Most commercial irrigation schedules in Texas were set by an irrigation contractor at startup and have barely changed since. Spring, summer, fall, winter — the same run times, the same days per week, the same program. The system over-irrigates in February, under-irrigates in August, and the controller programming interface is too confusing for the facilities manager to touch with confidence.
Evapotranspiration-based (ET-based) irrigation scheduling is the solution to this widespread problem. ET scheduling automatically adjusts irrigation run times based on actual weather data, ensuring the landscape receives the water it needs — not a fixed amount set for worst-case summer conditions and applied year-round.
What Evapotranspiration Is
Evapotranspiration is the combined rate at which water moves from the soil surface (evaporation) and from plant leaves (transpiration) back into the atmosphere. ET rate is the primary driver of landscape water demand — when ET is high, plants are losing water quickly and need irrigation to replace it. When ET is low, plants retain water longer and need less supplemental irrigation.
ET rate is determined by weather conditions: temperature, solar radiation, humidity, and wind speed. High temperature, high solar radiation, low humidity, and high wind all increase ET. A hot, sunny, dry, windy July day in Texas might have an ET of 0.3 inches. A cool, cloudy December day might have an ET of 0.05 inches. The difference in irrigation demand between these two conditions is a factor of 6:1.
Reference ET (ETo) is calculated using the Penman-Monteith equation — the internationally accepted method for computing ET from weather measurements. The equation was standardized by the American Society of Civil Engineers (ASCE) and produces consistent results from properly sited weather stations. Most smart irrigation controllers and ET scheduling services use the ASCE Penman-Monteith calculation or a simplified approximation of it.
How ET Scheduling Works in Practice
An ET-based irrigation controller adjusts its scheduling by calculating the daily or weekly ET of the landscape and adjusting run times to match. The inputs to this calculation are: the reference ET from a weather station or remote weather data service; a crop coefficient for the type of plants being irrigated (turf grass has a coefficient of approximately 0.6–0.8 for most Texas grass varieties); and the system’s precipitation rate for each zone (how much water it applies per hour).
The controller calculates the water deficit that’s accumulated in the landscape since the last irrigation cycle and programs run times to replace that deficit. If the past three days had high ET and no rain, the deficit is large and run times increase. If significant rainfall occurred, the deficit is reduced or zeroed out and scheduled irrigation is suspended. This is the fundamental logic of weather-based irrigation — matching application to demand rather than running a fixed schedule.
Implementation options vary from fully onboard ET controllers (with a connected weather station) to cloud-based ET adjustment services that push schedule changes to compatible controllers via the internet. On modern 2-wire platforms like the Hunter ACC2 and Rain Bird ESP-LXIVM, ET-based scheduling is a built-in feature when connected to a compatible weather station or ET data service. Retrofitting older controllers with ET capability typically requires replacing the controller.
Texas Climate Zones and ET Variation
Texas spans multiple climate zones with significantly different ET characteristics. Houston (Gulf Coast) has high humidity year-round that moderates ET compared to internal regions — but high rainfall that should reduce irrigation demand substantially. Dallas-Fort Worth experiences hotter, drier summers than Houston with higher peak ET but more defined seasonal variation. San Antonio sits at the transition between the humid east and arid west, with moderate annual rainfall concentrated in spring and fall.
Understanding the ET pattern for your specific location matters for programming ET-based scheduling properly. Houston properties may need more rain sensor sensitivity because local rainfall frequently provides adequate soil moisture even when ET conditions are demanding. DFW properties have longer dry summer periods where ET drives irrigation demand consistently for weeks without meaningful rainfall. One-size-fits-all ET scheduling parameters from an irrigation contractor unfamiliar with local climate patterns will underperform.
Local ET data services — Texas ET Network, Texas A&M AgriLife Extension’s TXET data — provide ground-truthed ET data specific to monitoring stations throughout the state. Using local ET data rather than generalized regional data improves scheduling accuracy and ensures the system is responding to actual conditions at the property’s location.
Expected Water Savings from ET Scheduling
The water savings achievable through ET-based scheduling depend heavily on the current programming baseline. A system that’s already carefully programmed with seasonal adjustments and a diligent facilities manager will save less than a system that’s been running the same summer schedule year-round. The widest gap — and the biggest savings — comes from systems that have been on autopilot with outdated or overly conservative fixed schedules.
Research and field studies consistently show 15–40% water use reduction when transitioning from fixed-schedule to ET-based irrigation on commercial turfgrass properties. Texas data from AgriLife Extension research plots has shown reductions at the high end of this range when baseline schedules were fixed at summer demand levels. For a large commercial property spending $200,000 per year on irrigation water, 25% savings means $50,000 annually — a payback period of 1–2 years on most ET scheduling implementations.
Beyond water cost, ET-based scheduling often improves turf quality by reducing overwatering in cool seasons. Turf that receives excessive water in spring and fall is more susceptible to fungal disease, develops shallow root systems (because roots follow available moisture to the surface), and is less heat-tolerant when summer arrives. Proper ET-calibrated irrigation through the shoulder seasons produces healthier, more drought-resilient turf than year-round over-irrigation.
Implementation: Getting Started
Implementing ET-based scheduling effectively requires three things: a controller capable of ET adjustment, accurate zone precipitation rate data, and a connection to reliable ET data. If your current controller supports ET scheduling (check the manual or call the manufacturer), you may be able to enable this feature with programming changes alone.
If your controller doesn’t support ET scheduling, a controller upgrade is necessary. For 2-wire systems, replacing the controller while retaining the existing wire path and decoders is often straightforward — a controller upgrade project that also enables ET scheduling delivers better water management for many years with a one-time capital investment.
Accurate zone precipitation rates are essential for ET scheduling to work correctly. The ET calculation tells you how many inches of water deficit to replace — the precipitation rate tells the controller how many minutes to run each zone to apply that many inches. Using incorrect precipitation rates (which is very common when rates haven’t been measured) means the ET scheduling calculation is correct but the application is wrong. A water audit that measures actual precipitation rates by zone provides the data needed for accurate ET scheduling configuration.
Conclusion
ET-based irrigation scheduling is the most impactful single change most Texas commercial properties can make to reduce water waste and improve turf quality simultaneously. It’s not a technology-for-its-own-sake investment — it’s a pragmatic response to the reality that fixed irrigation schedules in a highly variable climate like Texas consistently waste water and deliver inconsistent turf quality. For any commercial property with an irrigation bill above $50,000 annually, the ROI on proper ET scheduling implementation is compelling.