Ebb and Flow System Versus Overhead Sprinkler and Microirrigation for Container-Grown Woody Ornamental Production in Florida

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EBB AND FLOW SYSTEM VERSUS OVERHEAD SPRINKLER AND MICROIRRIGATION FOR CONTAINER-GROWN WOODY ORNAMENTAL PRODUCTION IN FLORIDA

LUIS CARLOS NOGUEIRA

A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY

UNIVERSITY OF FLORIDA

2005

Luis Carlos Nogueira

This dissertation is dedicated to my beloved parents, Luiz Nogueira and Ana Colli Nogueira, who always showed love, patience, understanding and hard work.

ACKNOWLEDGMENTS

It is always a good time to thank GOD! for the beautiful and powerful nature, full of all resources, for us to work with and learn from.

I am very thankful to Dr. Dorota Zofia Haman, a great person and a smart adviser, for the guidance, opportunity, friendship and huge support.

Many thanks go to the professors of my committee, Dr. Michael Dukes, Dr. John

Schueller, Dr. Robert Stamps and Dr. Thomas Burks, for all the valuable teachings,

patience, understanding, and encouragement at all times. I thank them all so much for

always telling me to move forward despite the obstacles I faced during my journey here.

Also many thanks go to the technician Danny Burch and engineers Larry Miller

and Wayne Williams, for lending me their dedicated expertise, patience, and willingness,

during all phases of my research. We enjoyed many hours of good times together in lab

work, fieldwork, and traveling.

I need to express my gratitude to all of my friends, in and out of the University,

people with whom I shared good and bad times, reminding me that there are other things

in life. All of that certainly added to my life experience. May all of us carry on and move

forward.

Finally, I need to mention that I am very thankful to (Empresa Brasileira de

Pesquisa Agropecuaria (EMBRAPA) and Coordenação de Aperfeiçoamento de Pessoal

de Nível Superior (CAPES) for making this possible through their significant financial

support.

TABLE OF CONTENTS

page

ACKNOWLEDGMENTS ...... iv

LIST OF TABLES...... vii

LIST OF FIGURES ...... viii

ABSTRACT...... x

CHAPTER

1 GENERAL INTRODUCTION ...... 1

2 LITERATURE REVIEW ...... 4

Water Supply for Agriculture and Irrigation ...... 4 Water and Nutrient Management in Nurseries ...... 5 Growth Studies of Containerized Ornamentals ...... 12 Water Quality in Streams and Reservoirs...... 18

3 GENERAL METHODOLOGY...... 24

4 GROWTH PARAMETERS OF CONTAINERIZED MAGNOLIA PLANTS UNDER THREE DIFFERENT IRRIGATION SYSTEMS...... 34

Introduction...... 34 Materials and Methods ...... 34 Results and Discussion ...... 35 Conclusions...... 37

5 CALIBRATION OF TDR SENSORS FOR MONITORING CONTAINER SUBSTRATE MOISTURE CONTENT ...... 42

Introduction...... 42 Materials and Methods ...... 46 Results and Discussions...... 47 Conclusions...... 48

v 6 CONCENTRATION AND LOADS OF NUTRIENTS FROM A WOODY ORNAMENTAL NURSERY USING THREE DIFFERENT IRRIGATION SYSTEMS ...... 52

Introduction...... 52 Materials and Methods ...... 53 Results and Discussions...... 54 Conclusions...... 61

7 RAINWATER HARVESTING EFFECTIVENESS OF A RECIRCULATORY SYSTEM USED FOR IRRIGATION OF CONTAINER-GROWN WOODY ORNAMENTALS ...... 72

Introduction...... 72 Materials and Methods ...... 73 Results and Discussion ...... 76 Conclusions...... 84

8 EVAPOTRANSPIRATION AND CROP COEFFICIENT OF MAGNOLIA PLANTS UNDER THREE DIFFERENT IRRIGATION SYSTEMS...... 89

Introduction...... 89 Materials and Methods ...... 90 Results and Discussion ...... 94 Conclusions and Recommendations...... 96

9 CONCLUSIONS AND RECOMMENDATIONS...... 102

Plant Growth...... 102 Calibration of TDR sensors and Field Monitoring...... 102 Concentration and Loads of Nutrients...... 102 Rainwater Harvesting and Recycling System...... 104 Evapotranspiration and Crop Coefficients...... 105

LIST OF REFERENCES...... 106

BIOGRAPHICAL SKETCH ...... 113

LIST OF TABLES

Table page

4-1 Plant height of magnolia trees measured during a 12-month period...... 39

4-2 Trunk diameter of magnolia trees measured during a 12-month period...... 39

4-3 Growth index of magnolia trees measured during a 12-month period...... 39

6-1 Concentration of nutrients (mg L-1) in water during a 12-month period...... 64

6-2 Loads of nutrients (kg ha-1) in water during a 12-month period ...... 65

7-1 Monthly water harvesting effectiveness and storage effectiveness for the recirculatory system ...... 88

7-2 Consolidated water harvesting effectiveness and storage effectiveness for the recirculatory system ...... 88

vii

LIST OF FIGURES

Figure page

3-1 General overview of the experimental plots at Holloway Tree Farm ...... 29

3-2 Layout of the experimental plots at Holloway Tree Farm...... 30

3-3 Components of the recirculatory system at Holloway Tree Farm ...... 31

3-4 Some aspects of data collection system at Holloway Tree Farm...... 32

3-5 Boxes used for water sampling at the ebb and flow plot...... 33

4-1 Plant height of magnolia trees measured during a 12-month period...... 40

4-2 Trunk diameter of magnolia trees measured during a 12-month period...... 40

4-3 Growth index of magnolia trees measured during a 12-month period...... 41

4-4 Historical amount of precipitation compared to local rainfall for 12-month period...... 41

5-1 Specifications of the Campbell Scientific CS616 TDR sensor used to monitor water content...... 50

5-2 Time Domain Reflectometry sensor inserted in the substrate in the 56.8 liters (15 gallons) container...... 50

5-3 Calibration curve for the substrate used to grow magnolias ...... 51

5-4 Substrate Moisture Content monitored in magnolia containers ...... 51

6-1 Variability of concentration of ammonia-N in water during a 12-month period .....66

6-2 Variability of concentration of nitrate-N in water during a 12-month period...... 66

6-3 Variability of concentration of TKN in water during a 12-month period...... 67

6-4 Variability of concentration of total P in water during a 12-month period...... 67

6-5 Variability of concentration of total N in water during a 12-month period ...... 68

viii 6-6 Variability of loads of ammonia-N in water during a 12-month period ...... 68

6-7 Variability of loads of nitrate-N in water during a 12-month period ...... 69

6-8 Variability of loads of TKN in water during a 12-month period ...... 69

6-9 Variability of loads of total P in water during a 12-month period ...... 70

6-10 Variability of loads of total N in water during a 12-month period ...... 70

6-11 Variability of concentration of nutrients detected in the reservoir...... 71

6-12 Variability of loads of nutrients released from the reservoir...... 71

7-1 Sensor and farmer readings of reservoir water level during a 2-day period showing reading checkpoint, rainfall events and full level threshold...... 86

7-2 Sensor readings of reservoir water level during a 24-hour period showing one rainfall and one irrigation event, when the reservoir was near to full...... 86

7-3 Amounts of harvested rainwater, well water, and reservoir overflow monitored from September 2002 through August 2004...... 87

8-1 Monthly average of reference evapotranspiration and crop evapotranspiration of magnolia plants cultivated under three different irrigation systems ...... 98

8-2 Sample of the reservoir water level measurements showing the effect of rainfall and irrigation events...... 98

8-3 Crop coefficients calculated for magnolia plants grown...... 99

8-4 Historical monthly normal of precipitation and monthly totals of precipitation...... 99

8-5 Historical monthly maximum air temperature and monthly maximum air temperature during the study...... 100

8-6 Historical monthly mean air temperature and monthly mean air temperature during the study...... 100

8-7 Historical monthly minimum air temperature and monthly minimum air temperature during the study period...... 101

Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy

EBB AND FLOW SYSTEM VERSUS OVERHEAD SPRINKLER AND MICROIRRIGATION FOR CONTAINER-GROWN WOODY ORNAMENTAL PRODUCTION IN FLORIDA

Luis Carlos Nogueira

May 2005

Chair: Dorota Zofia Haman Major Department: Agricultural and Biological Engineering

Runoff from agricultural production areas has an impact on water management in

the field. Ornamental plant production of is an important and profitable agricultural business in Florida, and is a main consumer of irrigation water and a potential

environmental polluter, mainly of water resources.

Our study of container-grown Magnolia trees was done in Leesburg, Florida,

under three irrigation systems: ebb and flow (recirculatory system), overhead sprinkler

irrigation, and microirrigation.

Peak crop evapotranspiration (ETc) occurred in July 2003 (6.09 mm day-1,

4.91 mm day-1, and 2.98 mm day-1, for ebb and flow, overhead sprinkler, and

microirrigation system, respectively). The highest value of reference evapotranspiration

(ETo) was 7.33 mm day-1 in July. Ebb and flow system produced higher values of Kc

(ranging from 0.71 to 1.04), followed by overhead sprinkler (from 0.29 to 0.85), and

microirrigation (from 0.13 to 0.59).

x All of the nutrients (NH4, NO3, TKN, Total P, and Total N) analyzed in the

reservoir water had very low concentrations. For nitrate, the maximum concentration was

1.9 mg L-1. The total loads released from the reservoir to the environment during the

-1 -1 -1 -1 study were 1.01 kg ha (NH4), 7.21 kg ha (NO3), 14.48 kg ha (TKN), 3.40 kg ha

(Total P), and 21.68 kg ha-1 (Total N).

A management strategy adopted for the recirculatory system improved rainwater

harvesting and reduced precipitation losses, allowing more water to stay in the reservoir

for irrigation, and avoiding water withdrawals from the aquifer. Before the strategy was

adopted, harvesting effectiveness was 44.5% (precipitation losses = 55.5%); afterward,

harvesting effectiveness was 75.7% (precipitation losses = 24.3%). These results show a

reduced potential for water pollution with nutrients and agrochemicals: less runoff from

the recirculatory system represents less discharge of these chemicals to the environment.

xi CHAPTER 1 GENERAL INTRODUCTION

The world's supply of fresh water is finite and is threatened by pollution. Rising

demands for water supply for agriculture, industry, and cities are leading to competition

in the allocation of limited fresh water resources. Water conservation and water reuse

produce substantial environmental benefits, arising from reductions in water diversions

and reductions in the impacts of wastewater discharges on environmental water quality

(Anderson, 2003).

Water plays an important role in the growth and productivity of plants and must be well managed to optimize production and minimize water and nutrient loss from the system. Since high quality fresh water is a finite resource, and is becoming scarce or very limited in certain areas of the globe, the economic and social implications of inefficient water use are becoming more evident. In addition, agricultural chemicals that are moving with water lost from the system can result in contamination of ground and surface waters.

Minimizing runoff and minimizing deep percolation protects the environment.

The ideal irrigation system allows for optimum moisture conditions in the plant root system and applies just the required amount of water for the crop, with a minimum amount of loss. In addition, the system and its management should minimize water withdrawals from the water source and keep the source from being polluted by percolation or runoff water that carries agrochemicals, such as fertilizers.

Ornamental plants produced in Florida include woody ornamentals (landscape trees and shrubs), tropical foliage, flowering plant products, cut foliage, and turfgrass sod.

1 2

Florida dominates production of tropical foliage with about 90% of U.S. sales (Hodges et

al., 2003). Container-grown landscape ornamentals in Florida are commonly irrigated

with an overhead system. This type of irrigation is especially common for production of

the most common container sizes, 15 liters and smaller. For these small containers, the

cost and labor to install and maintain a microirrigation system are often considered

prohibitive. However, overhead irrigation is a very inefficient way to irrigate container-

grown plants: the percentage of water actually reaching the container medium surface

ranges from 12 to 50% (Beeson and Knox, 1991).

In certain regions, restrictions on annual irrigation volumes have been enacted and

will likely expand. Thus, techniques that optimize growth and water conservation are

crucial to the Florida nursery industry (Beeson and Haydu, 1995).

Container production of nursery crops is intensive and is a potential source of nitrogen release to the environment (Colangelo and Brand, 2001). Introducing legislation to control runoff and charge for water used in agricultural production has encouraged commercial plant nurseries to collect and recycle their irrigation drainage (Headley et al.,

2001).

The outdoor ebb and flow irrigation system is innovative and has not been previously used (except for preliminary tests) in container production of woody ornamentals. In this production system, plants are placed on an impermeable surface in leveled basins that are periodically flooded for irrigation. Excess water is then returned to the detention pond. Runoff water from rainfall is also collected in the pond for future irrigations. As a result, all dissolved nutrients are retained in the pond, eliminating groundwater pollution from deep percolation and minimizing surface water pollution

3 from runoff. The only time nutrients may be released to the environment is during periods of exceptionally heavy rainfall, when the storage pond may overflow. In addition, the ebb and flow system allows unused nutrients in the detention water to be reapplied for use by the crop.

The goal of our study was to evaluate certain irrigation technologies to improve the information available on efficiency of the nursery production systems. The larger objective was to identify and evaluate a system that would result in more efficient use of inputs, reduce the environmental pollution potential, and result in better levels of production. The outdoors ebb and flow irrigation system parameters were defined, evaluated, and compared with overhead sprinkler and microirrigation system in a woody ornamental nursery.

CHAPTER 2 LITERATURE REVIEW

Water Supply for Agriculture and Irrigation

Various countries are facing a gap between water supply and demand. This gap is

closely linked with agricultural production and environmental issues and is due to small

amounts of precipitation, low availability of natural water sources, inefficient water usage

and/or increasing demand due to population increases. Special ventures must be

undertaken in order to supply water in adequate quantity and quality for all requirements.

These can be accomplished by the development of additional water sources that currently

are considered marginal. The additional sources include saline water, treated wastewater

and runoff water and are usually required to augment the limited supply from the regional

conventional high quality local sources (Oron, 2003).

Water conservation and water reuse programs result in substantial environmental

benefits, arising from reductions in water diversions and reductions in the impacts of

wastewater discharges on environmental water quality (Anderson, 2003). Improved water

conservation in landscapes, mainly in dry landscapes, may be achieved using plant

species with low water requirements. Selecting plants, however, demands information on

water needs of different species (Garcia-Navarro et al., 2004). Devitt et al. (1997)

demonstrated that leaf carbon isotope ratios could be used as a way of screening plant

response for low water-use landscapes.

The criteria used to evaluate any irrigation/plant production system for the most sustainable strategy (Ganoulis, 2003) include public health and environmental factors that

4 5

pose risks on human health, water pollution during and after irrigation, and efficiency of

water use; economic factors, including the water cost, the initial cost of the irrigation

system, maintenance costs and crop profitability; and social issues including the

employment of rural labor.

Replacing more conventional or other nonconventional water sources for agricultural irrigation with reclaimed water depends on reducing public health risks and on environmental risks to acceptable levels. For an acceptable solution, these risks should be weighed against economic benefits (Ganoulis, 2003). Treated municipal wastewater can be a good alternative source of water and nutrients for ornamental plant production

(Gori and Lubello, 2000).

Wastewater treatment was primarily implemented to enhance urban hygiene.

Treatment methods were improved to ensure environmental protection by removing nutrients to meet drinking water standards. In this process, energy is consumed and potential resources, like useful minerals, and high quality water are disposed of integrated management of assets (including drinking quality water, surface water, energy and nutrients), would make wastewater management more sustainable (Wilsenach et al.,

2003).

Water and Nutrient Management in Nurseries

Introduction of legislation to control runoff and charge for water used in agricultural production has encouraged commercial plant nurseries to collect and recycle their irrigation drainage (Headley et al., 2001). Runoff from a nursery typically contains

-1 -1 around 6 mg L Total N (> 70% as NO3), 0.5 mg L Total P (> 50% as PO4), and virtually no organic matter (BOD <5 mg L-1; DOC <20 mg L-1) (Headley et al., 2001).

Closed growing systems, such as those used in greenhouses, can minimize the leaching of

chemicals into the environment (Van Os, 1999).

Colangelo and Brand (2001) conducted a study to determine if trickle irrigation could be used by container nursery producers as an alternative to standard overhead irrigation to reduce nitrogen release into the environment. The effect of overhead irrigation and trickle irrigation on leachate nitrate-N concentration, flow-weighted nitrate-N concentration, leachate volume, and plant growth was investigated using containerized rhododendron supplied with a controlled-release fertilizer and grown outdoors on top of soil-monolith lysimeters. Leachate was collected over two growing seasons and over the winter periods, and natural precipitation was allowed as a component of the system. Precipitation accounted for 69% of the water entering the overhead-irrigated system and 80% of the water entering the trickle-irrigated system.

Leachate from fertilized plants exceeded the USEPA nitrate-N drinking water limit of 10 mg L-1 at several sampling events and reached a maximum of 26 mg L-1 with trickle irrigation. Average annual loss of nitrate-N in leachate for fertilized treatments was 51.8 and 60.5 kg ha-1 for the overhead and trickle treatments, respectively. Average annual

flow-weighted concentration of nitrate-N in leachate of fertilized plants was 7.2 mg L-1 for overhead irrigation and 12.7 mg L-1 for trickle irrigation.

Juntunen et al. (2002) studied the nutrient uptake by the plants and the nitrogen (N) and phosphorus (P) content of leachates from the substrate of silver birch, Norway spruce, and Scots pine. The doses of applied nutrients were 149 to 260 kg ha-1 of N and

60 to 108 kg ha-1 of P. Approximately half of those doses were premixed in the peat

substrate, and the other half was applied to the plants in liquid form during the growing

season. From the applied doses, 11 to 19% of N was detected in the volume of collected

leachate, and of 15 to 63% in the seedling tissue, depending on the species. The amount

of N not accounted for varied from 19 to 71%. Only 5 to 31% of P applied was detected

in the seedling tissue and 16 to 64% in the leached volume. It was also concluded that the

total loads of N and P to the environment can increase substantially if nutrients applied in

liquid form that fall off the trays of seedling containers are considered.

Harris et al. (1997) examined the losses of nitrate, phosphorus, and selected

agrochemicals from a peat-based growing medium used for hardy ornamental nursery

stock (HONS) production. Concentrations of nitrate-N in water draining from the beds

exceeded 200 mg L-1 and phosphorus (P) exceeded 20 mg L-1, which are considerably in excess of the European limit for drinking water and also represent a considerable eutrophication potential. The use of sand beds irrigated by a subsurface system did not noticeably reduce losses of nutrients, unless used in conjunction with a re-circulation system.

Fernandez-Escobar et al. (2004) investigated the growth and the N leaching losses of olive trees in 3-liter plastic pots fertilized with traditional (urea, ammonium sulfate, ammonium nitrate, and calcium nitrate) or slow-release N fertilizers [sulfur-coated urea

(Greenmaster), a nitrification inhibitor (Basammon), a low solubility material (Floranid), and a resin-coated urea (Multicote)]. Each plant received 2 g N from one of the N fertilizers at the beginning of a first experiment, and 0.75 g N in a second experiment.

Fertilized plants showed significantly increased vegetative growth compared to controls, but plants fertilized with 0.75 g N exhibited greater shoot growth than those that received

2 g N. No significant differences were found among fertilizers when 0.75 g N was

8 applied, but greater growth was obtained with Floranid and Multicote when 2 g N was applied to each plant. Regardless of N formulation, N was accumulated mainly in leaves of the olive plants. Most of the N recovered in the leachates was in the nitrate form. Total

N losses were higher when ammonium nitrate and calcium nitrate were applied, and lower with the slow-release fertilizers, except for Basammon.

Guimera et al. (1995) studied the effect of continuous fertigation regimes through drip irrigation on N uptake and leaching as well as on the yield of strawberries.

Nitrate-nitrogen leachates under the root zone were 1535 and 471 kg ha-1 of N respectively for wet treatments (watering when suction was -0.01 Mpa) and dry treatments (watering when suction was -0.07 Mpa). The N uptake was higher in the wet treatment. The N uptake was 12% and 23% of the total applied. The wet irrigation regime resulted in significantly increased yields. Management practices should be improved to account for crop needs and thus improve N uptake efficiency and reduce N leaching.

Couillard and Grenier (1989) conducted a study with Larix laricina grown on sand and nursery soil in a greenhouse and fertilized with anaerobically digested sludge at various rates and doses. No direct relationship could be established between the growth of seedlings and the quantities of sludge applied. There was a significant, positive correlation between the growth of seedlings and the phosphorus and nitrogen content of their tissues. Tissues had potassium deficiencies and an excess of calcium, magnesium, and trace elements.

Chamshama and Hall (1987) conducted an experiment with uniform nursery stocks of Eucalyptus tereticornis combining site preparation (bedding; disking; neither bedding nor disking) with initial nitrogen applications (75 g ammonium sulphate per plant; 0 g

ammonium sulphate per plant) and initial phosphorus applications (150 g triple super

phosphate per plant; 0 g triple super phosphate per plant). Monitoring was carried out for

2 years (by which time trees were up to 3.2 m tall and 5.0 cm in diameter at the root

collar). Survival at 2 years was significantly higher in plants that had received nitrogen

(65%) than in plants that had not (53%); and in plants on disked or bedded sites (62%)

than in plants on unworked soil (53%). Monthly height increment was briefly (but

significantly) increased in plants supplied with additional nitrogen and further enhanced

if there was also additional phosphorus. Monthly diameter increment was (over most of

the first year) significantly greater on sites prepared by bedding; significant increases also

resulted (though for more restricted periods) from site preparation by disking and from

providing additional nitrogen. At the end of 1 year, significantly higher concentrations of

foliar potassium, suggesting enhanced drought hardiness, were detected for plants on

bedded or disked ground. The concentration in these was 1%; on unworked ground, the

corresponding value was 0.8%. Combining bedding or disking with an initial application of nitrogen offset this effect. The value of phosphorus applications under the prevailing conditions is considered unproven (Chamshama and Hall, 1987).

A study was made of the effect of fertilization on strawberries grown in greenhouse soil and outdoor nursery beds (Eysinga and Caem, 1977). The response of the crop to

variations in fertilizer treatment was greater in the nursery beds than in the greenhouse.

Only nitrogen dressing was of some importance under greenhouse conditions, but too

much nitrogen proved to be harmful. The correct fertilization of the nursery beds with

nitrogen and potash is most important. Basic slag proved to be a suitable phosphate

fertilizer for the nursery beds, but triple superphosphate cannot be recommended.

Huett (1997b) studied nutrient losses from controlled-release fertilizers (CRFs) and an organic-based fertilizer under a range of irrigation conditions. The CRFs were

Osmocote NPK (3 to 4 months) (Osm), Nutricote NPK (90 days) (Nut), and Nut (40 days), and the organic based fertilizer was Dynamic Lifter (DL). They were applied pre- planting at a standard rate equivalent to 800 g m-3 of N and at double this rate to pots

containing sand, composted pine bark, and hardwood sawdust medium that had received

nutrient amendment during formulation. In leachate, nitrate was the main form of N from

CRFs and ammonium was the main form from DL. The maximum nitrate concentrations

at the standard fertilizer rate were 55 mg L-1 (Osm), 56 mg L-1 (Nut), and 46 mg L-1 (DL).

These increased to 78 and 165 mg L-1 when the rate of Osm and Nut was doubled. A

nitrate concentration of 279 mg L-1 was recorded with the Nut (40 days) formulation. The maximum leachate ammonium concentrations at the standard fertilizer rate were 64 mg L-1 (Osm), 51 mg L-1 (Nut), and 125 mg L-1 (DL). Leachate was diluted 1:4 in nursery runoff water by irrigation runoff, and concentrations exceeded the 10 mg L-1 limit

imposed by the Clean Waters Act of NSW.

Huett (1997a) investigated the effectiveness of controlled-release fertilizers (CRFs)

and an organic-based fertilizer in supporting the growth of groundcover species under a

range of irrigation conditions. Two experiments were conducted from spring to early fall

at a commercial nursery, with high irrigation rates (25 mm day-1). Fertilizers were applied

at standard rate and twice this rate. The N, P, and/or K concentrations in shoots of both

species at both rates of fertilizer application were lower (P < 0.05) than for species grown

with constant LF, indicating the inability of single pre-plant fertilizer applications to

maintain adequate nutrient supply. Blending a 40-day Nut formulation with the 90-day

formulation apparently improved nutrient release characteristics, because shoot P and K

concentrations and growth increased. Huett (1997a) also found that reduction in leachate

volume from the commercial rate (one-third) had no effect on plant growth. This

indicates that salt accumulation is unlikely to be a problem when irrigation is scheduled

to minimize container leaching.

Excessive leaching for containerized nursery plants fertilized with CRF results in

high nutrient loss, low residual nutrient content, reduced nutrient uptake in shoots, and

reduced shoot growth of some species (Huett and Morris, 1999).

Phosphorus transport in sediments moving in surface runoff flows has been studied

extensively, but problems of colloid facilitated through soil P pollution flows have only

recently received attention. There is almost no published information about sorption onto

such colloids (McGechan and Lewis, 2002). Plant availability of P depends on desorption

to reverse the fast sorption process, and this is limited by the amount of P that has not undergone the slow deposition process. However, the level of biologically available phosphorus (BAP) in a soil or soil-derived sediment, which leads to eutrophication of water bodies, includes much of the P deposited by slow reactions and also includes plant available components (McGechan, 2002).

Laverman et al. (2002) found a significant negative correlation between organic carbon and nitrate leaching, suggesting that denitrification occurred at sites with low nitrate leaching. Adelman and Tabidian (1996) found that nitrate leaching rates were affected more by changing carbon rates than by changing farm management practices, because an active population of denitrifying bacteria denitrifies the nitrogen while taking advantage of the organic carbon as carbon and energy sources.

For UK farmers involved in ornamental and nursery stock, trickle irrigation is

increasingly becoming the preferred choice. It is likely that under these high value

production systems, where crop product quality is essential, high levels of irrigation

efficiency are being obtained (Knox and Weatherhead, 2003). Nutrient runoff from

nurseries can be reduced by adopting efficient irrigation design, by scheduling irrigation,

and by minimizing the use of soluble fertilizer sources (Huett, 1997b).

Growth Studies of Containerized Ornamentals

Hardy ornamental nursery stock (HONS) is container grown in systems using

frequent irrigation and considerable applications of nutrients and pesticides. These

container systems are frequently isolated from the underlying soil by an impermeable

membrane resulting in near-surface drainage from the beds (Harris et al., 1997).

Witmer (2000) studied water use and growth of red and sugar maple during two years of pot-in-pot (P+P) production and during 3 years after transplanting to field soil.

Frequent irrigation (3 times a day) increased trunk-diameter growth of sugar maples in the second production cycle, and for red maples in both production cycles compared to standard once-a-day irrigation. Frequent irrigation had no effect on height growth of either species, but partially alleviated the late day water stress of red maples. The two ages of transplanting to field soil after 1 versus 2 years of P+P production made no difference on height and trunk diameter. However, height and trunk diameter differences between 1 and 2 year sugar maple trees persisted 3 years after transplanting.

To assess the growth of ornamental shrubs in peat alternative substrates, one ornamental species (Viburnum tinus L.), was cultivated in a number of different substrates in two climates: a French oceanic (Oce) and a Spanish Mediterranean (Med)

(Guerin et al., 2001). Plants were cultivated at a density of 6 plants/m2 in 4-liter

containers with drip irrigation. Plant height, dry mass, and leaf area were measured

monthly during cultivation. In both climates, substrates ranked the same whether height,

dry mass, or leaf area were considered. Those effects are related to the substrate

characteristics, mainly physical ones. As peat is used in a large range of situations, the

experiment showed that substrate performance varies with its use, so alternative

substrates can show better performance than those using peat.

An experiment carried out in Pistoia (the most important nursery area in Italy for

producing woody ornamental plants) showed better physiological and growth parameters

for plants irrigated with effluent (treated with UV irradiation in a disinfection pilot plant)

than for plants irrigated with traditional well water (Gori and Lubello, 2000).

Hurly et al. (1991) investigated the influence of modified Hoagland's nutrient

solution in combination with three nitrogen sources (urea, calcium, and ammonium

nitrate) on growth (height, stem diameter, leaf area, and shoot and root fresh and dry

mass) of emergent seedlings and of 4-month-old transplanted seedlings of guayule

(Parthenium argentatum, Gray). The measured growth parameters were shown to

increase in a concentration-dependent manner although, overall, no one treatment was

superior. Differences were observed in the response of transplanted seedlings to applied

nitrogen sources in regard to branching, flowering, seed, rubber, and resin production.

Calcium nitrate or urea at 210 mg L-1 of N gave higher seed yields and germination than ammonium nitrate. Resin levels in roots and shoots decreased with increasing levels of applied nitrogen, while the converse applied to levels of rubber when results were expressed on a percentage basis. However, the larger biomass of plants given supplementary nitrogen fertilization often resulted in greater yields of resin and rubber

when results were expressed on a plant basis. Seed and rubber production may be

improved by applying nitrate or urea to nursery-grown seedlings for a 2- to 3-year period

before field plantings.

Nitrogen (56, 112 or 224 kg ha-1 N) was applied as ammonium nitrate or urea formaldehyde before planting Scotch pine (Pinus sylvestris L.) seedlings in the fall and spring (Hensley and Aldridge, 1990). Controls received no fertilization. Survival and growth were measured. Effects of N fertilization on survival were significant. Higher levels of N resulted in lower survival without increased growth. Slow-release N allowed increased rates to be used without reducing survival, but there was no benefit in the higher N rates in terms of growth.

Welander and Ottosson (2000) studied the relationship between water consumption and growth in young seedlings of oak. The increase in dry mass over a certain period was compared with the transpiration during the same period. Dry mass and transpiration were closely correlated during the first and second year of growth in seedlings. The correlation

between growth and total water consumption became weaker when nutrient strength or

water availability changed. Water-use efficiency (WUE) became highest at the highest

nutrient strength and increased with a decrease in soil water content. Their results

indicate that young seedlings of oak may increase their water-use efficiency when

nutrient availability is increased by removing competing ground vegetation.

Devitt et al. (1997) studied the effect of leaching fraction (LF = drainage

volume/irrigation volume) and tree planting size on the carbon isotope ratio measured in

leaves of live oak, desert willow, and tall fescue, in an arid climate. Live oak and desert

willow were planted as 3.8, 18.9 or 56.8 liter nursery container plants in lysimeters where

hydrologic balances were maintained weekly. Average leaf WUE in live oak and tall

fescue were correlated with average leaf carbon isotope ratios. However, in tall fescue

leaf, WUE increased as the leaf carbon isotope ratio became more negative. In live oak,

the ratio became more positive as leaf WUE increased.

Wan et al. (2002) tested a hypothesis that variable precipitation may induce altered

rooting patterns. A nursery study was conducted over 2 years, to evaluate the effect of

seasonally variable soil moisture on the rooting pattern of shallow-rooted shrub broom

snakeweed (Gutierrezia sarothrae Britt and Rusby). Plants irrigated during spring and

summer, but grown under rainout shelters in the winter, produced more roots in the upper

30 cm of soil than did plants receiving natural precipitation, or plants irrigated in the

winter, but grown under rainout shelters in the spring and summer. Plants irrigated in the

winter, but grown under the rainout shelter in the spring and summer had 45-47% more

roots. This altered root distribution also enabled the plants to produce aboveground

biomass similar to that of plants receiving natural precipitation.

Wan et al. (1998) studied differences in transpiration and root growth in the

southern and northern populations of rabbitweed (Gutierrezia sarothrae L.) and

variations in tissue and leaf water relations. Seedlings from an Idaho (ID) and a Texas

(TX) seed source were grown either in an open nursery (full sunlight) or under shade.

There were no population differences in transpiration, root growth, and tissue water relation parameters when the plants were grown under the shade. However, significant population differences were observed in the plants grown in the open. Transpiration in the TX population increased twice as rapidly as the ID population in response to rising potential evapotranspiration (PET). In addition, the TX plants grew longer and larger

lateral roots than the ID plants, when both populations were grown in the open. Similar

changes in tissue-water relation parameters were observed in the ID seedlings subjected

to soil water deficit. Subjecting ID plants to drought may lead to restricted growth, reflected by hydraulic limitation of the plant root systems. Higher water use efficiency

(WUE) in the ID population reflected conservative water use at the leaf and tissue levels, which was consistent with the water-use pattern at the canopy level.

Jobidon et al. (1998) tested four different sizes of spruce seedlings in different sizes of containers and different water stress conditions. The increased water stress experienced by the large stock of spruce seedlings had an effect on the absolute growth rate (AGR) in height. These results emphasize the need to produce a large stock of spruce seedlings with well-developed root systems and root growth capacity, even though only moderate water stress was observed during the first 3 years of plantation growth.

Banon et al. (2004) investigated (in nursery) conditions the water relations and anatomical and morphological changes of Lotus creticus sub. creticus seedlings to two irrigation treatments (water stress and control) and temperature (unheated and night-heated greenhouse). Shoot and root growth, leaf stomatal density, leaf trichome density, xylem vessels in roots and stems, and water relations were studied because of their relation with drought resistance. Water stress led to substantial losses in dry weight, leaf area, root dry weight, and length. The limited osmotic adjustment reached by the plants may not maintain leaf turgor and growth. In general, deficit irrigation produced

Lotus plants with greater leaf trichome densities and produced stems and roots with more

xylem vessels. Night-time heating had little influence on these aspects. Temperature

reduced the leaf water potential of water-stressed plants, but had no effect on sufficiently

17 watered plants. Deficit irrigation under nursery conditions induced a suite of morphological and physiological adaptations (reduced leaf area, development of osmotic adjustment, increments of leaf hairs and number of xylem vessels of stem and roots) that might allow considerable adaptation to adverse conditions after transplanting.

Sanchez-Blanco et al. (2004) investigated the effect of different irrigation and air humidity conditioning treatments on the morphological and physiological responses of rosemary (Rosmarinus officinalis L.) in nursery conditions. Two irrigation treatments were used (control and deficit). At the end of the nursery period, deficit irrigation had altered the morphology of the R. officinalis plants by reducing plant height, stem diameter, leaf area, total dry weight, and root length. The plants subjected to deficit irrigation developed leaf osmotic adjustment. Plants exposed to deficit irrigation showed efficient stomatal regulation.

Marfa et al. (2002) studied growing media (binary mixtures) prepared with peat and peat-substitutes (cattle manure compost, forest waste compost, pine bark compost, yard compost and raw coir), and the composition of the root-zone solution monitored by the induced percolate (IP) method and the applied nutrient solution (NS). The results indicated that a steady-state nutrient level in the root zone can be achieved when a relatively low concentration of NS is applied by fertigation. Release of nutrients, especially nitrates, occurs during growing period. The biostability of the substrates and the initial availability of phosphorus and potassium determine the composition of the leachates. The results proved that the IP method can be used to monitor nutrient levels in the root zone and its use can enhance the nutrient-use efficiency in commercial nurseries.

For substrate production, 50% of the peat content in a common substrate used in

Spanish nurseries was successfully replaced with different mixtures of municipal solid wastes (MSW) compost, dry sewage sludge, grape marc, rice hull and pine bark, reducing the cost of substrates while not diminishing the quality of plants produced, and using similar amounts of water and nutrients. (Ingelmo et al., 1998).

Water Quality in Streams and Reservoirs

Environmental policies like European Union Water Framework Directive and US

Total Maximum Daily Load (TMDL) Concept are a result of the increasing of surface water quality issues in the European Union and United States. These policies require improved methods for investigation and evaluation of surface water quality as well as derivation and assessment of management practices (Horn et al., 2004).

Because adequate nutrient controls were not established when there were past opportunities to do so, nutrient pollution of estuaries and coastal waters has resulted in the impairment of ecosystems and major reductions or collapses of fisheries at numerous sites around the world, resulting in major economical and societal impacts. The root of the problem is that the political policies and processes have permitted municipalities, developers, industries and farmers to expand and operate without paying the full cost of their activities, at the expense of those who rely on the productivity and recreational value of the estuarine and coastal waters. Some governments have developed remedial nutrient control programs, but most of them have been under-funded and inadequately enforced, resulting in small increments of progress that tend to be lost because of inadequate land use and immigration controls. It is believed that nutrient recovery and controlled reuse can provide a major tool for the control of nutrient pollution and should be widely implemented (Randall, 2003).

Chemical water quality monitoring is essential in areas where the harmful effects of

naturally occurring or artificially introduced chemicals on human health and/or the

environment are significant. It is very difficult for developing countries to monitor a large

number of chemicals due to human and financial constraints and hence, simple guidelines

are required in selecting and prioritizing chemicals in the monitoring programs.

(Gheewala et al., 2003).

Management of water quality in lakes, streams and rivers, including determinations and allocations of acceptable total maximum daily loads (TMDLs), requires use of calibrated and reliable water quality models for prediction of pollutant concentrations under alternative management or load allocation scenarios (Supriyasilp et al., 2003).

Proper identification of water quality conditions in lake and river systems based on limited observations is an essential task for meeting the goals of environmental management. Owing to inherent imprecision, difficulties always exist in some conventional methodologies when describing integrated water quality conditions with respect to various chemical constituents, biological aspects, nutrients, and aesthetic qualities (Chang et al., 2001).

According to U.S. Congress (1990), nonpoint source pollution (NPSP) is defined by EPA as “pollution caused by sediment, nutrient, and organic and toxic substances originating from land-use activities and/or from the atmosphere, which is earned to surface water bodies through runoff or groundwater”, and since the contaminants most commonly derive from agricultural lands the exact source is not usually traceable.

A stringent water quality standard criterion for phosphorus and nitrogen compounds has been motivated worldwide by the needs to protect surface water bodies

against eutrophication phenomena. The current European regulation describes guidelines

for total phosphorus (TP) and nitrogen (TN) in treated effluent to respectively 80 or 70%

removal rate, or down to 1–2 mg L-1 TP and 10–15 mg L-1 TN (Lesjean et al., 2003).

TMDL are required by the US Environmental Protection Agency for pollutants that have impaired the designated uses of surface waters in the nation. Setting an appropriate

TMDL requires quantitative information on both the external pollutant inputs and the processes affecting pollutant dynamics within the ecosystem (Havens and Schelske,

2001). For example, TMDL procedures are used by the Environmental Protection

Agency to regulate salinity discharges from non-point sources to the San Joaquin River

(California) (Quinn and Hanna, 2003).

Natural, industrial and agricultural conditions influence the share of point and nonpoint sources of pollution in a river basin. Suspended solids, water quality parameters, mass flow of nutrients and atmospheric deposition are factors that must be considered as pollution in agriculture, forestry, and erosion sites (Berankova and

Ungerman, 1996).

The chemical interactions in the surface waters are very complex. Chemical factors in a complex interplay with hydrodynamic and food web interactions control the temporal variability in lake phytoplankton (Arhonditsis et al., 2004). Due to chronic nutrient enrichment of surface water, wetlands adjacent to land managed with fertilizer have been studied to determine their role in nutrient dynamics (Casey and Klaine, 2001).

The regional sand and gravel aquifer at Grand Forks, in Canada, has nitrate-N concentrations that exceed the maximum Canadian drinking water guideline (CDWG) of

10 mg L-1 of Nitrate-N (equivalent to 44 mg L-1 for nitrate) decreases with increasing

21 well depth and appears to be derived from the land surface; areas of elevated nitrate are associated with areas of major vegetable farming. Nitrate-N appears to be leaching into the aquifer. (Wei et al., 1993).

The TMDL process separates water bodies into those for which water quality goals can be achieved by present and future mandated reduction of point and nonpoint sources

(effluent limited water bodies) and those where mandated reduction will not achieve the water quality goals (water quality limited water bodies). Watersheds and receiving water bodies that are adversely affected predominantly by nonpoint (unregulated) discharges are declared as impaired and should be managed. Both reduction of waste discharges and enhancement of waste assimilative capacity-habitat restoration of the receiving water body should be considered in management of water quality limited receiving water bodies (Novotny, 1996).

Wetlands and streams buffer the interactions among uplands and adjacent aquatic systems. Phosphorus (P) is often the key nutrient found to be limiting in both estuarine and freshwater ecosystems. As such, the ability of wetlands and streams to retain P is key to determining downstream water quality. Phosphorus retention mechanisms include uptake and release by vegetation, periphyton and microorganisms; sorption and exchange reactions with soils and sediments; chemical precipitation in the water column; and sedimentation and entrainment. These mechanisms exemplify the combined biological, physical, and chemical nature of P retention in wetlands and streams. Methodologies used to estimate P retention include empirical input-output analysis and mass balances, and process kinetics applied at various scales, including micro- and mesocosms to full-scale systems. Although complex numerical models are available to estimate P retention and

transport, a simple understanding of P retention at the process level is important, but the

overall picture provided by mass balance and kinetic evaluations are often more useful in

estimating long-term P retention (Reddy et al., 1999).

Headley et al. (2001) found that TN and TP load removals from subsurface flow

wetlands were > 84% and > 65% respectively, with the majority of out-flowing TN and

TP being organic in form (0.45 mg L-1 TN and 0.15 mg L-1 TP in the effluent). Greater

than 90% load removal of NH4 and NO3 was achieved at all sites, with outlet

concentrations generally <0.01 mg L-1 for all. For TN, a strong relationship existed

between removal rate (g m-2 day-1) and loading rate (r2=0.995), while a weaker relationship existed for TP (r2=0.47).

Phosphorus (P) is considered a globally important pollutant of freshwater lakes

(Havens and Schelske, 2001). Success in reducing discharge of potential pollutants is

dependent upon facility design, operation, and financial commitment, besides regulatory

requirements and corporate philosophy (MacMillan et al., 2003).

Casey and Klaine, 2001) sampled golf course runoff and determined the loads of nitrate and phosphate transported during storms and the attenuation of those loads when runoff passed through a riparian wetland. All sampled storm events contained nitrate (2 to

1470 g per event) and phosphate (1 to 4156 g per event). Extensive nutrient attenuation occurred when water passed through the riparian wetland. In 11 events, nitrate and phosphate attenuation averaged 80 and 74%, respectively. Rapid and complete attenuation of phosphate immediately after runoff water infiltrated into the wetland subsurface was observed in this study. No phosphate was observed in discharge from the wetland. Nitrate attenuation occurred following a lag phase of several hours that was

probably due to reactivation of denitrifying enzymes. Nitrate attenuation was initially less

than 60% but increased to 100% in all experiments. The results indicated that intermittent inputs of nitrate and phosphate could be successfully attenuated in the wetland on the

time scale of natural storm events.

Strong public support and political commitment have allowed the Chesapeake Bay

Program to reduce nutrient inputs, particularly from point sources, by 58% for P and 28% for N. However, reductions of nonpoint sources of P and N were projected to reach only

19% and 15%, respectively, of controllable loadings (Boesch et al., 2001).

Water quality research in the Yazoo Basin uplands in Mississippi has shown sediment loads from a conventional-till upland soybean watershed to be about 19,000 kg/ha/yr, and responsible for 77-96% of P and N in transport. In contrast, sediment loads from a comparable no-till soybean watershed were only 500 kg/ha/yr, transporting about

31% of P and N in transport. Best management practices (BMPs) must be designed to remediate diffuse pollution and the transient nature of pollution events which can have a profound effect on the ecological health of streams and reservoirs (Schreiber et al., 2001).

Havens and Schelske, 2001), working on Lake Okeechobee (Florida, USA), considered how biological processes can influence the ability of lakes to assimilate P, and in turn, the ability of managers to select appropriate TMDLs. The results indicated that the ability of a shallow lake to assimilate P is substantially reduced when surplus levels of P occur in the water column, the phytoplankton becomes dominated by cyanobacteria, the benthic invertebrate community becomes dominated by oligochaetes, and submerged plant biomass is low. If some of these biological changes can be reversed in a rehabilitation program then the lake may be able to support a higher TMDL.

CHAPTER 3 GENERAL METHODOLOGY

A 1-year (March 2003 through February 2004) research project was conducted in a

woody ornamental container nursery at the Holloway Tree Farm in Leesburg, Florida

(Lat/Lon: 28°49'N / 81°49' W). The project consisted of a comparison of three irrigation

systems (Figure 3-1) that already existed at this farm: overhead sprinkler system (Figure

3-1A), microirrigation (Figure 3-1B), and an outdoor ebb and flow (Figure 3-1C), also

called recirculatory flood irrigation. One-year old clonal magnolia plants (Magnolia

grandiflora 'D.D. Blanchard') in 56.8-liter (15-gallon) plastic containers were used as the

plant material on each experimental plot. The plot layout for each irrigation system is

shown in the Figure 3-2.

The sprinkler head used in the overhead irrigation plot was an impact sprinkler with a single nozzle, model 1373 Red (L.R. Nelson Corporation, Peoria, IL) with the recommended operating pressure 207 kPa to 441 kPa (30 to 60 psi), and flow rate

11.0 L min-1 to 15.1 L min-1 (2.9 gpm to 4.0 gpm). At the plot the sprinkler heads were

operated at 207 kPa (30 psi). Sprinkler spacing was 7.0 m x 6.7 m (23 ft x 22 ft). (Figure

3-1A).

The microirrigation emitter used at the site was the “Brown Mini Flow

Spot-Spitter” (Roberts Irrigation Products, Inc., San Marcos, CA), 90o spray pattern, with the recommended operating pressure 69 kPa to 172 kPa (10 to 25 psi), and flow rate

15.9 L h-1 to 29.5 L h-1 (4.2 gph to 7.8 gph). It was operated at 138 kPa (20 psi) (Figure

3-1B).

24 25

Irrigation water for the ebb and flow system came from the reservoir (Figure 3-3A) that is a part of the recirculatory system. However, there was an option of adding well water to the reservoir during low rainfall periods.

A timer (Model Total Control, Irritrol Systems, Riverside, CA) controlled the overhead and microirrigation systems. The grower, as a part of the normal activities for the whole farm, determined the frequency of water application.

The recirculatory system consists of 13 flood plains (Figure 3-3B) connected to each other and to the reservoir by a buried pipe. Each flood plain has an area of about

0.28 ha (0.69 ac) that works as an irrigation water application unit and also as a rainwater-harvesting unit. A hydraulic valve (Figure 3-3C) commanded by a central controller allows the water to move in and out from the reservoir. The reservoir accumulates rainwater collected from all 13 flood plains (total area of 4.05 ha or 10.0 ac) during the rainy season and can be fed with well water during the dry season, if necessary.

A water level sensor (CS420-L Submersible Pressure Transducer, Campbell

Scientific, Inc., Logan UT) was installed for monitoring the water level in the reservoir.

The sensor was connected to a CR-10 datalogger (Campbell Scientific, Inc., Logan UT)

(Figure 3-4E). The readings of water level were recorded every 15 minutes, allowing enough precision to follow the dynamics of the reservoir 24 hours a day. Values registered by the water level sensor were checked with the daily manual readings kept by the grower for comparison.

The experimental plots were located within the regular production areas of the farm. For each irrigation system, an area with 40 plants of magnolia was selected for

monitoring. Well-established, 1-year old magnolia plants in 56.8-liter (15-gallon)

containers were placed in the experimental plots.

The substrate used in containers and all necessary cultural treatments were the

same as used in the other production areas of the farm. The substrate consisted of 45%

peat, 50% pine bark, and 5% sand (Florida Potting Soils, Inc., Orlando, FL). There was

no amendment in the substrate and the fertilizers were applied in June (12-month slow

release formula) and August (4-month slow release formula), using 240 g (0.53 lb) per

container. The 12-month product was “Florikan Blend 15-4-9”, containing 15.0% of

nitrogen (7.45% nitrate-N, 6.95% ammoniacal-N, 0.40% water soluble N, and 0.20%

water insoluble N), 4.0% of phosphorus pentoxide, and 9.0% of potassium oxide

(Florikan, Sarasota, FL). The 4-month product was “Graco 18-6-10 Top Dress”, containing 18.0% of Total Nitrogen (1.62% of Nitrate N, 4.66% of Urea N, and 11.72%

of Water Insoluble N), 6.0% of phosphorus pentoxide, and 10.0% of potassium oxide

(Graco Fertilizer Company, Cairo, GA).

Six plants were selected for water balance monitoring in each experimental plot.

The measurements of the plant growth (height, trunk diameter, N-S width and E-W width) were made manually every two months for the 6 selected plants and every 6 months for all 40 plants in the plot. The height and the width of the plants were measured using a regular measuring tape and the trunk diameter was measured using a caliper at 15 cm (6 in) high from the top of the container (ANLA, 2004). The growth index was calculated (Irmak, 2002) using Equation 3-1.

W + H GI = (3-1) 2

where

GI = Growth Index, cm W = Average of N-S and E-W width of the plant, cm H = Height of the plant, cm

Irrigation water applications under microirrigation and overhead sprinkler

irrigation were monitored using a 2.5-cm (1.0-inch) flow meter (ABB Water Meter, Inc.,

Ocala, FL) installed at the entrance of the experimental plot to accumulate all the applied

water to the plot. The flow meter readings were made on a weekly basis.

Fiberglass trays (Figure 3-4F) were constructed for collection of water typically lost to runoff and percolation in the overhead sprinkler system and microirrigation. The

trays were sized based on the plant spacing (91.4 cm x 79.2 cm or 3 ft x 2.6 ft) to collect

water that was lost from the production area assigned to one plant (Figure 3-2). The

runoff collected by the tray was stored in a plastic barrel of 190 liters (60 gallons) buried

adjacent to the plot (Figures 3-4A and 3-4C). Each tray was connected by a 1.9 cm

(¾ inch) polyethylene pipe to the barrel to convey the water. Runoff measurements were

made on a weekly basis.

The reservoir water and the runoff water from all three systems were analyzed for

nutrient content once a month. For the ebb and flow system, the water samples were

collected from the water trapped in the fiberglass boxes (Figures 3-1C and 3-4B) during

the flood irrigation event. The box dimensions were determined by the plant spacing

(91.4 cm x 79.2 cm or 3 ft x 2.6 ft) and the height was of 35.6 cm (14 inches), as shown

in Figure 3-5. The water samples were collected after the plant was removed and the

excess water was drained from the pot.

Monthly water analyses were made for NH4-N, NOx-N, TKN, and Total P aiming

to monitor the pollution potentials of all three systems. All monthly water samples were

28 analyzed at the UF/IFAS Extension Soil Testing Laboratory (Gainesville, FL), which is an EPA certified laboratory. The EPA methods used for the analyses were: EPA 360.1 for

NH4-N, EPA 353.2 for NOx-N, EPA 351.2 for TKN, and EPA 365.1 for Total P.

The climatological data were monitored by an automatic weather station (Campbell

Scientific, Inc., Logan, UT) (Figure 3-4D). Wind speed and direction, air temperature, humidity, rainfall and solar radiation were recorded every 30 minutes. The sensors used in the weather station were: “03001 Wind Sentry”, “HMP45C Temperature and Relative

Humidity Probe”, “TE525 Tipping Bucket Rain Gage”, and “LI-200SZ Radiation

Sensor”, all connected to a CR10X Datalogger.

For monitoring the potting medium moisture content, one TDR sensor was placed in each container (Figure 3-4G). The TDR sensor Water Content Reflectometer model

CS616 (Campbell Scientific (Logan, UT) consisted of two parallel rods 30 cm long and spaced 3.2 cm apart (Figure 3-4H). The moisture content was calculated using the calibration curve developed for the growing media and the time response recorded every

30 minutes by a CR10X datalogger (Campbell Scientific, Logan, UT) powered by a photovoltaic system (Figure 3-4D). The data was downloaded weekly using a notebook computer.

(A)

(B)

(C)

Figure 3-1. General overview of the experimental plots at Holloway Tree Farm. A) Overhead sprinkler system. B) Microirrigation system. C) Ebb and flow irrigation system.

6.40 m (21 ft)

M 1234567

P nn2 n4 n6 n M1 M2 0.79 m 0.91 m m1 m3 m5 m7 7.00 m (23 ft) m(2.6 ft) (3.0 ft) m

lM l4 l6 l X abcde fgh i jX

11a1 c1 e1 g1 i1 kk1 k3 k4 k7 k 0.79 m (2.6 ft) 0.91 m (3.0 ft) 22b2 d2 f2 h2 j2 j11 P j6 j

33 a3 A e3 g3 E Ii1 i3 i5 i7 I ) t b4 d4 C h4 j4 44h2 h4 h6 36 f hh

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66B d6 D h6 j6 11.09 m ( fN f4 f6 f 77 a7 c7 e7 g7 g7 ee1 e3 e5 e7 e 88b8 d8 f8 h8 j8 dd2 d4 R d X X abcde fgh i j cc1 O c5 c7 c A B C D E F (A) bb2 b4 b6 b CR10X Station 2: Sprinkler Plot aa1 a3 a5 a7 a Polyethylene Pipe 1" 1234567

0.79 m M General Flow Meter CR10X (C) (2.6 ft) 0.91 m Station 4: Ebb and Flow P Pressure Gauge (3.0 ft) A Runoff and TDR Monitored Magnolia M1 Wired Flow Meter

Flow Meter Wiring to CR10X TDR Sensor Wiring to CR10X

A Runoff Collector Barrel X Sprinkler Head

CR10X CR10X Station a1 Commercial Magnolia

9.80 m (29.9 ft)

abcde fgh I j k Imn

1 a1 c1 e1 g1 i1 k1 m1 1

2 b2 d2 f2 h2 j2 l2 n2 2 0.79 m (2.6 ft) 0.91 m (3 ft) M1 3 a3 c3 G g3 i3 K m3 3

4 b4 d4 f4 I j4 l4 n4 4

5 a5 c5 e3 g5 i5 L m5 5 6.7 m (22 ft)

6 b6 H f6 J j6 l6 n6 6 M2 7 a7 c7 e7 g7 i7 k7 m7 7

8 b8 d8 f8 h8 j8 l8 n8 8

abcde fgh I j k Imn (B) G H I J K L

CR10X Station 3: Microirrigation Plot Figure 3-2. Layout of the experimental plots at Holloway Tree Farm. A) Overhead sprinkler system. B) Microirrigation system. C) Ebb and flow irrigation system.

(A)

(B)

(C)

Figure 3-3. Components of the recirculatory system at Holloway Tree Farm. A) Reservoir. B) Flood plains. C) Hydraulic valve of each flood plain.

(A) (B)

(E) (F)

Power Ground Output Enable Shield

30 cm (G) (H) Figure 3-4. Some aspects of data collection system at Holloway Tree Farm. A) Barrels at microirrigation plot. B) Boxes at ebb and flow plot. C) Barrels at overhead sprinkler plot. D) Automatic weather station. E) Datalogger. F) Tray for runoff collection. G) TDR sensor for moisture content monitoring. H) TDR sensor specifications.

79.4 cm (31.2 in) 91.4 cm (36.0 in)

35.6 cm (14.0 in)

Figure 3-5. Boxes used for water sampling at the ebb and flow plot.

CHAPTER 4 GROWTH PARAMETERS OF CONTAINERIZED MAGNOLIA PLANTS UNDER THREE DIFFERENT IRRIGATION SYSTEMS

Introduction

Production of ornamental plants in nurseries is one of the fastest growing sector of agriculture in the United States and it involves a complex technology (Drakeford, et al., 2003). In Florida, there are more than 7,000 registered nursery growers (DPI, 2004), producing woody ornamentals (landscape trees and shrubs) and many other ornamental plants (Hodges et al., 2003).

Southern magnolia (Magnolia grandiflora) a medium-sized tree also called evergreen magnolia, large-flower magnolia, bull-bay, or big-laurel (Outcalt, 1990), has a single flower borne at the end of an elongated stalk or branch of the main axis of the plant, with separate petals and sepals (Ruppert, 1999). It is considered a drought tolerant plant (Knox 2001) and moderately fast-growing tree that grows best on rich, moist, well- drained soils (Outcalt, 1990).

The objective of this study was to monitor the main growth parameters of containerized plants of Magnolia grandiflora “DD Blanchard” grown in a nursery environment under three different irrigation systems: ebb and flow, overhead sprinkler and microirrigation system.

Materials and Methods

Plant growth parameters of magnolia were monitored during a period of 12 months from all three experimental plots at the farm. For each irrigation system, an area

34 35 with 40 plants of magnolia was selected in the regular nursery production areas for monitoring. All plants in the experimental plots were well-established, 1-year old magnolia plants cultivated in 56.8 liters (15 gallons) containers, representing the average conditions of the regular production areas. All the plants in the farm were cultivated using container substrate consisting of 45% peat, 50% pine bark, and 5% sand (Florida

Potting Soils, Inc., Orlando, FL). All the necessary cultural treatments were the same as used in the other production areas of the farm.

The plant growth parameters measured were height, trunk diameter, N-S width and

E-W width. The growth index was calculated using N-S width, E-W width, and plant height in the Equation 3-1. All the measurements were performed manually every two months for the 6 selected plants and every 6 months for all 40 plants in the plot. The height and the width of the plants were measured using a regular measuring tape and the trunk diameter was measured at 15 cm (6 in) above substrate level using a caliper

(ANLA, 2004).

Statistical analyses were performed for the growth parameters as repeated measures throughout the study period using SAS software (SAS Institute Inc., Cary, NC). Each set of data analyzed consists of a total number of 126 data points, which resulted from 7 collection dates (repetitions) for 3 irrigation systems with 6 replications.

Results and Discussion

Tables 4-1 to 4-3 and Figures 4-1 to 4-3 show the plant growth parameters plant height, trunk diameter, and growth index for Magnolia trees grown under three different irrigation systems. Each graph shows the data collected every other month during a period of 12 months, from February 2003 to February 2004.

The irrigation systems did have significant effect, at 5% level, on plant height and growth index, but no significant effect on trunk diameter, during the 12-month period.

The plants grown under ebb and flow system started with some advantage (first collection date on the graphs) regarding plant height when compared to the other two systems, however the difference was significant only when compared to microirrigation.

The ebb and flow system started in February 2003 with higher mean value for plant height (138 cm), which was not significantly different from overhead sprinkler (122 cm), but did differ at 5% level from microirrigation system (116 cm). Considering the growth index parameter, ebb and flow started in February 2003 with mean value (89 cm) significantly (at 5% level) higher than overhead sprinkler (74 cm) and microirrigation (75 cm) systems.

From April 2003 through August 2003 there was no significant difference at 5% level between the irrigation systems for the parameter plant height. Under overhead sprinkler irrigation system, plants grew up from 155 cm in April to 217 cm in August.

For microirrigation system the growth was from 153 cm to 227 cm from April to August, and for ebb and flow system, it was from 161 cm to 235 cm in same period.

The reason for the lack of more evident difference in growth under the three irrigation systems studied maybe related to the high amount of precipitation occurred during this period (Figure 4-4). In February and March the total precipitation was 336.6 mm, which is 92% higher than the historical precipitation (175.3 mm) for these two months. From June to August, the local precipitation totalized 769.6 mm, which is 68% higher than the historical amount (457.2 mm) for these three months. Therefore, the irrigation systems had contribution to the plant growth only for two months (April and

May), when the local precipitation (62.2 mm) represented only 35% of the historical amount (176.0 mm).

For the last three collection dates (October 2003, December 2003 and February

2004), the plant height means from ebb and flow system (250 cm, 270 cm, and 272 cm) did not differ at 5% level from microirrigation system means (238 cm, 261 cm, and 264 cm), but were significantly higher than means from overhead sprinkler system (220 cm,

226 cm, and 228 cm). Similar tendency occurred for growth index during this period

(from October 2003 to February 2004). The mean of growth index produced by ebb and flow irrigation system (from 155.0 cm to 176.3 cm) were significantly higher than overhead sprinkler means (from 140.7 cm to 150.3 cm), but did not differ from microirrigation system means (from 147.5 cm to 169.7 cm) at 5% level.

As already stated above, there was no significant effect for the parameter trunk diameter values during the whole period of study. However, a trend for higher values of trunk diameter in plants under the overhead sprinkler irrigation can be observed. The other growth parameters, showed a tendency to produce slightly lower values under sprinkler irrigation. The growth parameters under ebb and flow system resulted in slightly higher values, with intermediate values for microirrigation system.

Conclusions

Plant growth parameters of magnolia were monitored during a period of 12 months and ANOVA was performed for plant height, trunk diameter, and growth index of the magnolia trees under three different irrigation systems:

• Results showed that the irrigation systems did have significant effect on the parameters plant height and growth index during the period of study.

• In both cases, for plant height and growth index, the overhead sprinkler irrigation system produced smaller values than ebb and flow and microirrigation systems.

• There was no significant effect of irrigation systems on trunk diameter. However, for trunk diameter alone, overhead sprinkler irrigation system had the tendency to produce larger values during the whole period of study when compared to ebb and flow and microirrigation systems.

Table 4-1. Plant height of magnolia trees measured during a 12-month period at Holloway Tree Farm, Leesburg, FL. Plant height (cm) Month Overhead Sprinkler Microirrigation Ebb and Flow Feb 03 122 ab 116 a 138 b Apr 03 155 a 153 a 161 a Jun 03 210 a 207 a 212 a Aug 03 217 a 227 a 235 a Oct 03 220 a 238 ab 250 b Dec 03 226 a 262 b 270 b Feb 04 228 a 264 b 272 b Note: Means with same letter in a row are not statistically different at 5% level.

Table 4-2. Trunk diameter of magnolia trees measured during a 12-month period at Holloway Tree Farm, Leesburg, FL. Trunk diameter (cm) Month Overhead Sprinkler Microirrigation Ebb and Flow Feb 03 2.0 a 1.9 a 2.0 a Apr 03 2.3 a 2.2 a 2.2 a Jun 03 2.5 a 2.4 a 2.4 a Aug 03 2.8 a 2.6 a 2.6 a Oct 03 3.3 a 3.0 a 3.2 a Dec 03 3.6 a 3.2 a 3.4 a Feb 04 3.8 a 3.3 a 3.6 a Note: Means with same letter in a row are not statistically different at 5% level.

Table 4-3. Growth index of magnolia trees measured during a 12-month period at Holloway Tree Farm, Leesburg, FL. Growth index (cm) Month Overhead Sprinkler Microirrigation Ebb and Flow Feb 03 73.9 a 74.9 a 89.3 b Apr 03 86.4 a 86.2 a 101.2 a Jun 03 105.3 a 105.2 a 114.2 a Aug 03 135.0 a 135.5 a 141.9 a Oct 03 140.7 a 147.5 ab 155.0 b Dec 03 144.4 a 155.9 b 164.0 b Feb 04 150.3 a 169.7 b 176.3 b Note: Means with same letter in a row are not statistically different at 5% level.

350

300

250 m) (c t 200 igh e t H

n 150 a l P

100

0 3 3 3 3 3 3 4 3 3 3 3 3 4 0 0 0 0 0 0 0 0 0 0 0 0 0 t r r y c v g p Jul Ap Oc Jun Jan Ma Feb Feb Au Se De No Ma

Overhead Sprinkler Microirrigation Ebb and Flow

Figure 4-1. Plant height of magnolia trees measured during a 12-month period at Holloway Tree Farm, Leesburg, FL.

5 )

m 4 c (

er et m a

i 3 D k n u r

T 2

0 3 3 3 3 3 3 3 3 3 4 3 0 0 0 0 0 0 0 04 03 0 0 0 l t r r c y 0 v g p n n Ju Oc Ap Ja Ju Ma Feb Feb Au Se De No Ma

Overhead Sprinkler Microirrigation Ebb and Flow

Figure 4-2. Trunk diameter of magnolia trees measured during a 12-month period at Holloway Tree Farm, Leesburg, FL.

200

150 ) m (c

x e d n

i 100 h t w Gro

0 3 3 3 3 3 3 3 3 3 4 3 0 0 0 0 0 0 0 04 03 0 0 0 l t r r y 0 c v g p n n Ju Oc Ap Ja Ju Ma Feb Feb De Au Se No Ma

Overhead Sprinkler Microirrigation Ebb and Flow

Figure 4-3. Growth index of magnolia trees measured during a 12-month period at Holloway Tree Farm, Leesburg, FL.

350

300

250

200

150 Precipitation (mm)

100

0 Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb 2003 2004 Study period Historical data Figure 4-4. Historical amount of precipitation compared to local rainfall for 12-month period at Holloway Tree Farm, Leesburg, FL.

CHAPTER 5 CALIBRATION OF TDR SENSORS FOR MONITORING CONTAINER SUBSTRATE MOISTURE CONTENT

Introduction

There are many advantages of ornamental plant production in containers. However, due to specific characteristics of the substrate used in this type of production, it is difficult to reliably monitor the moisture content of the plant root zone using typical soil moisture instruments. At the same time, this monitoring helps with scheduling decisions that are necessary for efficient and economical irrigation management in container plant production.

Since the soil is the primary substrate for growing plants, many soil moisture sensors have been developed throughout the years. Each of them has advantages and disadvantages that make them more suitable for certain field applications, but none of them can be considered the “perfect” solution. Among all the instruments available on the market, the Time Domain Reflectometry (TDR) method is gaining more attention from researchers. This method is becoming more reliable due to technical improvements and better understanding of instrument performance, making the TDR instruments more versatile than other instruments for many field applications.

The TDR method for estimating the water content of porous media is based on the relationship between the dielectric constant and the amount of water present in the porous medium. Each model of probe or instrument contains specific electronics and software to convert the “time response” of an electrical impulse into “water content”, and each

42 43 porous medium will have specific influence on this relationship depending on its physical and chemical properties. Hence, it is very unlikely to have a generic calibration curve or unique mathematical model for all situations in the field, which brings up the necessity of determine a specific calibration curve for each specific field application (each soil or in this case growing substrate).

It is well known that gravimetric method is considered the standard method for determining the moisture content of soils and other porous media, mainly because of its simplicity and direct measurement of the moisture content. However, it is a destructive method and it requires a long time to produce the results. In addition, it does not allow repeatability at the same place, since a sample of the material is removed from the original spot. Searching for better solutions to overcome these disadvantages, new methods and sensors were developed and improved aiming at accuracy, repeatability and electronic data storage. Among these sensors are found the tensiometers, neutron probes, capacitance sensors, and several variations of TDR sensors. However, gravimetric method is usually used as a standard method for calibration of all these sensors.

TDR technology provides an indirect measurement of soil water content through its sensitivity to the dielectric permittivity of the material surrounding the probe rods. The volumetric water content is estimated based on the water high value of dielectric permittivity (81) compared to the values of the soil particles and the air (3 to 4). The water content and the consequent dielectric permittivity will influence inversely the propagation velocity of the electromagnetic pulse along the sensor rods, resulting in a specific value of signal travel time. The time response (output period) produced can be empirically related to water content using calibration equation (usually a linear or

44 quadratic equation). The nature of the material surrounding the sensor rods can produce different attenuations on the signal response, which implies the need for a calibration curve for each medium. For CS616 TDR probe, the precision and the resolution are not affected by attenuating media. The precision is 0.1% Volumetric Water Content (VWC) and the resolution is 0.05% VWC (Campbell Scientific, 2002).

Typically, in container-grown plant production, the medium is not soil but one of several substrates available for this purpose. Substrates are mixtures of certain organic and/or synthetic components developed with physical and chemical characteristics for supporting the plant growth, mainly related to root development and water and nutrient holding capacity. Since the container has a fixed shape, it represents a physical limitation for both the root development and the water movement. The irrigation system, with some exceptions for drip (type of microirrigation) systems, will not have direct influence on the size and shape of the wetted volume of substrate, influencing only the amount of water at each irrigation event. Assuming the objective of the irrigation system is to provide efficient conditions for wetting 100% of the container volume, the moisture sensor placed in the container is always located within the wetted volume of substrate.

In a typical commercial situation, when the instrument is used for irrigation management purposes, the soil moisture sensor is placed within the soil volume considered the effective root zone volume. Often, only one sensor can be used to represent the average moisture content within the root zone, mainly depending on the type and price of the sensor. For research purposes, more sensors are used to detect the moisture content conditions not only within the root zone, but also outside the root zone, according to the objective of the study. In most cases, especially when using

45 microirrigation, the irrigation system will have direct influence on the shape and the size of this wetted volume of soil and on the amount and the way of distribution of water that will be applied at each irrigation event.

Most of the soil-less substrates used in container-grown nurseries have large particles and consequently large pores spaces and small capability to hold easily available water (EAW) for plants when compared to most of natural soils. Although the water release curves follow a characteristic shape, the EAW varies greatly according to substrate composition and particle size. TDR technology has the possibility to accurately measure the volumetric water content of soil-less substrates and to allow improved control of irrigation amounts and frequency, with potential better retention of nutrients in the root zone, maximizing plant growth and minimizing leaching volumes (Murray et al.,

2000).

According to Murray et al. (2001), an important influence on the easily available water (EAW) is the container geometry, particularly the container height. Since the gravity acts in vertical plane causing increased drainage from taller containers of the same volume, the taller containers will hold proportionally less water, as volumetric percentage. These authors tested TDR sensors placed vertically and diagonally in containers and concluded that sensor placement is less important with spray stakes compared to drip emitters, due to water distribution in the whole volume of substrate, but diagonal placement may also be preferable if the spray stake can ensure a uniform coverage of each pot surface.

The objective here was to present the calibration curve for Time Domain

Reflectometry (TDR) sensors used in the typical nursery substrate and the information

46 obtained with the monitoring of substrate moisture content (SMC) in container-grown woody ornamental plants.

Materials and Methods

This chapter presents and discusses the data on TDR sensors calibration and moisture content monitoring of the growing medium (substrate) used in the containerized plant production at the farm. For container-grown plants, the medium is not soil but one of several substrates available for this purpose. Usually, they are a mixture of organic or synthetic components. At Holloway Tree Farm the substrate used consisted of 45% peat,

50% pine bark, and 5% sand (Florida Potting Soils, Inc., Orlando, FL).

The TDR sensor used was the Water Content Reflectometer model CS616

(Campbell Scientific (Logan, UT) that consists of two parallel rods 30 cm long and 3.2 cm apart (Figure 5-1). The moisture content was read and recorded every 30 minutes using a datalogger (CR10X, Campbell Scientific, Logan, UT) running on a battery charged by a photovoltaic system. The data was downloaded weekly using a notebook computer.

Based on the type of the sensor used (Campbell Scientific CS 616 Sensor) and on the size and shape of the 15 gallons container, it was decided that one sensor would be enough to represent the substrate moisture content (SMC) available for the plant in each container. Each sensor was placed half way between the container border and the plant trunk in the center (Ruiz-Sanchez et al., 2000). The sensor was inserted inclined (at 450 angle) in the substrate (Figure 5-2) to take advantage of the original length of the sensor rods (30 cm). It could not be inserted vertically without leaving part of the rods length outside of the substrate. Since proper probe installation largely controls the accuracy of the measurements (Serrarens et al., 2000), all the sensors were inserted carefully at the

47 same angle using a guiding tool developed for this purpose and with similar substrate moisture content (close to saturation) to assure better contact between the sensor rods and the medium.

The calibration of the TDR sensors was conducted in the Water Resources

Laboratory at the Agricultural and Biological Engineering Department, University of

Florida, in Gainesville, FL. The methodology used was recommended by Campbell

Scientific (2002), using six replications (six sensors). Six containers filled with substrate were brought from the Holloway Tree Farm and saturated for 48 hours. One TDR sensor was installed in each container and the readings were taken every week. The values of substrate moisture content (SMC), in cm3cm-3, were obtained gravimetrically and compared to the output period (OP), in µs, from the TDR sensors, stored to a CR10 datalogger.

In the field, as already stated in Chapter 3, for monitoring the substrate moisture content, one TDR sensor was placed in each container of the six plants selected from each irrigation system. The moisture content was calculated using the calibration curve developed for the substrate as described above.

Results and Discussions

Figure 5-3 shows the calibration curves for the substrate used to grow Magnolias at

Holloway Tree Farm. The graph shows both the original factory calibration curve and the laboratory-generated curve for comparison purposes. The factory (Campbell Scientific) calibration equation, normally used in the datalogger programs, is the quadratic equation

(SMC = 0.0007OP2 - 0.0063OP - 0.0663). The specific equation obtained in laboratory gravimetric calibration was SMC = -0.00003OP2 + 0.0339OP - 0.3863, with R2 = 0.9753.

The difference in volumetric water contents between the two curves varies between

11.9% and 25.1%, in average. These differences confirm that the original factory calibration (for mineral soils) would lead to underestimation of moisture content in the nursery substrate.

Figure 5-4 shows the variability of substrate moisture content monitored in containers used to grow magnolias under three different irrigation systems. Due to the irrigation management normally used by the farmer, all three irrigation systems resulted in moisture content values slightly below (before June 2003) or even above (after June

2003) the container capacity during the whole period of the field experiment. It is clear that the irrigation management strategy of the grower is on the safer side of the water supply for the plants. A slight trend of higher values of moisture content under ebb and flow system as compared to sprinkler and microirrigation systems can be observed during the entire season.

Conclusions

A calibration curve for TDR sensors in nursery growing medium was determined in laboratory. After the calibration, field monitoring of Substrate Moisture Content

(SMC), in cm3cm-3, as a function of the sensor Output Period (OP), in µs, was conducted during a period of 12 months in container-grown magnolia plants under three different irrigation systems:

• The calibration curve determined for the TDR sensors used in the growing medium used in the experiments was SMC = -0.00003OP2 + 0.0339OP - 0.3863, with R2 = 0.9753.

• The difference in volumetric water content between the calibration curve and the factory standard curve varied between 11.9% and 25.1%, in average, which confirms the need for a specific calibration for different media to avoid underestimation of moisture content.

• Under farmer’s management, the moisture contents under all three irrigation systems were slightly below (before June 2003) or above (after June 2003) the container capacity of the growing medium during the whole period of field monitoring.

Power Ground Output Enable Shield

3.2 cm 6.3 cm 30 cm 11 cm

Figure 5-1. Specifications of the Campbell Scientific CS616 TDR sensor used to monitor water content.

Figure 5-2. Time Domain Reflectometry sensor inserted in the substrate in the 56.8 liters (15 gallons) container used at the Holloway Tree Farm.

1.00

0.90 y = -3E-05x2 + 0.0339x - 0.3863 2 ) R = 0.9753 -3 0.80 cm 3

m 0.70

c Gravimetric ( Calibration nt

e 0.60 t n o 0.50 re C u t s i 0.40 2 o y = 0.0007x - 0.0063x - 0.0663 2

e M R = 1 t 0.30 a r

0.20

Subst Factory Standard Calibration 0.10

0.00 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 Output Period (µs)

SMC_Factory SMC_Gravimetric Poly. (SMC_Gravimetric) Poly. (SMC_Factory)

Figure 5-3. Calibration curve for the substrate used to grow magnolias at Holloway Tree Farm, Leesburg, FL.

1.00 ) -3 0.90 cm 3 0.80 m c 0.70

ntent ( 0.60 o C 0.50

0.40 isture o 0.30 ate M

r 0.20 t s 0.10 Sub 0.00

3 3 3 3 3 03 03 0 03 0 0 03 04 r r 0 l p t c b an 0 eb 03 un 03 u an 04 J F Ma Ap Nov De J Fe 1 5 2 6 30 J 7 1 0 0 1 1 21 May 25 J 03 Se 08 Oc 12 1 2 25

Date

Sprinkler Overhead TDR Microirrigation TDR Ebb and Flow TDR Figure 5-4. Substrate Moisture Content monitored in magnolia containers at Holloway Tree Farm, Leesburg, FL. (The horizontal dotted line indicates the container water capacity of the substrate).

CHAPTER 6 CONCENTRATION AND LOADS OF NUTRIENTS FROM A WOODY ORNAMENTAL NURSERY USING THREE DIFFERENT IRRIGATION SYSTEMS

Introduction

In the last ten years there has been an awakening of environmental consciousness in society. Agriculture and horticulture have had to face their polluting problems, such as the discharge of nutrients, the emission of pesticides and the waste of materials such as plastics and substrates for cultivation. Initial legislation of pollutants was rather drastic and not based on research. Later, forced by court judgments and social pressure, new regulations have set a timetable for all nurseries to adopt specific measures in order to decrease the leaching of water caring fertilizers and pesticides into the environment (Van

Os, 1999).

Container production of nursery crops is intensive and is a potential source of nitrogen release to the environment (Colangelo and Brand, 2001). According to Van Os

(1999) savings of up to 30% of water and up to 40% of fertilizers are possible in closed systems when compared to traditional open system production.

Nutrients are a limited resource and call for management. A sustainable nutrient management strategy reintegrates nutrients in the environment without accumulating harmful substances above an acceptable level (Lampert, 2003). Berankova and Ungerman

(1996) found a significant relationship between concentrations of nitrates in the runoff and application rates of mineral nitrogen fertilizers.

52 53

The objective of this study was to monitor and compare the concentrations and loads of nutrients originated from three different irrigation systems used in a woody ornamental nursery to produce containerized magnolias. The study also monitored the concentrations and loads of nutrients from the reservoir used in the farm for both rainwater harvesting and water supply to irrigation system at the farm.

Materials and Methods

This chapter presents and discusses the nutrient concentrations and loads contributed by three irrigation systems (overhead sprinkler, microirrigation, and ebb and flow) and the recirculation reservoir of the ebb and flow system to the environment. The study of nutrient concentration in the irrigation water of each system and in the reservoir started in March 2003 and was conducted until February 2004.

Water samples taken from the field once a month were taken to the UF/IFAS

Extension Soil Testing Laboratory (ESTL) to perform the analyses. The EPA methods used for the analyses were: EPA 360.1 for NH4-N, EPA 353.2 for NOx-N, EPA 351.2 for

TKN, and EPA 365.1 for Total P. TKN (Total Kjeldahl Nitrogen) refers to the organic nitrogen present in the water and Total N is the sum of NOx-N and TKN. The loads of all five nutrients were calculated from the concentrations of each nutrient multiplied by the amount of runoff from each system and from the reservoir.

The runoff from the reservoir was calculated based on the rainfall events that happened when the reservoir was already full. The total runoff volume was calculated based on the amount of additional rain and the total harvesting area that contributed to the recirculatory system. For the overhead sprinkler and microirrigation systems the runoff was collected from the production areas assigned to 6 selected plants from each experimental plot. The collection was made possible using a specially designed fiberglass

54 trays with dimensions coinciding with the plant spacing used at the farm and placing it under each of selected plants. The plant spacing in the nursery was a triangular spacing of

91.44 cm x 91.44 cm x 91.44 cm (3 ft x 3 ft x 3 ft), equivalent to rectangular spacing

91.44 cm x 79.25 cm (3 ft x 2.6 ft). Each of the six trays was connected through a polyethylene tube to an individual 190-liter plastic barrel buried outside of the experimental plot. Each of the 6 barrels accumulated the runoff water from the selected plant during approximately one week, when the water volume was measured and the barrels emptied to start a new collection cycle. The volumes of runoff presented in the tables are the monthly consolidation of the average runoff from 6 selected plants in each irrigation system.

Similarly, for the ebb and flow system a fiberglass box with the dimensions corresponding to the area assigned to each plant (91.4 cm x 79.2 cm or 3 ft x 2.6 ft) was used underneath of each selected plant to trap the water and allow the collection of the water sample (Figure 3-5).

Results and Discussions

Table 6-1 and Figures 6-1 through 6-5 show the concentrations of nutrients

(NH4-N, NO3-N, TKN, Total P, and Total N) in the water collected monthly from the irrigation systems and the reservoir. Table 6-2 and Figures 6-6 though 6-10 show the loads of all five nutrients calculated from the concentrations of each nutrient multiplied by the amount of runoff from each system and from the reservoir. Figure 6-11 illustrates the variability of concentration (mg L-1) of each nutrient in the reservoir water. Figure

6-12 presents the monthly loads (kg ha-1) of each nutrient released from reservoir throughout the period of 12 months of study.

Comparison of Concentrations from Irrigation Systems and Reservoir

Variability of concentrations for ammonia-N, nitrate-N, TKN, total P and total N in water collected from all three irrigation systems and from the reservoir during the

12-month period of monitoring are presented in Table 6-1 and Figures 6-1 through 6-5.

August 2003 was the month with highest levels of concentration for all 5 nutrients analyzed for overhead sprinkler and microirrigation systems. In this month, there was the second fertilizer application using a 4-month slow-release fertilizer (SRF) formula. The first SRF application was in June (12-month slow release formula).

Ammonia-N was found in very low concentrations in all months, except for

August, reaching maximum values of 14.20 mg L-1 for microirrigation and 10.91 mg L-1 for overhead sprinkler irrigation system. For ebb and flow system the maximum was

0.68 mg L-1 in Feb 2004, and for the reservoir the maximum was 0.41 mg L-1. These differences must be related to the effect of dilution that occur for the ebb and flow system and the reservoir due to the large amounts of water used, when compared to the two pressurized systems. The effect of dilution can be also seen for the other nutrients analyzed in this study.

Nitrate-N was found in highest concentrations among all five nutrients analyzed.

Nitrate-N concentration reached values above 10 mg L-1 in six out of 12 months of the period of study (from June to October and in December) for microirrigation system (with a maximum in August of 60.52 mg L-1). For overhead irrigation system it reached the value above 10 mg L-1 (20.15 mg L-1) only in August, soon after the second fertilizer application. Similar results were found by Colangelo and Brand (2001), where in their study leachate concentrations under trickle irrigation exceeded several times 10 mg L-1 of

Nitrate-N. As an example, for field crops, Hanna and Baker (2003) reported that a the

56 excess of water that drain from the root zone of a field growing corn optimally fertilized

-1 -1 with N, had high NO3-N concentrations (>10 mg L ). This value of 10 mg L is considered a limit of concentration for drinking water and may create a problem if the water is discharged into a source of drinking water. The ebb and flow system and the reservoir did not reach the limit at any time during the study. For the ebb and flow the maximum value was 6.38 mg L-1 and for the reservoir, all the values found were below

1.88 mg L-1 in all 12 months.

The highest concentration of TKN was 15.33 mg L-1 for microirrigation and the second highest was 11.62 mg L-1 for overhead sprinkler system, both in August. For the ebb and flow system and the reservoir the highest concentration were 4.44 mg L-1 and 5.7 mg L-1, respectively, both in April.

For total P, the highest concentration was 8.27 mg L-1, in August, for microirrigation. The overhead sprinkler system presented much lower concentrations in all months with a maximum of 2.22 mg L-1 also in August. The maximum concentration of total P in the water collected under ebb and flow system was 1.22 mg L-1, in April, and in the reservoir it was 0.76 mg L-1 in February.

Since total N is the sum of nitrate-N and TKN, and nitrate-N was in higher than

TKN concentrations during all 12 months, the variability of total N follows the same pattern as nitrate-N. There was a peak of 75.85 mg L-1, in August, for microirrigation.

The peak for overhead sprinkler was also in August when concentration was

31.77 mg L-1. The peak concentration for the ebb and flow system (6.99 mg L-1) occurred in July, and, the maximum value for the reservoir (6.33 mg L-1) was measured in April.

Comparison of Loads from Irrigation Systems and Reservoir

Table 6-2 and Figures 6-6 though 6-10 show the variability of loads of those 5 nutrients from all three irrigation systems and the reservoir. Ammonia-N was the chemical with lowest values of loads among all 5 nutrients during the entire period of the study. All values of loads were below 2.0 kg ha-1 for all chemicals and months. In

November the value was zero for all three systems and the reservoir since Ammonia-N was not detected in the runoff samples. In December, insignificant values were recorded, such as 0.04 kg ha-1. The maximum load values of ammonia-N for microirrigation

(1.37 kg ha-1) and overhead sprinkler (1.14 kg ha-1) systems occurred in August, the month when there was a fertilizer application. For the ebb and flow system and the reservoir all the values were lower than 1.0 kg ha-1 and were zero in 5 and 7 months, out of 12, respectively.

Loads of nitrate-N reached higher values for microirrigation (5.88 kg ha-1) and overhead sprinkler (2.05 kg ha-1) in August. For the ebb and flow irrigation system the maximum was 1.44 kg ha-1 in July. The highest value for the reservoir was 3.19 kg ha-1 in

March.

The maximum load of TKN in the 12-month period of study was 4.59 kg ha-1 (in

August) for the reservoir. For all three irrigation systems, the values were lower than

2.0 kg ha-1 in all months, with 1.49 kg ha-1 for microirrigation and 1.20 kg ha-1 for overhead sprinkler, also in August, and 1.29 kg ha-1 for ebb and flow in April. For the reservoir, the peak of TKN load was in August with 4.6 kg ha-1, followed by June

(3.8 kg ha-1), and the loads in all the other months were below 3.0 kg ha-1.

As discussed before, there is a contribution of water from rainfall to the reservoir.

There is also an option of adding the water from the well to the reservoir, if necessary.

Organic material and chemicals that come from all 13 flood plains irrigated by ebb and flow irrigation system are collected in the reservoir water. The irrigation management, chemical applications, and other agricultural practices follow different schedules for all

13 flood plains throughout the year. As a result, the loads from the ebb and flow experimental system are not necessarily directly related to the loads in the reservoir that are reflecting the concentrations from all 13 flood plains.

Total P load maximum value was 1.16 kg ha-1 for the reservoir, in August. All the other values of total P loads were lower than 1.0 kg ha-1 for all three irrigation systems and the reservoir in all 12 months of study. The ebb and flow system concentration was zero in 6 month (out of 12) and the reservoir in 7 month (out of 12) resulting in zero loads of this nutrient for the above months of study.

Total N loads followed a similar tendency as Nitrate-N loads for overhead sprinkler and microirrigation systems throughout the year, with a peak value in August

(3.25 kg ha-1 and 7.37 kg ha-1, respectively). Total N load maximum value for ebb and flow system was 1.58 kg ha-1 and for the reservoir was 6.38 kg ha-1.

Discussion of Concentrations from the Reservoir

The reservoir nutrient data (Table 6-1) show that the concentration of NH4-N was below 0.5 mg L-1 during all 12 months of monitoring. In two months (November 2003 and December 2003) the concentration was zero. The highest value found was

0.41 mg L-1 in May 2003, followed by 0.37 mg L-1 and 0.38 mg L-1 in August 2003 and

September 2003, respectively. In all other months the concentrations of NH4-N were below 0.15 mg L-1.

-1 For NO3-N, the highest concentration in the reservoir was 1.88 mg L in March

2003, while the lowest was 0.06 mg L-1 in two months (October 2003 and January 2004).

Considering the EPA limit of 10 mg L-1 for nitrate-N present in water, due to human health concerns, all the concentrations found in the reservoir were very low and do not represent a health problem. For TKN, the concentrations were much higher than NO3-N, since the reservoir water was very rich in organic material returning from the flood plains to the reservoir. The TKN concentration values ranged from 1.51 mg L-1 (March 2003) to

5.75 mg L-1 (April 2003). Similar analysis can be done for Total N, since it is the sum of

-1 nitrate-N (NO3-N) and TKN. Total N values varied from 1.45 mg L (November 2003) to 6.36 mg L-1 (April 2003).

All the concentrations for total P were below 1.0 mg L-1, varying from zero in Oct

2003 to 0.76 mg L-1 in Feb 2004. However, this concentration of phosphorus may represent a problem, since the limit imposed by (FDEP, 2003) for water discharged to the environment is 10 µg L-1, or 1,000 times less than the nitrate limit.

From Figure 6-11, it can be noticed that there is a certain pattern for the variability of the concentrations of TKN and Total N throughout the 12-month period of study, probably due to the relevant influence of the organic material in these two parameters.

There is a peak in April, followed by a decrease until December, when the values start to increase again. There is a tendency for the other nutrients to follow the same pattern, however, a different pattern can be observed for NO3-N. This likely can be attributed to the irregular pattern of precipitation and normal production practices at the farm, like application of fertilizers to all 13 flood plains independently from each other, removal and replacement of plants of different species, sizes and ages throughout the seasons.

Analyzing Loads from the Reservoir

There were 7 months (out of 12) with no loads of all nutrients released to the environment from the reservoir (Table 6-2) since there was no runoff overflow to the environment. Analyzing the seasons of the year, all 3 months of the summer 2003 (June,

July, and August), plus one month of spring 2003 (March), and one month of winter of

2003/2004 (February) contributed some loads of all nutrients to the environment. No load was observed during fall 2003 from the reservoir due to the low rainfall that was evenly distributed throughout this period. Because of the absence of runoff in some of the months and due to the different values of runoff and concentrations in each month, the pattern for the loads during the 12-month period does not follow the same trends as the concentration of nutrients (Figures 6-11 and 6-12). The highest loads were observed in

-1 -1 Aug 2003. The amounts released were: NH4-N = 0.68 kg ha , TKN = 4.59 kg ha , Total

-1 -1 P = 1.16 kg ha , and Total N = 6.38 kg ha . For NO3-N, the highest load was

3.19 kg ha-1 in Mar 2003.

Disregarding the months without any discharge from the reservoir, several observations can be made regarding the loads from the reservoir. The lowest load of

-1 NH4-N (0.05 kg ha ) occurred in Mar 2003. For NO3-N and TKN, the lowest loads happened in Feb 2004 with values of 0.41 kg ha-1 and 1.84 kg ha-1, respectively. The lowest loads of TKN (2.15 kg ha-1) and Total P (0.39 kg ha-1) occurred in Jun 2003.

The total loads for the whole period of 12 months released from the reservoir to

-1 -1 -1 the environment were 1.01 kg ha (NH4-N), 7.21 kg ha (NO3-N), 14.48 kg ha (TKN),

3.40 kg ha-1 (Total P), and 21.68 kg ha-1 (Total N).

During this study period, under the management practices used in the farm and with the given precipitation, the runoff from the reservoir was concentrated during the 3 summer months and in February and March (Figure 6-12).

Conclusions

Concentrations of nutrients (NH4, NO3, TKN, Total P, and Total N) in the water collected monthly from the irrigation systems (overhead sprinkler, microirrigation, and ebb and flow) and the concentration of nutrients in the overflow from the recirculation reservoir were monitored for 12 months (March 2003 to February 2004). Monthly and annual loads of all five nutrients were calculated from the concentrations of each nutrient multiplied by the amount of runoff from each system and from the reservoir.

For the Period of Study

• All the concentration values for total P in the reservoir were below 1.0 mg L-1, varying from zero in Oct 2003 to 0.76 mg L-1 in Feb 2004. However, this concentration of phosphorus may represent a problem, since the limit is 10 µg L-1, or 1,000 times less than the nitrate limit. The loads for total P were below 1.16 kg ha-1 for all the irrigation systems and the reservoir in all 12 months.

• The variability of concentration of NH4, NO3, TKN, total P and total N in water was most dependent on the time of fertilizer applications. The highest level of concentration for all 5 nutrients analyzed occurred in August 2003 when there was the second fertilizer application during the study period.

• Considering the EPA limit of 10 mg L-1 for Nitrate all the values of concentrations found in the reservoir were very low and do not represent a health problem. For TKN, the concentrations were much higher than NO3, since the reservoir water was very rich in organic material returning from the flood plains to the reservoir.

• Total N loads had a similar tendency in variability throughout the year as Nitrate-N loads for overhead sprinkler and microirrigation systems with a peak value in August (3.25 kg ha-1 and 7.37 kg ha-1, respectively). Total N load maximum value for ebb and flow system was 1.58 kg ha-1 (in July 2003) and for the reservoir was 6.38 kg ha-1 (in August 2003).

• Reservoir in general presented lowest values of concentrations and loads of all nutrients during the whole period of study compared to overhead sprinkler and microirrigation systems and the ebb and flow.

• For the reservoir specifically, there were 7 months (out of 12) with no loads (for all nutrients) since there was no runoff overflow from the reservoir. The absence of runoff in some of the months and the different values of runoff and concentrations in each month promoted a different variability pattern for concentrations and loads during the 12-month period. August was the month with highest releases to the environment for most of the nutrients, except for nitrate: 0.68 kg ha-1 (NH4-N); -1 -1 -1 4.59 kg ha (TKN); 1,16 kg ha (total P) and 6,38 kg ha (total N) For NO3-N, the highest load was 3.19 kg ha-1 in March 2003.

• The total loads for the whole period of 12 months released from the reservoir to the -1 -1 -1 environment were 1.01 kg ha (NH4-N), 7.21 kg ha (NO3-N), 14.48 kg ha (TKN), 3.40 kg ha-1 (Total P), and 21.68 kg ha-1 (Total N).

• During this study period, under the management practices used in the farm and with the given precipitation, the runoff from the reservoir was concentrated in March 2003, during the summer 2003 (June, July, and August) and in February 2004.

For Each Nutrient

• Ammonia was found in very low concentrations in all months, except for August, reaching values of 14.20 mg L-1 for microirrigation and 10.91 mg L-1 for overhead sprinkler irrigation system. Very low values were observed for the other months. For ebb and flow system and the reservoir, the highest values were 0.68 mg L-1 (February 2004) and 0.41 mg L-1 (May 2003), respectively. Ammonia was also the chemical with lowest values of loads (below 1.4 kg ha-1 from microirrigation system) among all 5 nutrients studied for the entire period.

• Nitrate was found in highest concentrations among all five nutrients analyzed. The highest value of nitrate concentration was 60.52 mg L-1, for microirrigation system, in August. In 6 out of 12 months it was above 10 mg L-1 for microirrigation system and only in August for overhead sprinkler irrigation system. For the reservoir, all the values found were below 1.88 mg L-1 in all 12 months. Loads of nitrate reached highest value for microirrigation 5.88 kg ha-1 in August, among all months, compared to overhead sprinkler (2.05 kg ha-1) and the reservoir (3.19 kg ha-1).

• The highest concentration of TKN was 15.33 mg L-1 for microirrigation and the second highest was 11.62 mg L-1 for overhead sprinkler system, both in August. For the reservoir, the highest concentration was 5.75 mg L-1, both in April. Load of TKN reached the peak in August, for the reservoir, with 4.59 kg ha-1. Overhead irrigation and microirrigation systems had TKN loads were lower than 1.5 kg ha-1 (in August).

• For total P, the highest concentration was 8.27 mg L-1, in August, for microirrigation. The overhead sprinkler system presented much lower concentrations in all months with a maximum of 2.22 mg L-1 in August. The

maximum concentration of total P from ebb and flow system was 1.22 mg L-1 in April 2003, and in the reservoir was 0.76 mg L-1 in February 2004.

• Since total N is the sum of nitrate-N and TKN, and nitrate-N was in much higher concentrations during all 12 months, the variability follows the same pattern as nitrate-N. There was a peak of 75.85 mg L-1, in August, for microirrigation. The peak for overhead sprinkler was also in August when concentration was 31.77 mg L-1. In July occurred the highest value for ebb and flow system (6.99 mg L-1) and in April was the maximum value for the reservoir (6.4 mg L-1).

Table 6-1. Concentration of nutrients (mg L-1) in water during a 12-month period at Holloway Tree Farm, Leesburg, FL. Overhead Sprinkler Microirrigation Date NH4 NO3 TKN Total P Total N NH4 NO3 TKN Total P Total N Mar 03 0.03 1.43 0.58 0.13 2.01 0.03 2.91 1.13 0.30 4.04 Apr 03 0.04 5.54 3.25 0.49 8.79 0.04 1.85 1.76 1.28 3.61 May 03 0.07 0.33 0.37 0.10 0.70 0.08 0.37 4.32 0.25 4.69 Jun 03 0.08 1.07 0.49 0.26 1.56 1.19 33.00 6.79 1.83 39.79 Jul 03 0.17 0.70 0.30 0.07 1.00 0.50 38.25 1.73 2.46 39.98 Aug 03 10.91 20.15 11.62 2.22 31.77 14.20 60.52 15.33 8.27 75.85 Sep 03 0.19 6.77 1.11 0.90 7.88 0.14 32.90 1.24 4.46 34.14 Oct 03 0.13 5.14 0.78 0.65 5.92 0.12 23.19 1.17 3.21 24.36 Nov 03 0.00 0.99 1.56 0.94 2.55 0.01 6.49 3.93 2.15 10.41 Dec 03 0.48 2.86 2.24 1.66 5.10 0.08 14.38 1.43 5.17 15.81 Jan 04 0.01 5.15 1.00 1.79 6.14 0.02 7.00 1.91 4.84 8.91 Feb 04 0.04 5.40 1.38 1.37 6.78 0.02 5.89 1.78 3.46 7.66 Maximum 10.91 20.15 11.62 2.22 31.77 14.20 60.52 15.33 8.27 75.85 Average 1.01 4.63 2.06 0.88 6.68 1.37 18.90 3.54 3.14 22.44 Minimum 0.00 0.33 0.30 0.07 0.70 0.01 0.37 1.13 0.25 3.61

Ebb and Flow Reservoir Date NH4 NO3 TKN Total P Total N NH4 NO3 TKN Total P Total N Mar 03 0.06 1.53 2.00 0.05 3.52 0.03 1.88 1.51 0.41 3.39 Apr 03 0.00 0.41 4.44 1.22 4.85 0.10 0.61 5.75 0.10 6.36 May 03 0.00 0.00 3.12 0.00 3.12 0.41 0.13 3.87 0.75 4.00 Jun 03 0.10 0.58 1.72 0.17 2.30 0.09 1.05 3.27 0.65 4.33 Jul 03 0.15 6.38 0.62 0.41 6.99 0.14 0.99 3.48 0.62 4.47 Aug 03 0.03 0.68 0.04 0.21 0.72 0.37 0.98 2.52 0.64 3.50 Sep 03 0.09 0.78 0.52 0.26 1.30 0.38 0.15 2.27 0.34 2.42 Oct 03 0.01 0.11 0.02 0.00 0.13 0.13 0.06 2.74 0.00 2.80 Nov 03 0.00 0.83 1.19 0.00 2.02 0.00 0.35 1.10 0.52 1.45 Dec 03 0.00 0.04 0.21 0.00 0.25 0.00 0.08 2.02 0.46 2.10 Jan 04 0.28 3.49 0.88 0.00 4.37 0.05 0.06 1.77 0.19 1.83 Feb 04 0.68 0.21 0.86 0.00 1.08 0.15 0.76 2.61 0.76 3.37 Maximum 0.68 6.38 4.44 1.22 6.99 0.41 1.88 5.75 0.76 6.36 Average 0.12 1.25 1.30 0.19 2.55 0.16 0.59 2.74 0.45 3.33 Minimum 0.00 0.00 0.02 0.00 0.13 0.00 0.06 1.10 0.00 1.45

Table 6-2. Loads of nutrients (kg ha-1) in water during a 12-month period at Holloway Tree Farm, Leesburg, FL. Overhead Sprinkler Microirrigation Date NH4 NO3 TKN Total P Total N NH4 NO3 TKN Total P Total N Mar 03 0.00 0.07 0.03 0.01 0.10 0.00 0.14 0.05 0.01 0.19 Apr 03 0.01 1.47 0.93 0.14 2.40 0.00 0.17 0.16 0.13 0.33 May 03 0.01 0.05 0.06 0.02 0.11 0.00 0.02 0.24 0.01 0.26 Jun 03 0.01 0.13 0.06 0.03 0.19 0.12 3.33 0.68 0.18 4.01 Jul 03 0.01 0.05 0.02 0.01 0.08 0.04 3.46 0.16 0.23 3.62 Aug 03 1.14 2.05 1.20 0.24 3.25 1.37 5.88 1.49 0.80 7.37 Sep 03 0.02 0.67 0.10 0.09 0.77 0.01 2.80 0.09 0.38 2.89 Oct 03 0.04 1.42 0.22 0.18 1.64 0.00 0.74 0.04 0.11 0.77 Nov 03 0.00 0.26 0.41 0.25 0.67 0.00 0.58 0.32 0.20 0.90 Dec 03 0.03 0.21 0.17 0.13 0.39 0.00 0.07 0.01 0.02 0.07 Jan 04 0.00 0.45 0.09 0.15 0.53 0.00 0.38 0.10 0.25 0.47 Feb 04 0.00 0.59 0.15 0.15 0.74 0.00 0.31 0.10 0.19 0.40 12-Month 1.28 7.43 3.44 1.38 10.86 1.56 17.87 3.42 2.52 21.29

Ebb and Flow Reservoir Date NH4 NO3 TKN Total P Total N NH4 NO3 TKN Total P Total N Mar 03 0.02 0.52 0.68 0.02 1.19 0.05 3.19 2.55 0.70 5.74 Apr 03 0.00 0.12 1.29 0.36 1.41 0.00 0.00 0.00 0.00 0.00 May 03 0.00 0.00 0.71 0.00 0.71 0.00 0.00 0.00 0.00 0.00 Jun 03 0.02 0.15 0.44 0.04 0.58 0.11 1.21 3.76 0.74 4.97 Jul 03 0.03 1.44 0.14 0.09 1.58 0.09 0.61 2.15 0.39 2.76 Aug 03 0.01 0.20 0.01 0.06 0.21 0.68 1.79 4.59 1.16 6.38 Sep 03 0.02 0.20 0.13 0.07 0.33 0.00 0.00 0.00 0.00 0.00 Oct 03 0.00 0.02 0.00 0.00 0.03 0.00 0.00 0.00 0.00 0.00 Nov 03 0.00 0.17 0.24 0.00 0.41 0.00 0.00 0.00 0.00 0.00 Dec 03 0.00 0.01 0.03 0.00 0.03 0.00 0.00 0.00 0.00 0.00 Jan 04 0.02 0.27 0.07 0.00 0.34 0.00 0.00 0.00 0.00 0.00 Feb 04 0.17 0.05 0.22 0.00 0.27 0.08 0.41 1.42 0.41 1.84 12-Month 0.31 3.14 3.95 0.64 7.09 1.01 7.21 14.48 3.40 21.68

Ammonia

60 ) -1

g L 50 m ( n o i 40 at r t Fertilizer Fertilizer

cen 30 Application Application n

o (June) (August)

C 20

0 Mar/03 Apr/03 May/03 Jun/03 Jul/03 Aug/03 Sep/03 Oct/03 Nov/03 Dec/03 Jan/04 Feb/04

Overhead Sprinkler Microirrigation Ebb and Flow Reservoir

Figure 6-1. Variability of concentration of ammonia-N in water during a 12-month period at Holloway Tree Farm, Leesburg, FL.

Nitrate

60 ) -1

L Fertilizer Fertilizer g 50

m Application Application ( (June) (August) on i

t 40 a r

ent 30 onc

C 20 10 ppm 10

0 Mar/03 Apr/03 May/03 Jun/03 Jul/03 Aug/03 Sep/03 Oct/03 Nov/03 Dec/03 Jan/04 Feb/04

Overhead Sprinkler Microirrigation Ebb and Flow Reservoir

Figure 6-2. Variability of concentration of nitrate-N in water during a 12-month period at Holloway Tree Farm, Leesburg, FL.

TKN

60 ) -1

g L 50 m n ( o i 40 at r t Fertilizer Fertilizer

cen 30 Application Application n

o (June) (August)

C 20

0 Mar/03 Apr/03 May/03 Jun/03 Jul/03 Aug/03 Sep/03 Oct/03 Nov/03 Dec/03 Jan/04 Feb/04

Overhead Sprinkler Microirrigation Ebb and Flow Reservoir

Figure 6-3. Variability of concentration of TKN in water during a 12-month period at Holloway Tree Farm, Leesburg, FL.

Total P

60 ) -1

g L 50 m ( n o i 40 at r t Fertilizer Fertilizer en

c 30 Application Application n

o (June) (August) C 20

0 Mar/03 Apr/03 May/03 Jun/03 Jul/03 Aug/03 Sep/03 Oct/03 Nov/03 Dec/03 Jan/04 Feb/04

Overhead Sprinkler Microirrigation Ebb and Flow Reservoir

Figure 6-4. Variability of concentration of total P in water during a 12-month period at Holloway Tree Farm, Leesburg, FL.

Total N

60 Fertilizer Fertilizer )

-1 Application Application L g 50 (June) (August) m ( on i 40 at r t n e 30 onc

C 20

0 Mar/03 Apr/03 May/03 Jun/03 Jul/03 Aug/03 Sep/03 Oct/03 Nov/03 Dec/03 Jan/04 Feb/04

Overhead Sprinkler Microirrigation Ebb and Flow Reservoir

Figure 6-5. Variability of concentration of total N in water during a 12-month period at Holloway Tree Farm, Leesburg, FL.

Ammonia

20 ) -1 15 ha g k ( d 10 Loa Fertilizer Fertilizer Application Application (June) (August) 5

0 Mar/03 Apr/03 May/03 Jun/03 Jul/03 Aug/03 Sep/03 Oct/03 Nov/03 Dec/03 Jan/04 Feb/04

Overhead Sprinkler Microirrigation Ebb and Flow Reservoir

Figure 6-6. Variability of loads of ammonia-N in water during a 12-month period at Holloway Tree Farm, Leesburg, FL.

Nitrate

20 )

-1 15 ha

k Fertilizer ( Fertilizer

ad Application Application 10 (June)

Lo (August)

0 Mar/03 Apr/03 May/03 Jun/03 Jul/03 Aug/03 Sep/03 Oct/03 Nov/03 Dec/03 Jan/04 Feb/04

Overhead Sprinkler Microirrigation Ebb and Flow Reservoir

Figure 6-7. Variability of loads of nitrate-N in water during a 12-month period at Holloway Tree Farm, Leesburg, FL.

TKN

20 Fertilizer Fertilizer Application Application ) -1 15 (June) (August) ha g k (

ad 10 Lo

0 Mar/03 Apr/03 May/03 Jun/03 Jul/03 Aug/03 Sep/03 Oct/03 Nov/03 Dec/03 Jan/04 Feb/04

Overhead Sprinkler Microirrigation Ebb and Flow Reservoir

Figure 6-8. Variability of loads of TKN in water during a 12-month period at Holloway Tree Farm, Leesburg, FL.

Total P

20 )

-1 15 ha

g k ( d a 10

Lo Fertilizer Fertilizer Application Application (June) (August) 5

0 Mar/03 Apr/03 May/03 Jun/03 Jul/03 Aug/03 Sep/03 Oct/03 Nov/03 Dec/03 Jan/04 Feb/04

Overhead Sprinkler Microirrigation Ebb and Flow Reservoir

Figure 6-9. Variability of loads of total P in water during a 12-month period at Holloway Tree Farm, Leesburg, FL.

Total N

20 ) -1 15 g ha k

( Fertilizer Fertilizer d 10 Application Application

Loa (June) (August)

0 Mar/03 Apr/03 May/03 Jun/03 Jul/03 Aug/03 Sep/03 Oct/03 Nov/03 Dec/03 Jan/04 Feb/04

Overhead Sprinkler Microirrigation Ebb and Flow Reservoir

Figure 6-10. Variability of loads of total N in water during a 12-month period at Holloway Tree Farm, Leesburg, FL.

Reservoir

80.0

70.0

60.0 ) -1 50.0

40.0

30.0

oncentration (mg L Fertilizer Fertilizer C 20.0 Application Application (June) (August) 10.0

0.0 Mar/03 Apr/03 May/03 Jun/03 Jul/03 Aug/03 Sep/03 Oct/03 Nov/03 Dec/03 Jan/04 Feb/04

NH4 NO3 TKN Total_P Total_N

Figure 6-11. Variability of concentration of nutrients detected in the reservoir at Holloway Tree Farm, Leesburg, FL.

Reservoir

25.0

20.0 ) -1 15.0

Fertilizer Fertilizer Application Application 10.0 (June) (August) Loads (kg ha

5.0

0.0 Mar/03 Apr/03 May/03 Jun/03 Jul/03 Aug/03 Sep/03 Oct/03 Nov/03 Dec/03 Jan/04 Feb/04

NH4 NO3 TKN Total_P Total_N

Figure 6-12. Variability of loads of nutrients released from the reservoir at Holloway Tree Farm, Leesburg, FL

CHAPTER 7 RAINWATER HARVESTING EFFECTIVENESS OF A RECIRCULATORY SYSTEM USED FOR IRRIGATION OF CONTAINER-GROWN WOODY ORNAMENTALS

Introduction

The world's supply of fresh water is finite and is threatened by pollution. Rising demands for water to supply agriculture, industry and cities are leading to competition over the allocation of limited fresh water resources (Anderson, 2003). Groundwater resources are often used for irrigation in competition with urban use, causing serious shortages (Gori and Lubello, 2000).

Water management is an essential feature of any project related with overall development of agriculture (Goel and Kumar, 2004). Sufficient water commonly represents one crucial factor in farmers' yearly gamble in securing a harvest. (Fox and

Rockstrom, 2000). Rainwater harvesting has a potential of addressing spatial and temporal water scarcity for domestic, crop production, livestock development, environmental management and overall water resources management (Ngigi, 2003).

Collecting and storing rainwater has been going on for hundreds of years with benefits of having a source of water for supplemental irrigation and reducing the amount of groundwater used for irrigation (Bargar, 2004). For nursery crop production, runoff, leachate, and rainwater could be captured and used as a source for irrigation water (Chen et al., 2003)

In Florida about 95% of drinking water comes from groundwater (Bargar, 2004) and there are more than 7,000 registered nursery growers (DPI, 2004). Since ornamental

72 73 plant production is traditionally a heavy user of potable water (Chen et al., 2002), it is very important to evaluate technologies and practices that have the potential to improve the efficiency of rainwater harvesting for nursery farms in Florida.

The objective of this study was to analyze the rainwater harvesting effectiveness of a recirculatory system in use for irrigation purposes in a woody ornamental nursery in central Florida for container-grown plant production.

Materials and Methods

Local precipitation data and the changes in reservoir water level were monitored daily for two years. The daily data were recorded locally by the farmer using his instrumentation and techniques and then were consolidated into monthly information.

The instrumentation consists of a manual rain gauge, a graduated scale for manual water level readings and a flow meter for measuring the water from the well added to the reservoir. This data collection is a part of a normal daily practice at the farm. All the measurements were made in English Units (inches), with two significant decimal digits, and converted into SI units (mm), rounding up to only one significant decimal digit, for the purpose of this analysis. The objective was to analyze the recirculatory system using simple water balance to determine the efficiency of the system in rainwater harvesting and ability to avoid or minimize runoff overflows. The overflows represent precipitation losses from the system and could represent potential agrochemical pollution to the environment.

The water balance took into consideration rainfall events and the reservoir water levels recorded during the studied period. A harvesting area of 4.1 ha, which is a sum of the plastic-covered areas of 13 flood plains and the reservoir, was used for all the calculations of harvested and lost precipitation. Harvested rainwater refers to the total

74 amount of rain that fell in the harvesting area and lost precipitation refers to the amount of harvested rainwater that did not remain in the recirculatory system since it was lost as an overflow from the reservoir. It was assumed that at the time when reservoir was full, the pot media was saturated and all additional rainfall falling on the plastic covered flood plains area and reservoir area was running off from the system. For detecting the exact moment when the reservoir was at full level, an electronic water level sensor (CS420-L

Submersible Pressure Transducer, Campbell Scientific, Inc., Logan UT) installed in the reservoir was used. The sensor was connected to a datalogger to accumulate readings every 15 minutes. The information was downloaded weekly from the datalogger and used to follow the daily variation of the reservoir water level and to compare them with the data collected by the farmer. A set of manual readings was made specifically to check the calibration of the sensor after installation. With the sensor readings every 15 minutes, it was easy to identify the rainfall events that should be accounted as precipitation losses, due to overflow, when comparing the level readings to the threshold for the reservoir full level. The reservoir full level threshold was identified as 1.7 m (66.9 in) using on-site observations and manual readings.

The Harvesting Effectiveness (HE), the Precipitation Losses (PL), and the Storage

Effectiveness (SE) for the recirculatory system were calculated for each month using

Equations 7-1, 7-2, and 7-3, respectively:

Harvesting Effectiveness (HE):

HP − LP HE = ×100 (7-1) HP where

HE = Harvesting Effectiveness (%)

HP = Harvested Precipitation (m3) LP = Lost Precipitation (m3)

Precipitation Losses (PL):

LP PL = ×100 (7-2) HP where:

PL = Precipitation Losses (%) LP = Lost Precipitation (m3) HP = Harvested Precipitation (m3)

Storage Effectiveness (SE):

TI − LP SE = ×100 (7-3) TI where

SE = Storage Effectiveness (%) TI = Total Input (TI = HP + WW) of water to reservoir (m3) HP = Harvested Precipitation (m3) WW = Well Water added to reservoir (m3) LP = Lost Precipitation (m3)

Harvesting Effectiveness (HE) is an indicator of how effective the recirculatory system was in saving the rainwater harvested in the reservoir in relation to the total harvesting area (4.1 ha). It is a ratio of the rainwater runoff saved to the total harvested rainwater. The Precipitation Losses (PL) is an indicator of how much of the rainwater is lost to the environment instead of being kept in the reservoir for irrigation purposes. It is a ratio of rainwater that fell in the area when the reservoir was already at full level, not able to take more volume of water, to the amount of total harvested water. Storage

Effectiveness (SE) is the indicator of how effective the system was in storing water from any source (precipitation and/or added well water) that entered the reservoir, contributing

76 to fill up its volume during each month. It is a ratio of the stored water (from any source) in the reservoir to the total input of water to the system.

In June 2003, the farmer redesigned the system so the reservoir water could be also used in another section of the nursery and changed the way the reservoir was managed.

As a result, the data could be subdivided into two groups that were analyzed separately.

Initially, only plants grown on the flood plains (3.63 ha) were using harvested rainwater.

After redesigning, the pressurized systems (10.12 ha of microirrigation and overhead sprinkler irrigation) were also supplied with water from the reservoir. Well water was added to the reservoir when needed, if there was not enough precipitation. By pumping additional water out of the reservoir to supply additional irrigated area, the farmer expected to increase harvesting effectiveness and storage effectiveness and minimize the runoff to the environment and the groundwater withdrawals.

Results and Discussion

Rainwater Harvesting and Recirculatory System

Figure 7-1 illustrates the variation of the reservoir level recorded with both sensor measurements (every 15 minutes) and manual farmer readings that were performed (once a day every morning). Figure 7-2 shows an example of one overflow event representing precipitation losses from the recirculatory system.

Tables 7-1 and 7-2 present the results from a 24-month period (from September

2002 through August 2004) of daily reservoir water level monitoring, rainfall that occurred at the Holloway Tree Farm, and the additional well water added to the reservoir.

Monthly information presented in Table 7-1 is a consolidation of the daily data recorded by the farmer using his instrumentation and techniques.

The total rainfall during 24 months of monitoring was 2,840 mm, and the total volume of the harvested rainwater was 116,541 m3. The total amount of well water added to the reservoir was 23,669 m3, resulting in a total of 140,210 m3 of water input to the system. The total amount of precipitation detected as producing overflow to the reservoir with consequent runoff from the system was 981 mm, meaning precipitation losses to the environment of 40,265 m3. This amount of precipitation losses represents 34.6% of the total harvested precipitation and 28.7% of the total water inputs (rainwater plus well water) to the reservoir during the monitored period.

The month with the lowest amount of rain was May 2003, with 21.6 mm, and the month with the largest amount of rain was Jun 2003, with 323.9 mm. Consequently, May

2003 and June 2003 were the months with the smallest and the largest amount of harvested water in 24 months, respectively 886 m3 and 13,291 m3. These amounts represent, respectively, 0.8% and 11.4% of the total harvested precipitation in the whole period of 24 months. In May 2003, the farmer needed to add 3,031 m3 of well water to the reservoir due to the low amount of precipitation. In June 2003, due to the lack of precipitation in the first week, the farmer added 598 m3 of well water. June was also the month with largest amount of total input of water (rain plus well) to the reservoir

(13,889 m3, followed by December 2002 (10,736 m3) and by August 2004 (10,372 m3), with the other months below 10,000 m3 of total input of water.

As a result of low rainfall in May, the reservoir level at the end of the month was low enough to accommodate a very large amount of rainwater harvested in June

(13,291 m3), resulting in a very large amount of stored water (9,719 m3), the second highest, corresponding to 68.6% of the total harvested rainwater, and 70.0% of the total

78 input of water. Even though, June still had a large amount of precipitation losses

(4,170 m3), the fifth largest, representing 31.4% of the harvested precipitation and 30.0% of the total input. This is due to the exceptionally high rainfall (323.9 mm) during this month.

The precipitation was very irregular during the 24-month study period. The total amount of runoff from the reservoir (981 mm; 40,265 m3) was generated by an irregular series of monthly totals. The distribution of the events was critical to the effectiveness of the storage. In the short period of four months of 2002, the lowest amount of rain was

31.8 mm in October and the highest was 246.4 mm in December. In these four months, the farmer added well water to the reservoir, with volumes ranging from 625 m3

(December 2002) to 4,864 m3 (October 2002). For 2003, the monthly amount of rain varied from 21.6 mm to 323.9 mm, which occurred in the consecutive months of May and June. Similar to what happened in the last four months of 2002, the farmer needed to add well water from September (4,308 m3) to December (104 m3) because of the low amount of rainwater available [September (73.7mm), October (50.8 mm), November

(30.5 mm), and December (57.2 mm)]. For 2004, in the eight months monitored, the lowest amount of rainfall was 24.1 mm in April and the highest was 252.7 mm in August.

In 2004, only in June the farmer added well water (728 m3) to the reservoir.

Due to the great variability of precipitation during the 24 months, and also due to the water removal from the reservoir for irrigation throughout the seasons, the monthly amount of precipitation losses varied greatly from zero (in 13 out of the 24 monitored months) to 6,619 m3 in August 2003. In 10 of the 13 months without overflow, the rainfall amounts were of 76.2 mm or smaller, except for June, July, and August of 2004,

79 with totals of 115.6 mm, 128.3 mm, and 252.7 m, respectively. The lack of overflow in these three months can be probably attributed to the higher demand for irrigation, since the reservoir supplied water to a larger area of the farm in 2004. This suggests that the addition of the pressurized systems to the reservoir as a source of irrigation water contributed to reduction of the runoff from the recirculatory system.

The smallest amount of precipitation losses, excluding the months with no losses, happened in Mar 2004 (1,042 m3), representing 33.3% of the harvested water in this month and 2.6% of the total amount of precipitation lost in all 24 months. The reasons for that may reside in the amount of precipitation that occurred during that month (76.2 mm).

The largest amount of precipitation losses occurred in August 2003 (6,619 m3), corresponding to 70.9% of the total harvested rainwater in the month, and 16.4% of the total amount of precipitation lost during the 24-month period of monitoring. The amount of precipitation that occurred in this month (227.3 mm) was high and it followed two months with relatively high amount of precipitation, June 2003 (323.9 mm) and July

2003 (218.4 mm), so there was little storage space available in the reservoir.

The proportion of the harvested water that was discharged as runoff showed an irregular pattern in the 24-month period. Figure 7-3 illustrates this variability across the seasons. It can be observed that there is no repeated pattern during the same seasons from one year to the other. The lowest amount of precipitation losses (25.0%) occurred in

July 2003 with 2,241 m3, representing 5.6% of the total amount of precipitation lost in

24-month period. The highest amount of precipitation losses (95.9%) occurred in January

2003 with 2,411 m3, representing 6.0% of the total amount of precipitation lost during the

24-month period.

Comparing the winter of 2002/2003 with the winter of 2003/2004, it was found that there was no similar pattern. December 2002 had 4.3 times more harvested rainwater than

December 2003, 10,112 m3 and 2,345 m3, respectively, and precipitation losses (4,952 m3) occurred only in December 2002. January 2003 and January 2004 had similar amount of harvested rainwater, 2,515 m3 and 2,398 m3, respectively, but only in January 2003 precipitation losses (2,411 m3) were observed. In February 2003, harvested water was

6,150 m3 and 91.5% of this amount was precipitation losses (5,629 m3), meaning that the majority of the rainwater that fell in the harvesting area did not remain available in the reservoir. That happened due to the large amount of rainfall that occurred in December

2002 (246.4 mm), replenishing the reservoir, combined with the very low demand for irrigation during the season, so that the reservoir level was too high to accommodate the amount of rain in the following months. In February 2004, from the amount of 5,681 m3 of harvested water (total rainwater that falls in the harvesting area), the precipitation losses were only 34.9% (1,981 m3) because of the lower levels in the reservoir.

The summer of 2003 had more precipitation than summer 2004 (218.4 mm to

323.9 mm, compared to 115.6 mm to 252.7 mm), which caused higher volumes of harvested rainwater in 2003 (8,965 m3 to 13,291 m3) than in 2004 (4,743 m3 to

10,372 m3). While in 2003 there were precipitation losses in all three months of June

(4,170 m3), July (2,241 m3) and August (6,619 m3), in 2004 there were no precipitation losses at all in any of these 3 months. In both cases, only in June well water was added to the reservoir (598 m3 in June 2003 and 728 m3 in June 2004).

Harvesting Effectiveness of the Recirculatory System

The overall harvesting effectiveness for the Recirculatory System was 65.4%, meaning that, on average, for the entire 24-month period of study, 34.6% of the harvested

81 rainwater was lost to the environment. In a typical overhead irrigation system or microirrigation system, where the runoff is not collected and recycled, most of the rainwater is lost to deep percolation and surface runoff during the whole irrigation season. This water contains dissolved agrochemicals (fertilizers and pesticides) that can pollute surface and groundwater. In the ebb and low system, the chemicals are discharged to environment only during runoff events when the reservoir overflows.

For the months when there was no overflow (13 months out of 24), the harvesting effectiveness was 100%, as expected. Excluding the months with no overflow, the harvesting effectiveness varied from 4.1% in January 2003 to 75.0% in July 2003. The largest amount of rainwater saved in the reservoir was 10,372 m3 (252.7 mm) in August

2004, when the harvesting effectiveness was 100%, since no losses occurred. This happened because of the higher demand of the reservoir water to irrigate a larger area coinciding with smaller amounts of rain during the previous months, which resulted in lower pond water level that allowed 100% of the harvested water to stay in the system.

However, August 2004 was not the month with the largest volume of harvested water in the period of study. In June 2003, the largest volume of harvested water (total rainwater that falls in the harvesting area) was 13,291 m3 (out of 323.9 mm of rain, the largest in 24 months), and the harvesting effectiveness was 68.6%, due to reservoir overflow of 4,170 m3. On the contrary, the smallest amount of rainwater saved in the reservoir was 104 m3

(2.6 mm, as a result of 61.3 mm of rain minus 58.7 mm of lost precipitation) in January

2003. In this month, the highest percentage of precipitation losses occurred (95.9%), since the reservoir had already high water levels, due to the rains during the previous month and low irrigation demand in January.

Comparing the Two Phases of Management

Table 7-2 shows the consolidated totals of harvested water for both phases of the management practices adopted in the farm: before and after June 2003, when the management strategy for the reservoir water has been changed.

The first phase consists of 9 months (from September 2002 to May 2003), when the reservoir water was used only for irrigating the 13 flood plains (3.63 ha). During this phase, the amount of rain was 937 mm, which produced 38,463 m3 of harvested rainwater. From this amount, 21,331 m3 (55.5%) were precipitation losses. In percentages of the totals for the 24 months period, the harvested water represented 33.0%, and the precipitation losses represented 53.0%. During this phase, the farmer added 14,351 m3 of well water that represented 60.6% of the total period.

Phase 2 started in June 2003 and was monitored for the purpose of this study until

August 2004, totaling 15 months. During this phase, the reservoir water was used for irrigation of both areas: flood plains (3.63 ha) and pressurized systems (10.12 ha). The total rainfall during the 15 months of this phase was 1,902 mm, producing 78,078 m3 of harvested water. From this precipitation amount, 18,934 m3 (24.3%) were precipitation losses (reservoir overflow). The amount of water saved in the reservoir in this phase was

59,144 m3, meaning 75.7% of harvesting effectiveness. Comparing the totals of phase 2 with the totals of the 24-month period, the harvested rainwater represented 67.0%, the precipitation losses represented 47.0%, and the saved volume of rainwater represented

68.5%.

Overall, the change in management had a good effect on reducing the amount of precipitation losses from the system to the environment. During the initial management phase, from September 2002 to May 2003, there were 4 months (out of 9) with no

83 overflow from the reservoir. The precipitation losses varied from 36.8% (September

2002) to 95.6% (January 2003). Looking at the precipitation losses of each month in the whole period of 24 months it was found that these five months contributed more than 5% of total lost precipitation, and three of these months had relative precipitation losses

(based on this month total precipitation) greater than 12%. During the second phase, from

June 2003 to August 2004, when the new management was already being used, there were no precipitation losses in 9 months (out of 15), and for the other 6 months the precipitation losses varied from 25.0% (July 2003) to 70.9% (August 2003). These monthly amounts of precipitation losses represent 2.6% to 16.4% of the total lost during the whole 24-month period. There were high precipitation losses (from 5.6% to 16.4% of the total period) in the first three months of the second management phase (June 2003 to

August 2003), however after that, the losses were more scattered and in lower amounts

(2.6% to 7.2% of the total period).

The above numbers indicate clearly the higher harvesting effectiveness of the second phase (75.7%), when the new management strategy started, compared to the first phase (44.5%), when only the flood plains areas were irrigated with the reservoir water.

That means more water collected from the rain and saved to be used when necessary.

Also, it means less withdrawals of water from surface or groundwater sources, and less runoff with potential of pollution to the environment. In addition, this is also an indication of the potential of this system to achieve the more strict goals of the environmental protection agencies in conserving water and protecting the environment with more efficient strategies in irrigated agriculture.

Conclusions

Rainwater Harvesting and Recycling System

Precipitation Losses

• There was great variability of precipitation losses throughout the seasons and no repeated pattern during the same seasons from one year to the other was observed. This was caused for both the irregular precipitation distribution and farmer management.

• In the first management phase, no precipitation losses were observed in 4 months (out of 9) from September 2002 to May 2003. However, in the other 5 months of this phase the precipitation losses varied from 36.8% (September 2003) to 95.6% (January 2003), being the highest in whole period of 24 months.

• In the second management phase (from June 2003 to August 2004), there were no precipitation losses in 9 months (out of 15), and for the other 6 months the precipitation losses varied from 25.0% (July 2003) to 70.9% (August 2003). These numbers indicate that the new management strategy for the reservoir water is progressively reducing the runoff from the system to the environment.

• The highest percentage of precipitation losses (95.9%) occurred Jan 2003, due to low irrigation demand and because the rains during the previous month promoted high water levels in the reservoir.

Harvesting effectiveness

• Excluding the months with no overflow, the harvesting effectiveness varied from 4.1% to 75.0%. The overall harvesting effectiveness for the Recirculatory System was 65.4%.

• The largest amount of rainwater saved in the reservoir was 10,372 m3 (252.7 mm) in August 2004, when the harvesting effectiveness was 100% since no losses occurred.

• The smallest amount of rainwater saved in the reservoir was 104 m3 (2.6 mm, as a result of 61.3 mm of rain minus 58.7 mm of lost precipitation) in January 2003.

• During the first phase (9 months, September 2002 to May 2003), when the reservoir water was used only for irrigating the 13 flood plains (3.63 ha), the total amount of rain was 937 mm, which produced 38,463 m3 of harvested rainwater. From this amount, 21,331 m3 (55.5%) were precipitation losses.

• During the second phase (15 months, June 2003 to August 2004), when the reservoir water was used for irrigation of both areas [ebb and flow (3.63 ha) and microirrigation system (10.12 ha)], the total of rainfall was 1,902 mm, producing

78,078 m3 of harvested water. From this amount, 18,934 m3 (24.3%) were precipitation losses.

• These numbers indicate clearly the higher harvesting effectiveness of the second phase (75.7%), when the new management strategy started, compared to the first phase (44.5%), when only the flood plains areas (ebb and flow system) were irrigated with the reservoir water.

In general, the results show less runoff with potential of pollution to the environment in the second phase of management. In addition, this is also an indication of the potential of this system to achieve more water conservation and environmental protection with the adoptive management of pond level and irrigation applications

2.2

2.0

1.8 1.7 m 1.6

) 1.4 l (m

e 1.2 v

e Full level L r 1.0 te

a Sensor reading: Manual reading: W 0.8 4 1.81 m (71.256 in) 1.81 m (71 /16 in) 0.6 Check point day and time: 0.4 Mar/08/03 - 16:00

0.2

0.0 08 Mar 03 00:00 08 Mar 03 12:00 09 Mar 03 00:00 09 Mar 03 12:00 10 Mar 03 00:00

Sensor Readings Farmer Readings Checkpoint Checkpoint Reading

Figure 7-1. Sensor and farmer readings of reservoir water level during a 2-day period showing reading checkpoint, rainfall events and full level threshold.

2.2

2.0

1.8 1.7 m Full 1.6

1.4 (m) 1.2 Rainfall = 5.08 mm

1.0 Flood Plain Irrigation Overflow = 208.28 m3 Water Level 0.8

0.6

0.4

0.2

0.0 Aug 19 Aug 19 Aug 19 Aug 19 Aug 19 Aug 20 Aug 20 Aug 20 Aug 20 Aug 20 Aug 20 12:00 14:24 16:48 19:12 21:36 0:00 2:24 4:48 7:12 9:36 12:00 2003 Figure 7-2. Sensor readings of reservoir water level during a 24-hour period showing one rainfall and one irrigation event, when the reservoir was near to full.

14000

12000 ) 3 m (

t 10000 n e pon

8000 e Com

6000 r Balanc e t Wa

rvoir 4000 se Re

2000

0 Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug

Fall Winter Spring Summer Fall Winter Spring Summer 2002 | 2003 | 2004 Harvested Rainwater Rainwater Overflow Losses Well Water Figure 7-3. Amounts of harvested rainwater, well water, and reservoir overflow monitored from September 2002 through August 2004 at Holloway Tree Farm, Leesburg, FL.

Table 7-1. Monthly water harvesting effectiveness and storage effectiveness for the recirculatory system from Holloway Tree Farm Nursery, during a 24-month period. Precipitation Precipitation Harvesting Well Total Storage Percentages of 24-Month Totals Date/Seasons Total Lost Saved Harv. Losses Effectiveness Water Input Effectiveness Precipitation Total Input mm mm mm m3 m3 % m3 % m3 m3 m3 % Harv. Lost Saved Well Stored Sep 144.8 53.3 91.4 5,942 2,189 36.8 3,753 63.2 2,536 8,478 6,289 74.2 5.1 5.4 4.9 10.7 6.3 Fall Oct 31.8 0.0 31.8 1,303 0 0.0 1,303 100.0 4,864 6,167 6,167 100.0 1.1 0.0 1.7 20.5 6.2 2002 Nov 54.2 0.0 54.2 2,226 0 0.0 2,226 100.0 3,193 5,419 5,419 100.0 1.9 0.0 2.9 13.5 5.4 Dec 246.4 120.7 125.7 10,112 4,952 49.0 5,160 51.0 625 10,736 5,785 53.9 8.7 12.3 6.8 2.6 5.8 Winter Jan 61.3 58.7 2.5 2,515 2,411 95.9 104 4.1 0 2,515 104 4.1 2.2 6.0 0.1 0.0 0.1 Feb 149.9 137.2 12.7 6,150 5,629 91.5 521 8.5 0 6,150 521 8.5 5.3 14.0 0.7 0.0 0.5 Mar 186.7 149.9 36.8 7,662 6,150 80.3 1,512 19.7 0 7,662 1,512 19.7 6.6 15.3 2.0 0.0 1.5 Spring Apr 40.6 0.0 40.6 1,668 0 0.0 1,668 100.0 102 1,770 1,770 100.0 1.4 0.0 2.2 0.4 1.8 May 21.6 0.0 21.6 886 0 0.0 886 100.0 3,031 3,917 3,917 100.0 0.8 0.0 1.2 12.8 3.9 Jun 323.9 101.6 222.3 13,291 4,170 31.4 9,121 68.6 598 13,889 9,719 70.0 11.4 10.4 12.0 2.5 9.7 2003 Summer Jul 218.4 54.6 163.8 8,965 2,241 25.0 6,724 75.0 0 8,965 6,724 75.0 7.7 5.6 8.8 0.0 6.7 Aug 227.3 161.3 66.0 9,330 6,619 70.9 2,710 29.1 0 9,330 2,710 29.1 8.0 16.4 3.6 0.0 2.7 Sep 73.7 0.0 73.7 3,023 0 0.0 3,023 100.0 4,308 7,331 7,331 100.0 2.6 0.0 4.0 18.2 7.3 Fall Oct 50.8 0.0 50.8 2,085 0 0.0 2,085 100.0 1,787 3,872 3,872 100.0 1.8 0.0 2.7 7.6 3.9 Nov 30.5 0.0 30.5 1,251 0 0.0 1,251 100.0 1,793 3,044 3,044 100.0 1.1 0.0 1.6 7.6 3.0 Dec 57.2 0.0 57.2 2,345 0 0.0 2,345 100.0 104 2,449 2,449 100.0 2.0 0.0 3.1 0.4 2.5 Winter Jan 58.4 0.0 58.4 2,398 0 0.0 2,398 100.0 0 2,398 2,398 100.0 2.1 0.0 3.1 0.0 2.4 Feb 138.4 48.3 90.2 5,681 1,981 34.9 3,701 65.1 0 5,681 3,701 65.1 4.9 4.9 4.9 0.0 3.7 Mar 76.2 25.4 50.8 3,127 1,042 33.3 2,085 66.7 0 3,127 2,085 66.7 2.7 2.6 2.7 0.0 2.1 Spring Apr 24.1 0.0 24.1 990 0 0.0 990 100.0 0 990 990 100.0 0.8 0.0 1.3 0.0 1.0 2004 May 127.0 70.2 56.8 5,212 2,881 55.3 2,331 44.7 0 5,212 2,331 44.7 4.5 7.2 3.1 0.0 2.3 Jun 115.6 0.0 115.6 4,743 0 0.0 4,743 100.0 728 5,471 5,471 100.0 4.1 0.0 6.2 3.1 5.5 Summer Jul 128.3 0.0 128.3 5,264 0 0.0 5,264 100.0 0 5,264 5,264 100.0 4.5 0.0 6.9 0.0 5.3 Aug 252.7 0.0 252.7 10,372 0 0.0 10,372 100.0 0 10,372 10,372 100.0 8.9 0.0 13.6 0.0 10.4 Total 2840 981 1859 116,541 40,265 34.6 76,276 65.4 23,669 140,210 99,945 71.3 100.0 100.0 100.0 100.0 100.0

Table 7-2. Consolidated water harvesting effectiveness and storage effectiveness for the recirculatory system from Holloway Tree Farm Nursery, during a 24-Month period. Precipitation Precipitation Harvesting Well Total Storage Percentages of 24-Month Totals Management Date/Seasons Total Lost Saved Harv. Losses Effectiveness Water Input Effectiveness Precipitation Total Input Strategy mm mm mm m3 m3 % m3 % m4 m4 m3 % Harv. Lost Saved Well Stored Sep Before Fall Oct Jun/2003: 2002 Nov Reservoir Dec Water Winter Jan Used 937 520 417 38,463 21,331 55.5 17,132 44.5 14,351 52,814 31,484 59.6 33.0 53.0 22.5 60.6 31.5 Feb Only for Mar Ebb & Flow Spring Apr Irrigation May System Jun 2003 Summer Jul Aug Sep After Fall Oct Jun/2003: Nov All Dec Three Winter Jan Irrigation 1,902 461 1,441 78,078 18,934 24.3 59,144 75.7 9,318 87,396 68,462 78.3 67.0 47.0 77.5 39.4 68.5 Feb System Mar Using Spring Apr Reservoir 2004 May Water Jun Summer Jul Aug Total Overall 2,840 981 1,859 116,541 40,265 34.6 76,276 65.4 23,669 140,210 99,945 71.3 100.0 100.0 100.0 100.0 100.0

CHAPTER 8 EVAPOTRANSPIRATION AND CROP COEFFICIENT OF MAGNOLIA PLANTS UNDER THREE DIFFERENT IRRIGATION SYSTEMS

Introduction

Population growth and higher living standards will cause ever-increasing demands for good quality municipal and industrial water. At the same time, more and more irrigation water will be needed to meet increasing demands for food (Bouwer, 2003).

In the southeastern United States, evapotranspiration represents a significant component of the water balance (Jacobs et al., 2002) and an important consideration for water resources management and irrigation scheduling (Jia et al., 2004). Efficient use of natural water resources in agriculture is becoming an important issue in Florida because of the rapid depletion of freshwater resources due to the increasing trend of industrial development and population growth (Irmak et al., 2003).

The demand for landscape plantings that have a low water requirement is increasing, however there is limited information about water use of landscape plants in the literature (Garcia-Navarro et al., 2004), including woody ornamentals (Buerle and

Post, 2004). Measurement of plant water use during nursery production may be useful for predicting the relative water use of various species after establishment in the landscape

(Garcia-Navarro et al., 2004). In addition, advances in irrigation technology provide numerous tools to landscape managers and water agencies for conserving water in landscapes (Pittenger et al., 2004).

89 90

The objective of this study was to determine the crop evapotranspiration and crop coefficients of young (1to 2-year old) magnolia trees cultivated under three different irrigation systems: sprinkler overhead, microirrigation and ebb and flow system, in an ornamental nursery in central Florida.

Materials and Methods

Plant evapotranspiration was calculated based on the water budget (Equation 8-1).

The water budget consists of a water balance in the system based on all the inputs of water (irrigation and rain), all the outputs (drainage and runoff) and the change of water content in the root zone (plant container). In this specific case, water applications consisted of two components irrigation and/or rain and were calculated using the

Equation 8-2. Water losses for this study had only one component called runoff. This included the water lost from the bottom of the containers. The change of moisture content in the root zone is a change in volumetric moisture content of the growing media in the container and was continuously monitored using TDR probes.

ETc = WA −WL ± ∆SWC (8-1)

where

ETc = Calculated crop evapotranspiration, mm day-1 WA = Water applications, mm day-1 WL = Water losses collected as runoff, mm day-1 ∆SWC = Variation in substrate water content, mm day-1

WA = Irr + Rain (8-2)

where

Irr = Water application through irrigation events, mm day-1 Rain = Water application through rainfall events, mm day-1

Six plants in each system were monitored for the water budget calculations. The calculations of the total water balance for overhead sprinkler irrigation and for microirrigation systems were similar. The calculations were performed on a weekly basis and then, the average daily ETc was calculated for each system. The amount of applied water by both systems was obtained using flow meters that were read once a week. The amount of rain (from the rain gauge) was added as the second component of water application for that specific period. The runoff per plant from each system was obtained on a weekly basis from the amount of water collected in six 190-liter barrels from the trays under six selected plants in each area.

Based on TDR readings, the component related to moisture change in the growing media (SWC) was assumed to be negligible and was not included in the calculations. By selecting the starting and the ending points of the water balance at the specific time of the irrigation cycle the moisture content of the media can be assumed equal and the change is insignificant.

For the ebb and flow system, the calculations followed the approach described in

Chapter 7 for calculating the amount of overflow from the reservoir. With reservoir level monitored every 15 minutes, and every irrigation event and rainfall event recorded, it was possible to identify the exact moment when each irrigation event started and ended. Due to the dynamic nature of the water level in the reservoir during a regular day at the farm, it was decided that the readings around midnight would represent a stable situation. The values of water level in the reservoir at the stability conditions before and after irrigations or rainfall events were used for calculating the amount of water used during any specific period.

Considering the geometry of the reservoir and its water level around midnight, the volume of water stored in the reservoir before and after each irrigation event was calculated (Equations 8-3 and 8-4). The difference between the two volumes gave the amount of water removed from the reservoir during that specific day (Equation 8-5).

h RV(h) = [()SA(h) + BA + ( SA(h) × BA)] (8-3) 3

where

3 RV(h) = Reservoir volume as a function of water level h (m ) h = Water level or height of water in the reservoir (m) 2 SA(h) = Surface area of the water at the h level (m ) BA = Bottom area of the reservoir (constant) (m2)

SA(h) = SL(h) × SW(h) (8-4)

where

2 SA(h) = Surface area of the water at the h level (m ) SL(h) = Surface length of the water at the h level (m) SW(h) = Surface width of the water at the h level (m)

Knowing how many flood plains were irrigated during that day allowed for calculating the amount of water used for each flood plain, since the plains have the same dimensions. Considering the number of plants in the flood plains the volume of water per plant was estimated. The average monthly values of plant water use under the ebb and flow irrigation system were estimated in a similar way using irrigation records and the rainfall data. The amount of rain included in the water balance for this system was the resulting difference between the total rainwater caught in harvesting area of the flood plains and the amount that returned to the reservoir.

It is necessary to notice that in the ebb and flow system a lot of surface area is wet and exposed to evaporation. In addition, due to small irregularities of the plastic-covered

93 surface water ponding occurs on the flood plain area. This amount of water does not return to the reservoir and is considered as water applied, which is inherent in this kind of irrigation system.

The FAO Penman Monteith equation (Allen et al., 1998) and the climatic data obtained from the automatic weather station described in Chapter 3 were used to calculate the reference evapotranspiration, ETo. The FAO Penman Monteith was used as a model and it is presented in Equation 8-6.

900 0.408∆(Rn − G) + γ u2 (es − ea ) ETo = T + 273 (8-6) ∆ + γ (1+ 0.34u2 )

where

ETo = Reference evapotranspiration, mm day-1 Rn = Net radiation at the crop surface, MJ m-2 day-1 G = Soil heat flux density, MJ m-2 day-1 T = Air temperature at 2 m height, oC -1 u2 = Wind speed at 2 m height, m s es = Saturation vapor pressure, kPa ea = Actual vapor pressure, kPa es-ea = Saturation vapor pressure deficit, kPa ∆ = Slope vapor pressure curve, kPa oC-1 γ = Psychrometric constant, kPa oC-1

These values of ETo were used to calculate the Kc values for the magnolia plants grown under each system throughout the studied period, using the respective ETc values

(Eq. 8-1). The calculations were made using the Equation 8-7.

ETc Kc = (8-7) ETo

where

Kc = Crop coefficient ETc = Crop evapotranspiration, mm day-1 ETo = Reference evapotranspiration, mm day-1

Results and Discussion

The plant evapotranspiration under all three treatments and reference ETo are presented in Figure 8-1. The values of average monthly crop evapotranspiration showed in the Figure 8-1 represent the monthly consolidation of the water application (irrigation events + rain events), and the respective amount of runoff for overhead sprinkler and for microirrigation systems. The reference ET is calculated using Eq. 8-6. Figure 8-2 shows a sample of measurements of the reservoir water level using the pressure transducer. Figure

8-3 shows the values of crop coefficients calculated for the same period of study. Figure

8-5 shows the variability of monthly precipitation recorded during the study period compared to the historical average precipitation for Leesburg, FL. Figures 8-6 to 8-8 show the maximum, mean and minimum values of air temperature recorded during the study period as compared to the historical average maximum, mean and minimum temperatures for Leesburg, FL.

The plant growth, already discussed in Chapter 4, had a consistent impact on increasing of water use and consequently on Kc values.

In Figure 8-1 it can be observed that in general, the ebb and flow system resulted in higher amounts of evapotranspiration for the magnolia plants, followed by the overhead sprinkler irrigation system. The microirrigated magnolias had the lowest ET rates from all treatments. Despite the fact that the irrigation systems are supposed to supply water efficiently to fulfill the crop water requirements, there are inherent differences to each system that play an important role on the amount of water available for evapotranspiration in a cultivated area. For each system, the variability throughout the studied period is related to weather factors, plant growth and water management adopted to supply water to the plants. Among all three systems, the microirrigation system

95 resulted in a less variability and in lower values of plant water use during the study period. All three systems showed a peak of water use in July 2003 with 6.09 mm/day,

4.91 mm/day, and 2.98 mm/day, for ebb and flow, overhead sprinkler, and microirrigation system, respectively.

The reference evapotranspiration (ETo) shows a consistent variation throughout the

12-month period of study, with highest values during the summer time as expected. The highest value of ETo was 7.33 mm day-1 in July, followed closely by August with 7.28 mm day-1.

The Kc values calculated for each irrigation system are presented in the Figure 8-3.

The ebb and flow system produced the highest values of Kc, followed by overhead sprinkler and by microirrigation system. The higher values observed for ebb and flow system compared to overhead sprinkler and to microirrigation systems may be attributed to the high amount of water applied by this system and high amount of evaporation, inherent to this system. A large area of plastic surface remains wet resulting in relatively high evaporation component of ETc. In comparison, the overhead sprinkler and microirrigation systems apply less water then ebb and flow. Among all three irrigation systems, the microirrigtion system proved to be the most conservative.

All three curves representing crop coefficients follow the expected pattern however, it can be noticed that for the summer months (June, July, August) the values are the same. The temperature (maximum, mean and minimum) and precipitation during the study were much higher than the historical average for this location (Figures 8-4 through

8-7). The study period was exceptionally wet and very hot and likely had an impact on the young magnolia plants and on crop coefficients. The June, July and August Kc values

96 indicate that the plants were not actively growing during this time. That implies that more study is necessary to determine magnolia response to the high temperature environments.

For the second half of the study period, from October to February, plant growth resulted in continuously increasing crop coefficients with the final values of 1.04, 0.85 and 0.59 for ebb and flow, microirrigation and sprinkler system respectively. For the overhead sprinkler irrigation system, there was one higher value (1.12) that does not fit into the normal trend of variability observed with the other two systems. That was probably caused by an increase in water application decided by the farmer, following his water management strategy for this irrigation system.

The main advantage of the ebb and flow system is the fact that almost all the water comes from rain harvesting and it is re-circulated in the system without using groundwater supplies. The system applies more water compared to overhead sprinkler and microirrigation systems; however, it has less impact on quantity of groundwater resources. The recirculation pond provides storage and buffer for nutrients reducing the runoff released to the environment and the amount of nutrients that are discharged from the production system. As a result, the ebb and flow system has less potential of the environmental pollution.

Conclusions and Recommendations

Using the information collected from the irrigation systems and from the weather station, the crop evapotranspiration, the reference evapotranspiration and the Kc for containers-grown magnolias under overhead sprinkler, micro irrigation and ebb and flow irrigation systems were calculated. The results showed that:

• Most of the time the ebb and flow system resulted in higher amounts of evapotranspiration for the magnolia plants, followed by overhead sprinkler

irrigation system. The microirrigation system resulted in lower values of water use during the whole period of study.

• All three systems had a peak of ETc in the month of July 2003 (6.09 mm day-1, 4.91 mm day-1, and 2.98 mm day-1, for ebb and flow, overhead sprinkler, and microirrigation system, respectively).

• There was a consistent variation of reference evapotranspiration values throughout the period of study, with highest values of 7.33 mm day-1 in July, followed closely by August with 7.28 mm day-1.

• The ebb and flow system produced higher values of Kc (ranging from 0.71 to 1.04), followed by overhead sprinkler (from 0.29 to 0.85) and by microirrigation system (from 0.13 to 0.59).

• Despite the fact that the ebb and flow system applies more water compared to overhead sprinkler and microirrigation systems, there is still advantage for this system since most of the water applied to the plants is recirculated to the reservoir, and the runoff is not going directly to the environment. Since most of the water used during the year is harvested rainwater, less water is removed from the aquifer.

7 )

-1 6

4 ETc (mm day 3

0 Mar-03 Apr-03 May-03 Jun-03 Jul-03 Aug-03 Sep-03 Oct-03 Nov-03 Dec-03 Jan-04 Feb-04

Sprinkler Microirrigation Ebb&Flow ETo Figure 8-1. Monthly average of reference evapotranspiration and crop evapotranspiration of magnolia plants cultivated under three different irrigation systems at Holloway Tree Farm, Leesburg, FL.

2.0

1.8 Full 1.6

1.4

) Level Stable Level Stable 1.2

evel (m 1.0 L

0.8 Water 0.6 Rainfall = Rainfall = 0.4 12.70 mm 5.08 mm Flood plain irrigation events 0.2

0.0 17 Jan 18 Jan 19 Jan 20 Jan 21 Jan 22 Jan

2004

Figure 8-2. Sample of the reservoir water level measurements showing the effect of rainfall and irrigation events.

1.4

1.2

1.0

0.8

Kc values 0.6

0.4

0.2

0.0 Mar-03 Apr-03 May-03 Jun-03 Jul-03 Aug-03 Sep-03 Oct-03 Nov-03 Dec-03 Jan-04 Feb-04

Sprinkler Microirrigation Ebb&Flow

Figure 8-3. Crop coefficients calculated for magnolia plants grown at Holloway Tree Farm, Leesburg, FL.

350

300

250

200

150 Precipitation (mm)

100

0 Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb 2003 2004 Study period Historical data Figure 8-4. Historical monthly normal of precipitation and monthly totals of precipitation for Holloway Tree Farm, Leesburg, FL. 100

30 ) 25

20 r Temperature (oC i 15 A

0 Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb 2003 2004 Study period Tmax Historical data Tmax Figure 8-5. Historical monthly maximum air temperature and monthly maximum air temperature during the study at Holloway Tree Farm, Leesburg, FL.

25 )

15 r Temperature (oC i A

0 Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb 2003 2004 Study period Tmean Historical data Tmean Figure 8-6. Historical monthly mean air temperature and monthly mean air temperature during the study at Holloway Tree Farm, Leesburg, FL.

101

25 )

15 r Temperature (oC i A

0 Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb 2003 2004 Study period Tmin Historical data Tmin Figure 8-7. Historical monthly minimum air temperature and monthly minimum air temperature during the study period at Holloway Tree Farm, Leesburg, FL.

CHAPTER 9 CONCLUSIONS AND RECOMMENDATIONS

Plant Growth

The ANOVA results demonstrated that the irrigation systems had significant effects on plant height and growth index during the period of study. In both cases, the overhead sprinkler irrigation system produced smaller values than ebb and flow and microirrigation systems. There was no significant effect of irrigation systems on trunk diameter. However, overhead sprinkler irrigation system had the tendency to produce larger trunk diameter when compared to ebb and flow and microirrigation systems.

Calibration of TDR sensors and Field Monitoring

The difference in volumetric water content between the calibration curve and the factory standard curve varied between 11.9% and 25.1%, in average, which confirms the need for a specific calibration for different media to avoid underestimation of moisture content. Under farmer’s management, the moisture contents under all three irrigation systems were slightly below (before June 2003) or above (after June 2003) the container capacity of the growing medium during the whole period of field monitoring.

Concentration and Loads of Nutrients

For the Period of Study

The variability of concentration of NH4-N, NO3-N, TKN, total P and total N in runoff water from all the systems was most dependent on the time of fertilizer applications. The highest level of concentration for all 5 nutrients analyzed in all systems

102 103 occurred in August 2003 when there was the second fertilizer application during the study period.

Ammonia was found in very low concentrations in all months, except for August, reaching values of 14.20 mg L-1 for microirrigation and 10.91 mg L-1 for overhead sprinkler irrigation system. For ebb and flow system and the reservoir, the highest values were 0.68 mg L-1 (February 2004) and 0.41 mg L-1 (May 2003), respectively. Ammonia was also the chemical with lowest values of loads (below 1.4 kg ha-1 from microirrigation system) among all 5 nutrients studied for the entire period.

Nitrate was found in highest concentrations among all five nutrients analyzed. The highest value of nitrate concentration was 60.52 mg L-1, for microirrigation system, in

August. In 6 out of 12 months it was above 10 mg L-1 for microirrigation system and only in August for overhead sprinkler irrigation system. Loads of nitrate reached highest value for microirrigation 5.88 kg ha-1 in August, among all months, compared to overhead sprinkler (2.05 kg ha-1) and the reservoir (3.19 kg ha-1).

The highest concentration of TKN was 15.33 mg L-1 for microirrigation and the second highest was 11.62 mg L-1 for overhead sprinkler system, both in August. For the reservoir, the highest concentration was 5.75 mg L-1, both in April. Load of TKN reached the peak in August, for the reservoir, with 4.59 kg ha-1. Overhead irrigation and microirrigation systems had TKN loads lower than 1.5 kg ha-1 (in August).

104 total P from ebb and flow system was 1.22 mg L-1 in April 2003, and in the reservoir was

0.76 mg L-1 in February 2004.

The total loads for the whole period of 12 months released from the reservoir to the environment were 1.01 kg ha-1 (NH4-N), 7.21 kg ha-1 (NO3-N), 14.48 kg ha-1 (TKN),

3.40 kg ha-1 (Total P), and 21.68 kg ha-1 (Total N).

Rainwater Harvesting and Recycling System

Precipitation Losses

In the first management phase, no precipitation losses were observed in 4 months

(out of 9) from Sep 2002 to May 2003. However, in the other 5 months of this phase the precipitation losses varied from 36.8% (Sep 2003) to 95.6% (Jan 2003), being the highest in whole period of 24 months.

In the second management phase (from Jun 2003 to Aug 2004), there were no precipitation losses in 9 months (out of 15), and for the other 6 months the precipitation losses varied from 25.0% (Jul 2003) to 70.9% (Aug 2003). The highest percentage of precipitation losses (95.9%) occurred Jan 2003, due to low irrigation demand and because the rains during the previous month promoted high water levels in the reservoir.

Harvesting effectiveness

During the first phase (9 months, Sep 2002 to May 2003), when the reservoir water was used only for irrigating the 13 flood plains (3.63 ha), the total amount of rain was

937 mm, which produced 38,463 m3 of harvested rainwater. (From this amount, 21,331 m3 (55.5%) were precipitation losses).

During the second phase (15 months, Jun 2003 to Aug 2004), when the reservoir water was used for irrigation of both areas (ebb and flow (3.63 ha) and microirrigation system (10.12 ha)), the total of rainfall was 1,902 mm, producing 78,078 m3 of harvested

105 water. (From this amount, 18,934 m3 (24.3%) were precipitation losses). The harvesting efficiency during this time was 75.7%. The overall harvesting effectiveness for the

Recirculatory System was 65.4%.

Evapotranspiration and Crop Coefficients

The rate of evapotranspiration was higher for the magnolias grown under the ebb and flow system followed by overhead sprinkler irrigation system (with exception of

December 2003). The microirrigation system resulted in lower values of water use during the whole period of study. All three systems had a peak of water use in the month of July

2003 (6.09 mm day-1, 4.91 mm day-1, and 2.98 mm day-1, for ebb and flow, overhead sprinkler, and microirrigation system, respectively).

There was a consistent variation of reference evapotranspiration values throughout the period of study, with highest values of 7.33 mm day-1 in July, followed closely by

August with 7.28 mm day-1.

The ebb and flow system produced higher values of Kc (ranging from 0.71 to 1.04), followed by overhead sprinkler (from 0.29 to 0.85) and by microirrigation system (from

0.13 to 0.59).

Despite the fact that the ebb and flow system applies more water compared to overhead sprinkler and microirrigation systems, its advantage is that most of the water applied is re-circulated to the reservoir, and the runoff is not discharged to the environment directly. Most of the water used during the period of study was harvested rainwater and very small amount was removed from the aquifer for ebb and flow irrigation.

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BIOGRAPHICAL SKETCH

Luis Nogueira was born in Santa Teresa, Espírito Santo state, Brazil, in April 1963.

He received his bachelor’s degree in agronomy from the Federal University of Espírito

Santo, Alegre, ES, in December 1983. In January 1984, he started his master’s program at the Federal University of Ceará, with irrigation and drainage as a major. During his master’s program he had several extension, teaching, and research opportunities in special programs held by the Agricultural Engineering Department, which granted him an invitation for a job position in February 1986, as Assistant Researcher at the FCPC

(Ceará State Foundation for Research and Culture), even before finishing the master’s program. He defended his master’s thesis in April 1987 and continued to work for FCPC until February 1988.

In March 1988, he entered Brazilian Corporation for Agricultural Research

(EMBRAPA) where his responsibilities included participation in regional community extension, teaching, and research activities. He was the Coordinator of the PNP-TI

(EMBRAPA’S National Research Program for Irrigation Technology), and served in this position for 2 years. In November 1993, he was transferred to another EMBRAPA

Research Center, also in the Northeast Region, responsible for coordinating and executing activities for agricultural development of the ecosystem known as coastal tablelands. There, he had the opportunity to work closely with farmers of an irrigation district installed in this ecosystem for production of 7,000 ha of tropical fruit crops

(coconut, banana, citrus, avocado, pineapple, passion fruit, and several others).

113 114

With financial support from EMBRAPA and from CAPES, he enrolled in graduate school at the University of Florida in Fall 2000. While doing his coursework, he was also engaged in ongoing research at Irrigation Park (led by Dr. John Schueller) and in a new research project at Pine Acres (led by Dr. Michael Dukes). From this research experience, he prepared and delivered an oral presentation at the 62nd Annual Meeting of the Soil and Crop Science Society of Florida (Spring 2002) and published a refereed paper in the proceedings. In Fall 2002, he started installing the field experiments of his research project (under the direction of Dr. Dorota Haman) at Holloway Tree Farm, Leesburg, FL.

In Spring 2003, he prepared and presented a poster on this preliminary data obtained from his research project at the Graduate Student Forum of the University of Florida. He received his Doctor of Philosophy degree in May 2005.