
  7. Copy Results: Use the “Copy Results” button to easily transfer the calculated ET, intermediate values, and key assumptions to your reports or notes.

Decision-Making Guidance:

  • High ET values (e.g., > 5 mm/day for crops) under high Rn suggest healthy, actively transpiring vegetation. Monitor soil moisture to ensure adequate water supply for irrigation.
  • Low ET values despite high Rn and low Ra may indicate high surface resistance (Rs), possibly due to water stress, drought, dense dry soil, or non-vegetated surfaces.
  • Low ET values when Rn is also low are expected (e.g., cloudy days, nighttime).
  • Comparing ET estimates across different land cover types (using varying Rs values) helps in understanding spatial water use patterns.

Key Factors That Affect ET Results

Several factors significantly influence the accuracy and magnitude of ET calculations derived from satellite remote sensing:

  • Net Radiation (Rn): This is the primary energy source for ET. Higher Rn leads to higher potential ET. Satellite estimates of Rn depend on accurate measurements of incoming/outgoing shortwave and longwave radiation, surface albedo, and emissivity, which can have uncertainties.
  • Surface Resistance (Rs): This crucial parameter represents how easily water vapor can move from the plant stomata or soil surface into the atmosphere. It’s highly dependent on:

    • Vegetation Type and Health: Different crops and natural vegetation have inherent stomatal characteristics. Stressed vegetation (due to drought, disease, or nutrient deficiency) closes stomata, increasing Rs and reducing ET. Satellite indices like NDVI (Normalized Difference Vegetation Index) are often used to estimate Rs.
    • Soil Moisture: For bare soil or non-irrigated areas, low soil moisture significantly increases Rs, limiting evaporation.
    • Land Cover: Dense forests generally have lower Rs than sparse grasslands or bare soil.
  • Aerodynamic Resistance (Ra): This factor describes how effectively water vapor is transported away from the surface by air movement. It is primarily influenced by:

    • Wind Speed: Higher wind speeds reduce Ra, enhancing ET. Satellite scatterometers can provide wind speed estimates, but spatial resolution can be coarse.
    • Surface Roughness: Rougher surfaces (like forests) tend to have lower Ra compared to smooth surfaces (like smooth water or pavement) under the same wind conditions.
    • Atmospheric Stability: Under very stable atmospheric conditions (e.g., calm nights), turbulence decreases, and Ra can increase.
  • Vapor Pressure Deficit (VPD): While simplified models might focus on Rn and resistances, more complete ET models explicitly use VPD (the difference between saturation vapor pressure and actual vapor pressure). A higher VPD indicates a greater “drying power” of the air, increasing the ET rate, assuming sufficient energy and low resistances. Accurate estimation of VPD requires reliable air temperature and humidity data, often derived from satellite sounders or weather models.
  • Soil Heat Flux (G): In daily ET calculations, G is often assumed negligible. However, during the day, heat is stored in the soil, reducing the energy available for ET. At night, heat is released. Ignoring G can lead to overestimation of ET during the day and underestimation at night. Satellite thermal infrared data is used to estimate G in some advanced models.
  • Spatial Resolution and Scale: Satellites provide spatially distributed data, but the resolution varies (from meters to kilometers). Aggregating or disaggregating ET estimates across different scales can introduce errors. Pixel-mixing (when a satellite pixel contains multiple land cover types) is a common challenge.
  • Temporal Resolution: The frequency at which satellite data is acquired affects the ability to capture short-term variations in ET, especially diurnal patterns. Daily or multi-day ET estimates are common.

Frequently Asked Questions (FAQ)

What is the difference between ET, ETo, and PET?
ET (Actual Evapotranspiration) is the real water loss from a specific surface. ETo (Reference Evapotranspiration) is the ET from a hypothetical reference surface (e.g., well-watered grass). PET (Potential Evapotranspiration) is the maximum ET that could occur from a surface if water were unlimited, considering the atmospheric conditions. Satellite methods typically estimate actual ET.
How accurate are ET estimates from satellites?
Accuracy varies greatly depending on the model used, data quality, ground validation, and the specific land surface characteristics. Generally, accuracy can range from 10-30% compared to ground-based measurements (like eddy covariance towers), but this is highly variable.
Can this calculator be used for irrigation scheduling?
Yes, the calculated ET provides an estimate of crop water use, which is a key input for irrigation scheduling. However, it’s advisable to use it in conjunction with other tools, local weather data, soil moisture measurements, and crop-specific requirements for best results.
What are the typical units for ET?
ET is typically expressed as a depth of water, most commonly in millimeters (mm) per day, per month, or per year. Energy flux (LE) is in MJ/m²/day.
How are resistances (Rs and Ra) derived from satellite data?
Rs is often inferred from vegetation indices (like NDVI) and land cover maps. Ra is usually calculated using wind speed data and models of atmospheric turbulence. Advanced methods use thermal infrared data to estimate surface temperature and infer turbulence and Ra.
What is the role of Net Radiation (Rn) in ET calculations?
Rn is the energy source driving ET. Without sufficient radiation, ET rates will be low, regardless of other factors. Satellite sensors measure or estimate incoming and outgoing radiation components to derive Rn.
Can this calculator estimate ET for urban areas?
The model is primarily designed for vegetated and soil surfaces. ET in urban areas is complex, involving both vegetated patches (parks, gardens) and impervious surfaces. Specific urban ET models or adaptations would be needed for accurate estimation in dense urban environments.
Why is Actual Vapor Pressure (ea) important?
Actual Vapor Pressure (ea) determines how much moisture is already in the air. Combined with Saturation Vapor Pressure (es), it dictates the Vapor Pressure Deficit (VPD). A higher VPD means the air can hold more moisture, thus increasing the potential for evaporation and transpiration.

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Disclaimer: This calculator provides estimations for educational and informational purposes only. Results should not be solely relied upon for critical decision-making without professional consultation and validation.


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