Science topic

# Evapotranspiration - Science topic

Explore the latest questions and answers in Evapotranspiration, and find Evapotranspiration experts.

Questions related to Evapotranspiration

I downloaded the latent heat flux from fluxnet, the latent heat flux is per hour in W m-2. I summed each value per hour of the day to get the daily sum.

Now I have the daily sum of latent heat flux in W m-2 and want to daily evapotranspiration in mm.

You can calculate this with the formula ET= λ LE/λ. First you calculate the heat of vaporization; λ = 2.501 – (2.361 x 10^-3) x Ta. Where Ta is temperature air in celcius, I also have this daily data.

My calculations in my code (df stands just for dataframe and double ** is ^):

df['heat_of_vaporization'] = 2.501-(2.361*10**-3)*df['TA_daily_average']

df['ET'] = df['LE_daily_sum']/(df['heat_of_evaporation']*1000 *1000)*3600

Is the calculation right? It think I get the good data. I did * 3600 because of the seconds in an hour, added all the hours so not 3600*24 I think. Are the *1000 *1000 also right?

Thanks a lot!

We are working on a formula to calculate irrigation needs for agricultural soil, to help farmers (and the planet) with saving water. We work with water sensors in the agri fields and want to assist the farmers with a time sheet for telling them when they would need to start irrigation. Let's say you need to irrigate field A in 4 days and field B in 9, so they would have a timetable. We have many different factors at the moment, and we do not think it is realistic to account for them all because it would make the formula too complicated and maybe inaccurate. We have the following factors in mind:

Absolute and relative humidity of ambient air. (plus minus 2 meter)

Near surface soil humidity.

Soil humidity at the lower basis A(h) horizon (plus minus 30 cm), both absolute and relative.

Air temperature.

Soil temperature at the depths given above (1-5 cm and plus minus 30 cm).

Amount of precipitation over the last 24-48 hours.

Evaporation + transpiration= evapotranspiration rate.

Duration of sunshine exposure over last 12-24 hours.

Amount of water required by the crop for healthy growing circumstances (statistical data).

Stage of plant growth

Wind

Irrigation practice.

Climate

Type of soil (to account for soil drainage)

Plant density

They all affect the irrigation needs but some are not as important, please assist me with your expertise in telling me which are not as impactful/ important. And which are absolutely crucial to account for. Maybe we even have missed some?

With kind regards, Morris la Crois

With the help of standardized Precipitation Evapotranspiration Index how we get return period of drought?

We are working on a formula to calculate irrigation needs for agricultural soil, to help farmers (and the planet) with saving water. We work with water sensors in the agri fields and want to assist the farmers with a time sheet for telling them when they would need to start irrigation. Let's say you need to irrigate field A in 4 days and field B in 9, so they would have a timetable. We have many different factors at the moment, and we do not think it is realistic to account for them all because it would make the formula too complicated and maybe inaccurate. We have the following factors in mind:

Absolute and relative humidity of ambient air. (plus minus 2 meter)

Near surface soil humidity.

Soil humidity at the lower basis A(h) horizon (plus minus 30 cm), both absolute and relative.

Air temperature.

Soil temperature at the depths given above (1-5 cm and plus minus 30 cm).

Amount of precipitation over the last 24-48 hours.

Evaporation + transpiration= evapotranspiration rate.

Duration of sunshine exposure over last 12-24 hours.

Amount of water required by the crop for healthy growing circumstances (statistical data).

Stage of plant growth

Wind

Irrigation practice.

Climate

Type of soil (to account for soil drainage)

Plant density

They all affect the irrigation needs but some are not as important, please assist me with your expertise in telling me which are not as impactful/ important. And which are absolutely crucial to account for. Maybe we even have missed some?

With kind regards, Morris la Crois

relationship of evapotranspiration fraction (ETf ) with stress coefficient (Ks ) due to effect the salinity of water, are found paper and researches please

effecting the stress on evapotranspiration by salt and deficit water

can give you equation

**Standardized Precipitation Evapotranspiration Index (SPEI)**Comparative analyses of SPI and SPEI and drought index.

**Kindly any experts shared the procedure details.**Here, I need with

**blockwise (taluk/tehsil) field measured hydrometereological data (2000 to 2022)**for Southern India especially.

Even I know their limited mointoring facility in Southern India. But there will be possible in few mointoring facility case at Metropolitan cities like Bengaluru, Coimbatore, Chennai, Madurai etc..

Note: Rainfall (daily), Max and min Temperature (daily), relative humidity (daily), Solar radiation (daily), evapotranspiration (Monthly), Soil moisture (Monthly) etc.

I have computed the evapotranspiration in MATLAB using the FAO PM method and found negative values especially in January month. The study site was in Sicily, Italy ( very rare for snow and uncommon the temperature less than 0 degree temperature) Could yo suggest me why the value is negative, please?

Hi,

I am trying to understand the limitations of the Simplified Surface Energy Balance (SSEB) approach and Landsat Collection 2 (C2) Provisional ETa Science Products to estimate actual evapotranspiration of different crops in various locations.

These would be used by an agribusiness to monitoring water consumption and water availability for crops (wheat, rice and corn) grown in 14 different countries

I am struggling to understand if and how these can be applied to different crop / locations couples as Landsat Collection 2 (C2) Provisional ETa Science Products are yet to be validated.

Thanks for your help,

Best regards.

I have a monthly dataset of GLDAS evapotranspiration (version 3.6 a with 3-hourly temporal resolution). The conversions I have come across suggests multiplying the dataset values with 86400*(Number of days in the month) which sounds reasonable however the dataset values are all greater than 1 thus, this conversion will result in unrealistic ET values (>86400 mm at least).

So, I was wondering if the monthly dataset are actually daily ET values averaged over the month, making the actual units of the dataset kg/m2/day (mm/day) which require multiplication only with the number of days in the month.

Please provide your opinion over this.

I want to quantify the impacts of LAI changes (or “greening”) and stomatal closure on ET changes in FLUXNET sites. Are there any recommended statistical methods？

Hello, so I am trying to carry out a very simple and high-level approach for calculating the effect of building height on green roof cooling performance, and have been trying to use a certain building height-cooling decay rate I found in the literature, but am unsure if I am actually using it correctly and wanted to ask the research experts here for perhaps some guidance. I will further explain my project below with an example.

Let’s say I have 3 buildings, building A, B, and C in a city, each with a green roof. I also have a land surface temperature map of that city. I then want to find the cooling intensity/performance of each green roof. Here, this is defined as the difference in temperature between the LST of the green roof site itself, and the LST at the distance where the cooling effect ends. This means I need to calculate the cooling extent of each green roof. To accomplish this, I draw buffer doughnut rings around the green space site, and take the average LST value of each buffer ring. I will expect the ring averages to gradually increase moving away from the green roof site, as the cooling effect fades away. However, once I get to a ring distance where the cooling actually drops, then I will mark that as the point where the cooling extent ends. And so then, to find the cooling intensity/performance of each green roof, I take the absolute value of the difference between the LST at the green roof itself and the average LST at the distance where the cooling effect ends. For example, if the green roof itself has an LST of 25C and the distance where the cooling effect is marked as ending is 31C, then I take the difference and say that green roof has a cooling intensity of 31-25 = 6C. Ok great, done.

This buffer ring method to determine cooling extents is proposed in this paper “Quantifying the local cooling effects of urban green spaces: Evidence from Bengaluru, India” by Shah, Garg, and Mishra (2021):

Now I want to find, how is the cooling intensity of a green roof affected by the height of the building? I am basing this on the assumption that the higher a green roof is off the ground, the more the cooling performance will decay. I want to find what this building height to cooling performance decay relationship is. From this paper “Modeling the outdoor cooling impact of highly radiative “super cool” materials applied on roofs” by Sinsel et al. (2021):

I see that for every increase in 1-meter height, the cooling performance decreases by .003C (the paper says .003 K, but just converting to C since C and K have the same magnitude). I am trying to apply this decay rate to my example to see if I can understand how cooling intensity will decrease with building height.

And so for my example: Building A is 15 meters tall, Building B is 25 meters tall, and Building C is 42 meters tall. I want to account for how severely the height of each building will damped/lessen its cooling intensity/performance. And so, for the cooling intensities I would have calculated using the previously mentioned technique, this would assume that the green roof was 0 meters off the ground. And so to actually find how that cooling intensity would be lowered, I will apply the .003C/meter rate. Calculating cooling intensity for each green roof I get: Building A is 6C, Building B is 4C, and Building C is 3.4C. And so I calculate:

Building A: .003C x (15 meters) = .045 C, and so 6C – 0.045C = 5.955 C cooling intensity

Building B: .003C x (25 meters) = .075C, and so 4C - .075C = 3.925 C cooling intensity

Building C: .003C x (42 meters) = 0.126C, and so 3.4C - 0.126C = 3.274C cooling intensity

However, this would assume that the relationship is linear, while the paper says the relationship is nonlinear. Since this paper does not say what “nonlinear” means here, I turn to this paper “The impact of building height on urban thermal environment in summer: A case study of Chinese megacities” by Wang and Xu (2021):

which says the relationship between building height and LST is “negative logarithmic”, and so I use the natural log now and calculate:

Building A: .003C x ln(15 meters) = 0.00812C, and so 6C – 0.00812C = 5.99188 C cooling intensity

Building B: .003C x ln(25 meters) = 0.00966C, and so 4C – 0.00966C = 3.99034C cooling intensity

Building C: .003C x ln(42 meters) = 0.01121C, and so 3.4C - 0.01121C = 3.38879C cooling intensity

But wait, that’s barely anything! It’s almost as if the height of the building has no effect on cooling intensity at all now!

Just to sanity check this, let’s imagine a building D. Treating this green roof as if it were 0 meters above ground, I calculate a cooling intensity of 5.6C. Now let’s say this building is really tall, 200 meters tall. Now at that height, I think it would be reasonable to say that the green roof at the top would likely have a very, very small effect on cooling ground surface temperature for nearby pedestrians, if any effect at all. So let’s try this out with the linear approach and the nonlinear approach:

Building D: .003C x (200 meters) = 0.6C, and so 5.6C – 0.6C = 5C cooling intensity

I was expecting there to be no cooling intensity as all, given how high above the ground the green roof is, but OK.

Building D: .003C x ln(200 meters) = 0.01589 C, and so 5.6C – 0.01589 C = 5.58411C cooling intensity

And so a green roof being 200 meters above the ground have just about the same cooling intensity/performance as if it were 0 meters above ground?? That doesn’t make sense! How can a green roof 200 meters in the sky provide the same cooling relief to nearby pedestrians as a green roof (or technically a green space I suppose if it were 0 meters off the ground) 0 meters off the ground?? It just doesn’t make sense to me! And so while I recognize this building height-cooling decay rate is justified and credited in the literature, I am just not understanding how these results seem reasonable. And so I would like to ask, am I approaching the use of the rate correctly or is my math totally wrong here? Also, I completely recognize understanding green roof cooling performance is far more complex than what I have here, accounting for variables such as evapotranspiration rates and albedo, however, I am trying to keep this very simple and high level for the moment, just so I can understand the role of building height here. I would really appreciate any guidance and feedback on my approach here! Sorry for the very long post, but I wanted to fully explain my example problem! Thank you!

I have been applying SIMHYD model in the southeast Australian catchments with the daily rainfall, streamflow and potential evapotranspiration data. Unfortunately, the calibration result varies within the negative range. I have tried 100s of combinations in changing calibration periods, parameters value etc but none of these are working. Has anyone tried SINHYD? Please share your experience. Thanks

I'm going to apply the FAO's equation for the

**wind climate erosivity**of the Tibetan Plateau, but the potential evapotranspiration (PET) is sometimes less than precipitation (P) in this region. I'm wondering if the negative value calculated in this case has any particular meaning. Obviously, it will affect the aggregation of monthly data to annual data.Hi all,

Using HEC-HMS I have established a model and am able to successfully run simulations in a basin for the data set range I have (precipitation, evapotranspiration and river gauge for comparison) from 2008-2020, however I'm struggling to confirm how I move past the simulation and transition into forecasting over long periods (say 10 years for example) to determine what type of flows could potentially be harvested from a basin.

I understand I want to perform continuous modelling, however I I'm having a problem with the precipitation values past the date range I have. When I use the specified hyetograph method, the precipitation data doesn't carry into my forecast period so I end up with no outflow after this period. When I try other precipitation methods (i.e standard project storm) it only provides a storm event at the very beginning of the simulation within the first 24 hours.

I can't find anything in the meteorological model or forecast alternative where it's obvious to direct HEC-HMS to future forecasting based on predicted rainfall. Is this something that's available in HEC-HMS? Is there a certain precipitation model that I need to use? Any help would be greatly appreciated.

Hello how is calculate evopotranspiration from raster data using GIS ?

For instance, Worldclim data or like it use calculation for evopotranspiration .

If you have a suggestion about question and usefull data source could you share with me ?

There are many commonly used methods for esimtation of evapotranspiration which are based on temperature, radiation, mass and energy transfer etc. or a compbination of thse. Methods such as Penman-Monetieth, Pendman, Hargreaves, Priestley-Taylor, Thronthwaite etc. fall under these categories. What I want to know is the applicability of these methods primarily based on the climatic conditions of the area. Like whichmethod is suitable for humid conditions or arid climate? If someone asks me what method should I use to estimate the ETo for an area in Mumbai, which method should I use?

i want to calculate crop water requirement of different fodders crop before experiments but i don't have such data to calculate evapotranspiration.

is there any other method to calculate crop water requirement ?

please guide me about this matter

#cropwater requirement

Lot of methods are available for estimation of evapotranspiration.pl. suggest any instrument which will directly give the ET at a particular location.

Whether river flow or actual evapotranspiration is more useful for calibrating hydrological models.

Good morning,

Can anyone suggest a dataset presenting historic reference evapotranspiration in the different provinces?

Thanks a lot !

I come to know that water content in plant or crop can be measured using remote sensing techniques or using evapotranspiration mechanism. I am interested to know how to measure this information in order to know the crop water consumed in plant or in field level.

One such technique is measure evapotranspiration thru imaging using satellite imagery or using UAV imagery I am not sure. I am interested to know which technology is used to measure such data. what is the method/technology to implement in satellite or in Software in ground computer after the satellite imagery is received.

how can I get this data ? It is related to hydrus 1d

I am developing an intelligent irrigation system. I have automatic solenoid valves capable of irrigating at the value of the daily evapotranspiration. and I have soil sensors that measure soil moisture. Is there a simple study to find a correlation between evapotranspiration and soil moisture. I propose to use evapotranspiration value for water quantity prediction and humidity value for exact quantity correction and adjustment. are there any other avenues.

Hi all, I am searching for some values of Crop Evapotranspiration Coefficient (Kc) for natural forest habitats (coniferous forests, broadleaves forests...). On FAO database they only refer to crops like beans, rice, and wheat, but no data on forests. Thank you very much to anyone who can help

I want to downscale time-series imagery data using precipitation and evapotranspiration (temporal) and possibly even topography (static) using Google Earth Engine (GEE) Random Forest Regression. I have processed the remote sensing products to the same temporal and spatial resolution and joined them.

Typically the code would be something like:

// Create a classifier

var classifier = ee.Classifier.smileRandomForest().setOutputModel('REGRESSION').train({

features:training_data,

classProperty: 'what_I_want_to_predict',

inputProperties: ['predictor_variables']

});

var classified = predictor_variables_data.classify(classifier);

My question is:

1. How do I include temporal and static data as predictor variables (training data)? How do I sample it?

2. How does one apply the RDR model across monthly images over 2 years for example? Do you run the model 24 respective times?

Regards,

Cindy

I am looking for an equation similar to Priestley-Taylor (1972) but with the fewest parameters.

The papers using machine-learning particularly deep-learning models in hydrological prediction (runoff, soil moisture, evapotranspiration, etc.) increase dramatically in recent years. In my viewpoint, these data-driven methods require substantial data to derive solid predictions. I am not sure what is the advantage of these models over the process-based models in predicting hydrological processes.

I want to get the source and how to interpret the data

Hi,

The aim of the study is to calibrate hydrological model (SWAT model in this case) using remotely sensed actual evapotranspiration (ET) at a daily basis. Consequently, autocalibration requires daily remotely sensed ET. Unfortunately, the MOD16 estimates of ET are at a level of total 8-day, and cannot be directly used in autocalibration.

In this paper, for a similar problem, authors used NLDAS estimates of daily actual ET to disaggregate MODIS 8-day ET using a temporal scaling factor. According to the authors this method can be valid since the NLDAS estimates capture the daily variation of ET well. https://www.sciencedirect.com/science/article/pii/S0022169418307856

In my region, such data are not available freely. I have only MODIS 8-day ET, and daily observed meteorological data (precipitation and temperature, wind speed, humidity, solar radiation). I don't know if MODIS 8-day ET can be disaggregated to daily using other information such as precipitation and temperature?

Thank you very much

I want to estimate temperature-based Reference/Potential Evapotranspiration for humid conditions.

Four temperature-based method:

Jansen and Haise (1963)

McGuiness Bordne (1972)

Hargreaves model (Hargreaves and samani, 1985)

Oudin et al (2015).

Above these method, which one is best for humid conditions?

I want to calculate Potential evapo-transpiration with less data requirement so which method can be used for this which will give accurate and appropriate results.

I'm looking for a software or model to calculate evapotranspiration. The type of the output should be excel spreadsheet or database . Is there any tool to calculate evapotranspiration in ArcGIS ? Is there any method to convert the output of cropwat or ETo calculator into excel spreadsheet or database?

Crop coefficients can be greater than 1.00.

Ex: Corn 1.15

Then ETa=Kc *ETo, it seems to be ETa greater than ETo.

But ETo is the evaporative power of the amosphere. is it possible to go over that value?

How to caculate monthly evapotranspiration without radiation data?

I have LULC and ET data for the past three decades and have predicated LULC for future time period (e.g., 2025-2055). Now, I want to predict ET using land use land cover changes.

I am trying to determine the actual evapotranspiration using soil water balance method. But cannot determine deep percolation. Could you please let me know if there's any method, formulas to estimate the DP. Thank you.

Is there an equation to calculate soil moisture excess by using daily precipitation and evapotranspiration data, and soil water content at field capacity, wilting point and saturation?

Currently i am getting NSE= -12.371 and PBIAS= 205.91%. Trying to get them into acceptable performance measures. Kindly suggest some solutions.

Thanks.

A lysimeter decreased in weight by 120 kg over a period when irrigation and rain was 30 mm. What was the evapotranspiration (in mm) if the area of the lysimeter was 1 m

^{2}an the height 0.8 m ?My final goal is to find a multiple linear regression to predict actual evapotranspiration, ET (response variable) using remotely sensed land surface temperature and ground-observed air temperature (explanatory variable). All are raster (.tif) format. They are 5-year dataset with the same extent and temporal (16days) and spatial (500m by 500m) resolution.

I was trying to find some ways for spatial regression, raster regression, spatial statistics, etc. but I fail to one that can be applicable to my case. Most ways that I found didn't handle the time series as two explanatory variable at the same time.

Has there been anyone who tried or applied this type of approaches?

In each iteration, I get the same value of H for different values of aerodynamic resistance and the temperature difference between two heights. Do the results make sense? Is it necessary to adjust the air density value for each step?

I am trying to get information about potential evapotranspiration for the south of Ecuador, however, until the moment all the sources visited are monthly, or daily but with poor resolution.

I wish to shedule irrigation for a crop cultivar of which Kc value is unknown. Can't I use ETo directly without considering Kc since Kc is unknown?

- I was just curious to know the difference between the reference evapotranspiration (RET) and the potential evapotranspiration (PET). Are they same? If not, then what is the basic difference and what is the relationship between them? I mean, if I have PET, then can I calculate the other one or vice-versa? If yes, then how?
- I have some automated weather station (AWS) data which contains the sunshine hours (daily). How can I estimate the solar radiation from that data? Is it possible? Also, is there any readily global data available for solar radiation/humidity/wind speed etc data for calculating the ET?

Thanks in advance!

I am working on a small mountainous forested catchment. any advice for the simplest distributed hydrological model able to account for subsurface flow and deep infiltration with accurate modeling of flow in gullies and rivers and strongly simplified evapotranspiration ?

I need some reanalysis datasets to verify the outputs from a land surface model. The desired parameters are surface latent as well as sensible heat fluxes, evapotranspiration, leaf area index, Gross Primary Production, NEP, Ecosystem respiration, etc.

For instance if a 250m x 250m pixel has 20 mm ET value, it is how much mm for one hectare, also how much it would be in m3/ha?

Thanks

*Simple*water balance equation, P = E + Q, where change in storage can be considered negligible. Apart from having sufficiently long time series of observation of hydrologic variables like streamflow (Q), meteorolgical variables like (P = precipitation, E = evapotranspiration) for a particular time series, what are the other criteria that must be needed to be satisfied to use this simple water balance equation for study of impact of climate change on water resources?

I have been using the SWAT model, and simulation has been done several times by changing the evapotranspiration calculation method and the rate of hydrological parameters like Soil Evaporation Compensation (ESCO), Groundwater Re-evaporation (GW_REEVAP), Curve Number (CN2), Available water capacity of the soil layer (Sol_Awc), and Slope range of the area.

So, the annual precipitation is 318 mm, the annual surface runoff is 602 mm, but the annual evapotranspiration is based on the Hargraves method (1450 mm) and based on thornthwaite method ( 840 mm). so why runoff and ET are more than precipitation? it can be acceptable in terms of the water balance?

Any solution or recommendation to encounter it, please?

ERA5 reanalysis data has four distinct variable domains such as atmosphere (surface), atmosphere (upper air), land (biosphere), and land (hydrology). However, I'm confused about which variable domain's data should I use to calculate the reference evapotranspiration?

I have to validate the actual ET obtained from model output by using the actual ET value derived from the pan evaporation value. Is there a method to calculate the daily AET from pan evaporation?

What is the difference between the AET and the PET ?

I need to calculate actual evapotranspiration. kindly suggest me if there is any alternative method of evapotranspiration calculation.

I would like to examine seasonal actual evapotranspiration as a function of potential evapotranspiration and soil moisture. I have some water balance information: precipitation, streamflow, spring flow, and volumetric water content but not groundwater recharge. I also have sufficient meteorological information to estimate potential ET. This is in a heterogeneous landscape and evapotranspiration is water-limited throughout most of the growing season. I have information regarding the bulk density, field capacity, and texture of some soils in the area. Are there any established methods that examine this relationship? Any suggestion regarding existing research into this topic, particularly for arid and semi-arid landscapes, is appreciated. Thank you!

Is the Penman-Monteith equation applicable when the wind speed is very low (close to zero)? Thank you

I need at least two hydrological model suitable for use over west Africa and takes precipitation and potential evapotranspiration as input dataset

When I need to determine an alternative equation for estimating reference evapotranspiration for local with missing data, using meteorological data, from official weather stations, this means that I assume that the humidity is missing and I ignore it and estimate it according to the equations recommended by (FAO Irrigation and Drainage Paper No. 56 Chapter 3) and then determine suitable an alternative equation for estimating reference evapotranspiration, and then also determine the evapotranspiration from the standard equation (FAO Penman-Monteith equation 56) to performance evaluation with an alternative equation.

I also assume for temperature is missing and I ignore it and estimate it according to the equations and determine an alternative equation for estimating reference evapotranspiration, and so on for all climatological parameters.

Or what is the basic rule in determining alternative equations to calculate the reference evapotranspiration in places that are missing data, using meteorological data?

Because all those who define alternative equations for estimating reference evapotranspiration rely on data from agro-meteorological stations.

I am looking for an equation or any method basis on digital parameters to calculate evpotranspiration . I want to design this in hdl code and implement on fpga.

I am measuring the crop water use (ET) by using pots and lettuce crop as plant material, all the data of daily weighted pots are ready but I want to find the surface area of each pot. Can please help me to find the surface area of a pot with the above-mentioned diameters and height to compute daily evapotranspiration.

Exist studies which compare evapotranspiration in the water-stressed condition and in condition with unlimited water availability? For example, is there a significant difference between evapotranspiration from a forest in a floodplain or around a water reservoir and evapotranspiration from a similar forest far from water resources.

I put the Algorithm Sebal in Python language, can be opened in .txt, to estimate evapotranspiration in TM - Landsat 5 images, which works on Grass's G.dal platform, which is an extension of Qgis. Soon, I will make available those of Landsat 8.

Energy exchanges at the soil-plant-atmosphere interface, through the components of the radiation balance (Rn) and the heat fluxes in the soil (G), sensitive (H) and latent (LE), are essential for climate modeling and hydrological, which in turn affect the entire biosphere. Thus, having as objectives: (1) to estimate and compare the behavior of the energy balance components, using the SEBAL algorithm - Surface Energy Balance Algorithm for Land, in different types of land use and cover and (2) validation.

Please, when using, quote from: Lima, T.A.S .; (2020) Hydrogeological characterization and water use of a sector of sands, sandstones and gravel on the coast of Baixo Alentejo. 203 pp Master's Dissertation in the Geomatics course, University of Algarve.

Access:

What will be the best method to calculate evapotranspiration using NACORDEX data (Relative Humidity, Shortwave Radiation, Wind, Temp(max,min), Precp)?

There are some explanation in the previous post.

I believe that NACORDEX has many more variables, and we can use them in a more scientific way to calculate Evapotranspiration. Your thoughts are welcome. Thanks

The given Penman-Monteith method is an energy balance method. The key equation shows Rn - G - λET

*-*H = 0 . Whereas there is no method given to calculate H, and I could not find its explanation.Dear All,

I want to plot a Scatterplot of Evapotranspiration rasters to compare two ET products, just like the figure attached, which software should I use. thank you in advance

Regards,

Sadiq

I am measuring the crop water use (ET) by using pots and lettuce crop as plant material, all the data of daily weighted pots are ready but I want to find the surface area of each pot. Can you please help me to find the surface area of a pot with the above-mentioned diameters and height to compute daily evapotranspiration?

increasing transpiration and evaporation with raising temperature cause increasing in actual evapotranspiration ETa and reduction of yield and Biomass

Does anyone know how to perform a sensitivity analysis for crop evapotranspiration (

FAO Penman-Monteith equation) using daily meteorological data?

Who can help me to understand the SEBAL Model for Evapotranspiration estimation for Sentinel Data (S2 and S3)

I am working on two projects that both require me to estimate Evapotraspiration in my areas of interest. The first project is to calculate ET in rice fields (in a controlled field and in a local or subsistence farm set-up). The second project is looking at calculating ET in a natural woodland environment that offers natural resources ecosystem services within community forests.

in both cases, I have limited climate data to estimate ET and I am therefore relying on freely avail satellite data to extract these information.

I am conducting a study to comapare different ET products. So far I have downloaded Gleam, landflux Eval, Terra Climate, Modis Mod16 products. I need the name of atleast 4 more products

Thanks in advance.

I'm working with precipitation data, soil moisture data, evapotranspiration data from various sources and resolutions. While using programming languages like MATLAB or Python for downscaling coarser data to finer resolution, we have a choice of selecting any interpolation or extrapolation method such as linear interpolation, cubic interpolation, Nearest neighbor interpolation, piecewise cubic interpolation, etc... Which interpolation and extrapolation methods are suitable from climatic variables precipitation, soil moisture, evapotranspiration, soil moisture index?