A 3-year study was conducted in the Catawba-Wateree River Basin during the spring and summer months of 2009-2011 to evaluate the water savings potential of three smart irrigation controllers compared with standard timer-based irrigation controllers. Thirty-six residential sites, 12 on each of three Duke Energy lakes (Lake Norman, Lake Hickory, and Lake Wylie), were selected for the study. Each site had an automated, underground irrigation system that directly drew water from the Duke Energy lake that the property bordered. None of the systems had previously been metered and there was no charge to homeowners for withdrawing water from the bordering lake. All sites were instrumented with water meters in 2009 to monitor irrigation water withdrawals, and irrigation system audits were performed before installation of smart technologies. After collecting baseline water-use data in 2009, existing controllers were replaced with one of three smart controllers at 27 of the study sites in 2010, and irrigation was monitored through the end of the 2011 irrigation season. Irrigation treatments included a standard irrigation controller with an add-on soil moisture sensor system (SMS), an evapotranspiration (ET) based controller that received daily reference evapotranspiration estimates from a third-party provider (ET1), an evapotranspiration-based controller with an on-site weather sensor (ET2), and a comparison group that used the existing irrigation controller with no intervention (COMP). Weekly water withdrawals were monitored with on-site data loggers, and turf quality was visually rated and characterized with a normalized difference vegetation index (NDVI) meter. The SMS treatment applied the most irrigation per week (mean of 27.4mmweek-1), compared with 24.7mmweek-1 for the ET1 treatment, and the COMP and ET2 treatments that applied 20.9 and 19.9mmweek-1, respectively. Although applying the most irrigation, the SMS treatment had the greatest effect on water-use behavior for sites receiving technologies, reducing irrigation by 11.7mmweek-1 compared with the baseline year in which the SMS group applied the most water. There was no evidence of a change in water-use behavior in the COMP treatment, but collectively the smart treatments reduced irrigation from 60% more than the gross irrigation requirement (GIR) in 2009 to only 10% more than GIR in 2010 and 2011, without adversely affecting the turf quality. Visual turf quality ratings in the COMP treatment were slightly less than the minimally acceptable level, which may have resulted from underirrigation during high water demand periods. Several challenges to retrofitting existing systems and issues with smart controllers were observed, including poorly designed and maintained existing irrigation systems, incompatibility between existing controllers and SMS sensor modules, failure of all nine soil-moisture sensors, communication failures in ET-based controllers, and manual overrides of smart technologies by study participants. This study emphasizes the importance of proper installation, programming, and maintenance of smart technologies on suitable irrigation systems if they are to function correctly. To maximize water savings, smart irrigation retrofits should be targeted toward systems that historically overirrigate.

Irrigation is the most common and standard practice for maintaining turfgrass and landscape plants in residential settings. The main objective of this study was to quantify the residential irrigation water use in Cary, North Carolina. A subobjective was to develop distributions of monthly reference evapotranspiration (ETo) and gross irrigation requirements (GIRs) for the area using long-term weather data. As part of the subobjective, an investigation was performed to compare daily measured solar radiation with two empirical methods of estimating solar radiation (R-s). The goal of this investigation was to determine the relative accuracy of these methods and to evaluate the impact of using R-s estimates in the computation of ETo and GIR for the Raleigh-Durham area, where Cary is located. Irrigation water use data from 2005 to 2007 for 120 randomly sampled residences were evaluated. The average lawn area of the sampled residences was 713 m(2). None of the sampled households used drip irrigation. A negative correlation existed between the irrigated area and applied water depth. The MayOctober period accounted for 84-89% of the total annual outdoor water use for the 3 years evaluated. A trend of applying more water than the gross irrigation requirement was observed during the lawn renovation period (mid-September through late October). Solar radiation was computed using two methods: the Hargreaves and Samani method based on difference in maximum and minimum temperature, and the Doorenbos and Pruitt method based on percent possible sunshine. Solar radiation estimated using the percent possible sunshine method showed a strong relationship (R-2 = 0.88) with measured solar radiation and proved to be a much more reliable way of estimating solar radiation than the temperature difference method for the Raleigh-Durham region. Estimates of mean, median, and P-80 (80th percentile) monthly ETo and GIR constructed from a 60-year data set show that ETo tends to peak in July at an average of 154 mm, whereas GIR peaks in June with an average of 105 mm. The distribution of GIR is substantially more variable than ETo due mostly to variability in rainfall, illustrating the difficulty in applying the correct amount of water consistently from year to year in subhumid to humid regions. (C) 2014 American Society of Civil Engineers.

AbstractA study was conducted in Cary, North Carolina, in the spring and summer of 2009 with the purpose of evaluating the effectiveness of two “smart irrigation” controllers based on the amount of irrigation applied and resulting turf quality in residential settings. Twenty-four residential sites were selected, in clusters of four, representing six geographical areas within the town. Each geographical cluster included one site of each treatment. The treatments were standard irrigation controller with an add-on soil moisture sensor system (SMS); standard irrigation controller with an add-on evapotranspiration-based adjustment system (ET); standard irrigation controller using seasonal runtimes based on historical climate data (ED); and a control group which used a standard irrigation controller with no intervention (CON). Weekly water usage was obtained from irrigation meter readings and turf quality was characterized using a visual rating and a normalized difference vegetation index (NDVI) meter. Maximum ...

Increasing competition for water and the desire for high-quality turfgrass require sound irrigation water management. The main objective of this study was to evaluate two types of commercially available irrigation control technologies: one based on evapotranspiration (ET) estimates and the other based on feedback from a soil-moisture sensor (SMS). Irrigation treatments were combinations of controller technology: a timer-based standard controller system (TIM), an add-on (1 set point) SMS system (SMS1), and an evapotranspiration (ET)based system (ETB), and watering frequency: weekly, twice per week, and daily (1, 2, and 7 days per week, respectively) plus a 10th treatment of an on-demand (2 set point) SMS system (SMS2). Both irrigation efficiency and adequacy were best for the SMS2 treatment when averaged over all three years. The SMS1 treatment provided good irrigation efficiency, but irrigation adequacy suffered, most noticeably with the twice per week treatment. The ET treatment provided good irrigation adequacy, but had the poorest irrigation efficiency. SMS treatments resulted in average water savings of 39% in SMS1 treatments and 24% in the SMS2 treatment compared to the timer-based treatments, whereas the ET treatments applied 11% more water, on average, than the timer-based treatments. The weekly SMS1 treatment applied the least amount of water (10 mm week(-1)), whereas the twice per week ET treatment applied the most water (26 mm week(-1)). DOI: 10.1061/(ASCE)IR.1943-4774.0000528. (C) 2013 American Society of Civil Engineers.

ABSTRACTDigital image analysis (DIA) provides an accurate, nondestructive, and objective assessment of turf color. Previous research developed an index known as the dark green color index (DGCI) via DIA as an indicator of turf color. The objective of this study was to use DGCI variability to better predict a visual rating (VR) index used to evaluate tall fescue (Festuca arundinacea Schreb.) color under different irrigation treatments. To develop DGCI statistics, two freeware software packages (Image J and R) were used to extract and process information from digital images. The model to predict VR from DIA was developed and calibrated using candidate DGCI statistical moments from 120 images in a calibration data set using a multiple linear regression procedure. Fitness of calibration and validation models were verified using the adjusted coefficient of determination, root mean square error, and the Mallow's Cp statistic. The two‐variable model produced more precise estimates (adjusted R2 = 0.926 and 0.899) than the model that only used one term in predicting the VR values (adjusted R2 = 0.879 and 0.843) for calibration and validation sets, respectively. These data suggest incorporating a measure of color uniformity improves the use of DGCI in predicting VR values compared to using only the mean of DGCI values to predict VR values. Model refinements may be needed for other turf species, but current work suggests using additional statistical moments such as SD improves VR estimate precision and accuracy.

Liquid manure is usually treated through application to agricultural land using irrigation systems. Land application of liquid manure needs to follow established guidelines in order to achieve economic goals as well as to protect the environment. Guidance at the time of this study in North Carolina suggested calibration of land application equipment be performed once every three years by the "catch can" method, a time- and labor-consuming method. The goals of this project were to investigate the relationship between liquid manure application uniformity by using data from historical uniformity assessment trials and from additional trials conducted during the study, and to use the results to provide guidance in developing a simplified field method for uniformity assessment. Trials were performed to test the liquid manure application uniformity for different irrigation system types, sprinkler types and models, nozzle types, nozzle diameters, and nozzle pressures. Wind speed during the trials was monitored. Different sprinkler overlaps were achieved by superposition, thereby allowing for assessment of multiple sprinkler spacings for each trial. Regression models were constructed using historic and study-period trial data and a process of main effect selection, collinearity checking, interaction term and quadratic term selection, parameter estimation, and normality testing of model residuals. The model for stationary systems performed well with an adjusted R-2 of 0.72 and predicted application uniformity showed the expected tendencies with changes in predictive factors. The model for traveling gun systems did not perform as well as that for stationary systems; the adjusted R-2 was only 0.33. The results of this study were used to amend uniformity assessment requirements to a simple procedure requiring measurement of sprinkler nozzle pressure, wetted diameter, and sprinkler spacing.

Although millions of dollars are spent restoring wetlands, failures are common, in part because the planted vegetation cannot survive in the restored hydrology. Wetland restoration would be more successful if the hydrologic requirements of wetland plant communities were known so that the most appropriate plants could be selected for the range of projected hydrology at the site. Here we describe how hydrologic models can be used to characterize the long-term hydrology of wetland plant communities, and we show how these results can be used to define wetland design criteria. In our study, we quantified differences in long-term (40-year) hydrologic characteristics of the pond pine woodland (PPW), nonriverine swamp forest (NRSF), high pocosin (HP), and bay forest (BF) plant communities native to the North Carolina Coastal Plain. We found that the median water level was 8 cm below the land surface in PPW and 9, 2, and 8 cm above the land surface for NRSF, HP, and BF, respectively. When the land surface was inundated, the median duration of inundation was 91 d year-1 for PPW and 317, 243, and 307 d year-1 for NRSF, HP, and BF, respectively. Our models suggested that the PPW received an average of 15% of its water input from groundwater inflow, whereas the other communities we modeled did not appear to receive groundwater inflow. Using these results and soil organic layer thickness, we developed and propose design criteria linking soil, vegetation, and hydrology parameters that should contribute to improved restoration success.

A three year residential lake water use study in the Catawba River Basin was initiated in 2009 to assess current water withdrawals for landscape irrigation and the water conservation potential of "smart irrigation" technologies. The study is being conducted by North Carolina State University, on properties bordering Duke Energy managed lakes, in North Carolina and South Carolina, that withdraw lake water for landscape irrigation. Assessment of current irrigation water use began in 2009 with a survey to which over 1,400 residences responded (reflecting a 7.4% return rate). Survey results were used to select thirty-six residences (twelve on each of three lakes along the Catawba River) for further evaluation. Water meters with loggers were installed on the main lines of irrigation systems of the selected residences in the summer of 2009 to monitor lake water withdrawals for landscape irrigation under current practices. Two weather stations and four atmometers were also installed in the region to monitor reference evapotransporation during the study. Three types of smart irrigation technologies (two ET-based controllers and one soil-moisture sensor system) were installed at twenty-seven of the study sites at the beginning of the 2010 irrigation season. The technologies were distributed such that each lake had six sites with ET-based controllers, three sites with soil-moisture sensors, and three sites with no intervention, which would serve as a comparison group. Metering of irrigation water withdrawals continued throughout the 2010 irrigation season after installation of smart irrigation technologies. Turf quality assessments were made throughout the year using a visual turf quality rating and a Normalized Difference Vegetative Index (NDVI) obtained with a turf color meter. The study will conclude with data collected in the 2011 irrigation season.

A Subsurface Drip Irrigation (SDI) system was installed in February 2007 on the Swine Unit of the Central Crops Research Station in Clayton, North Carolina to land apply anaerobic swine lagoon effluent on soybeans. Drip tape with 15 mil wall thickness rated at 2.20 L/H [0.58 gph] with emitter spacing of 0.30 meter [1.0 ft]) was installed at 0.96 m (38 in.) row spacing at 0.25 m (10 in.) depth in a Norfolk loamy sand soil. The SDI system covered about 0.2 ha (0.5 ac). The other half of the field was served by a traditional sprinkler irrigation system. The objective of the study was to compare relative environmental impacts of the two systems and to evaluate the technical feasibility of using an SDI system to land apply liquid swine manure. Environmental impact was assessed by collecting soil-water samples of chloride at 30 and 60 cm and collecting ammonia air samples after land application events. Technical feasibility of the SDI system was assessed by evaluating the distribution of liquid manure from the driplines and by comparing soybean yield to the traditional sprinkler system in addition to observing backflushing cycles and flow rates. There was no statistical difference in average chloride concentrations in soil-water samples. Total ammoniacal nitrogen air sample concentrations were lower in the SDI system, averaging about twenty percent of the concentration of samples taken from the sprinkler system area. Effluent spread about 0.30 meters laterally (one-direction) from the driplines. There was no statistical difference in yield by application method when combining over years.

Several municipalities and water suppliers in North Carolina are interested in the implementation of smart irrigation technologies to conserve water. Some of these entities are interested in evaluating these smart technologies in residential settings prior to adopting any formal policies relating to their use. Two studies are being conducted in North Carolina for such purposes; one in the Town of Cary and another in the Catawba River Basin. In the recently completed Town of Cary study, water use and turf quality were compared between four groups: residences supplied with a weather-based (ET) system, residences supplied with a soil-moisture-sensor-based (SMS) system, residences supplied with guidance on how to program their irrigation controllers, and a comparison group with no intervention; while in the ongoing Catawba River Basin study, a second ET controller group is being included and there is no guidance group. The Catawba Basin study began with a survey designed to assess basic irrigation water use patterns to which over 1,400 residences responded, and continued with cooperator selection and water meter installation. Weather stations and atmometers were deployed to help establish reference evapotranspiration estimates. Water use results from the Town of Cary study showed that the SMS group applied the least amount of water followed by the ET controller group. No statistical difference in average weekly water use was found between the ET group and the group provided with controller run-time guidance. Preliminary water use data from the Catawba River Basin study show an average daily withdrawal (total volume metered/days meter installed) of about 800 gallons for data collected from mid-July to 1 Nov. 2009.

An efficiently managed irrigation system is important in order to achieve the dual goals of water conservation and acceptable turf quality. The main objective of this study was to identify changes and correlations among turf visual rating, canopy reflectance, canopy temperature and digital imagery index in evaluating turfgrass quality under different irrigation treatments. A study of ten irrigation treatments on tall fescue plots combining controller technology (a standard time-based system, two soil-moisture-based systems, and an evapotranspiration based system) and watering frequency (once per week, twice per week and seven days per week) replicated four times in a randomized complete block design was done at the North Carolina State University Lake Wheeler Turf Field Laboratories. Different turf quality measurements were taken on a weekly basis during the summer of 2008 and 2009. An imagery analysis index, dark green color index (DGCI), was strongly and positively correlated with a visual rating index(r = 0.67 and 0.85, for 2008 and 2009 respectively) and normalized difference vegetation index (NDVI) (r = 0.83 and 0.87, for 2008 and 2009 respectively), but negatively and weakly correlated with canopy and ambient air temperature differentials (ΔT) (r = -0.06 and -0.24, for 2008 and 2009 respectively). Because of their objective measurements, digital imagery analysis and canopy spectral reflectance techniques can be used effectively to evaluate the variability in turf quality under different irrigation treatments (technology x frequency), thus improving irrigation management finding the treatment has low water-use with acceptable turf quality.

A subsurface drip irrigation (SDI) system was installed in the Piedmont of North Carolina in a clay soil in the fall of 2001 to test the effect of dripline spacing on corn and soybean yield. The system was zoned into three sections; each section was cropped to either corn (Zea mays L.), full-season soybean [Glycine max (L.) Merr.], or winter wheat (Triticum aestivum) double cropped to soybean representing any year of a typical crop rotation in the region. Each section had four plots; two SDI plots with dripline spacing at either 1.52 or 2.28 m, an overhead sprinkler irrigated plot, and an unirrigated plot. There was no difference in average corn grain yield for 2002-2005 between dripline spacings or between either dripline spacing and sprinkler. Irrigation water use efficiency (IWUE) was greater for sprinkler irrigated corn than for either SDI treatment and there was no difference in IWUE in soybean. Water typically moved laterally from the driplines 0.38 to 0.50 m. SDI yield and IWUE increased relative to sprinkler yields and water use efficiency in the second and third year of the study. This may suggest that initial fracturing of the heavy clay soil during SDI system installation and subsequent settling of the soil affected water distribution.

Decreasing the amount of water applied by residential irrigation systems without causing negative effects on turfgrass quality is a challenge. A variety of technologies are available in the market that seeks to reduce irrigation water use. These technologies include rain sensors, and soil moisture sensor (SMS) based and evapotranspiration (ET) based controllers. A study was conducted in Cary, North Carolina with the purpose of evaluating the effectiveness of two smart systems, based on the amount of irrigation applied and turf quality in residential settings. The study included 24 residential sites that were divided into six geographical regions, each group within a region receiving four different treatments. The treatments were: SMS) an irrigation controller with a soil moisture sensor, ET) an evapotranspiration based controller, ED) a standard irrigation controller using seasonal runtimes based on historical climate data and Control) irrigation controller with no intervention. Data was collected from May 2009 through September 2009. Maximum water savings were achieved by the SMS treatment followed by ET, ED and Control treatments. According to visual turfgrass rating, only the Control group was found to have turf quality below an acceptable level.

In addition to nutrients, poultry are fed trace elements (e.g., As) for therapeutic purposes. Although a large proportion of the nutrients are assimilated by the birds, nearly all of the As is excreted. Hence, turkey litter constituents can leach into the soil and contaminate shallow ground water when it is stockpiled uncovered on bare soil. This study quantified the leaching of turkey litter constituents from uncovered stockpiles into the underlying soil. Four stockpiles were placed on Orangeburg loamy sand in summer 2004 for 162 d; 14 d after their removal, four stockpiles were created over the same footprints and left over winter for 162 d. Soil samples at depths of 7.6 to 30.5 cm and 30.5 to 61 cm adjacent to and beneath the stockpiles were compared for pH, electrical conductivity, total C, dissolved organic C, N species, P, water-extractable (WE)-P, As, WE-As, Cu, Mn, and Zn. All WE constituents affected the 7.6- to 30.5-cm layer, and some leached deeper; for example, NH(4)(+)-N concentrations were 184 and 62 times higher in the shallow and deep layers, respectively. During winter stockpiling, WE-As concentrations beneath the stockpiles tripled and doubled in the 7.6- to 30.5-cm and 30.5- to 61-cm layers, respectively, with WE-As being primarily as As(V). Heavy dissolved organic C and WE-P leaching likely increased solubilization of soil As, although WE-As concentrations were low due to the Al-rich soil and low-As litter. When used as drinking water, shallow ground water should be monitored on farms with a history of litter stockpiling on bare soil; high litter As; and high soil As, Fe, and Mn concentrations.

A study was initiated in Fall 2006 in Raleigh, North Carolina to compare two types of commercially available irrigation control technologies, one based on estimates of evapotranspiration (ET) and the other based on feedback from soil moisture sensors. Water applied and turf quality from one ET-based system and two sensor-based systems were compared to a system using a standard time-based irrigation schedule. The effect of irrigation frequency was also a part of the study. Estimates of turf ET were obtained from the Penman-Monteith equation using on-site weather data, and also from an atmometer. Results from the twenty week evaluation in 2007 showed that on average the “add-on” soil-moisture-based system evaluated applied the least amount of water while the ETbased system evaluated applied the most water. Weekly irrigation frequencies used the least amount of water, followed by bi-weekly and daily frequencies in increasing amounts when averaged across all technologies. Minimally acceptable turf quality was maintained by all technologies and frequencies through most of the study, but turf quality declined substantially the last month of the study for the add-on system and standard timer-based system. The “on-demand” sensor-based system resulted in the best combination of water efficiency and turf quality.

Understanding the hydrology of soils that have been drained is necessary for wetland restoration and in determining whether redoximorphic features are relicts of a former hydrologic regime. This study shows how two kinds of hydrologic models can be used to estimate the quantities of ground water entering a site, as well as compute long-term (40 years) records of water table fluctuations. A water budget was computed for a Carolina Bay wetland that had been drained for agriculture but was being restored to a wetland. Precipitation, potential evapotranspiration, surface outflow, and water stored in the soil were evaluated for a 13-min period to determine the amount of ground water entering the bay. A water table simulation model (DRAINMOD) was used at an additional site in NC to compute 40-year records of hourly water table fluctuations along a soil toposequence. The data were then related to percentages of redox depletions having chromas of 2 or less. The water budget showed that ground water comprised 35% of the total water input into the bay, indicating the site was functioning as a discharge area. Water table hydrographs were used to confirm the ground water inflow estimates as well as the estimate of potential evapotranspiration. The 40-year record of water table data obtained from DRAINMOD was summarized as the average number of times the soils at a given depth was saturated for 21 continuous days or longer. Historic rainfall data were selected from an area having the same rainfall distribution as found at the experimental site. The relationship between number of saturation events and percentage of redoximorphic features showed that some features were forming in soil horizons that saturated only four times within a 10-year period. These were not considered to be relict features because they formed during infrequent saturation events.

A subsurface drip irrigation (SDI) system was installed in 2001 in the Coastal Plain of North Carolina. Initially, four zones were installed, each with 0.91 m dripline spacing. In 2002, a fifth zone with 1.82 m dripline spacing was added. This system irrigated a cotton (Gossypium hirsutum L.) and peanut (Arachis hypogea L.) rotation on a Norfolk sandy loam soil. Seed cotton yield data was collected from 2001 to 2004. In addition to SDI, overhead sprinkler irrigation was applied to cotton plots from 2001 to 2003. This study was concurrent with another study that evaluated the effect of irrigation system type, cotton growth regulator (mepiquat chloride), herbicide (glyphosate) treatment, and planting date on lint yield and quality. Although the soil is classified as a sandy loam, water moved laterally to the midpoint of the 1.82 m spaced dripline; this was likely due to the pan layer found at about 0.3 m just below the dripline depth of 0.23 m. There was no difference in lateral water movement between the two dripline spacings. Seed cotton yield and irrigation water use efficiency was not statistically different between irrigation system type or dripline spacing over all years in the study. Seed cotton yield averaged 3.44 Mg ha-1 for the 0.91 m dripline spacing and 3.22 Mg ha-1 for the 1.82 m spacing for the three-year period 2002-2004 compared to an unirrigated average of 2.58 Mg ha-1 for the same period. Average irrigation water use efficiency was greater for the 0.91 m dripline spacing but not statistically different from the 1.82 m spacing. For 2001-2003, when sprinkler-irrigated plots existed, seed cotton yield averaged 3.55 Mg ha-1 for the 0.91 m dripline spacing, 3.35 Mg ha-1 for the sprinkler-irrigated plots, and 2.56 Mg ha-1 for the unirrigated plots. Drought conditions existed in 2002, when 258 mm of rain occurred between planting and final irrigation. The other growing seasons received relatively high amounts of rainfall: 524, 555, and 643 mm in 2001, 2003, and 2004, respectively.

Subsurface drainage, a water management practice used to remove excess water from poorly drained soils, can transport substantial amounts of NO3 from agricultural crop production systems to surface waters. A field study was conducted from the fall of 1986 through 1994 on a tile-drained Canisteo clay loam soil (fine-loamy, mixed, superactive, calcareous, mesic Typic Endoaquoll) to determine the influence of time of N application and use of nitrapyrin [NP; 2-chloro-6-(trichloromethyl) pyridine] on NO3 losses from a corn (Zea mays L.)-soybean [Glycine max (L.) Merr.] rotation. Four anhydrous ammonia treatments [fall N, fall N + NP, spring preplant N, and split N (40% preplant and 60% sidedress)] were replicated four times and applied at 150 kg N ha(-1) for corn on individual drainage plots. Sixty-two percent of the annual drainage and 69% of the annual NO3 loss occurred in April, May, and June. Flow-weighted NO3-N concentrations in the drainage water were two to three times greater in the two years following the three-year dry period compared with preceding and succeeding years. Nitrate N concentrations and losses in the drainage from corn were greatest for fall N with little difference among the other three N treatments. Nitrate losses from soybean were affected more by residual soil NO3 following corn than by the N treatments per se. Averaged across the four rotation cycles, flow-normalized NO3-N losses ranked in the order: fall N > split N > spring N = fall N + NP. Under these conditions NO3 losses from a corn-soybean rotation into subsurface drainage can be reduced by 13 to 18% by either applying N in the spring or using NP with late fall-applied ammonia.