Runoff Water Quality from Different Urban Agricultural Systems Using Common Nutrient Management Practices

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Leigh Whittinghill Department of Environmental Science and Forestry, The Connecticut Agricultural Experiment Station, New Haven, CT 06511, USA

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Major Ballard College of Agriculture, Community, and the Sciences, Kentucky State University, Frankfort, KY 40601, USA

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Anju Chaudhary College of Agriculture, Community, and the Sciences, Kentucky State University, Frankfort, KY 40601, USA

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Smriti Kandel College of Engineering, University of Texas Arlington, Arlington, TX 76019, USA

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Caitlin Mullins Kentucky Department of Environmental Protection, Frankfort, KY 40601, USA

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Pradip Poudel Department of Plant Science, Pennsylvania State University, State College, PA 16801, USA

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In recent decades, as global population has continued to increase, so has the demand for food (Ackerman et al. 2014; Opitz et al. 2016). This demand is only projected to rise as not only the population increases, but also the percentage of inhabitants in urban areas increases as well (Lin et al. 2015; Opitz et al. 2016). This situation has led to many communities experiencing food insecurity, primarily in urban areas throughout the globe (Ackerman et al. 2014; Lin et al. 2015). It has been widely documented that low-income and disadvantaged communities have less access to nutritionally dense foods, and these areas of reduced access are often called food deserts (Lin et al. 2015; Opitz et al. 2016). Food insecurity and food deserts are now among the most pressing issues in US cities (Meenar and Hoover 2012). To address this rise in food demand, especially for nutritionally adequate food, various forms of urban agriculture have risen in popularity. Additional motivations, such as the desire for locally grown food, the fact that culturally important foods may not be available in grocery stores, the need to reduce inconveniences related to supply chain issues such as those seen during the coronavirus disease 2019 pandemic, and the environmental and health benefits of urban agriculture, are also contributing to its growth (Gunia 2020; Kuta 2021; Lin et al. 2015; McDougall et al. 2019; McGril 2021; Mok et al. 2014; Van Tuijl et al. 2018).

Urban agriculture has many definitions, but can be described simply as the process of growing food crops, or ornamental and medicinal plants—and even raising livestock—within cities and towns (Goldstein et al. 2016; Lin et al. 2015; Opitz et al. 2016). Some of the more common types of urban agriculture include community gardens, backyard gardens, and rooftop gardens, which are also referred to as green roofs (Mok et al. 2014). Although hydroponic and other indoor systems are available, outdoor soil or soil-based media production methods remain among the most common forms of urban agriculture (Mok et al. 2014). Furthermore, controlled environment agriculture and vertical farming require a huge initial investment and energy, making these methods less sustainable and suitable for small-scale farmers in an urban setting than outdoor vegetable production such as raised beds or green roofs (Barbosa et al. 2015; McDougall et al. 2019). It was estimated that urban agriculture could fulfill ∼15% to 20% of the global food supply (Knizhnik 2012; Lin et al. 2015), reaching as high as 90% of local vegetable, egg, and milk needs, and 70% of poultry needs in some cities (Nugent 2002). Since the early 1990s, urban agriculture in the United States has grown by more than 30%, primarily in underserved communities (Lin et al. 2015). Urban agriculture could provide 7% to 8% of the current vegetable consumption in Oakland, CA, USA (McClintock et al. 2013) and 15% of the food supply in Sydney, Australia (McDougall et al. 2020), when unoccupied urban land areas are used for food production.

Urban agriculture has also gained popularity in the past two decades because of greater public awareness and concern for carbon footprints. Environmental benefits of urban agriculture include supporting native biodiversity by providing food and habitat resources, mitigating air pollution and urban heat island effects, providing stormwater management, and lowering energy use required for food transport (Ackerman et al. 2014; Lin et al. 2015; Mok et al. 2014). Benefits of urban agriculture can also include community building, mitigation of childhood obesity and malnutrition, improved mental and physical health, and educational benefits to students (Bahamonde 2019; Colman 2017; Ghose and Pettygrove 2014; Lin et al. 2015; Meenar and Hoover 2012; Monroe 2015; Nogeire-McRae et al. 2018; Ohly et al. 2016; van Averbeke 2007). In particular, creating urban farms in low-income communities can revitalize these communities by promoting social cohesion and improving economic well-being (Angotti 2015).

Benefits of urban agriculture to the environment have been widely documented; however, there is also the potential for some negative effects associated with the increased practice of urban agriculture. One of the most significant environmental concerns with any agricultural system is the transport of excess nutrients and other agriculture-associated contaminants into waterways (Berka et al. 2001; Hart et al. 2004; King and Torbert 2007; Kleinman et al. 2011). The use of conventional or manufactured fertilizer has been attributed to increased rates of nutrient runoff, especially when applied before periods of increased precipitation (King and Torbert 2007). The same applies to outdoor urban agriculture (Bachman et al. 2016; Lusk et al. 2020), especially in areas where management is switching from no or low fertilizer use to greater fertilizer use for crop production (Bachman et al. 2016; Janke et al. 2017; Spence et al. 2012), and in areas such as parking lots that lack surrounding vegetation (Hale et al. 2015; Shetty et al. 2019). In addition, the use and overuse of nutrient sources has been shown to contribute to nutrient runoff from both green roofs (Czemiel Berndtsson 2010; Mitchell et al. 2017; Toland et al. 2012) and ground-level systems (Cameira et al. 2014; Dewaelheyns et al. 2013; Huang et al. 2006; Salomon et al. 2020; Shrestha et al. 2020; Small et al. 2019; Wielemaker et al. 2018, 2019). These substances can alter and affect the water quality of runoff negatively, which can lead to the impairment or degradation of nearby aquatic systems as well as potential health hazards (Berndtsson et al. 2009).

Nitrogen (N) and phosphorus (P) are the nutrients commonly found in fertilizers most associated with increased aquatic plant or algal growth and eutrophication risks (Anderson et al. 2002; Conley et al. 2009; Correll 1998; Smith and Schindler 2009). Nitrogen, which supports protein synthesis, and P, which is needed for DNA, RNA, and energy transfer, are needed by both terrestrial and aquatic plants (Conley et al. 2009). In excess, however, the presence of N and P can accelerate the growth of aquatic plants and harmful cyanobacteria (Conley et al. 2009). Anthropogenic eutrophication and dead zones are the number-one problem facing aquatic ecosystems globally, and can affect all types of aquatic systems (Kleinman et al. 2011; Smith and Schindler 2009). Nitrogen in reactive forms such as ammonium (NH4+) and nitrate (NH3) can cause soil acidification if excess fertilizer is applied, which can lead to leaching of aluminum and other toxic metals into waterways (Chadwick and Chen 2002).

Important physicochemical properties of water, such as pH, electrical conductivity, color, and turbidity, help to explain the quality of runoff water and its possible effect on aquatic life cycles (Rameshkumar et al. 2019; Whittinghill et al. 2016). Use of different growing media, sources of fertilizer, and crop management practices may have an effect on these criteria. A pH that is too high or too low can kill many aquatic species, affect hatching and survival rates, and stress the entire aquatic animal system (Freda 1987). Most aquatic animals prefer a pH of 6 to 9 (Collier et al. 1990). Changing pH levels (high or low) may also facilitate the solubilization of numerous harmful heavy metals, hence increasing the risk of absorption by aquatic organisms (Gensemer et al. 2018). Electrical conductivity is a measure of the salinity of water. Increasing the salt level in freshwater aquatic systems may increase the cost of water treatments for human consumption, reduce freshwater diversity, alter ecosystem function, and, ultimately, affect socioeconomic well-being by altering the goods and services of the freshwater aquatic system (Cañedo-Argüelles et al. 2016). Water color, measured on the platinum/cobalt (Pt/Co) scale, is usually used to analyze the pollution level in wastewater. Water with a yellow tint has more watercolor on the Pt/Co scale and is considered more polluted. In general, such color in water is a result of the humic and fulvic fractions of dissolved organic compounds (Bennett and Drikas 1993). Turbidity is a water-quality parameter that measures the optical clarity of water (Davies-Colley and Smith 2001). Increased turbidity means less solar radiation penetration. High turbidity influences aquatic life through a reduction in photosynthesis and dissolved oxygen, affects movement resulting from poor visualization, and kills fish directly or reduces their growth (Sader 2017). Turbidity could also be a good factor to predict aquatic life diversity and richness (Figueroa-Pico et al. 2020).

There has been extensive research over many decades on the effects of conventional farming practices on excess nutrient input and pesticide contamination, and the associated impacts of these contaminants on the water quality of various aquatic ecosystems (Berka et al. 2001; Elrashidi et al. 2005; Gaudreau et al. 2002; Hart et al. 2004; Heathwaite et al. 1998; King and Torbert 2007; Kleinman et al. 2011; Liu et al. 2014; McLeod and Hegg 1984). Until recently, there was a lack of research on monitoring these same effects from commonly used urban agricultural systems at ground level. Research has focused more on the use of green roof systems as opposed to soil-based urban agriculture systems used at ground level (Beck et al. 2011; Czemiel Berndtsson 2010; Emilsson et al. 2007; Getter and Rowe 2006; Kok et al. 2013; Toland et al. 2012; Whittinghill et al. 2016). At ground-level urban sites, where use of soil fertility testing and nutrient application recordkeeping can be limited (Small et al. 2019; Whittinghill and Sarr, 2021; Wielemaker et al. 2019; Witzling et al. 2011), overapplication of nutrients is especially common. This has been tied to nutrient buildup in the soil (Abdulkadir et al. 2013; Cameira et al. 2014; de Barros Sylvestre et al. 2019; Dewaelheyns et al. 2013; Huang et al. 2006; Salomon et al. 2020; Shrestha et al. 2020; Small et al. 2019; Witzling et al. 2011) and an increase in the nutrient concentration of runoff water (Huang et al. 2006; Jackson et al. 1994; Shrestha et al. 2020). Excessive nutrient losses can also be attributed to a preference for compost as a nutrient source (Cameira et al. 2014; Dewaelheyns et al. 2013; Metson and Bennett 2015; Small et al. 2019; Wielemaker et al. 2019); the lower fertilizer nutrient equivalencies for composts the year of application, with continued nutrient release in subsequent years; and a difference in the availability of nutrients from compost (Maltris-Landry et al. 2016; Mikkelsen and Hartz 2008; Wielemaker et al. 2019). It has been suggested that these nutrient inefficiencies in urban agriculture could represent a significant component of the global P budget, if urban agriculture were scaled up to its full potential (Small et al. 2019). It is, therefore, imperative to understand more fully the effects of nutrient runoff from ground-level urban agriculture systems on water quality. Our research compared water-quality variables from four different nutrient sources applied to raised beds and container gardens.

The container gardens used in this experiment were constructed from small plastic wading pools. This growing system has been used on rooftops (Hell’s Kitchen Farm Project 2020) and has received increased social media attention (Michaels 2021; Pinterest 2021). These small plastic pools are readily available during the growing season and can be purchased at a fairly low cost. When comparing cost per area, small plastic pools cost about $12 for 1 m2 of planting area, compared with almost $70 for raised beds with sides (Durham et al. 2018), ∼$40 to $80 for nursery pots (Hummert International 2021), and as much as $127 for other commercially available planters (Lowe’s 2021). This makes the pool growing system a low-cost option suitable for urban areas without soil or where soil is contaminated and considered unsafe for growing. However, this growing system has received very little scientific attention, especially in terms of how it may affect yields and nutrient leaching when compared with raised beds and other in-ground production systems. Including the small plastic pool growing system in our research is a first step in addressing this knowledge gap.

Materials and Methods

Data collection for this study began in 2018 and continued into 2019 at the Harold R. Benson Research and Demonstration Farm in Frankfort, KY, USA, using two different ground-level production systems that are commonly used for urban agriculture: raised beds and containers. For the construction of these systems, all the materials were purchased from Lowe’s Co., Inc. (Mooresville, NC, USA). All lumber used was pressure-treated with EcolifeTM (Viance, LLC, Charlotte, NC, USA). The raised beds and containers were constructed in May 2018 over a 156.1-m2 area and treated with one of four different fertilizer treatments. Both the raised beds and containers were elevated 0.6 m off the ground on 1.22- × 1.22-m platforms. The upright supports were constructed using 10.16- × 10.16-cm lumber. The deck of the platform was constructed with 5.08- × 10.16-cm lumber for the frame and two joists, then was topped with severe-weather common, square southern yellow pine plywood sheeting. Sixteen of these elevated platforms were topped with raised beds; the remaining 16 were topped with containers. Both raised beds and pool containers were fitted with gutters and downspouts connected to a 7.6-L bucket (Fig. 1).

Fig. 1.
Fig. 1.

The gutter and downspout with bucket attachment for water collection pictured on a raised-bed platform.

Citation: HortScience 58, 8; 10.21273/HORTSCI17215-23

The raised beds measured 1.22 × 1.22 m, with a depth of 30.48 cm, and were made using 5.08- × 10.16-cm and 5.08- × 15.24-cm lumber. They were then lined with black Smartpond® nylon mesh pond liner (West Palm Beach, FL, USA) to act as a barrier, then filled to a depth of 20.32 cm with premium shredded topsoil (Table 1). To collect runoff from the raised beds and avoid losing soil, a 5.08-cm gap covered with Phifer Super Solar charcoal fiberglass replacement screen (Phifer, Inc., Tuscaloosa, AL, USA) was left in the front of each bed. Covered gutters were then attached to the front of each bed at this gap.

Table 1.

Analysis results of the premium shredded topsoil as provided by the University of Kentucky Soil Testing Laboratory.

Table 1.

Blue, plastic, round wading/kiddie pools (Summer Waves, purchased at Lowe’s, Mooresville, NC, USA) were used for the container plots. These pools measured 114 cm in both length and width, and were filled to a depth of 17.78 cm with premium shredded topsoil (Table 1), which was the maximum amount of soil these containers could hold. To allow for water drainage, two 1.27-cm holes were drilled at the front of each pool, even with the bottom of the pool. The holes were attached to gutters using Eastman 1.27-cm polyvinylchloride clear vinyl tubing (Eastman Chemical Co., Kingsport, TN, USA). To improve drainage after installation, a small amount of Rooflite® drain media wrapped in Rooflite® separation fabric (Skyland, LLC, Landenberg, PA, USA) was added to each plot over the drainage holes.

Following a randomized complete block design with modifications to reduce edge effects, which was necessary because of varying topography and shading within the study area, four fertilizer treatments were replicated four times in each of the two systems. The four fertilizer types used were conventional (10N–10P–10K Twin Pines® All Purpose Fertilizer, Know, IN, USA), organic (Espoma® 3N–4P–6K Tomato Tone, 12N–0P–0K Blood Meal, and 4N–12P–0K Bone Meal, Milleville, NJ, USA), 14.42 kg/m2 compost (0.1N–0.1P–0.1K; Michigan Peat Garden Magic® Compost and Manure, Houston, TX, USA), and 7.21 kg/m2 compost + organic fertilizer (0.1N–0.1P–0.1K; Michigan Peat Garden Magic® Compost and Manure, and Espoma® 3N–4P–6K Tomato Tone and 12N–0P–0K Blood Meal). The fertilizers and compost used are readily available to urban farmers and growers in the region. The target nutrient application rates for each of these fertilizer treatments were 19.61 g/m2 N, 16 g/m2 phosphorus pentoxide, and 16 g/m2 potassium oxide, as recommended for greens by the College of Agricultural and Environmental Sciences at the University of Georgia (Athens, GA, USA). The actual nutrients supplied by each treatment are listed in Table 2. The conventional fertilizer treatment was applied to supply the recommended amount of N. The organic fertilizer treatment used the three listed fertilizers to supply the recommended amounts of all three nutrients. The nutrient contributions of the low-compost treatment were estimated to be 6.59 g/m2 N, and 7.21 g/m2 P and potassium (K) based on the listed product nutrient content, so small amounts of all three organic fertilizers were used to supply the remaining nutrients to meet the full nutrient recommendation. The compost-only treatment was estimated to supply 14.42 g/m2 P and K in the first year after application, based on the listed product nutrient content. Fertilizer was applied before each planting, whereas compost was applied at the beginning of each growing season (Table 3).

Table 2.

Nutrients added by compost at the beginning of the growing season and by fertilizers with each planting in each nutrient management treatment.

Table 2.
Table 3.

The nutrient management, planting, and harvesting timeline with calendar dates and days after compost addition for the 2 years of the study for both the container and raised-bed growing systems.

Table 3.

Crops planted included seven types of greens, which were planted in succession in each plot of every treatment: Lactuca sativa (Encore lettuce mix), Eruca sativa (Astro arugula), Brassica rapa (Mizuna Asian greens), Brassica juncea (Red giant mustard greens), Beta vulgaris (Fordhook giant Swiss chard), Brassica napus (Red Russian kale), and Spinacia oleracea (Covair spinach). Some of the plants listed were grown in 2018 but not 2019, or vice versa (Table 3). Planting started later than expected in 2018 because of plot construction, so lettuce was not planted, and the arugula crop was planted later than expected. In 2019, Swiss chard was added during the warmest part of the summer because of its greater heat tolerance. A drought was also experienced in Aug, Sep, and Oct 2019, which slowed crop growth, so spinach was not planted. The same planting density, 386 plants/m2, was used for each crop in all treatments. This planting density was derived from a variety of sources, including local Extension recommendations, other Extension recommendations for the production of baby greens, and the Johnny’s Selected Seed website (https://www.johnnyseeds.com). Plants were irrigated with drip irrigation to supply 2.5 cm of water per week, including rain.

Runoff samples were collected from each plot once a month, weather permitting, from Jul 2018 through Feb 2020. Water-quality analysis was not performed for 4 separate months during the study period: Dec 2018, and Mar, Sep, and Nov 2019. No water was collected during these months because there was either no rain (Sep 2019) or insufficient rain, or larger rainstorms occurred when samples could not be collected. When storms early in the month did not result in enough runoff water, further attempts were made to collect water later in the month. Samples of 250 mL each were collected from each plot with a functional gutter and downspout, and were transported to Kentucky State University’s Aquaculture Research Center for laboratory analysis. The pH values were measured using a FisherbrandTM Accumet™ AP110 Meter Kit (Thermo Fisher Scientific, Inc., Waltham, MA, USA). Conductivity values were acquired using an Oakton® Con 6+ Meter Kit (Vernon Hills, IL, USA). Color was analyzed using a LaMotte® Smart3 Colorimeter (Lamotte Co., Chestertown, MD, USA), and turbidity was measured using a LaMotte® 2020 we turbidity meter. Nitrate-N, NH4+-N, total P, and K were analyzed using Hach water-quality testing protocols and a Hach® DR600 Spectrophotometer (Hach, Loveland, CO, USA). Before nutrient analysis, samples were filtered according to vacuum filtration techniques and using grade 40 Whatman® paper filters (Global Life Sciences Solutions USA, LLC, Marlborough, MA, USA), which were 4.7 cm in diameter.

Occasional issues with downspout or collection bucket failure occurred and resulted in lower than necessary water collection volumes. In these cases, either no analysis was performed or some of the analyses were performed and were chosen based on water volume requirements to maximize the number of analyses that could be performed. Water collection system failures increased in the second study year as downspouts aged. Laboratory equipment failure resulted in the inability to test accurately for K in runoff samples from most container plots in Sep 2018. Nitrate-N could not be tested for any plots in Jul 2019 because the laboratory was shorthanded and samples needed to be stored for longer than recommended for that analysis. This, combined with occasional downspout failure or low runoff volume, resulted in missing data points for some of the plots in each growing system and each fertilizer treatment at least once. Because sampling took place on different days after compost addition (DAC) in study years 1 and 2, comparisons between years were limited to samplings that took place within 7 d of each other when there was a significant interaction between DAC and study year, and the study year main effect as appropriate. There were four pairs of sampling dates that were within 7 d of each other: 61 and 67, 145 and 152, 184 and 186, and 281 and 286 (Table 4). Average air temperature and total precipitation data were obtained from the Franklin County MESONET weather station located at the Harold R. Benson Research and Demonstration Farm, 250 m from the experimental site. Climatic normal air temperature and precipitation data based on a time period from 1981 to 2010 were obtained from the National Oceanographic and Atmospheric Administration National Climate Data Center (2020) for the weather station at the Capital City Airport in Frankfort, KY, USA.

Table 4.

Water sampling dates and their corresponding days after compost addition for the 2 years of the study.

Table 4.

Statistical analysis was performed in R (version 1.2.5001; R Foundation for Statistical Computing, Vienna, Austria). Data that did not conform to a normal distribution were transformed using cube root (conductivity), log10 (color, K) and inverse (turbidity, NO3-N, NH4+−N, P) transformations. Type II sum of squares analysis of variance with repeated measures was performed for each water-quality variable, with growing system, fertilizer treatment, days from compost addition, and study year as factors with interactions. Post hoc testing was performed using least square means, with an alpha level of 0.05. Means presented are untransformed mean values.

Results

Weather data.

In total, 1341 mm of rainfall occurred during the study period in 2018 and 1483 mm in 2019. Precipitation during the study period in 2018 was greatest in August (236 mm) and lowest in June (135 mm) (Fig. 2A). Precipitation in 2018 was more than the climatological normal during all months of the study period. In 2019, October had the greatest rainfall, with a total of 232 mm, which was 16% of the annual total. July, August, and September received lower than normal rainfall in 2019, with just less than 76 mm total monthly rainfall for July and August. There was a drought in Kentucky in 2019 from the last week of August to early October. There were only 10 mm of precipitation between 28 Aug and 6 Oct. Temperature patterns in 2018 and 2019 were similar to each other and to the climatological normal temperatures (Fig. 2A).

Fig. 2.
Fig. 2.

(A) Monthly total precipitation and average temperature for the period of study between May 2018 and December 2019, and the 30-year (1981–2010) climatological normal (National Oceanic and Atmospheric Administration, National Climate Data Center 2020). (B) Total precipitation between sampling times for the first (2018) and second (2019) years of the study, where d: is the number of days between that sampling and the previous sampling.

Citation: HortScience 58, 8; 10.21273/HORTSCI17215-23

Physical and chemical characteristics.

Model simplification was performed to remove nonsignificant interactions with an alpha level of 0.05. All three-way interactions were not significant for pH, conductivity, color, and turbidity (Supplemental Table S1). All two-way interactions were also not significant for pH, color, and turbidity (Supplemental Table S1). Only significant interactions and main effects are discussed further.

The conventional fertilizer plots had the least runoff pH (7.51 ± 0.04), but were only significantly less than the compost-only plots (7.67 ± 0.04) (Fig. 3A). There were significant differences in runoff pH across sampling times (Fig. 3B), with a slight increase from the start of the experiment to 131 DAC, followed by a slight decrease to the end of the study year. Runoff water pH was least at 286 DAC (7.11 ± 0.04) and 328 DAC (7.12 ± 0.10), and greatest at 131 DAC (8.19 ± 0.03). There were significant differences between the first and second study year for two of the four pairs of sampling dates: 61 and 67 DAC (7.99 ± 0.06 vs. 7.67 ± 0.07), and 281 and 286 DAC (7.62 ± 0.04 vs. 7.10 ± 0.04). In both cases, the first study year was significantly greater than the second study year. The runoff collected from the container system had significantly lower pH values (mean ± SE, 7.53 ± 0.03) in comparison with the runoff collected from the raised-bed system (7.62 ± 0.03) (Fig. 3C).

Fig. 3.
Fig. 3.

The pH of runoff water for each (A) nutrient management treatment, (B) sampling time in days after compost addition for study years 1 and 2, and (C) growing system. US Environmental Protection Agency (2022a) freshwater minimum and human health maximum pH (US Environmental Protection Agency 2022b) thresholds are included as solid and dashed lines, respectively. Letters denote significant differences between growing systems, among nutrient management treatments, or among sampling times. Max = maximum; Min = minimum.

Citation: HortScience 58, 8; 10.21273/HORTSCI17215-23

There were no significant differences among fertilizer treatments in the second year of the study, but in the first year of the study, conductivity was greatest in runoff from the conventional fertilizer treatment (608 ± 73 μS/cm), but was only significantly greater than the compost-only treatment (277 ± 26 μS/cm) (Fig. 4A). Conductivity differed significantly by sampling time (Fig. 4B). During the first study year, conductivity was significantly greater during the growing season (61, 84, 131, and 152 DAC) than during the winter months. During the first study year, this pattern was not as visible, when conductivity was greater than the winter months only for the first (4 DAC) and third (67 DAC) samplings. Runoff water conductivity was greater in the first year of the study than the second year of the study in both growing systems when averaged across nutrient management treatment and sampling time (Fig. 4C), in all nutrient management treatments when averaged across growing system and sampling time (Fig. 4A), and for all four pairs of sampling dates when averaged across growing system and nutrient management treatment (Fig. 4B). In the first year of the study, the raised beds (539 ± 42 μS/cm) had significantly greater conductivity than the container plots (350 ± 33 μS/cm), but not during the second year of the study (217 ± 28 and 162 ± 23 μS/cm, respectively) (Fig. 4C).

Fig. 4.
Fig. 4.

The conductivity of runoff water for each (A) nutrient management treatment, (B) sampling time in days after compost addition for study years 1 and 2, and (C) growing system. Letters denote significant differences among means. Uppercase letters denote differences between growing systems and among nutrient management treatments within study year; lowercase letters denote significant differences between study years within growing system and nutrient management treatment.

Citation: HortScience 58, 8; 10.21273/HORTSCI17215-23

There was no significant difference in color among the nutrient management treatments (Fig. 5A). There were significant differences among sampling times for color, with a slight decrease in color with time from compost addition (Fig. 5B), but color was greatest in runoff from the conventional fertilizer treatment (742 ± 114 Pt/Co) and least in the compost-only treatment (453 ± 56 Pt/Co). The greatest color was seen at 44, 55, 84, and 281 DAC (1739 ± 329, 1585 ± 293, 1022 ± 79, and 1684 ± 197 Pt/Co, respectively), which were all significantly greater than the least color seen at 145, 243, 286, and 328 DAC (83 ± 18, 126 ± 40, 75 ± 18, and 144 ± 38 Pt/Co, respectively). The only pair of sampling dates that had color significantly different between the 2 study years was 281 and 286 DAC, for which study year 1 was significantly greater than study year 2 (Fig. 5B). Runoff water color was significantly greater from the raised beds (645 ± 66 Pt/Co) than from the containers (464 ± >53 Pt/Co) (Fig. 5C).

Fig. 5.
Fig. 5.

The color of runoff water for each (A) nutrient management treatment, (B) sampling time in days after compost addition for study years 1 and 2, and (C) growing system. US Environmental Protection Agency (1986) domestic water supply maximum thresholds are included as dashed lines. Letters denote significant differences between growing systems, among nutrient management treatments, or among sampling times. Max = maximum; PtCo = platinum/cobalt scale.

Citation: HortScience 58, 8; 10.21273/HORTSCI17215-23

Turbidity of runoff water from the conventional fertilizer treatment [31 ± 5 nephelometric turbidity unit (NTU)] was significantly greater than the organic fertilizer treatment (17 ± 3 NTU), but there were no other significant differences among nutrient management treatments (Fig. 6A). Turbidity followed the same pattern as color over time, with the greatest samples at 44, 55, 84, 253, and 281 DAC (50 ± 9, 40 ± 7, 23 ± 2, 42 ± 9, and 91 ± 11 NTU, respectively), and the lowest at 145 DAC (1 ± 0), followed closely by 243 DAC (6 ± 3 NTU) (Fig. 6B). Three out of four paired sampling dates had significant differences between study years: 145 and 152, 184 and 186, 281 and 286. For all three, the samples from year 1 had greater turbidity than the samples from year 2 (Fig. 6C). Turbidity of runoff water from the raised beds (23 ± 2 NTU) was significantly greater than that of the containers (17 ± 2 NTU) (Fig. 6C).

Fig. 6.
Fig. 6.

The turbidity of runoff water for each (A) nutrient management treatment, (B) sampling time in days after compost addition for study years 1 and 2, and (C) growing system. Letters denote significant differences between growing systems, among nutrient management treatments, or among sampling times. NTU = nephelometric turbidity unit.

Citation: HortScience 58, 8; 10.21273/HORTSCI17215-23

Macronutrients.

Model simplification was performed to remove nonsignificant interactions with an alpha level of 0.5. All three-way interactions were not significant for NO3-N, NO4+-N, and K (Supplemental Table S2). The three-way interaction between growing system, nutrient management treatment, and study year was significant for P (Supplemental Table S2). The only significant two-way interaction for NO4+ and P was between nutrient management treatment and sampling time, and the only significant two-way interaction for K was between growing system and nutrient management treatment (Supplemental Table S2). Only significant interactions and main effects are discussed further.

Within the container plots averaged across study year and sample time, the compost + organic fertilizer treatment had the greatest NO3 content (17.98 ± 8.40 mg/L). That treatment and the organic fertilizer treatment (17.75 ± 7.22 mg/L) were significantly greater than the compost-only treatment (4.72 ± 1.84 mg/L), but not greater than the conventional fertilizer treatment (13.83 ± 6.98 mg/L) (Fig. 7). There were no significant differences among nutrient management treatments within the raised-bed plots averaged across study year and sample time (Fig. 7) or within either study year when averaged across growing system and sample time (Fig. 8). There were significant differences in runoff NO3 concentrations among sampling times when averaged over growing systems and nutrient management treatment (Fig. 9). The average NO3 concentration was greatest 67 DAC (52.48 ± 21.45 mg/L), but was not significantly greater than 61, 84, 131, 152, 184, and 328 DAC. The average NO3 concentration was the least 286 DAC (0.09 ± 3.55 mg/L) and was significantly less than all other sampling times. In general, NO3 concentrations were greatest during the growing season. The NO3 content of study year 1 was significantly greater than study year 2 in the conventional fertilizer treatment (28.54 ± 5.39 vs. 25.44 ± 12.61 mg/L) and compost + organic fertilizer treatment (18.44 ± 3.89 vs.15.63 ± 5.65 mg/L) (Fig. 8). Two of four paired sampling dates had significant differences between study years: 145 and 152, and 281 and 286 (Fig. 8). For the first pair, study year 1 was significantly less than study year 2; for the second pair, study year 1 was significantly less. There was only a significant difference between NO3 content of runoff from the container and raised-bed growing systems within the compost-only treatment when averaged over study year and sample time, for which the raised beds (10.29 ± 2.45 mg/L) were significantly greater than the container plots (4.72 ± 1.84 mg/L) (Fig. 7).

Fig. 7.
Fig. 7.

Nitrate-nitrogen concentration from runoff from each growing system and nutrient management treatment combination averaged across sampling times and study years for (A) the entire range of the data and (B) the range containing the majority of the observations. Letters denote significant differences among means. Uppercase letters denote differences among nutrient management treatments within growing systems; lowercase letters denote significant differences between growing systems within nutrient management treatment. US Environmental Protection Agency (2022b) drinking water maximum and national pollutant discharge elimination system stormwater discharge (US Environmental Protection Agency 2015) thresholds are included as solid and dashed lines, respectively. Max = maximum.

Citation: HortScience 58, 8; 10.21273/HORTSCI17215-23

Fig. 8.
Fig. 8.

Nitrate-nitrogen concentration from runoff from each nutrient management treatment and study year combination averaged across growing systems and sampling times for (A) the entire range of the data and (B) the range containing the majority of the observations. Letters denote significant differences among means. Uppercase letters denote differences among nutrient management treatments within growing systems; lowercase letters denote significant differences between growing systems within nutrient management treatment. US Environmental Protection Agency (2022b) drinking water maximum and national pollutant discharge elimination system stormwater discharges maximum (US Environmental Protection Agency 2015) thresholds are included as solid and dashed lines, respectively. Max = maximum.

Citation: HortScience 58, 8; 10.21273/HORTSCI17215-23

Fig. 9.
Fig. 9.

Nitrate-nitrogen concentrations from each sampling time in days after compost addition for study years 1 and 2 for (A) the entire range of the data and (B) the range containing the majority of the observations. Letters denote significant differences among means. US Environmental Protection Agency (2022b) drinking water maximum and national pollutant discharge elimination system stormwater discharges maximum (US Environmental Protection Agency 2015) thresholds are included as solid and dashed lines, respectively. Max = maximum.

Citation: HortScience 58, 8; 10.21273/HORTSCI17215-23

There were no significant differences among fertilizer treatments for most sampling times, except 61, 84, and 186 DAC (Fig. 10A–D). In all three cases, the conventional fertilizer treatment had the greatest average NO4 concentration. At 61 DAC, the conventional fertilizer treatment (13.04 ± 6.97 mg/L) was significantly greater than the organic fertilizer (1.71 ± 1.08 mg/L) and compost-only (0.36 ± 0.24 mg/L) treatments, but not the compost + organic fertilizer treatment (1.14 ± 0.29 mg/L). At 84 DAC, the conventional fertilizer treatment (2.79 ± 0.37 mg/L) was significantly greater than all other treatments, which were not significantly different from each other (0.46 ± 0.12, 0.19 ± 0.06, and 0.16 ± 0.04 mg/L, respectively, for the organic fertilizer, compost + organic fertilizer, and compost-only treatments). At 186 DAC, the conventional fertilizer treatment (6.78 ± 3.72 mg/L) was only significantly greater than the compost-only treatment (0.08 ± 0.02 mg/L). Although there are significant differences among sampling times within all four nutrient management treatments, there are no clear patterns of change over time (Fig. 10A–D). Two of four paired sampling dates had significant differences between study years—61 and 67 DAC, and 184 and 186 DAC—but not within all nutrient management treatments (Fig. 10B–E). For the conventional and organic fertilizer treatments, there is an increase in variability with the onset of the planting season and fertilizer applications (Fig. 10A and B). For all nutrient management treatments, there is a spike in runoff concentrations of NO4+ after the final harvest. This takes place at 186 and 243 DAC for the conventional fertilizer treatment, and 243 DAC for the remaining nutrient management treatments (Fig. 10A–D). For all treatments except the conventional fertilizer treatment, the NO4+ concentrations at 243 DAC were significantly greater than at any other sampling time. When there was a significant difference, runoff from study year 1 had significantly lower NO4 concentrations than study year 2. Growing system had no effect on NO4+ in runoff (F = 1.907, P = 0.177). The distribution of NO4+ runoff in the two growing systems is shown in Fig. 10E.

Fig. 10.
Fig. 10.

Distribution of mean values of ammonia from runoff from each sampling time in days after compost addition for study years 1 and 2 for the (A) conventional fertilizer, (B) organic fertilizer, (C) low-compost + organic fertilizer, and (D) compost-only nutrient management treatments, and (E) the two growing systems (containers and raised beds). US Environmental Protection Agency (2013) acute and chronic exposure thresholds are included as solid and dashed lines, respectively. Letters and asterisks denote significant differences among means. Uppercase letters denote differences among nutrient management treatments within sampling times; lowercase letters denote differences among sampling times within nutrient management treatment. Asterisks denote significant differences between study years within nutrient management treatment for paired sampling dates, with two asterisks indicating the lower mean.

Citation: HortScience 58, 8; 10.21273/HORTSCI17215-23

There were few differences among fertilizer treatments within study year and growing system. In general, the conventional fertilizer treatment had the greatest runoff water P concentrations of all nutrient management treatments. The conventional fertilizer treatment was significantly greater than all other nutrient management treatments (range, 0.061 ± 0.07 to 0.70 ± 0.16 and 0.47 ± 0.07 to 0.68 ± 0.13 mg/L, respectively) in the containers in study year 1 and the raised beds in study year 2 (2.37 ± 0.37 and 3.36 ± 0.76 mg/L, respectively) (Fig. 11). For the raised beds in study year 1, the conventional fertilizer treatment (2.39 ± 0.75 mg/L) was only significantly greater than the organic fertilizer and compost-only treatments (0.62 ± 0.13 and 0.89 ± 0.24 mg/L, respectively). At 61 DAC, the conventional fertilizer treatment (6.28 ± 2.27 mg/L) was significantly greater than the organic fertilizer treatment (0.70 ± 0.28 mg/L) (Fig. 12). At 67 and 281 DAC, the conventional fertilizer treatment (1.88 ± 0.49 and 2.59 ± 0.49 mg/L, respectively) was significantly greater than the conventional fertilizer treatment (0.30 ± 0.08 and 0.40 ± 0.08 mg/L, respectively) (Fig. 12). No other significant differences among nutrient management treatments were found. There are no significant differences in runoff P content over time for the organic fertilizer treatment (Fig. 12B). For the conventional fertilizer and compost + organic fertilizer treatments, there were two peaks in runoff content: at 61 and 84 DAC, respectively, and at 186 and 281 DAC, respectively (Fig. 12A and C). The compost-only treatment appears to have only the first peak at 84 DAC, with lower and consistent P levels after 131 DAC (Fig. 12D). There was a significant difference between study years for the conventional fertilizer treatment in container plots, where the first study year was significantly greater than the second (Fig. 11). There were no other significant differences in runoff P concentration between study years within any other nutrient management treatment–growing system combination or for any paired sampling times (Fig. 12). No significant differences in P were found between growing systems within any nutrient management treatment in the first study year, and there was only a significant difference between growing systems for the conventional fertilizer treatment in the second study year (Fig. 11). In this case, the raised bed had greater runoff water P concentration than the container.

Fig. 11.
Fig. 11.

Distribution of phosphorous concentrations from runoff from four nutrient management strategies within each growing system for study years (A) 1 and (B) 2. Letters and asterisks denote significant differences among means. Uppercase letters denote differences between growing systems within nutrient management treatments; lowercase letters denote differences among nutrient management treatments within growing system. Asterisks denote significant differences between study years within nutrient management treatment and growing system, with two asterisks indicating the lower mean. US Environmental Protection Agency (2015) stormwater discharge maximum, and threshold to prevent the development of biological nuisances and to control eutrophication (US Environmental Protection Agency 1986) are included as solid and dashed lines, respectively.

Citation: HortScience 58, 8; 10.21273/HORTSCI17215-23

Fig. 12.
Fig. 12.

Distribution of phosphorous concentrations from runoff for each sampling time in days after compost addition for the (A) conventional fertilizer, (B) organic fertilizer, (C) compost + organic fertilizer, and (D) compost-only nutrient management treatments. Letters denote significant differences among means. Uppercase letters denote differences among nutrient management treatments within sampling time; lowercase letters denote differences among sampling times within nutrient management treatments. US Environmental Protection Agency (2015) stormwater discharge maximum, and threshold to prevent the development of biological nuisances and to control eutrophication (US Environmental Protection Agency 1986) are included as solid and dashed lines, respectively.

Citation: HortScience 58, 8; 10.21273/HORTSCI17215-23

Within the raised beds, the conventional fertilizer treatment also had the greatest K in runoff of all nutrient management treatments (Fig. 13A). It was significantly greater than the compost + organic fertilizer (21.1 ± 2.5 mg/L) and compost-only treatments (17.0 ± 2.7 mg/L), but not the organic fertilizer treatment (32.3 ± 5.4 mg/L). There were no significant differences among nutrient management treatments within the container system (range, 12.6 ± 2.1 to 28.7 ± 6.8 mg/L). There were significant differences among sampling times, with greater average K and greater variability in K in runoff and during the growing season (Fig. 13B). Runoff K was greatest at 84 DAC (65.2 ± 5.3 mg/L) and least at 248 DAC (4.0 ± 1.8 mg/L). There was a significant difference between study years for one pair of sampling dates: 145 and 152 DAC. Runoff K at 152 DAC (study year 1) (51.2 ± 7.1 mg/L) was among the greatest of all sampling dates, and 145 DAC (study year 2) (27.8 ± 17.1 mg/L) was significantly less (Fig. 13B). There was only a significant difference in K in runoff between container plots and raised-bed systems in the conventional fertilizer treatment, where K in runoff from the raised bed (69.6 ± 12.6 mg/L) was significantly greater than the container plots (28.7 ± 6.8 mg/L) (Fig. 13A).

Fig. 13.
Fig. 13.

Distribution of potassium concentration from runoff from (A) each growing system and nutrient management treatment combination, and (B) each sampling time in days after compost addition. Letters denote significant differences among means. Lowercase letters denote differences among nutrient management treatments within growing system (A) or among sampling times (B). Uppercase letters denote differences between growing systems within nutrient management treatment (A) or study years for pairs’ sampling dates (B).

Citation: HortScience 58, 8; 10.21273/HORTSCI17215-23

Discussion

Nutrient management treatment.

The small difference between the pH of runoff water from the different treatments (7.51 vs. 7.67) and a lack of difference in the proportion of samples from any fertilizer treatment that do not meet the US Environmental Protection Agency pH water-quality standards for freshwater (US Environmental Protection Agency 2022a) and human health (US Environmental Protection Agency 2022b) (χ2 = 0.279, P = 0.965) suggest that the statistically significant difference (Fig. 3B) is not meaningful from a water-quality standpoint. Variability among the samples may be obscuring the patterns seen in other studies. Applications of manure-based composts increase the pH of soils (Adugna 2018; Beochat et al. 2013; Bowden et al. 2007; Giannakis et al. 2014; Gilley and Eghball 2002). Use of compost also increases soil pH above that of soils that have received inorganic fertilizers (Bowden et al. 2007; Dewaelheyns et al. 2013). Some evidence of a dose response to compost has been found (Adugna 2018; Giannakis et al. 2014), although that was not seen here.

Although not always significantly different from the other nutrient management treatments, the conventional fertilizer treatment was greatest for conductivity (Fig. 4A), color (Fig. 5A), and turbidity (Fig. 6A). The conductivity levels found in our study appear similar to those found in other studies in urban settings. Whittinghill et al. (2016) observed conductivity values up to 473 μS/cm from an agricultural green roof. In some cases, values observed by our study exceeded this, although most were less than 500 μS/cm. Toor et al. (2017) monitored runoff from a residential neighborhood and found conductivity values sometimes twice as high (3640 μS/cm) as those observed in our study. Although agriculture can increase runoff conductivity over some urban landscapes (Whittinghill et al. 2016), results suggest that these effects may be no worse than those of some other land uses (Toor et al. 2017).

Similar results for color have been reported in runoff from green roofs (Berghage et al. 2009) and container production (Hoskins et al. 2014). This suggests that application of chemical fertilizers could lead to a yellow to brown color of runoff water, which when mixed with proximal water sources could produce “objectionable color” for aesthetic purposes. The US Environmental Protection Agency (1986) criteria for water quality lists this objectionable color at a threshold of 75 Pt/Co for sources of domestic water supply. All of the average color values observed in our study exceed the 75 Pt/Co threshold, regardless of fertilizer treatment (Fig. 5A), and there were no differences in the proportion of samples that surpassed this threshold among the fertilizer treatments (χ2 = 3.027, P = 0.387). Color and turbidity are also listed as important for the depth of the compensation point for photosynthetic activity in a waterbody, which should not be reduced by more than 10% (US Environmental Protection Agency 1986). It is unclear how color and turbidity values observed in this study would affect this measure in downstream water bodies, but there is a correlation (Pearson’s R = 0.8149, P < 0.001) between high color and high turbidity in samples collected in our study. This correlation and the connection to a known water-quality issue could warrant further study of the effects of the color and turbidity of runoff water from urban agriculture. The greater turbidity of runoff observed here than in a previous study on a rooftop farm (Whittinghill et al. 2016) suggests that the growing media influence turbidity. In our study, a lot of silt or clay was observed settling in some of the water collection sample bottles. The water in these samples was more cloudy visibly than that of other samples and took longer to filter before other analyses could be performed.

In general, the conventional fertilizer treatment also contained greater amounts of NO4+, P, and K (Fig. 10A–D, Figs. 11 and 12, and Fig. 13A, respectively). Although not always significantly greater than the organic fertilizer treatment, it was significantly greater than the compost-only treatment and often significantly greater than the compost + organic fertilizer treatment. Even when there were no significant differences, the conventional fertilizer treatment exhibited greater variability in NO3, NO4+, P, and K (Figs. 6, 7, 10A–D, 11, 12, and 13A, respectively). The greater variability in NO3 in runoff from the conventional fertilizer treatment translates to significantly more samples the 10-mg/L US Environmental Protection Agency drinking water limit for NO32 = 10.124, P = 0.017) when compared with the compost-only treatment. The conventional fertilizer treatment also had significantly more samples exceeding US Environmental Protection Agency ambient freshwater-quality thresholds for NO4+ for acute (χ2 = 21.975, P > 0.001) and chronic (χ2 = 27.848, P > 0.001) exposures (US Environmental Protection Agency 2013), and for the multisector general permit (MSGP) 2-mg/L P maximum for stormwater discharges from agriculture (χ2 = 88.824, P > 0.001) (US Environmental Protection Agency 2015) than any of the other fertilizer treatments. The number of observations from our study that exceed US Environmental Protection Agency water-quality thresholds for freshwater, in particular the MSGP stormwater discharge from agriculture thresholds of NO3 and P, and the P threshold to prevent the development of biological nuisances and to control eutrophication is concerning. Although a single runoff event from a single raised bed or pool container is unlikely to cause eutrophication on its own, the runoff from all urban agriculture in a watershed or urban area could. When you consider urban agriculture’s continued expansion and the number of urban areas that discharge stormwater directly into surface waterbodies, this becomes more likely. For example, Small et al. (2019) found that compost application in urban gardens constituted one of the largest inputs of P in the Twin Cities’ watershed.

In other studies, the type of fertilizer applied to agricultural land has been shown to have a direct impact on the amount of NO3 in runoff (Kramer et al. 2006; McLeod and Hegg 1984; Yang et al. 2012). In our research, conventional fertilizer treatments were found to have more variation in NO3 values in runoff, whereas the compost-only fertilizer treatment had less variation than the other fertilizer treatments (Fig. 7). The runoff NO3 values observed in our experiment were much greater than those observed in container nursery production (Pershey et al. 2015; Yadzi et al. 2019), an operational rooftop farm and ornamental green roofs (Whittinghill et al. 2016), and a residential neighborhood (Toor et al. 2017). Another study by Matlock and Rowe (2017) found NO3 levels of greater magnitudes as well, although these were mostly from a single compost type and, from the start of the experiment, not observed throughout the duration of the experiment. These results suggest that an increase in NO3 in runoff is likely to take place as land uses change to urban agriculture, and that increase could pose a significant water-quality concern for downstream waterbodies.

The levels of NO4+ observed in our study are more similar to those found in other research than the NO3 levels. Toor et al. (2017) observed non- NO3-N levels as high as 22 mg/L in runoff from a residential area, and Li et al. (2015) found levels up to 9.13 mg/L in urban runoff. Levels were greater, however, than those observed on a rooftop farm using green roof media and ornamental green roofs (Whittinghill et al. 2016). Unlike the study by Whittinghill et al. (2016), these results exceed both acute and chronic US Environmental Protection Agency exposure guidelines (US Environmental Protection Agency 2013) (Fig. 10A–D). The type of soil or growing media used can be an important factor to consider in NO4+ retention. Ammonia in soil particles is adsorbed by clay and is immobilized, which reduces leaching, and NO4+ in soil solution is readily converted into NO3 (King and Torbert 2007). Nitrate is negatively charged and is highly susceptible to loss through leaching and runoff (Chadwick and Chen 2002).

Phosphorus levels in runoff from the organic fertilizer, compost + organic fertilizer, and compost-only treatments in our study are similar to those found in other studies on container production (Pershey et al. 2015), residential communities (Toor et al. 2017), other urban runoff (Li et al. 2015), and green roofs (Matlock and Rowe 2017; Whittinghill et al. 2016). Phosphorus concentrations in runoff from the conventional fertilizer treatment in our study were greater than many of those reported, except for those reported by Toor et al. (2017), when reclaimed water was used (average, 12.5 mg/L). These differences can be attributed to two causes. First, research in traditional agricultural settings has shown that the form of nutrient applied also influences nutrient losses. Heathwaite et al. (1998), for example, found that grassland areas receiving inorganic fertilizers had greater P loss than the grassland areas receiving solid cattle manure and liquid cattle slurry. Although the N and P applied per hectare was more in areas treated with solid cattle manure than in areas treated with inorganic fertilizer, the P loss was greater from areas treated with inorganic fertilizer. A similar result was found by Gaudreau et al. (2002), where runoff loss of dissolved P from the manure fertilizer was found to be 44% less than the runoff from the inorganic fertilizer at equal P application rates in turfgrass plots. This was thought to be because of the less soluble and less transportable nature of manure nutrients.

Second, mean P (Fig. 11) and K (Fig. 13A) in runoff from plots using conventional fertilizer could be explained, in part, by how the fertilizer was applied. The conventional fertilizer was applied to supply adequate N. In a 10N–10P–10K fertilizer with crops that require more N than P or K, this means that P and K will be oversupplied. In this case, 3.61 g/m2 of extra P and K were applied to the conventional fertilizer plots. Three organic fertilizers were used to supply the recommended amounts of N, P, and K for both the organic fertilizer and compost + organic fertilizer treatments. The application method used for the conventional fertilizer appears to have had a greater effect on P in runoff than K. Despite the overapplication of K in the conventional fertilizer treatment, concentrations of K in runoff water from that treatment were not greater than that of the organic fertilizer treatment in either growing system or the compost + organic fertilizer treatment in the container growing system. One study on growing media for containers suggests that excess K may be retained in the media cation exchange capacity and swapped out for other anions such as calcium and magnesium (Hoskins et al. 2014). These other cations were not measured in our study, but could account for the differences in the effect that overapplication of P and K had on runoff water content of those nutrients. Future studies including measurements of these nutrients in runoff and soils could provide a greater understanding of the processes at play.

The compost-only treatment undersupplied P and K by about 1.58 g/m2 when comparing the nutrient recommendations to the nutrients supplied by the compost. Despite this, there is no statistical difference between the amounts of P in runoff from this treatment and the organic fertilizer treatment or the compost + organic fertilizer treatment, or between the K in runoff in the two compost treatments. This underapplication of P and K also had no consistent effect on crop yields (data not shown). Other studies that measured nutrient leaching from systems using different amounts of compost did observe a dose response to the fertilizer (Shrestha et al. 2020; Small et al. 2019). The amounts of nutrients supplied by compost and possibly the amount of compost used in both studies was, however, greater than in our study. Unlike our study, the amount of P supplied by Shrestha et al. (2020) was also greater than that supplied by the synthetic fertilizer treatment in that study, which corresponded to greater P leaching as well. Small et al. (2019) also found that manure-based composts had a greater increase than municipal compost.

Sampling time.

Although some studies have found a relationship between rainfall and the values of various water-quality metrics (Hoskins et al. 2014; Teemusk and Mander 2007), this was not observed in our study. Correlations between pH (R2 = 0.0304, P = 0.0001), conductivity (R2 = 0.0041, P = 0.1542), color (R2 = 0.0037, P = 0.1841), turbidity (R2 = 0.0003, P = 0.7127), NO3-N (R2 = 0.0142, P = 0.0117), NO4+-N (R2 = 0.0117, P = 0.0166), P (R2 = 0.0015, P = 0.3917), and K (R2 = 0.0108, P = 0.0232), and rainfall between samples were weak or not significant. For the two variables with significant correlations, there are some differences that would account for it. The greatest average pH (8.20) was measured at the same time as the greatest rainfall (356 mm) between samplings at 131 DAC (Figs. 3B and 2B), which is opposite to a previously observed pattern of greater pH when rainfall is low (Teemusk and Mander 2007). The two pairs of dates for which the first study year had significantly greater pH than the second study year also had different amounts of rainfall. The sample taken 61 DAC (year 1) had more precipitation than the sample at 67 DAC (287 and 72 mm, respectively), but the second pair had similar rainfall between samplings (178 mm, for both 281 and 286 DAC). In general, sampling times with more rain since the previous sample was collected appear to have lower concentrations of NO3. For example, the sample collected 145 DAC has a lower concentration than the sample collected on 186 DAC (Fig. 9). Both of these sampling times have a similar amount of time between fertilizer application and runoff sampling (Table 3), but the 145-DAC sample had more precipitation since the last sample was taken (Fig. 2B). This difference in precipitation is also likely the cause of the difference between study years for the samples taken 145 and 152 DAC (Figs. 2B and 8).

For the other variables, peaks in the measured variables do not always correspond to peaks in precipitation. There are numerous examples of this mismatch. The 145- and 286-DAC samples, for example, have similar amounts of precipitation between samplings to the 281-DAC sample, but did not result in high color or turbidity readings (Figs. 2B, 4C, and 5C). Similarly, sampling times with equal or greater precipitation between samplings (e.g., 55 and 131 DAC) (Fig. 2B) do not have spikes in NO4+ in runoff that correspond to the one seen at 243 DAC (Fig. 10A–D). The first peak in P runoff takes place before the heaviest rain between 84 and 131 DAC in study year 1 (Figs. 2B and 11), nor does it match sampling times that are soon after a fertilizer application in the conventional fertilizer treatment (Fig. 12A and Table 3). For K, both 67 and 84 DAC have high runoff concentrations (Fig. 13B), but very different amounts of rainfall since the previous sampling time (Fig. 2B).

Another trend in differences among sampling times seems to relate to samples taken during the growing season and samples taken closer to compost or fertilizer application. Conductivity in the first study year is greater and more variable during the growing season, but did not exhibit a relationship to compost or fertilizer application. Several sample timings with greater average conductivity took place long after fertilizers were applied; the 131- and 152-DAC samples were taken 25 and 19 d, respectively, after the previous fertilizer application (Table 3). In the second year of the study, samples taken soon after fertilizer application also had relatively low conductivity; the 55- and 105-DAC samples were taken 1 and 6 d, respectively, after the previous fertilizer applications (Table 3). The link between color and turbidity, and the addition of compost and fertilizers appears to be stronger. High runoff color just after compost addition (4 d), with a general trend of decreasing color until just before compost reapplication, suggests that materials being flushed out of the system over time are affecting color. The lack of effect of compost treatment suggests the source is not compost alone. There are a couple of peaks that could also be associated with fertilizer addition, at 55 and 84 DAC (Fig. 5B), which were 1 and 2 d, respectively, after the previous fertilizer application (Table 3). A similar pattern was seen in turbidity, with greater values early in the study year (Fig. 6B). Other studies have reported a relationship between turbidity and temperatures, with greater turbidities found during the winter months when temperatures are lower (Islam et al. 2006; Liu et al. 2007).

General trends were observed in nutrient runoff, with NO3, P, and K concentrations increasing into the growing season (between 4 and 67 or 84 DAC) (Figs. 9, 12, and 13B, respectively). Nitrate and K concentrations then decline again after 186 and 152 DAC, respectively, but P concentrations peaked again after the growing season. This suggests a general ramping up of nutrient leaching from spring to summer, when fertilizer applications begin and nutrients begin to be released from the compost, then a decline of all except P when fertilizer applications stop at the end of the growing season. Samples taken during the growing season (April through October) also tended to exceed 10-mg/L US Environmental Protection Agency thresholds for NO3 more than those taken during the winter months (November through February) (χ2 = 23.066, P ≪ 0.001). There was no significant difference in the number of samples that exceeded the 0.68-mg/L water-quality threshold for NO32 = 1.287, P = 0.257). The second, smaller peak of P just after the growing season in some nutrient management treatments suggests the release of excess P after crops are no longer being grown (Fig. 12). This second peak in P leaching results in no significant differences between the growing season and winter in the number of samples that exceed the P thresholds for stormwater management or control eutrophication (χ2 < 0.001, P = 1 and χ2 = 0.199, P = 0.656, respectively). Jackson et al. (2009) also saw a decrease in substrate solution NO3, P, and K with increasing time from fertilizer application. Other studies have reported decreases in nutrient runoff over time, with high nutrient runoff just after fertilizer applications, which decreases with time as the crops grow and take up more nutrients (Broschat 1995; Emilsson et al. 2007; Matlock and Rowe 2017; Pershey et al. 2015; Shuman 2002; Smith et al. 2007).

Ammonium exhibited a different pattern, with greater levels after the growing season (Fig. 10A–D). Ammonium levels in runoff water exceeded US Environmental Protection Agency quality standards for acute (χ2 = 14.532, P = 0.001), but not chronic (χ2 = 0.018, P = 0.894) exposures more during the winter months than the growing season (US Environmental Protection Agency 2013). This greater NO4+ loss in December at 243 DAC might be a result of mineralization of organic matter and crop residues leftover in the plots into NO4+. Warm temperatures in October and early November after the final harvest could contribute to mineralization, the products of which are flushed out of the system during later storms. Additional study of N cycling in urban agriculture systems could also help explain why the pattern of NO4+ leaching was so different from that of NO3.

Growing system.

For all water-quality metrics for which there was a significant difference between the two growing systems, the raised beds had greater values than the containers. For many water-quality metrics, this difference was present in only one fertilizer treatment or study year. These differences also did not always translate to meaningful differences in water quality. For pH, both averages were close to neutral and within US Environmental Protection Agency water-quality standards for freshwater (US Environmental Protection Agency 2022a) and human health (US Environmental Protection Agency 2022b). When examining the total range of values measured, the container system had a significantly greater proportion of samples (χ2 = 8.971, P = 0.003) that did not meet US Environmental Protection Agency guidelines limiting pH between 6.5 and 9 (US Environmental Protection Agency 2022a). Eight samples read less than 6.5 and three read more than 9, but no samples from the raised beds read outside these thresholds (Fig. 3C). The range of values from both systems for conductivity (Fig. 4C), color (Fig. 5C), and turbidity (Fig. 6C) was similar. There was also no significant difference between the two growing systems in terms of the number of samples that exceeded the US Environmental Protection Agency 75-Pt/Co color threshold (χ2 = 0.307, P = 0.579) for the domestic water supply (US Environmental Protection Agency 1986).

The raised beds had a greater mean runoff of NO3-N only within the compost-only treatment, but the range of values observed from both systems for that nutrient management treatment was similar (Fig. 7). There were differences in how many of the observations from the two growing systems compared with US Environmental Protection Agency water-quality guidelines. Significantly more runoff samples from the raised beds exceeded the 10-mg/L domestic water supply limit (χ2 = 8.524, P = 0.003) (US Environmental Protection Agency 2022b) and the 0.68-mg/L limit for MSGP for stormwater discharges, which covers agricultural activities (χ2 = 4.648, P = 0.031) (US Environmental Protection Agency 2015). There were no significant differences between the growing systems for NO4+-N, and only a difference for P within the conventional fertilizer treatment in the second study year. There were no significant differences between the growing systems in how many samples exceeded ambient freshwater-quality thresholds for NO4+ for acute (17 mg/L; χ2 = 0.188, P = 0.664) or chronic (1.9 mg/L; χ2 = 1.189, P = 0.275) exposure (US Environmental Protection Agency 2013), or the MSGP 2-mg/L P maximum for stormwater discharges from agriculture (χ2 = 1.775, P = 0.183) (USDA 2015). All but three samples from the kiddie pool containers and one sample from the raised beds exceeded the 0.05-mg/L P threshold to prevent the development of biological nuisances and to control eutrophication (US Environmental Protection Agency 1986). As with P, K was only different between the two systems in the conventional fertilizer treatment (Fig. 13). Results suggest that nutrient management strategy and other factors have a greater impact than growing system on runoff water quality.

Conclusion

The impacts of nutrient management systems in urban agriculture have important implications for the environmental sustainability of urban agricultural practices and urban centers. This will be especially important given the current increase in urban agriculture. During this study, compost fertilizer was also found to have fewer peaks in NO4+-N leaching than the conventional fertilizer treatment and lower variability in the NO3-N concentrations in runoff compared with the conventional and organic fertilizer treatments. This suggests that conventional fertilizer sources are more susceptible to nutrient leaching than compost. Greater P and K concentrations in the runoff from conventional fertilizer than in the other treatments used in our study can be attributed to the oversupply of P and K while maintaining recommended doses of N for greens. This highlights the importance of applying a mix of nutrient sources to supply those nutrients in the correct balance for the crops being grown. The prevalence of overapplication of nutrients, or applying nutrients in unbalanced quantities in urban agriculture, and its possible effect on runoff water quality needs to be studied more.

Expansion of urban agriculture will likely include novel production systems, including low-cost found-object containers such as the kiddie pool containers used in our study. The kiddie pool containers used in our study did not create substantially different runoff water quality than the raised beds, suggesting they are a good candidate for continued use in urban agriculture and for future research. One area for future research on kiddie pool containers suggested by the results of our study is drainage: how to create adequate drainage to minimize waterlogging but still prevent excessive water loss.

The high levels of NO3-N and P in runoff water observed in this and other studies indicate the potential for urban agriculture runoff to contribute to eutrophication, especially as the area in production continues to expand. Additional research that provides ways to minimize this leaching would support farmer education about the issues of nutrient management and water quality, and would lead to more efficient use of nutrients in urban agriculture. In general, compost fertilizer treatments resulted in better water quality than other fertilizer treatments in the study, supporting the continued use and popularity of compost in urban agriculture. Runoff sampling time was seen to have effects on all study water-quality parameters. These effects could be the result of different rainfall patterns, proximity to compost and fertilizerapplications, and the growing seasons of the crops. Further study on the effects of rainfall patterns, amount of rainfall after fertilizer application, and growing season is recommended.

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Supplemental Table S1. Analysis of variance results for the interactions of growing system, nutrient management treatment, sampling time, and study year for pH, conductivity, and color.

TS1

Supplemental Table S2. Analysis of variance results for the interactions of growing system, nutrient management treatment, sampling time, and study year for nitrate- and ammonia-nitrogen, total phosphorus, and potassium.

TS2
  • Fig. 1.

    The gutter and downspout with bucket attachment for water collection pictured on a raised-bed platform.

  • Fig. 2.

    (A) Monthly total precipitation and average temperature for the period of study between May 2018 and December 2019, and the 30-year (1981–2010) climatological normal (National Oceanic and Atmospheric Administration, National Climate Data Center 2020). (B) Total precipitation between sampling times for the first (2018) and second (2019) years of the study, where d: is the number of days between that sampling and the previous sampling.

  • Fig. 3.

    The pH of runoff water for each (A) nutrient management treatment, (B) sampling time in days after compost addition for study years 1 and 2, and (C) growing system. US Environmental Protection Agency (2022a) freshwater minimum and human health maximum pH (US Environmental Protection Agency 2022b) thresholds are included as solid and dashed lines, respectively. Letters denote significant differences between growing systems, among nutrient management treatments, or among sampling times. Max = maximum; Min = minimum.

  • Fig. 4.

    The conductivity of runoff water for each (A) nutrient management treatment, (B) sampling time in days after compost addition for study years 1 and 2, and (C) growing system. Letters denote significant differences among means. Uppercase letters denote differences between growing systems and among nutrient management treatments within study year; lowercase letters denote significant differences between study years within growing system and nutrient management treatment.

  • Fig. 5.

    The color of runoff water for each (A) nutrient management treatment, (B) sampling time in days after compost addition for study years 1 and 2, and (C) growing system. US Environmental Protection Agency (1986) domestic water supply maximum thresholds are included as dashed lines. Letters denote significant differences between growing systems, among nutrient management treatments, or among sampling times. Max = maximum; PtCo = platinum/cobalt scale.

  • Fig. 6.

    The turbidity of runoff water for each (A) nutrient management treatment, (B) sampling time in days after compost addition for study years 1 and 2, and (C) growing system. Letters denote significant differences between growing systems, among nutrient management treatments, or among sampling times. NTU = nephelometric turbidity unit.

  • Fig. 7.

    Nitrate-nitrogen concentration from runoff from each growing system and nutrient management treatment combination averaged across sampling times and study years for (A) the entire range of the data and (B) the range containing the majority of the observations. Letters denote significant differences among means. Uppercase letters denote differences among nutrient management treatments within growing systems; lowercase letters denote significant differences between growing systems within nutrient management treatment. US Environmental Protection Agency (2022b) drinking water maximum and national pollutant discharge elimination system stormwater discharge (US Environmental Protection Agency 2015) thresholds are included as solid and dashed lines, respectively. Max = maximum.

  • Fig. 8.

    Nitrate-nitrogen concentration from runoff from each nutrient management treatment and study year combination averaged across growing systems and sampling times for (A) the entire range of the data and (B) the range containing the majority of the observations. Letters denote significant differences among means. Uppercase letters denote differences among nutrient management treatments within growing systems; lowercase letters denote significant differences between growing systems within nutrient management treatment. US Environmental Protection Agency (2022b) drinking water maximum and national pollutant discharge elimination system stormwater discharges maximum (US Environmental Protection Agency 2015) thresholds are included as solid and dashed lines, respectively. Max = maximum.

  • Fig. 9.

    Nitrate-nitrogen concentrations from each sampling time in days after compost addition for study years 1 and 2 for (A) the entire range of the data and (B) the range containing the majority of the observations. Letters denote significant differences among means. US Environmental Protection Agency (2022b) drinking water maximum and national pollutant discharge elimination system stormwater discharges maximum (US Environmental Protection Agency 2015) thresholds are included as solid and dashed lines, respectively. Max = maximum.

  • Fig. 10.

    Distribution of mean values of ammonia from runoff from each sampling time in days after compost addition for study years 1 and 2 for the (A) conventional fertilizer, (B) organic fertilizer, (C) low-compost + organic fertilizer, and (D) compost-only nutrient management treatments, and (E) the two growing systems (containers and raised beds). US Environmental Protection Agency (2013) acute and chronic exposure thresholds are included as solid and dashed lines, respectively. Letters and asterisks denote significant differences among means. Uppercase letters denote differences among nutrient management treatments within sampling times; lowercase letters denote differences among sampling times within nutrient management treatment. Asterisks denote significant differences between study years within nutrient management treatment for paired sampling dates, with two asterisks indicating the lower mean.

  • Fig. 11.

    Distribution of phosphorous concentrations from runoff from four nutrient management strategies within each growing system for study years (A) 1 and (B) 2. Letters and asterisks denote significant differences among means. Uppercase letters denote differences between growing systems within nutrient management treatments; lowercase letters denote differences among nutrient management treatments within growing system. Asterisks denote significant differences between study years within nutrient management treatment and growing system, with two asterisks indicating the lower mean. US Environmental Protection Agency (2015) stormwater discharge maximum, and threshold to prevent the development of biological nuisances and to control eutrophication (US Environmental Protection Agency 1986) are included as solid and dashed lines, respectively.

  • Fig. 12.

    Distribution of phosphorous concentrations from runoff for each sampling time in days after compost addition for the (A) conventional fertilizer, (B) organic fertilizer, (C) compost + organic fertilizer, and (D) compost-only nutrient management treatments. Letters denote significant differences among means. Uppercase letters denote differences among nutrient management treatments within sampling time; lowercase letters denote differences among sampling times within nutrient management treatments. US Environmental Protection Agency (2015) stormwater discharge maximum, and threshold to prevent the development of biological nuisances and to control eutrophication (US Environmental Protection Agency 1986) are included as solid and dashed lines, respectively.

  • Fig. 13.

    Distribution of potassium concentration from runoff from (A) each growing system and nutrient management treatment combination, and (B) each sampling time in days after compost addition. Letters denote significant differences among means. Lowercase letters denote differences among nutrient management treatments within growing system (A) or among sampling times (B). Uppercase letters denote differences between growing systems within nutrient management treatment (A) or study years for pairs’ sampling dates (B).

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