Smart Farm Water Use Efficiency

This dataset provides granular, event-level records of water usage across smart farms equipped with IoT sensors. It includes detailed information on irrigation events, crop types, sensor readings, and compliance with sustainability goals, enabling advanced benchmarking, efficiency analysis, and regulatory reporting for precision agriculture.

  • last updated 30 Dec 2025
  • by GoMask
The brief that made it

Benchmarking water use efficiency across farms and crop types

Sample rows

preview · 8 of 60 rows · all 22 columns
farm_idstringwater_sourcestringweather_temperature_cfloatcompliance_flagbooleancountrystringfarm_namestringlocation_latitudefloatlocation_longitudefloatregionstringirrigation_event_idstringtimestamp_startdatetimetimestamp_enddatetimewater_volume_litersfloatarea_irrigated_hectaresfloatcrop_typestringyield_kgfloatsensor_idstringsoil_moisture_pctfloatweather_rainfall_mmfloatirrigation_methodstringefficiency_scorefloatnotesstring
FARM001well19.3trueUSAGreen Valley Farms37.7749-122.4194CaliforniaIEVT10012024-04-15T07:15:002024-04-15T09:00:003800.52.5lettuce1800SENSOR-A1263.20drip0.87Optimal morning irrigation, soil moisture within target.
FARM002river15falseUSAHighland Ranch40.7128-74.006New YorkIEVT10022024-05-06T16:45:002024-05-06T17:30:0012001potato950SENSOR-B2158.82.5sprinkler0.62Rainfall reduced required volume, compliance target not met.
FARM003municipal12trueUKSunrise Acres51.5074-0.1278SurreyIEVT10032024-04-20T06:30:002024-04-20T08:00:0027001.8wheat2300.5SENSOR-C3372.10pivot0.81Efficient use under moderate temperatures.
FARM004river23.5falseFranceRiverbend Farm48.85662.3522Île-de-FranceIEVT10042024-06-10T14:00:002024-06-10T16:00:0055003corn2900SENSOR-D1968.30flood0.68High volume due to heat, efficiency below target.
FARM005rainwater18.7trueAustraliaMountainview Estate-33.8688151.2093NSWIEVT10052024-03-22T05:10:002024-03-22T06:40:003200.72barley1400.5SENSOR-E4447.80drip0.92Rainwater system improved efficiency.
FARM006well31falseUAEDesert Bloom25.27698755.296249DubaiIEVT10062024-05-01T04:00:002024-05-01T05:00:0070004.5tomato4200SENSOR-F7739.50sprinkler0.52Desert conditions required excess water.
FARM007municipal11.4trueDenmarkNordic Harvest55.676112.5683ZealandIEVT10072024-04-12T10:30:002024-04-12T12:00:0021001.7rye1300SENSOR-G0878.91.2drip0.86High soil moisture, minimal irrigation.
FARM008well17.8trueUSASilver Plains34.0522-118.2437CaliforniaIEVT10082024-06-05T07:00:002024-06-05T08:00:0034002.2lettuce1650SENSOR-H9961.30pivot0.91Efficient pivot irrigation.

What the 60 rows show

from the 60-row sample

Well (water source) stands out: mean weather_temperature_c is 23.3, against 17.9 for the rest.

  • 93%compliance_flag = true
  • 18.4median weather_temperature_c
  • 4irrigation methods
  • 6,200median water_volume_liters
  • 1.9median area_irrigated_hectares
  • 3,650median yield_kg
Mean weather_temperature_c by water_source60 rows
0204023.3well17 rows19.4river15 rows17.0municipal16 rows17.3rainwater12 rows
weather_temperature_c60 rows, in bands of 5
0153031122119452035weather_temperature_c →

Median 18.4, from 7.4 to 34.0.

country60 rows · top 10 of 24 values
  1. USA18
  2. UK7
  3. Canada7
  4. Australia5
  5. France2
  6. Brazil2
  7. New Zealand2
  8. UAE1
  9. Denmark1
  10. Japan1
22 columns by typefrom the column list below
  • string 10
  • float 9
  • datetime 2
  • boolean 1

Columns

22 columns in four groups
blueprint · 22 columns
columntypedescriptionexample
Text 10 columns
farm_idstringUnique identifier for the smart farmuniqueFARM001
farm_namestringName of the smart farmGreen Valley Farms
countrystringCountry where the farm is locatedUSA
regionstringRegion or state where the farm is locatedoptionalCalifornia
irrigation_event_idstringUnique identifier for each irrigation eventuniqueIEVT1001
crop_typestringType of crop irrigatedlettuce
sensor_idstringUnique identifier for the IoT sensor collecting dataSENSOR-A12
irrigation_methodstringMethod of irrigation used (e.g., drip, sprinkler, flood)drip · sprinkler · flood · pivot · otherdrip
water_sourcestringSource of water used for irrigation (e.g., well, river, municipal)well · river · municipal · rainwater · other · optionalwell
notesstringAdditional notes or comments about the irrigation eventoptionalPivot system effective.
Numbers 9 columns
location_latitudefloatLatitude coordinate of the farm location-90 to 9037.7749
location_longitudefloatLongitude coordinate of the farm location-180 to 180-122.4194
water_volume_litersfloatTotal volume of water used during the irrigation event (in liters)0 or more3800.5
area_irrigated_hectaresfloatArea irrigated during the event (in hectares)0 or more2.5
yield_kgfloatCrop yield (in kilograms) associated with the irrigation event0 or more · optional1800
soil_moisture_pctfloatAverage soil moisture percentage during the irrigation event0 to 100 · optional63.2
weather_temperature_cfloatAverage ambient temperature (Celsius) during the irrigation eventoptional19.3
weather_rainfall_mmfloatTotal rainfall (mm) during the irrigation event0 or more · optional0
efficiency_scorefloatCalculated water use efficiency score for the irrigation event (0-1 scale)0 to 1 · optional0.87
Dates and times 2 columns
timestamp_startdatetimeStart timestamp of the irrigation event2024-04-15T07:15:00
timestamp_enddatetimeEnd timestamp of the irrigation event2024-04-15T09:00:00
True or false 1 column
compliance_flagbooleanIndicates if the irrigation event complied with resource management goalstrue

Use it for

  • compliance flag93%56 of 60 rowsmean weather temperat…23.3well19.4river17.0muni…17.3rain…

    An agriculture dashboard

    The compliance_flag rate, weather_temperature_c by water_source and a breakdown of country. Excel, Power BI or Tableau.

  • Why do the 17 well rows have a mean weather_temperature_c of 23.3?

    A root-cause class exercise

    Hand out the rows and one question. The answer is in the data, not in the brief.

  • A software demo

    Believable farms with farm_name, location_latitude and location_longitude to fill a screen in front of a buyer.

Not quite right?

Make it yours.

Same 22 columns, your size and your rules. See 20 rows before you pay.

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This dataset60 rows22 columns
Yours1,000 rows22 columnslocation_latitude: UK only

blueprint · smart-farm-water-use-efficiency

Behind this dataset

Same schema. As many rows as you need.

These 60 rows came out of a blueprint — 22 columns with generation rules behind each one. Open it in Data Factory to retune a column, add your own, wire in foreign keys, and run it at the size you actually need.

Rules it was built with
  • Each row represents a unique smart farm field per week.
  • Includes IoT sensor readings for soil moisture and water applied.
  • Records must include crop type and growth stage.
  • Calculates efficiency score based on yield-to-water ratio.
  • Flag fields exceeding local water allocation guidelines.
Rows
Open the blueprint in Data Factory

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Exports
CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence
yours to use, including commercially
API slug
smart-farm-water-use-efficiency

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