国内外城市草坪灌溉水分利用效率的研究进展

Growing concerns about climate change and water scarcity have intensified the need for sustainable turfgrass management, particularly by optimizing water‐use efficiency. This 2‐year field study evaluated the effects of rootzone construction methods and irrigation delivery systems on water retention characteristics and perennial ryegrass performance under 60% reference evapotranspiration (ETO) deficit irrigation. Three rootzone constructions (two two‐layered and one three‐layered) were investigated using sprinkler and subsurface drip irrigation (SDI) systems. Key parameters assessed included soil water tension, rootzone water storage (RWS), turfgrass quality (TQ), turfgrass coverage, and normalized difference vegetation index. Significant interactions between rootzone construction and irrigation systems were observed. The three‐layered SDI system demonstrated significantly higher RWS and TQ than the two‐layered SDI systems, which showed rapid RWS and TQ decline. While two‐layered sprinkler systems maintained acceptable TQ longer than their SDI counterparts, they proved to be less efficient than the three‐layered SDI system. These findings highlight the critical role of aligning rootzone design with irrigation methods in enhancing water‐use efficiency and turfgrass performance in water‐scarce environments. This study provides valuable insights for sustainable turfgrass management strategies in response to increasing water constraints.

Irrigated turfgrass is a major crop in urban areas of the drought-stricken Western United States. A considerable proportion of irrigation water is wasted through the use of conventional sprinkler systems. While smart sprinkler systems have made progress in reducing temporal mis-applications, more research is needed to determine the most appropriate variables for accurately and cost-effectively determining spatial zones for irrigation application. This research uses data from ground and drone surveys of two large sports fields. Surveys were conducted pre-, within and towards the end of the irrigation season to determine spatial irrigation zones. Principal components analysis and k-means classification were used to develop zones using several variables individually and combined. The errors associated with uniform irrigation and different configurations of spatial zones are assessed to determine comparative improvements in irrigation efficiency afforded by spatial irrigation zones. A determination is also made as to whether the spatial zones can be temporally static or need to be re-determined periodically. Results suggest that zones based on spatial soil moisture surveys and simple observations of whether the grass felt wet or dry are better than those based on NDVI, other variables and several variables in combination. In addition, due to the temporal variations observed in spatial patterns, ideally zones should be re-evaluated periodically. However, a less labor-intensive solution is to determine temporally static zones based on patterns in soil moisture averaged from several surveys. Of particular importance are the spatial patterns observed prior to the start of the irrigation season as they reflect more temporally stable variation that relates to soil texture and topography rather than irrigation management.

Low-quality (i.e., impaired) water sources are commonly used to irrigate warm-season turfgrass landscapes as a result of limited supplies of potable water sources. Currently, there is great need to define the impacts of impaired water sources on turfgrass water consumption, growth, and quality. The objectives of this study were to characterize actual evaporation (ETa), clipping production, and quality of three hybrid bermudagrass varieties [‘TifTuf’, ‘Tifway’, and ‘Midiron’; Cynodon dactylon (L.) Pers. × C. traansvalensis Burtt Davy] grown under three water sources [reverse osmosis (RO), local well, and recycled], each supplied at full irrigation levels (1.0 × ETa) over two 8-week study periods. When pooling across water source and date, TifTuf maintained the highest visual quality and normalized difference vegetation index (NDVI) compared with both Midiron and Tifway. This was accompanied by a greater daily ETa rate, clipping production, and water use efficiency (WUE) compared with Midiron in both studies. When pooling across variety and date, daily ETa of turfgrass receiving recycled water was 5% to 10% less than those receiving the local well or RO water. In addition, turfgrasses receiving local well water held the greatest visual quality and NDVI compared with those receiving either RO water in the summer study. Visual quality and NDVI were also less in turfgrasses receiving RO water compared with those receiving local well or recycled water in the fall. Despite turfgrasses having a lower ETa under recycled water in both study periods, these plants had significantly greater clipping production compared with RO water in the summer. Also, clipping production under recycled water did not differ significantly from the other two sources in the fall study. Furthermoe, in both studies, WUE was similar for turfgrasses receiving recycled water compared with those receiving RO or local well water. Results demonstrated that irrigation water quality influences critical factors for hybrid bermudagrass growth and that considerable variability exists among three commercially available varieties for evapotranspiration rates, quality, and clipping production.

An irrigation sprinkler is used to water agricultural crops, lawns, landscapes, golf courses, and other areas, also aiding in cooling and dust control. Sprinkler irrigation mimics rainfall and is promoted over surface methods, especially in regions like Coimbatore, where annual rainfall ranges from 550 to 900 mm. This paper examines the efficiency of sprinkler irrigation at RVS Technical Campus, aiming to optimize water use and reduce human intervention. The study focuses on an impact sprinkler system, monitoring soil moisture to determine water needs and using a rotating system to ensure accurate water scheduling and minimize runoff. KEYWORDS: Sprinkler irrigation, Soil Moisture, Water efficiency, Installation, Design.

No abstract available

The increasing global reliance on water resources has necessitated improvements in turfgrass irrigation efficiency. This study aimed to compare measured field data with predicted data on irrigation water distribution in turfgrass rootzones to verify and enhance the accuracy of the HYDRUS-2D simulation model. Data were collected under controlled greenhouse conditions across unvegetated plots with two- and three-layered rootzone construction methods, each receiving 10 mm of water (intensity of 10 mm h−1) via subsurface drip irrigation (SDI) or a sprinkler (SPR). The water content was monitored at various depths and time intervals. The hydraulic soil parameters required for the simulation model were determined through laboratory analysis. The HYDRUS-2D model was used for testing the sensitivity of various soil hydraulic parameters and subsequently for model calibration. Sensitivity analysis revealed that soil hydraulic property shape factor (n) was most sensitive, followed by factor θsw (water content at saturation for the wetting water retention curve). The model calibration based on shape factors n and αw either in Layer 1 for SPR variants or in both upper layers for SDI variants yielded the highest improvement in model efficiency values (NSEs). The calibrated models exhibited good overall performance, achieving NSEs up to 0.81 for the SDI variants and 0.75 for the SPR variants. The results of the irrigation management evaluation showed that, under SPR, dividing the irrigation amount of 10 mm into multiple smaller applications resulted in a higher soil storage of irrigation water (SOIL_S) and lower drainage flux (DFLU) compared to single large applications. Furthermore, the model data under the hybrid irrigation approach (HYBRID-IA) utilizing SPR and SDI indicated, after 48 h of observation, the following order in SOIL_S (mm of water storage in the topmost 50 cm of soil): HYBRID-IA3 (3.61 mm) > SDI-IA4 (2.53 mm) > SPR-IA3 (0.38 mm). HYDRUS-2D shows promise as an effective tool for optimizing irrigation management in turfgrass rootzones, although further refinement may be necessary for specific rootzone/irrigation combinations. This modeling approach has the potential to optimize irrigation management, improving water-use efficiency, sustainability, and ecosystem services in urban turfgrass management.

As water scarcity is worsened by drought and climate change, there is more interest in efficient management of urban irrigation, requiring understanding of the drivers of evapotranspiration (ET) and the role of irrigation inputs. We developed and validated a method to accurately measure ET of turfgrass lawns in contrasting climates using portable static chambers. We made in situ measurements of ET and irrigation inputs in lawns across three metropolitan areas in the United States with varying climatic conditions, water availability, and water conservation policies: Salt Lake Valley, Utah; San Fernando Valley, California; and Tallahassee, Florida. In full sun, mean daily ET estimates (ETsun) were 0.7 ± 0.4 mm day−1 in Tallahassee, 1.6 ± 0.8 mm day−1 in Los Angeles, and 3.3 ± 1.1 mm day−1 in Salt Lake Valley. In the shade, daily ET estimates (ETshade) were two to three times lower. In all three regions, ET was primarily driven by solar radiation (I0) and atmospheric vapor pressure deficit (D). Across the cities, irrigation rates were a key driver of ET, along with I0 and D. Daily irrigation ranged from 0 mm day−1 in Tallahassee (most were unirrigated) to 1.9 ± 1.2 mm day−1 in Los Angeles and 5.1 ± 2.9 mm day−1 in Salt Lake Valley. ET increased linearly with irrigation up to ~3 mm day−1, after which ET remained relatively constant despite irrigation increases. Our results highlight the importance of accounting for nonlinear responses and shading effects on ET in developing accurate irrigation recommendations.

This publication discusses Florida residents’ awareness and perceptions of irrigation restrictions to illuminate the processes that support or prevent their compliance with these policies. Written by Sravani Pasula, Dharmendra Kalauni, Laura Warner, John Diaz, Ange Asanzi, James Harmon, Deirdre Irwin, and Robin L. Grantham, and published by the UF/IFAS Department of Agricultural Education and Communication, May 2024.

Highlights A turfgrass water response function was developed for 'Westcoaster' tall fescue. The Weathermatic smart controller demonstrated reliable estimations of reference evapotranspiration. Restricting irrigation frequency did not yield water savings or lead to improvements in turfgrass quality. Abstract. Efficient landscape irrigation is an important water conservation strategy and reduces strain on limited water resources in inland Southern California. A three-year field irrigation trial was conducted in Riverside, California, to evaluate the response of 'Westcoaster' tall fescue (Festuca arundinacea Schreb.) to a wide range of autonomous irrigation scenarios implemented using a Weathermatic smart controller. The response of the turfgrass was assessed using visual rating (VR) and normalized difference vegetation index (NDVI) data collected with a handheld sensor. These experimental data were then used to develop a regression-based turfgrass water response function (TWRF), which was further employed to estimate the response of tall fescue to different irrigation levels during years with varying atmospheric evaporation demands, including extreme conditions. A strong correlation was observed between NDVI and VR (r = 0.88). A minimum NDVI threshold of 0.7 was identified to maintain an acceptable level of tall fescue quality for residential areas. During the trial periods, irrigation application rates below 100% of reference evapotranspiration (ETo) were insufficient to sustain the desired quality of tall fescue. The TWRF estimations suggested that 60% ETo can be applied for short periods (7 to 43 days, depending on the atmospheric evaporative demands) during the summer before the visual quality drops below the minimum threshold. Comparing different irrigation strategies, it was observed that on-demand irrigation, which adjusts irrigation frequency based on ETo demand, resulted in higher NDVI and VR values compared to a limited watering schedule of only a few days per week. Analysis of soil moisture data revealed that the primary root water uptake occurred mainly in the topsoil layer (<33 cm), and the applied irrigation water primarily replenished the shallow soil layer (<20 cm) due to the coarse sandy loam soil characteristics. The Weathermatic controller, equipped with on-site air temperature measurements, provided reliable ETo estimations and can be used for autonomous landscape irrigation scheduling in semiarid regions. Keywords: Keywords., Evapotranspiration, Remote sensing, Smart irrigation controller, Urban irrigation, Water conservation.

- This paper introduces an innovative smart irrigation system aimed at optimizing water usage in agricultural and landscaped environments. The system comprises two integrated units: Stationary Supply Unit and Sprinkling Vehicle. The stationary unit serves as a centralized control hub, equipped with a thermal imaging camera, environmental sensors, and a motorized hose reel mechanism. It collects and processes environmental data—including temperature, fog, and light intensity—through sensor fusion and image processing algorithms to determine optimal irrigation timing and zones. The vehicle, a mobile sprinkling unit, receives wireless commands from the stationary unit and performs precise irrigation using two types of sprinkler heads: a 360° circular sprinkler and a guided, stepper-motor-controlled directional nozzle. Powerful microcontrollers manage real-time communication and ensure operational synchronization, including built-in safety features to pause activity under adverse conditions. The system effectively minimizes water waste, increases irrigation efficiency, and represents a practical implementation of IoT technologies in sustainable agricultural management.

In the context of agricultural and horticultural daily routines, watering is a pivotal and labor-intensive task. Regardless of prevailing weather conditions—whether excessively hot and dry or overly cloudy and wet—controlling the amount of water reaching plants remains crucial. Contemporary watering systems effectively deliver water precisely when plants require it. However, manual watering necessitates considerations of both timing and quantity. To alleviate the manual burden on gardeners and streamline their tasks, we have developed an automated plant watering system. Integrating this system into gardens or agricultural fields ensures optimal growth for all plants while promoting water conservation. This study employs a Raspberry Pi, programmed to monitor the moisture levels of plants at specific intervals. If the moisture content falls below a predefined threshold tailored to each plant’s water requirements, the system autonomously dispenses the necessary amount of water until the threshold is met.

This publication is intended to provide information about Floridians’ expected outcomes associated with complying with irrigation restrictions so educators and communicators (e.g., Extension professionals and conservation coordinators) can integrate this information into outreach. Written by Laura Warner, Sravani Pasula, Dharmendra Kalauni, Jamie Loizzo, and Sadie Hundemer, and published by the UF/IFAS Department of Agricultural Education and Communication, August 2024.

No abstract available

Effective irrigation scheduling is essential for improved water management in irrigated areas, with soil moisture monitoring recognized as one of the most effective methods. However, challenges such as the high cost of sensors and the difficulties in monitoring large areas hinder their practical application, particularly for smallholder farmers. This study aimed to design and test a locally made low‐cost Arduino‐based soil moisture (ASM) sensor for real‐time irrigation scheduling. The ASM sensor was first tested in the laboratory and then deployed in a wheat field in comparison with a Pycom soil moisture (PSM) sensor and a conventional soil moisture (CSM) method. Initial results indicated that ASM readings were about 13% lower than CSM values, with a linear regression slope of 0.87. After calibration, the slope improved to 1.0, correcting the underestimate. Based on performance metrics including RMSE, relative error, confidence index and index of agreement, the sensor showed a strong linear correlation (R2 = 0.97) with CSM both before and after calibration, which was rated as ‘excellent’. The PSM sensor achieved near‐perfect agreement with CSM results, showing the reliability of low‐cost sensor alternatives. Overall, the ASM sensor demonstrated accuracy, cost‐effectiveness and practical suitability, offering a valuable solution for enhancing irrigation scheduling in resource‐limited settings.

Efficient water management is critical where water scarcity limits crop productivity. In order to overcome this problem, soil moisture sensors have been used for precision irrigation scheduling; however very less studies have compared different sensor types and their impact in vegetable crops. The study was conducted at Water and Land Management Training and Research Institute (WALAMTARI), Hyderabad to evaluate the performance of Electrical Resistance and Capacitance basedsoil moisture sensors for precision irrigation scheduling in a bottle gourd crop. Sensors were installed at two soil depths (0-15 cm, 15-30cm) and readings were compared with gravimetric soil moisture measurements and performance metrics included Mean Square Error (MSE) and Root Mean Squared Error (RMSE) were calculated. Results indicated that capacitance sensors provided more consistent and responsive measurements across varying soil moisture levels, while ER sensors showed greater variability under field conditions. Capacitance sensors were installed in bottle guard field and yield matrices were recorded. From the results, it can be concluded that Capacitance-based soil moisture sensor based irrigation system improved yield by 21% and irrigation water use efficiency by 51% compared to existing manual irrigation practice. Thus, it is recommended for precision irrigation scheduling to improve water use efficiency and crop productivity.

The use of tall fescue is increasing in the European transition zone because of its inherent tolerance to heat and drought stresses. Climate change, as expressed by more frequent drought occurrences, presents a challenge for selecting appropriate turfgrass cultivars. A field study was conducted at the Experimental Agricultural Farm of the University of Padova (Legnaro, Italy) to assess the response of 20 tall fescue cultivars grown without irrigation for 2 years (with a single emergency irrigation application in Jul 2022). The cultivars were evaluated every 2 weeks from Mar 2021 to Mar 2023 to determine the texture, uniformity, density, color, quality, green turf cover, and normalized difference vegetation index (NDVI). The cultivars tested were Bullseye, Darlington II, Detonate LS, Forlaine, Grande II, Lexington, Melya-ne, PPG-TF238, PPG-TF254, PPG-TF315, PPG-TF336, RGT Nuance, Rhambler SRP, Talladega II, Thor, Thunderstruck, Tough, Triad, Turfway, and ZRC-1. The results confirmed the ability of tall fescue species to tolerate drought stress as imposed within the parameters of this field study. For all cultivars, a slight decrease in quality was observed only in the summer of the second year under severe drought conditions. The inherent low cold tolerance of tall fescue compared with that of other cool-season species observed for all the study cultivars resulted in lower quality, color, and uniformity during the winter, but density was maintained throughout the entire study period. The best-performing cultivars based on quality, NDVI, and green turf cover were PPG-TF336, Triad, and ZRC-1. Therefore, tall fescue provides a sustainable solution for amenity turfgrass lawns in water deficit climates, and turf-type tall fescue cultivars with the desired characteristics of optimum quality and drought tolerance should be considered for lawns with the European transition zone.

An automatic, weight-based, small 20 cm diameter pan was used for real-time calculations of evaporation and precipitation in a semiarid environment. The water evaporated from the evaporimeter (EP) was found to be a significant predictor of evapotranspiration (ETO; r2 = 0.84), which was calculated with the Penman–Monteith (P-M) equation by retrieving climatic data from a weather station. The results revealed seasonal variations of the pan coefficient (KP; dimensionless), with a mean value estimated at 0.84 (±0.16). Validation of ETO measurements using a calibrated regression model (ETO = 0.831*EP + 0.025), against the P-M equation indicated a high correlation coefficient (r2 = 0.99, slope of the regression line of 0.9). The present paper evaluates and discusses the potential of using a reduced-size pan for real-time monitoring of water evaporation and precipitation, proposing an open-source irrigation decision support system.

Modern agriculture, especially in areas experiencing scarcity of water and varying climatic conditions, is dependent on effective irrigation management. In this study, a new model of an irrigation system has been designed by the author. This model uses the best possible prediction of machine learning algorithms so that wastage of water resources may be avoided by predicting the irrigation schedule. The inputs to this model are soil moisture data, weather prediction, and crop-specific parameters, which generate personalized irrigation recommendations. A novelty of this paper lies in its design of such a system. The model's key strength lies in its adaptability to different agricultural environments, such that it may be widely applied. Methodology The data gathering, feature engineering, model training, and evaluation form the core of the methodology. Results Comparisons with the traditional approach present improvements in irrigation efficiency, where a significant amount of water saved and higher crop yield have been observed. Scalability and real-time decision making are promising prospects for precision agriculture. Future work includes expansion of the scope of the system towards adding more integrate with other farming technologies for a more complete smart farming solution and be influenced by environmental factors.

Water scarcity and growing environmental concerns have increased the need for effective irrigation and fertilization practices in turf management. This study investigated the effects of different irrigation levels (IL) and nitrogen doses (ND) on turf quality, color, clipping yield, and selected physiological parameters of tall fescue [Schedonorus arundinaceus (Schreb.) Dumort] under Mediterranean climate conditions. The experimental design was randomized blocks in a split‒split plot design with three replications. The irrigation levels were set at 25% (IL1), 50% (IL2), 75% (IL3), and 100% (IL4) pan evaporation, while nitrogen doses of 0.00, 1.25, 2.50, and 5.00 g m−2 were applied. The irrigation level and nitrogen application significantly affected turf color, quality, clipping yield, leaf relative water content, chlorophyll content, turgor loss, and electrolyte leakage. Increased irrigation and nitrogen levels increased the leaf RWC and chlorophyll content while reducing turgor loss and electrolyte leakage, ultimately improving plant tolerance to environmental stress. Our findings suggest that acceptable turf color and quality throughout the year can be achieved with a 50% irrigation level and a nitrogen dose of 5.00 g m−2. A more economical and environmentally friendly alternative may be the combination of 50% irrigation and 2.50 g m−2 nitrogen, which is particularly effective in spring and autumn. In contrast, the combination of 25% or 50% irrigation with 1.25 g m−2 nitrogen did not result in acceptable turf quality in any season. However, acceptable turf color and quality can still be maintained in water-limited regions, especially during spring and autumn, by applying 5 g m−2 nitrogen under 25% irrigation.

Water scarcity poses a substantial challenge for turfgrass irrigation in the drought- and heat-stressed Desert Southwest region of the United States. Bermudagrass (Cynodon spp.), renowned for its exceptional drought resistance, is the predominant warm-season turfgrass in the region. Selecting and using drought-resistant bermudagrass cultivars remains a primary strategy for sustaining the turfgrass industry in the region. This study evaluated 48 hybrid bermudagrasses (Cynodon dactylon × C. transvaalensis Burtt-Davy), including two commercial cultivars (‘TifTuf’ and ‘Tifway’, as controls), under 80% × ETo (0.8ET), 60% × ETo (0.6ET) and 40% × ETo (0.4ET) reference evapotranspiration (ETo) replacement irrigation systems at Maricopa, AZ. The experiment was laid out in a split-plot design with two replications, where the 3 irrigation treatments were assigned to main plots and 48 genotypes were in sub-plots. Analysis of data from two years (2022 and 2023) revealed significant differences among bermudagrass hybrids, irrigation treatments, and their interaction effects. The hybrids exhibited substantial variation for spring green-up, density, turf color, and quality. With the largest deficit irrigation treatment 40% × ETo (0.4ET), OSU2104, OSU2106, and OSU2105 showed greater mean greenness and aesthetic quality scores than recorded for ‘TifTuf’ (6.5), a popular drought-tolerant cultivar. The results highlight the prevalence of genetic variation in germplasm with potential for development of improved varieties for drought tolerance.

Water is essential for turf growth. It is required for germination, photosynthesis, and as a part of the turf. Most of the water absorbed by turf is transpired through the leaves into the atmosphere. This water moves nutrients from the soil into the plant, but equally important, it eliminates heat buildup from solar radiation. The water applied by an irrigation system will evaporate from the soil and be transpired from plant surfaces. Evaporation and transpiration (evapotranspiration) depend mostly on the climate around the plant; thus, the amount of water used by turf changes with the seasons. This document explains what to do for a well-managed turf.

The efficient use of water resources is a growing priority in multiple sectors, including the turfgrass industry. Nanobubbles (NB) represent an innovative technology that, by enriching solutions with various gases, offers significant benefits in several industrial areas. In crop irrigation, they have been shown to increase dissolved oxygen in the root zone and thereby boost yields. The objective of this study was to evaluate the impact of the use of oxygen NB in irrigation water on turfgrass quality, considering different levels of water restriction (0%, 30%, and 50% of daily crop evapotranspiration), compared to conventional irrigation. During the summer of 2024, trials were conducted using turf quality indices based on multispectral reflectance and RGB digital image analysis. The results showed that the use of NB allowed for a reduction in irrigation by 50% without compromising turf quality, reaching values similar to treatments without water restriction. In contrast, treatment with the same restriction but without NB (WNB50%) showed a deterioration in quality. This study shows NB as an innovative tool to optimize water use, with great potential for applications in landscape green areas, promote water use efficiency, and reduce the costs associated with irrigation.

The use of drought‐resistant grasses and deficit irrigation practices can reduce irrigation volume without sacrificing lawn quality, but a specific lawn's irrigation requirement may vary by soil texture or irrigation frequency. Two Kentucky bluegrass (Poa pratensis L.) cultivars (Mallard and Geronimo), two soil textures (silt loam and loamy sand), two irrigation frequencies (1× and 3× week−1), and two irrigation volumes (40% and 80% reference evapotranspiration replacement) were evaluated in a lysimeter experiment. The experiment was replicated over three runs: late summer 2018 and early and late summer 2019. Turf quality was determined by evaluating green turfgrass coverage, and water use was determined by monitoring lysimeter weights. Mallard and Geronimo did not differ in water usage, but Mallard maintained greater coverage throughout the experiment. Lysimeters replacing 80% reference evapotranspiration averaged 1.4× greater water use and coverage than those replacing 40% reference evapotranspiration over the three experimental runs. Irrigation frequency and soil texture had minimal practical impact on water use and variable effect on turfgrass coverage. Turfgrass grown in lysimeters filled with silt loam and irrigated at 40% reference evapotranspiration demonstrated periods of greater coverage compared to turfgrass in lysimeters with loamy sand under the same irrigation regime. While soil texture may have minimal impact on water consumption during extended drought stress, these findings highlight the importance of adjusting irrigation practices to maintain turfgrass coverage. This refined understanding can allow end‐users to implement customized irrigation strategies that preserve turfgrass quality while minimizing water waste.

No abstract available

Selecting a vegetation layer design goes along with determining its future irrigation need. Therefore, it is essential to take a design decision that is minimising the cumulated construction and irrigation costs in a given depreciation period. This contribution showcases a decision support approach using long term weathering time series and soil water balances with example data for turf soccer fields in six German regions. The approach relies on minimising both material and irrigation costs by modifying soil layer design parameters; here the layer thickness and therefore its water retention capacity. E.g. suggested layer thicknesses between 200 and 250 mm for Stuttgart lead over 10–40 year depreciation periods to estimated substrate and water cost savings between 90 and 194% in comparison to a standard substrate layer thickness of 80 mm. For practical applications, the presented theoretical approach needs to be adapted with the usable soil water storage capacity and relationships describing evapotranspiration for given substrate-turfgrass combinations.

Managing turfgrass in arid and semiarid areas of the southern United States is becoming increasingly challenging due to prolonged drought and diminishing water resources. Turfgrass managers have been seeking products that control pests while promoting drought resistance. CivitasTM Turf Defense is a new petroleum-derived spray oil (PDSO) mixed with green pigment. Like other traditional PDSO products, Civitas is reported to have positive effects on turfgrass pest control and management. However, limited information is available regarding its impact on water conservation in turfgrass. The objective of this study was to evaluate the effects of Civitas on bermudagrass (Cynodon spp.) under deficit irrigation conditions. A 2-year study was conducted in Riverside, CA, USA, to evaluate the effect of Civitas on bermudagrass irrigated at 55% or 65% of reference evapotranspiration (ETo), which represented a 20% or 10% savings in water, respectively. Civitas was applied at 4.5 or 8.5 oz/1000 ft2 every two weeks (2019–20), and 8.5 oz/1000 ft2 every 3 weeks (2019 only), compared with an untreated control. Results show that Civitas improved bermudagrass quality under deficit irrigation at both rates, but the 3-week application interval was less effective compared with the 2-week application interval at either rate. Civitas applied at 8.5 oz/1000 ft2 every 2 weeks resulted in better turfgrass quality than the 4.5 oz/1000 ft2 rate in the first year only. Results suggest that using Civitas on bermudagrass can save up to 20% water while maintaining desirable turf quality.

No abstract available

No abstract available

26 Irrigated agriculture is the dominant user of water globally, but most water withdrawals are not 27 monitored or reported. As a result, it is largely unknown when, where, and how much water is 28 used for irrigation. Here, we evaluated the ability of remotely sensed evapotranspiration (ET) 29 data, integrated with other datasets, to calculate irrigation water withdrawals and applications in 30 an intensively irrigated portion of the United States. We compared irrigation calculations based 31 on an ensemble of satellite-driven ET models from OpenET with reported groundwater 32 withdrawals from hundreds of farmer irrigation application records and a statewide flowmeter 33 database at three spatial scales (field, water right group, and management area). At the field 34 scale, we found that ET-based calculations of irrigation agreed best with reported irrigation when 35 the OpenET ensemble mean was aggregated to the growing season timescale (bias = 1.6% to 36 4.9%, R 2 = 0.53 to 0.74), and agreement between calculated and reported irrigation was better for 37 multi-year averages than for individual years. At the water right group scale, linking pumping 38 wells to specific irrigated fields was the primary source of uncertainty. At the management area 39 scale, calculated irrigation exhibited similar temporal patterns as flowmeter data but tended to be 40 positively biased with more interannual variability. Disagreement between calculated and 41 reported irrigation was strongly correlated with annual precipitation, and calculated and reported 42 irrigation agreed more closely after statistically adjusting for annual precipitation. The selection 43 of an ET model was also an important consideration, as variability across ET models was larger 44 than the potential impacts of conservation measures employed in the region. From these results, 45 we suggest key practices for working with ET-based irrigation data that include accurately 46 accounting for changes in soil moisture, deep percolation, and runoff; careful verification of 47 irrigated area and well-field linkages; and conducting application-specific evaluations of 48 uncertainty. 49 50 Graphical Abstract

In the farming lands of agriculture, water is lost due to evaporation and transpiration. The evaporation and transpiration rate varies day by day according to the climatic conditions of the area. Both overwatering and underwatering are the primary factors influencing a plant's ability to grow. To find the accurate irrigation level we need to identify the loss of water due to evaporation and transpiration. To identify this loss we planned to design the evapotranspiration detector. This detector is used to find the moisture content in soil and plants. Through this, monitoring the amount of water to be irrigated can be determined. This could help in protecting the agricultural land from water logging and irrigation management. This paper describes the working and construction of an evapotranspiration detector.

No abstract available

No abstract available

In today’s climatic conditions such as unprecedented amounts of rain and frequent heat waves, cultivating has become a tedious task. Predicting nature’s next move is not easy but what we can do is minimize its effect on the yield. There are so many regions that receive excessive rainfall, suffer frequent flash floods and scorching heat. To adapt to these conditions, sensor networks can be deployed in the fields and the available resources should be used as efficiently as possible. In order to fulfill this requirement, power storage capable of storing energy efficiently from solar panels and an irrigation controller which monitors the land, be it for farm, gardening or horticulture with little to none intervention in certain aspects. The existing products in the market have proprietary parts, features and they don’t endorse cross-compatibility with other products. Keeping the design open source and easy to work promotes recycling and reparability something essential in the current time of global silicon shortage. Farmers or gardeners often don’t know the amount of water and the intervals of irrigation for many exotic and domestic species of plants, they then end up growing crops such as wheat and rice which need flooding of the field, the cultivation of these species can be promoted and be made easy with the project. Telemetry and connected technologies are part of every system these days. The project monitors various parameters and depending on the conditions, will carry out necessary action such as irrigation in only amounts required by the field. This is possible through PWM control of motors coupled with valves.

Automatic Smart Plant Watering System is a smarter solution that works on Arduino Uno, which can automatically operate for plant watering at optimal moisture conditions of soil. It checks the moisture with the help of a soil moisture sensor and, once the level of moisture goes down below a threshold, initiates a water pump. This user-friendly system is also energy efficient, making it suitable for busy or travel users, further contributing to sustainability plant care, thereby making it ideal for residential and nursery settings while emphasizing the promising use of smart agriculture and IoT technologies. This paper focuses on developing a smart water framework designed to efficiently manage water distribution based on real-time soil and environmental conditions.

Low-cost capacitive soil moisture sensors have potential application in precision irrigation in Thailand. However, these sensors require proper calibration and are affected by soil temperature fluctuations that reduce their measurement accuracy. This study developed and validated a combined calibration and temperature compensation approach for the commercially available soil stick sensor. The calibration was performed using soil samples ranging from sandy clay loam to silty clay. A temperature compensation equation was developed by measuring the sensor responses under varying soil temperatures and moisture content levels in outdoor conditions. The sensor performance was assessed against a reference Time-Domain Reflectometry (TDR) sensor (TRIME-PICO64) and evaluated based on continuous field measurements for 14 days. The temperature compensation equation reduced the diurnal temperature effects through a linear correction model. The calibration showed a piecewise linear relationship between the Relative Voltage (VR) and volumetric water content (qV) with a strong correlation. The performance of the calibrated soil stick sensor was comparable to the TDR sensor, with the Confidence Index values exceeding 0.8. These findings indicated that the calibrated and temperature-compensated low-cost capacitive sensors could provide accurate soil moisture measurements for precise irrigation scheduling.

This research presented a unique architecture based on the Internet of Things (IoT) and ARM for managing soil moisture and irrigation. The framework's goal is to reduce manual fieldwork and move data to a cloud server that can be accessed via an online application. The suggested plan offers benefits in terms of lower expenses, limiting water waste, and lessening physical interference. It also promotes irrigation that requires little upkeep and is ecologically friendly. Temperature, humidity, and sound sensors are paired with an ARM singleboard computer, also known as the Raspberry relay module is positioned to control the water flow. The values collected by the sensor are saved on the cloud server, and the web application provides the required values and recommendations. When soil moisture levels are low and ground temperatures are high, the irrigation system automatically activates, allowing for email notification to the user. The model displayed anticipated effects at different levels of humidity.

The increasing demand for sustainable and automated agricultural practices has led to the development of intelligent systems aimed at enhancing productivity and reducing manual labor. This research presents the design and implementation of an Autonomous Water Supplying Vehicle integrated with a Soil Moisture Sensor and Grass Cutting Mechanism. The proposed system is intended for use in gardens, lawns, and small-scale agricultural fields, where regular irrigation and maintenance are crucial for plant health. The autonomous vehicle is equipped with a soil moisture sensing unit that continuously monitors the moisture level of the soil in real-time. When the sensor detects that the soil moisture content falls below a predefined threshold, the onboard water supply system is activated to irrigate the dry areas precisely, thereby conserving water and preventing over-irrigation. The use of soil moisture feedback ensures adaptive and efficient watering based on actual ground conditions, promoting better plant growth and resource utilization. In addition to irrigation, the vehicle includes a motorized grass cutting module capable of trimming overgrown grass while navigating through the field. This dual-functionality enables simultaneous lawn care and irrigation, reducing the need for separate maintenance operations. The system's navigation is facilitated by a combination of programmed path algorithms and obstacle detection sensors to ensure safe and efficient movement across varied terrain. This project highlights the integration of sensor-based automation with mobile robotics to provide a cost-effective and eco-friendly solution for land maintenance. The design emphasizes low power consumption, autonomous functionality, and minimal human intervention. The results demonstrate that such systems can significantly improve water management efficiency and landscape upkeep, paving the way for smart farming and gardening technologies.

The calibration of capacitive soil moisture sensors is an essential step towards their integration into smart solutions. This study investigates the calibration of a widely used low-cost capacitive soil moisture sensor (SKU:SEN0193, DFRobot, Shanghai, China) in a loamy silt soil typically found in the Puglia region of Italy. The calibration function was derived from a random sample of 12 sensors, with three soil sample replicas per sensor, each of which had one of five gravimetric soil moisture contents, from relatively dry (5%) to full saturation (40%). The study reports the resulting calibration function along with the accuracy achieved with the generalized calibration function. The sensors proved to be accurate, with an R2 value ranging between 0.85 and 0.87 and a root mean square value (RMSE) ranging between 4.5 and 4.9%. The variation between the sensors was also investigated. The results showed that with higher soil moisture contents (above 30%), the sensor-to-sensor variability becomes significant, with a coefficient of variation (CV) ranging between 10 and 16%; meanwhile, in lower soil moisture contents, the CV ranged between 6.5 and 10.3%, implying that it is more consistent in lower moisture content within this soil condition. The resulting calibration function enhances the integration of such low-cost sensors into smart farming solutions. With proper calibration, these affordable capacitive sensors can achieve a high degree of accuracy, making them a viable option for widespread use in cost-effective precision agricultural applications.

The moisture of the soil plays an essential role in the irrigation field as well as in gardens for plants. As nutrients in the soil provide the food to the plants for their growth. Supplying water to the plants is also essential to change the temperature of the plants. The temperature of the plant can be changed with water using the method like transpiration. And plant root systems are also developed better when rising within moist soil

Time series modeling and forecasting play important roles in many practical fields. A good understanding of soil water content and salinity variability and the proper prediction of variations in these variables in response to changes in climate conditions are essential to properly plan water resources and appropriately manage irrigation and fertilization tasks. This paper provides a 48-h forecast of soil water content and salinity in the peculiar context of irrigation with reclaimed water in semi-arid environments. The forecasting was performed based on (i) soil water content and salinity data from 50 cm beneath the soil surface with a time resolution of 15 min, (ii) hourly atmospheric data and (iii) daily irrigation amounts. Exploratory data analysis and data pre-processing phases were performed and then statistical models were constructed for time series forecasting based on the set of available data. The obtained prediction models showed good forecasting accuracy and good interpretability of the results.

Brazil has been experiencing several instabilities regarding the climate. There is a great climatological variation in the cultures that have been suffering drastically from this stress, mainly water. Therefore, it is necessary to quickly and efficiently check the soil moisture rate, before any operation in the field, avoiding production losses and unnecessary extra expenses for the producer. Methods for measuring soil moisture are extremely important for carrying out adequate irrigation, thus optimizing water resources and saving water. Humidity directly affects seed quality, germination rate and crop yield, other unit operations. In this study the low-cost WeMos sensor was evaluated regarding its efficiency and possible calibration in comparison to high-cost equipment with an average of US$: 405,75 dollars. The gravimetric method was used to calibrate the sensor, which consists of sample preparation, drying, determination of its mass and evaluation calculation. The gravimetric method was used to calibrate the sensor, which consists of sample preparation, drying, determination of its mass and evaluation calculation. From the data obtained, the equation was used, which was first inserted into the programming carried out in the Arduino system transmitted to the WeMos sensor. The results obtained by the WeMos sensor were consistent with the gravimetric humidity results obtained. It is concluded that the WeMos Arduino sensor presents reliability in sampled data and that it is an economically viable option for rural producers who need to obtain an answer regarding the humidity of the planting soil.

Smart irrigation as one of implementations of the Internet of Things (IoT) in agriculture aims to control and monitor water supply in accordance to crop needs. The control systems are designed using the Arduino Nano platform and the soil moisture sensor YL 69. The accuracy of the sensor is very influential on the performance of the control system, so that sensor calibration is done before it is applied to smart irrigation. The calibration method used in this research is the Gravimetric Water Content method. The media used in calibration is a mixture of soil and sand as Smart Irrigation as one of the implementations of the Internet of Things (IoT) in agriculture aims to control and monitor water supply in accordance to crop needs. The control system is designed using the Arduino Nano platform and the soil moisture sensor YL 69. The accuracy of the sensor is very influential on the performance of the control system, so that sensor calibration is done before it is applied to smart irrigation. The calibration method used in this research is the Gravimetric Water Content method. The media used in calibration is a mixture of soil and sand as much as 5% of the soil. Water weighed 4.71% from soil weight added to increase soil moisture level in calibration process. Based on the calibration results obtained from the sensor reading 201 shows 18.31% of soil moisture in dry soil. With nine times of water addition to soil obtained soil saturation point to water with sensor reading 633 which shows result 61.91% of soil moisture. The experimental results show the polynomial curve of order 3

Soil moisture monitoring is essential for optimizing irrigation strategies, enhancing crop yields, and conserving water resources in precision agriculture. Traditional sensing methods often rely on battery-powered devices, which require maintenance and periodic replacement. This work introduces a batteryless ultrahigh frequency radio frequency identification (UHF RFID) soil moisture sensor that leverages RFID technology and an interdigitated capacitor (IDC) for capacitive sensing. The proposed sensor integrates a meandered dipole antenna and an EM4152 RFID chip, enabling wireless monitoring of soil Volumetric Water Content (VWC) without the need for an external power source. The sensor’s performance is validated through controlled soil moisture experiments, where capacitance readings are correlated with reference measurements from the commercial TEROS 10 soil moisture sensor. The sensor was tested and calibrated using three different soil types: sandy, clay, and a commercial combo substrate. The results demonstrate strong linear correlations with TEROS 10 measurements across all soil types, with coefficients of determination of R2 = 0.9648 (sandy), R2 = 0.9512 (clay), and R2 = 0.9444 (combo). Furthermore, tests conducted at varying water contents and a read range of up to 3.5 meters validate the sensor’s robustness across different soil conditions. The findings highlight the potential of battery-less RFID-based sensing for sustainable and maintenance-free soil moisture monitoring in agricultural applications.

Irrigation is important for agricultural activities because it distributes water into irrigation area and provides water for crop growth. The appropriate and effective water allocation supports agricultural productivity. Generally, irrigation activities get water from rainfall and it is very depending on several climate variables for example temperature, humidity, duration of radiation and wind velocity. Several climatic variables are important for agriculture since they affect the evapotranspiration rate that it will determine irrigation water requirement rate. Therefore, irrigation water requirement is sensitive if climate change happened. In the other hand, decreasing of agriculture area as the agricultural land conversion gradually will reduce the irrigation service area particularly in the fast-growth area in development. So that, irrigation water requirement also will be reduced. Irrigation water requirement should be evaluated simultaneously in order that it can be allocated appropriately. This paper was written to develop an evaluation method for irrigation water requirement through analysis of climate change trend, agricultural land conversion and irrigation efficiency based on the literature review. The reviews result selected method i.e. Mann Kendall Test for climate change trend analysis, spatial analysis for agricultural land conversion and comparison of inflow and outflow for irrigation efficiency analysis.

The present work proposes the use of green infrastructure (GI) called sustainable urban agriculture drainage systems with water reuse (SUADS-WR) to manage percolated water sustainably in urban agricultural areas (f.i. golf courses). The substrate of the system is commonly used in golf courses and includes a subsurface reservoir for water that exceeds the edaphic zone. Data obtained from a lysimeter, installed in a golf course in Spain, are used to validate the methods employed in developing hydro-informatics tools based on daily water balance, which estimates the water requirement for crops, reservoir height, and capacity for unused water reuse. Reference evapotranspiration can be estimated using the Penman–Monteith or Hargreaves–Samani method. The results were compared with experimental data, revealing that the estimated irrigation depths were lower than the supplied ones and that the estimated percolation was consistent with the measured field drainage. The applicability of the proposed methods for determining the reservoir height and irrigation depth for any type of crop in urban agricultural areas is confirmed. With the implementation of SUADS-WR, the harvested water depth can cover more than 38% of the annual water demand for the crop and utilize leached fertilizers, thus preventing pollution of the receiving surface water body or groundwater.

Progressive urbanization and increasing pressure on urban green areas necessitate the search for innovative, ecological, and efficient solutions for lawn management. The shallow root system of grasses, combined with a long vegetation period, makes these plants particularly sensitive to water and nutrient deficiencies. One research direction involves the use of zeolites, natural aluminosilicate minerals that, due to their porous structure and high sorption capacity, improve water retention and nutrient availability in soil. The aim of this study was to assess the effect of different zeolite doses on the initial growth and development of two turfgrass species (Lolium perenne, Festuca rubra), as well as on selected lawn performance traits, and to determine the persistence of these effects over time. This research was conducted in 2020–2023 under pot and micro-plot experiment conditions, using mixtures containing the above species. Four levels of zeolite addition to the substrate were applied: 0% (control), 1%, 5%, and 10%. The results clearly confirmed the beneficial effects of zeolite. Its addition improved the germination, growth, and biomass yield of aboveground parts and roots, as well as enhancing turf aesthetics, ground cover, and winter hardiness, while reducing the proportion of dicotyledonous species. The best effects were obtained with the 5% dose, which should be considered optimal—it significantly improved lawn utility parameters with lower material input compared to the 10% dose. Species response varied: L. perenne responded more strongly to improved water–air conditions, whereas F. rubra utilized higher zeolite doses more effectively in root system development. The highest overall effectiveness was recorded with the 10% dose. Zeolite effectiveness was greatest in the first year after application, showing a declining trend in subsequent years, although a positive effect was still observed in the third year of use. The findings support the recommendation of zeolite as an ecological soil additive that enhances lawn quality and durability, particularly in low-fertility soils and under water deficit conditions. Its application may represent an important component of modern green space management technologies in line with the principles of sustainable development.

Returning turfgrass clippings to soil (i.e., mulching) has been shown to yield many benefits, such as reducing fertilizer requirements. However, previous reports on the contribution of clippings to turfgrass fertilization varies widely, making it difficult for turfgrass managers to adjust their fertilization practices. Other potential benefits of this practice, such as soil water conservation, still need to be quantified. The objectives of this project were to measure the contribution of Kentucky bluegrass clippings to N, P and K fertilization under four different N levels and to measure the impact of clippings management on turfgrass color (NDVI), soil nutrient and water content as well as thatch accumulation. A field experiment was conducted over three years, with treatments consisting of two clipping management strategies (returned or removed) and four nitrogen levels (0, 48, 96 and 144 kg N ha -1 yr -1). Clippings were collected on every mowing date and were analyzed for N, P and K foliar content. Soil volumetric water content and NDVI were measured weekly, while thatch accumulation and soil chemical content (Mehlich-3) were assessed twice per year. Increasing N fertilization resulted in an increase in both clippings dry matter yield (DMY) and foliar N concentration. Returning grass clippings was equivalent to doubling the amount of N applied through the fertilizer and resulted in an increase in turfgrass color and soil P and K levels. For P and K, clippings contribution was more affected by their DMY than by foliar concentrations. Grass clippings did not contribute to thatch accumulation, but resulted in a consistent increase (3.9% on average) in soil volumetric water content.

Turfgrass irrigation based on evaporative requirements strengthens water conservation efforts. A study was conducted from 1998 to 2000 to determine actual evapotranspiration (ETa) of warm and cool‐season turfgrasses and to develop crop coefficient (KC) values normalized for growing degree days. Predicted values of maximum ETa and KC were calculated, and data from a second study were used to validate the fitted polynomial functions. Estimated ETa differed in 1998 and 1999 and ranged from 5.42 mm day−1 (Poa pratensis L. ‘Adelphi’ in 1998) to 6.69 mm day−1 (Lolium perenne L. ‘Seville’ in 1999) for cool‐season turfgrasses (CS) and from 4.54 mm day−1 [Buchloe dactyloides (Nutt.) Engelm. ‘Bison’ in 1999] to 5.15 mm day−1 [Cynodon dactylon (L.) Pers. ‘Guymon’ in 1998] for warm‐season turfgrasses (WS). For CS, between‐year variation was greater than differences within years, but for WS, within‐year differences were greater than between years. A quadratic function was used to model the trend in KC. For CS, KC differed among years, with similar trends in 1998 and 1999. Generally, values for CS ranged from 0.76 to 0.95 and for WS from 0.68 to 0.76. We were unable to establish a clear trend that would group both CS and WS into high water use versus low water use. If a variable KC based on our models had been applied during the 3‐year period, irrigation amounts would have been reduced by approximately 10% for CS and by 15% for WS when compared to a constant KC.

Disturbed soils, including manufactured topsoils, often lack physical and chemical properties conducive to vegetation establishment. As a result, efforts to stabilize disturbed soils with vegetation are susceptible to failure. Urban organic waste products such as wood mulch, composted leaf and yard waste, and biosolids are widely distributed as organic amendments that enhance sustainability and plant establishment. Correct use can be determined by examining soil properties such as pH; the concentration of soluble salts (SS); and plant available nutrients - particularly N, C and P; as well as root and shoot growth. This research examined the effects of three typical organic amendments on fertility, establishment, and nutrient loss. A manufactured topsoil was used as the base soil for all treatments, including a control unamended soil (CUT), and soil amended with either mulch (MAT), composted leaf and yard waste (LAT), or biosolids (BAT). A 2 % organic matter concentration increase was sought but not achieved due to difficulty in reproducing lab results at a larger scale. Results showed that LAT improved soil fertility, particularly N-P-K concentrations while maintaining a good C:N ratio, pH, and SS concentration. BAT was the most effective at enhancing shoot growth but results suggest that improved growth rates could result in increased maintenance. Additionally, biosolids were an excellent source of nutrients, especially N-P-K and S, but diminished root growth and N leachate losses indicate that N was applied in excess of turfgrass requirements. Therefore, biosolids could be used as fertilizer, subject to recommended rates for turfgrass establishment to prevent poor root growth and waterborne N pollution. To ensure establishment efforts are successful, MAT is not recommended without a supplemental source of soluble N. Altogether, study results and conclusions could inform others seeking to improve specifications for disturbed soil where turfgrass establishment is needed to stabilize soil.

In the context of rapid urbanization and increasing water demand in agriculture, the reuse of treated domestic wastewater is emerging as an important solution toward developing green and sustainable cities. This study aims to assess the potential for reusing treated domestic wastewater in Tan Uyen City, Binh Duong Province. Data were collected from the city's domestic wastewater treatment system, with key analyzed parameters including BOD5, COD, TSS, NH4+, NO3-, total nitrogen (TN), total phosphorus (TP), alkalinity, and color. The results indicate high treatment efficiency, with COD reduced by 94.49% (from 290.4 ± 0.2 mg/L to 16 ± 1 mg/L), BOD5 by 97.1% (from 93.36 ± 0.03 mg/L to 2.706 ± 0.001 mg/L), TSS by 97.36% (from 196.8 ± 0.1 mg/L to 5.2 ± 0.1 mg/L), and Coliform by 99.69% (from 80162 ± 3 MNP/100 mL to 250.6 ± 0.1 MNP/100 mL). Additionally, NH4+ decreased from 40.54 ± 0.02 mg/L to 0.168 ± 0.02 mg/L (99.59% efficiency), NO3- from 4.58 ± 0.01 mg/L to 1.34 ± 0.03 mg/L (70.74%), total nitrogen from 39.6 ± 0.1 mg/L to 6.96 ± 0.01 mg/L (82.42%), and total phosphorus from 3.84 ± 0.01 mg/L to 1.14 ± 0.01 mg/L (70.31%). The color was significantly reduced from 427.4 ± 0.1 Pt/Co to 20.8 ± 0.1 Pt/Co (95.13%). The analysis results show that the treated water meets the requirements of QCVN 39:2011/BTNMT, and it can be reused for purposes such as irrigation of landscape greenery, vegetables, or short-term industrial crops. The study recommends enhancing post-treatment water quality monitoring and developing effective reuse models to improve water resource conservation, reduce pressure on freshwater sources, and promote sustainable urban agricultural development in Tan Uyen City.

No abstract available

Periodic drought and shortage of potable water have led many municipalities in Florida to set limitations and restrictions on irrigation frequency for home lawns. These restrictions do not take into account turfgrass health and response and may be inappropriate across different species and cultivars; hence, there is a need to identify genotypes that could sustain quality and performance under reduced irrigation. A study was conducted at the University of Florida Plant Science Research and Education Unit in Citra, FL, to assess turfgrass response of 10 bermudagrass (Cynodon spp.), nine zoysiagrass (Zoysia spp.), and five seashore paspalum (Paspalum vaginatum Swartz) cultivars to different irrigation regimes, consisting of non‐irrigated control (Rainfed), soil moisture sensor (SENSOR)‐based (up to 152 mm mo−1), 8X per month (8XMO up to 152 mm mo−1), 4X per month (4XMO up to 76 mm mo−1), 2X per month (2XMO up to 38 mm mo−1), and 1X per month (1XMO up to 19 mm mo−1). Plots were evaluated for turfgrass quality and percent green cover using digital image analysis every 3 days over a 22‐month period. Bermudagrass was able to sustain acceptable turfgrass quality during one of the growing seasons when irrigated 4XMO, showing substantial water savings compared to the other two species. SENSOR irrigation significantly reduced water consumption for all the three species and produced turfgrass quality similar to 8XMO irrigation. Results indicate that selecting the right cultivar for the area could help sustain turfgrass aesthetic and functionality.