This work was funded in part by a Capacity Building Grant awarded to the University of Maryland Eastern Shore (UMES) by the National Institute of Food and Agriculture. The authors would like to thank Don Mahan (UMES) for his help in setting up the rainfall simulator and in conducting rainfall simulations. Thanks are also extended to Janice Donohoe (UMES) for performing laboratory analyses and undergraduates students (UMES) for their help in conducting the rainfall simulation experiment and processing of samples.

1. Soil Collection and Preparation
<ol>
	<li>Collect the soil from the surface horizon of the soil profile to accurately represent physical and chemical conditions of the soil surface. Note: If possible soil should be collected from the top 5 cm of the surface. The area for soil collection should be small enough to limit variation in soil physical and chemical properties.</li>
	<li>Sieve the soil through a coarse (20 mm) screen to remove rocks. Note: Sieving is easier if the soil is somewhat moist.</li>
	<li>Spread the sieved soil out on a heavy tarpaulin in a thin layer to facilitate drying, preferably in a green house or warm indoor environment.</li>
	<li>Mix the soil with a shovel, rake or by pulling the edges of the tarp from one side to the other as if folding a giant calzone. Note: Be careful not to rip or tear the tarp with the edge of a shovel or rake. Repeat this process several times until the soil is thoroughly mixed.</li>
	<li>Take 10 samples from different places in the pile of thoroughly mixed soil and conduct a Mehlich-3 phosphorus test17 to test for homogeneity. Note: Homogeneity is achieved when the results of the 10 samples have a coefficient of variation (CV) of &#60; 0.05. Where: CV = standard deviation/mean.</li>
	<li>If the CV of the Mehlich-3 phosphorus test is &#62; 0.05, continue mixing the soil and repeat the homogeneity test.</li>
</ol>
2. Packing Soil Boxes
<ol>
	<li>Note: Soil boxes should be of uniform volume with identical dimensions of length, width and depth (100 cm x 20 cm x 7.5 cm) with nine 5-mm drain holes in the bottom. Boxes should have a 5-cm lip and a collection gutter on one end (Figure 1).</li>
	<li>Line the bottom of the boxes with 4 ply cheese cloth to keep soil from washing out of the holes in the box while allowing water to flow through when the soil is saturated.</li>
	<li>Pack the first soil box by scooping enough dried, sieved, and homogenized soil into the box to fill it about half deep when smoothed out (about 3.5 cm). Spread the soil evenly and pack it with a flat brick. Note: Soil should be sufficiently dry so it does not compact under the pressure of the brick.</li>
	<li>Add another 2 cm of soil and level it out with a leveling gauge to a packed depth of 5 cm, the height of the lip of the box that spills into the gutter&#160;(Figure 2).</li>
	<li>Weigh the amount of soil that was added to the first packed box, and add the same weight of soil to all remaining boxes. Pack each box to achieve a soil depth of 5 cm and uniform bulk density.</li>
	<li>Vacuum the gutters of the soil boxes to remove any soil that spilled into the gutter during the packing process.</li>
</ol>
3. Mounting Soil Boxes in the Rainfall Simulator
<ol>
	<li>Position a frame constructed out of 2 in&#160;x 6 in&#160;pressure treated lumber in the center of the rainfall simulator upon which the soil boxes will be placed. Note: The frame should have a cross member in the middle to provide rigidity. Placing soil boxes on a bottomless frame minimizes splash that would otherwise occur from a solid platform immediately below the soil boxes and allows free drainage from the holes in the bottom of the boxes.</li>
	<li>Position the frame on cement blocks at a height that allows placement of collection bottles and funnels below the spouts on the collection gutters at the front of soil boxes mounted on the platform.</li>
	<li>Further elevate the back of the platform, using bricks, lumber and shims, such that the back of a soil box placed on the platform is 3 cm higher than the front of the box, resulting in a 3% slope. Measure the slope by placing a board (&#62;100 cm length) on the back of a soil box mounted on the platform. Using a carpenter&#8217;s level, hold the board level and raise the back of the platform such that the front of the box is 3 cm below the level board (Figure 3). Note: Be sure the front and back of the platform is level from side to side.</li>
	<li>Locate the point directly below the overhead nozzle and avoid placing a box in that position to avoid large drops from the nozzle at the beginning or end of a rainfall event from falling on a soil box, then place five or six boxes evenly spaced on the platform. Mark the position of the boxes and always place boxes in these same positions.</li>
</ol>
4. Selecting the Source of Irrigation Water
<ol>
	<li>Select an irrigation water source that is relatively free of all elements and compounds, particularly those of interest to the study. Analyze the water source in advance of the study to determine water purity. Note: If necessary, exchange resins should be used to achieve desired water purity.</li>
	<li>Provide a main water source to the rainfall simulator that exceeds a pressure of 8 psi and a flow rate of 5 gpm. Note: Normal municipal sources exceed these minimum requirements. If using water tanks and pumps, be sure the pumps are capable of delivering a water supply that exceeds the minimum pressure and flow rate.</li>
</ol>
5. Selecting the Nozzle Size to Use
<ol>
	<li>Select one of four standard nozzle sizes that are used for rainfall simulations. Note: Each nozzle has an optimal performance pressure and flow to achieve proper droplet size and intensity (Table 1). Selection of nozzle size for use in a particular study is determined in relation to the intensity (cm/hr) of the natural rainfall event to be represented.</li>
</ol>
6. Rainfall Simulator Operation
<ol>
	<li>Position the (1) single lever ball valve (Figure 4) to the closed position, lever at 90 degree angle across pipe, and turn on the main water source (municipal or pump).</li>
	<li>Turn the square set screw on the top of the (3) pressure regulator valve (Figure 4) counter clockwise to reduce the pressure and open the next-in-line (4) in-line flow control valve completely.</li>
	<li>Open the (1) single lever ball valve (Figure 4) completely and adjust the (3) pressure regulator valve by turning the set screw clockwise to achieve approximately 8 psi in the (6) pressure gauge located near the top of the rainfall simulator. Note: Once the (3) pressure regulator valve has been set to slightly exceed the desired nozzle pressure, it should not have to be adjusted during the operation of the rainfall simulator unless the main water source pressure changes.</li>
	<li>Partially close the (4) in-line flow control valve (Figure 4) until the (5) flow meter reads the approximate flow rate in gallons per min&#160;for the nozzle in use and the (6) pressure gauge reads the approximate psi for the nozzle in use (Table 1).</li>
	<li>Close the (1) single lever ball valve (Figure 4) to stop the flow without changing the flow rate and pressure settings.</li>
</ol>
7. Nozzle Calibration and Rainfall Uniformity
<ol>
	<li>Cover the holes in the bottoms of 5 or 6 empty soil boxes with duct tape to prevent water from leaking out of the boxes and place them in the marked positions on the wooden frame (see step 3.4).</li>
	<li>Position and hold a 10 ft length of 2 inch PVC pipe with a 45&#176; elbow attached to the end over the nozzle and open the (1) single lever ball valve.</li>
	<li>Collect the discharge from the PVC pipe in a large graduated cylinder for 10 sec.</li>
	<li>Make minor adjustments to the (4) in-line flow control valve and repeat the 10 sec&#160;collections until the 10 sec&#160;flow volume matches the corresponding value for the nozzle in use (Table 1). Once the correct flow rate is achieved, use the value on the flow meter as a means of monitoring variation in flow due to possible pressure fluctuations. Note: For properly calibrating the nozzle, the 10 sec&#160;flow volume is a more accurate measure than the reading on the flow meter.</li>
	<li>Remove the 10 foot length of PVC pipe to allow rainfall to wet the box area and note the time of rainfall initiation.</li>
	<li>After exactly 10 min&#160;abruptly stop the rainfall by positioning the 10 foot PVC pipe over the nozzle to divert flow and close the (1) single lever ball valve.</li>
	<li>Measure the volume of water (ml) collected in each box by pouring it into a graduated cylinder, and calculate rainfall depth by dividing volume by the area of the bottom of the box (2,000 cm2).</li>
	<li>Calculate the coefficient of variation for rainfall depth. Note: Rainfall uniformity is achieved when rainfall depth in the 5 or 6 boxes has a coefficient of variation &#60;0.05. Where: CV = standard deviation/mean.</li>
	<li>If the CV is not less than 0.05, turn the nozzle &#188; turn tighter and repeat the calibration process. Note: The nozzle might need to be turned several times to achieve a CV of less than 0.05.</li>
	<li>Once a CV of less than 0.05 is achieved, repeat the calibration several times to ensure that rainfall intensity across runs is consistent.</li>
</ol>
8. Conducting a Rainfall Simulation
<ol>
	<li>Following calibration, place packed soil boxes in the marked positions on the wooden frame (see step 3.4).</li>
	<li>Position runoff collection bottles and funnels below the drain spouts and prevent rainfall from directly falling into the gutter by using a paper clip to attach a shield over the gutter (Figure 5).</li>
	<li>Repeat steps 7.2-7.5 to recalibrate nozzle flow rate immediately prior to a rainfall simulation event and initiate rainfall.</li>
	<li>Record the time of runoff initiation for each box when water draining from the drain spout turns from a slow drip to a continuous stream.</li>
	<li>Collect runoff samples at prescribed time intervals during the event by switching collection bottles or at the end of an event of predetermined duration.</li>
	<li>To terminate a rainfall event, stop the rainfall by positioning the 10 foot PVC pipe over the nozzle to abruptly divert flow and close the (1) single lever ball valve.</li>
	<li>Collect the runoff samples and record volume using a graduated cylinder or by mass assuming that water weighs 1 g/cm2.</li>
	<li>Mix the samples thoroughly so that all sediment is in suspension and then take a subsample for laboratory analysis.</li>
</ol>

<ol>
	<li>Glibert, P. M., Trice, T. M., Michael, B., Lane, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Urea+in+the+tributaries+of+the+Chesapeake+and+Coastal+Bays+of+Maryland.">Urea in the tributaries of the Chesapeake and Coastal Bays of Maryland.</a> Water Air Soil Poll. 160, 229-243 (2005).</li><li>Glibert, P. M., Harrison, J., Heil, C., Seitzinger, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Escalating+worldwide+use+of+urea-a+global+change+contributing+to+coastal+eutrophication.">Escalating worldwide use of urea-a global change contributing to coastal eutrophication.</a> Biogeochemistry. 77, 441-463 (2006).</li><li>Howard, M. D. A., Cochlan, W. P., Ladizinsky, N., Kudela, R. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Nitrogenous+preference+of+toxigenic+Pseudo-nitzschia+australis+(Bacillariophyceae)+from+field+and+laboratory+experiments.">Nitrogenous preference of toxigenic Pseudo-nitzschia australis (Bacillariophyceae) from field and laboratory experiments.</a> Harmful Algae. 6 (2), 206-217 (2007).</li><li>Mutchler, C. K., Hermsmeier, L. F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+review+of+rainfall+simulators.">A review of rainfall simulators.</a> Trans. ASAE. 8 (1), 67-68 (1965).</li><li>Kleinman, P. J. A., Sharpley, A. N., Veith, T. V., Maguire, R. O., Vadas, P. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Evaluation+of+phosphorus+transport+in+surface+runoff+from+packed+soil+boxes.">Evaluation of phosphorus transport in surface runoff from packed soil boxes.</a> J. Environ. Qual. 33, 1413-1423 .</li><li>Kibet, L. C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Phosphorus+runoff+losses+from+a+no-till+coastal+plain+soil+with+surface+and+subsurface-applied+poultry+litter.">Phosphorus runoff losses from a no-till coastal plain soil with surface and subsurface-applied poultry litter.</a> J. Environ. Qual. 40, 412-420 (2011).</li><li>Feyereisen, G. W., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Effect+of+direct+incorporation+of+poultry+litter+on+phosphorus+leaching+from+coastal+plain+soils.">Effect of direct incorporation of poultry litter on phosphorus leaching from coastal plain soils.</a> J. Soil Water Cons. (4), 243-251 (2010).</li><li>Vadas, P. A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+model+for+phosphorus+transformation+and+runoff+loss+for+surface-applied+manures.">A model for phosphorus transformation and runoff loss for surface-applied manures.</a> J. Environ. Qual. 36, 324-332 (2007).</li><li>Bhardwaj, A., Singh, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Development+of+a+portable+rainfall+simulator+infiltrometer+for+infiltration+runoff+and+erosion+studies.">Development of a portable rainfall simulator infiltrometer for infiltration runoff and erosion studies.</a> Ag. Water Manage. 22 (3), 235-248 (1992).</li><li>Moore, I. D., Hirschi, M. C., Barfield, B. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Kentucky+rainfall+simulator.">Kentucky rainfall simulator.</a> Trans. ASAE. 26, 1085-1089 (1983).</li><li>Grismer, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Standards+vary+in+studies+using+rainfall+simulators+to+evaluate+erosion.">Standards vary in studies using rainfall simulators to evaluate erosion.</a> Ca. Agri. 66 (3), 102-107 (2012).</li><li>Ries, J. B., Iserloh, T., Seeger, M., Gabriels, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Rainfall+simulations+-+constraints,+needs+and+challenges+for+a+future+use+in+soil+erosion+research.">Rainfall simulations - constraints, needs and challenges for a future use in soil erosion research.</a> Z. Geomorphol. Suppl. 57 (1), 1-10 (2013).</li><li>Liao, N. L., Egan, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Determination+of+urea+brackish+and+seawater+by+flow+injection+analysis+colorimetry.">Determination of urea brackish and seawater by flow injection analysis colorimetry.</a> QuickChem Method. , (2001).</li><li>. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=SAS+Institute.">SAS Institute.</a> The SAS system, version 8.0. , (2000).</li><li>Humphry, J. B., Daniel, T. C., Edwards, D. R., Sharpley, A. N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+portable+rainfall+simulator+for+plot-scale+runoff+studies.">A portable rainfall simulator for plot-scale runoff studies.</a> Appl. Eng. Agric. 18, 199-204 .</li><li>. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=National+Phosphorus+Research+Project.">National Phosphorus Research Project.</a> National research project for simulated rainfall- surface runoff studies: Protocol [Online]. , (2013).</li><li>Mehlich, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mehlich+No.+3+soil+test+extractant:+A+modification+of+Mehlich+No.+2+extractant.">Mehlich No. 3 soil test extractant: A modification of Mehlich No. 2 extractant.</a> Comm. Soil Sci. Plant Anal. 15, 1409-1416 (1984).</li><li>Dunne, T., Black, R. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=An+experimental+investigation+of+runoff+production+in+permeable+soils.">An experimental investigation of runoff production in permeable soils.</a> Water Res. Res. 6 (2), 478-490 (1970).</li></ol>

The authors declare no competing financial interests.

Runoff is mainly generated by two mechanisms, infiltration excess runoff and saturation excess runoff18 and is influenced by soil properties, antecedent soil moisture, topography, and rainfall intensity. Rainfall simulation can be used to fix the rainfall intensity variable and study one or more of the remaining variables. Rainfall intensity and duration can also be controlled over a limited range for study by changing the nozzle size. The most critical steps for conducting rainfall simulation studies on packed soil boxes are: 1) ensuring uniform packing of soil boxes; 2) controlling antecedent soil moisture content; 3) calibrating flow rate for the selected nozzle so that drop size and velocity approximates natural rainfall; and 4) adjusting nozzle position to ensure uniform rainfall across all soil boxes.
At the end of the calibration process, once a CV of less than 0.05 is achieved for rainfall uniformity across all soil boxes, the 10 min&#160;calibration should be repeated several times to ensure that rainfall intensity across runs is consistent. A CV can also be calculated for uniformity across runs. If the CV for uniformity across runs is less than that for uniformity of rainfall across all boxes, consider grouping replicate treatments within individual runs to minimize variation across treatments. Otherwise, to reduce the error associated with box position and across runs, randomize both treatments and replicates according to box position, taking steps to limit placing a treatment in a position more than once.
Using this rainfall simulator design and a standard protocol for properly calibrating the simulator will improve comparisons of results across studies conducted by different researchers. The data derived this way can be used to predict what happens under natural rainfall and better understand the processes and factors that control losses to the environment from nonpoint sources of contaminants. Such studies can yield valuable data for use in developing models for predicting the fate and transport of sediment and chemical pollutants in runoff under natural rainfall conditions.

The environmental impacts of agriculture are a global and rapidly increasing concern, especially in light of the uncertainties of global change. Rainfall is a driving force for the transport of environmental contaminants from agricultural soils to surficial water bodies via surface runoff. A large body of research is focused on better understanding the interactions between rainfall and soil conditions as they determine nonpoint sources of sediment, nutrient, and pesticide losses from agricultural soils. The objective of this study was to characterize the effects of antecedent soil moisture content on the fate and transport of surface applied commercial urea, a common form of nitrogen (N) fertilizer, following a rainfall event that occurs within 24 hr&#160;after fertilizer application.
There are few studies of the fate and transport of urea in soils, because urea is rapidly hydrolyzed to ammonium following fertilizer application and therefore not often available for transport. However, recent watershed studies suggest that urea can be transported from agricultural soils to coastal waters and cause shifts toward populations of organisms that produce harmful toxins1,2. Both laboratory and field experiments have shown that when the domoic acid-producing diatom Pseudo-nitzschia australis (P. australis) was grown in urea enriched seawater, the amount of domoic acid produced was greater than when grown on nitrate- or ammonium-enriched seawater3. This study used simulated rainfall to investigate the processes that control the potential for urea-N losses in runoff following commercial fertilizer application.
Due to the variability of natural rainfall, rainfall simulators have been used to apply uniform rainfall rates over land surfaces or packed soil boxes to evaluate runoff under controlled conditions. Rainfall simulators were initially used to study soil erosion4. However, over the years they have been used to measure other constituents in surface runoff and leachate from soils5-7. Field studies using natural rainfall have also been conducted to assess losses of soil constituents in runoff. Trends between natural rainfall and rainfall simulation data follow a similar pattern, pointing to a consistency in processes. Therefore rainfall simulation can be used in studies to predict the likely occurrence of what happens under natural rainfall8.
A variety of rainfall simulators have been developed, and typically they use nozzle sprayers to apply water at desired rates and durations. In terms of size, rainfall simulators range from a simple, small, portable infiltrometer with a 6&#160;in&#160;diameter rainfall area9 to the complex Kentucky rainfall simulator, which covers a plot 14.75 ft x 72 ft (4.5 m x 22 m)10. One shortcoming in the body of research that employed rainfall simulation is that there is no single standardized design or protocol for conducting rainfall simulations11. In fact, at the 2011 &#8220;International Rainfall Simulator Workshop&#8221; at Trier University, Germany, a collaborative community of scientists from 11 participating countries concluded that a standardization of rainfall simulation and simulators is needed in order to ensure the comparability of results and to promote further technical developments to overcome physical limitations and constraints12. This study seeks to partially address that need by presenting a detailed description of a standardized protocol for conducting rainfall simulations using a simulator that is already widely adopted for use in North America.
This experiment is part of a larger study designed to assess the source of urea in estuarine waters of the Chesapeake Bay where toxic algal blooms are known to occur annually. The specific objective of the experiment was to determine the effect of antecedent soil moisture content on urea losses in runoff. Duplicate uniformly packed soil boxes were prewetted to one of six different moisture contents representing 50, 60, 70, 80, 90, and 100% of field capacity. Urea was surface applied in prill form at a rate of 150 kg N/ha. Within 24 hr&#160;the boxes were subjected to uniform rainfall of 40 min&#160;duration at a rate of 3.17 cm/hr, equivalent to a natural precipitation event that commonly occurs on an annual basis on the Eastern Shore of the Chesapeake Bay in Maryland. Runoff samples were collected at 2 min intervals, immediately filtered using a glass filter (0.45 &#181;m), and stored at 4&#160;&#176;C until they were analyzed within 24 hr of collection. Urea-N concentrations were determined by flow injection analysis colorimetry13. Data were analyzed using SAS v.9.114, and statistical results were considered significant at P &#8804;0.05.
The portable rainfall simulator that was utilized in this study meets the design specifications15 and protocol that was developed by the National Phosphorus Project16. In the U.S. and Canada, this simulator design and protocol has been widely adopted as the standard method for use in determining both dissolved and particulate-bound phosphorus loss in runoff. Although runoff samples were analyzed for urea rather than phosphorus, the method for applying uniform and consistent rainfall to packed soil boxes is the same as that which is briefly described in the National Phosphorus Project rainfall simulation protocol.

<table border="0" cellpadding="0" cellspacing="0" width="808">
	<colgroup>
		<col />
		<col />
		<col />
		<col />
	</colgroup>
	<tbody>
		<tr height="42">
			<td height="42" style="height:42px;width:249px;">Rainfall Simulator</td>
			<td style="width:175px;">&#160;Joern&#39;s Inc.</td>
			<td style="width:147px;">TLALOC 3000</td>
			<td style="width:239px;">Size 1.5m x 2.0m (size optional)</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:249px;">Rainfall Simulator</td>
			<td>&#160;Joern&#39;s Inc.</td>
			<td style="width:147px;">TLALOC 4000</td>
			<td>Size 2.0m x 2.0m (size optional)</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:249px;">Rainfall Nozzle</td>
			<td style="width:175px;">Spraying Systems Inc.</td>
			<td style="width:147px;">3/8HH-SS17WSQ</td>
			<td>Size 17 nozzle</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:249px;">Rainfall Nozzle</td>
			<td style="width:175px;">Spraying Systems Inc.</td>
			<td style="width:147px;">3/8HH-SS24WSQ</td>
			<td>Size 24 nozzle</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:249px;">Rainfall Nozzle</td>
			<td style="width:175px;">Spraying Systems Inc.</td>
			<td style="width:147px;">1/2HH-SS30WSQ</td>
			<td>Size 30 nozzle</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:249px;">Rainfall Nozzle</td>
			<td style="width:175px;">Spraying Systems Inc.</td>
			<td style="width:147px;">3/8HH-SS50WSQ</td>
			<td>Size 50 nozzle</td>
		</tr>
	</tbody>
</table>

a protocol for conducting rainfall simulation to study soil runoff

Rainfall is a driving force for the transport of environmental contaminants from agricultural soils to surficial water bodies via surface runoff. The objective of this study was to characterize the effects of antecedent soil moisture content on the fate and transport of surface applied commercial urea, a common form of nitrogen (N) fertilizer, following a rainfall event that occurs within 24&#160;hr&#160;after fertilizer application. Although urea is assumed to be readily hydrolyzed to ammonium and therefore not often available for transport, recent studies suggest that urea can be transported from agricultural soils to coastal waters where it is implicated in harmful algal blooms. A rainfall simulator was used to apply a consistent rate of uniform rainfall across packed soil boxes that had been prewetted to different soil moisture contents. By controlling rainfall and soil physical characteristics, the effects of antecedent soil moisture on urea loss were isolated. Wetter soils exhibited shorter time from rainfall initiation to runoff initiation, greater total volume of runoff, higher urea concentrations in runoff, and greater mass loadings of urea in runoff. These results also demonstrate the importance of controlling for antecedent soil moisture content in studies designed to isolate other variables, such as soil physical or chemical characteristics, slope, soil cover, management, or rainfall characteristics. Because rainfall simulators are designed to deliver raindrops of similar size and velocity as natural rainfall, studies conducted under a standardized protocol can yield valuable data that, in turn, can be used to develop models for predicting the fate and transport of pollutants in runoff.

One reason for conducting the current experiment was to explore factors that may have contributed to poor results from a previous experiment where urea loss in runoff was being compared across several forms of fertilizers and manures that contained urea. All treatments were applied to soils that had been saturated and allowed to drain to field capacity. Results for five replicates of the urea prill treatment ranged from concentrations of 1-12 mg/L&#160;urea-N in runoff. This order of magnitude variation among replicates was unacceptable under controlled conditions and confounded the results of the experiment. A strong positive relationship between total volume of runoff and urea-N concentration in runoff suggested that physical conditions, such as packing or variable antecedent moisture conditions due to different draining and drying conditions, were causative factors.
In order to investigate the cause for such extreme variation in urea concentrations in runoff, all boxes in the current experiment were carefully packed with equal weights of uniformly mixed silt loam soil as depicted in Figures 1 and 2 to minimize variation in physical conditions. To achieve 50, 60, 70, 80, 90, and 100% of approximate field capacity as determined by wetting, then oven drying a small quantity of sieved soil, the weight of water required to wet the soil to corresponding antecedent soil moistures of 14, 17, 19, 22, 25, and 27% was calculated, added to the boxes, and allowed to equilibrate O/N. The rainfall simulation followed the exact protocol described above and depicted in Figures 3-5. The 17 wsq Full Jet 3/8 HH nozzle (Table 1) was used to deliver a rainfall intensity of 3.2 cm/hr&#160;over a 40 min&#160;period which is equivalent to a natural precipitation event that commonly occurs on an annual basis on the Eastern Shore of the Chesapeake Bay in Maryland.
The resulting total runoff volumes, loads, and flow weighted concentrations are summarized in Table 2. There was a significant positive relationship between total runoff volume and antecedent moisture condition (Figure 6). Wetter soils had less capacity to store water and lower infiltration rates resulting in greater runoff volumes. There was a significant negative relationship between time to runoff and antecedent moisture condition (Figure 7). Water infiltrated into drier soils for a longer period of time before they became wet near the surface, causing runoff to occur. Not surprisingly, there was a positive relationship between total load urea-N in runoff and total runoff volume (Figure 8). It is well known in hydrologic studies that flow volume is usually a strong predictor of total load. How concentration will behave in response to a runoff event is less predictable. Flow weighted concentration was calculated by summing the loads for each 2 min&#160;runoff collection and dividing by total runoff volume. It is equivalent to the concentration in a single collection of runoff at the end of the 40 min&#160;rainfall period. In this study, there was a significant positive relationship between flow weighted concentration in runoff and antecedent moisture condition (Figure 9). Given the positive linear relationships between runoff volume and antecedent soil moisture and flow weighted concentration and antecedent moisture condition, a significant positive relationship between total load urea-N and antecedent moisture condition was expected. However, this significant relationship was best described by an exponential equation (Figure 10).
In order to visualize urea-N loss in runoff over time, individual 2 min&#160;concentrations and cumulative loads in one replicate of a soil box representing each antecedent moisture condition was plotted over the 40 min&#160;rainfall time interval (Figure 11). Although concentrations in runoff can vary somewhat erratically over time (e.g.&#160;in the case of the 90% moisture), concentrations generally start high and decrease over time. Cumulative loads over time are much smoother functions, and they illustrate the significant relationships previously discussed. Time to runoff is longer, urea-N concentrations in runoff are lower, and cumulative loads are less for drier soils. Although urea hydrolyzes rapidly in soils, when rainfall occurs within hours of surface application, much of the N is still present in urea form and is subject to loss in runoff. Urea is a neutral molecule and is not strongly sorbed to the surfaces of soil particles. As water infiltrates the drier soils during the early part of a rainfall event it carries dissolved urea down into the soil and away from the surficial runoff zone. When runoff does begin, there is less urea present and concentrations in runoff are lower. From a practical sense, urea would almost always be applied under drier conditions as farm equipment could not traverse soils that are at field capacity.
<img alt="Figure 1" fo:content-width="5in" fo:src="/files/ftp_upload/51664/51664fig1highres.jpg" src="/files/ftp_upload/51664/51664fig1.jpg" /> 
Figure 1.&#160;Schematic of packed soil runoff box. A metal box (100 cm x 20 cm x 7.5 cm) with a 5&#160;cm lip on the forward end is packed with soil to a depth of 5 cm. Runoff that spills over the 5&#160;cm lip is collected in an attached gutter that is shielded against rainfall falling directly into the gutter. Nine 5&#160;mm diameter holes allow water that infiltrates the soil to drain from the boxes and prevent ponding. A nipple attached near the forward edge of the bottom of the gutter allows runoff water to drain into funnels and collection bottles positioned below the nipple.
<img alt="Figure 2" fo:content-width="5in" fo:src="/files/ftp_upload/51664/51664fig2highres.jpg" src="/files/ftp_upload/51664/51664fig2.jpg" /> 
Figure 2.&#160;Box packing materials. Approximately 4 layers of cheesecloth in the bottom of the box prevent soil loss but allow water to drain freely. A leveling gauge consisting of acrylic glass sandwiched between two wooden boards is as wide as the box (20 cm) and as deep (2.5 cm) as the difference between the sides of the box (7.5 cm) and the top of the gutter (5 cm). By resting the board on the lip of the box the acrylic glass is used to grade soil to the depth of the gutter.
<img alt="Figure 3" fo:content-width="5in" fo:src="/files/ftp_upload/51664/51664fig3highres.jpg" src="/files/ftp_upload/51664/51664fig3.jpg" /> 
Figure 3.&#160;Positioning the platform. Position the platform so that when the packed soil boxes are in position, they all have the same slope. For this study, the desired slope was 3%. While holding a board level, position the platform so that the down slope, gutter end of the box is 3 cm below the upslope end. The platform should be level in the cross slope direction.
<img alt="Figure 4" fo:content-width="5in" fo:src="/files/ftp_upload/51664/51664fig4highres.jpg" src="/files/ftp_upload/51664/51664fig4.jpg" /> 
Figure 4.&#160;Rainfall simulator controls beginning from the water source and progressing through the plumbing system to the nozzle. (1) Single lever ball valve: This is a quick shutoff valve. Lever in line with pipe is on; lever at 90 degree angle across pipe is off. Use this valve to turn flow on and off without disturbing valves that control pressure and flow rate. Open fully and close fully. Do not try to use this valve to control flow rate. (2) Sediment filter: Check filter periodically and replace element as needed to prevent clogging with sediment. (3) Pressure regulator valve: This valve controls the pressure in the line from this point forward. Too much pressure may break pipes, hoses or connections. (4) In-line flow control valve (Gate valve): This valve is used to fine tune the flow to the nozzle in order to achieve the desired flow rate and nozzle pressure. (5) Flow meter: Measures approximate flow rate. (6) Pressure gauge: Measures approximate pressure at the nozzle.
<img alt="Figure 5" fo:content-width="5in" fo:src="/files/ftp_upload/51664/51664fig5highres.jpg" src="/files/ftp_upload/51664/51664fig5.jpg" /> 
Figure 5.&#160;Boxes positioned on the platform for rainfall simulation. Place 5 or 6 boxes in marked positions for each rainfall simulation event. Avoid positioning a box directly under the nozzle to prevent dripping directly onto a box surface.
<img alt="Figure 6" fo:content-width="5in" fo:src="/files/ftp_upload/51664/51664fig6highres.jpg" src="/files/ftp_upload/51664/51664fig6.jpg" /> 
Figure 6.&#160;Total runoff volume is positively correlated with antecedent soil moisture content (R2 = 0.64).
<img alt="Figure 7" fo:content-width="5in" fo:src="/files/ftp_upload/51664/51664fig7highres.jpg" src="/files/ftp_upload/51664/51664fig7.jpg" /> 
Figure 7.&#160;Time to runoff is negatively correlated with antecedent soil moisture content (R2 = 0.48). The surface of a wet soil saturates quickly. Rainfall that exceeds the hydraulic conductivity of the saturated soil generates runoff.
<img alt="Figure 8" fo:content-width="5in" fo:src="/files/ftp_upload/51664/51664fig8highres.jpg" src="/files/ftp_upload/51664/51664fig8.jpg" /> 
Figure 8.&#160;Total load urea-N is positively correlated with runoff volume (R2 = 0.81). Differences in runoff volume overwhelm differences in concentration of urea-N in runoff.
<img alt="Figure 9" fo:content-width="5in" fo:src="/files/ftp_upload/51664/51664fig9highres.jpg" src="/files/ftp_upload/51664/51664fig9.jpg" /> 
Figure 9.&#160;Flow weighted concentration of urea-N is positively correlated with antecedent soil moisture content (R2 = 0.66). Drier soils allow infiltration that leaches urea-N into the soil and away from the soil surface. When runoff does occur, less urea-N is available at the surface for movement in runoff.
<img alt="Figure 10" fo:content-width="5in" fo:src="/files/ftp_upload/51664/51664fig10highres.jpg" src="/files/ftp_upload/51664/51664fig10.jpg" /> 
Figure 10.&#160;Total load urea-N is positively correlated with antecedent soil moisture content (R2 = 0.74). The positive relationships between total runoff volume and antecedent soil moisture content and between flow weighted concentration of urea-N and antecedent moisture content combine to result in an exponential relationship (y = 0.2043 e0.0405x).
<img alt="Figure 11" fo:content-width="5in" fo:src="/files/ftp_upload/51664/51664fig11highres.jpg" src="/files/ftp_upload/51664/51664fig11.jpg" /> 
Figure 11.&#160;Urea-N concentration and cumulative load relationships over time for one replicate of each antecedent soil moisture content. Although urea-N concentration is not always a smooth function through time, the significant relationships previously discussed can be visualized.
<table border="0" cellpadding="0" cellspacing="0" width="613">
	<colgroup>
		<col />
		<col />
		<col />
		<col />
		<col />
	</colgroup>
	<tbody>
		<tr height="29">
			<td height="29" style="height:29px;width:173px;">Nozzle Size</td>
			<td style="width:96px;">Intensity</td>
			<td style="width:145px;">Optimum Pressure</td>
			<td style="width:83px;">Flow</td>
			<td style="width:117px;">10 sec Flow</td>
		</tr>
		<tr height="29">
			<td height="29" style="height:29px;width:173px;"></td>
			<td style="width:96px;">cm/hr</td>
			<td style="width:145px;">psi</td>
			<td style="width:83px;">gpm</td>
			<td style="width:117px;">ml</td>
		</tr>
		<tr height="29">
			<td height="29" style="height:29px;width:173px;">17 wsq Full Jet 3/8 HH</td>
			<td style="width:96px;">3.2</td>
			<td style="width:145px;">6.0</td>
			<td style="width:83px;">1.5</td>
			<td style="width:117px;">940</td>
		</tr>
		<tr height="29">
			<td height="29" style="height:29px;width:173px;">24 wsq Full Jet 3/8 HH</td>
			<td style="width:96px;">3.3</td>
			<td style="width:145px;">6.0</td>
			<td style="width:83px;">1.8</td>
			<td style="width:117px;">1,140</td>
		</tr>
		<tr height="29">
			<td height="29" style="height:29px;width:173px;">30 w Full Jet 1/2 HH</td>
			<td style="width:96px;">6.0</td>
			<td style="width:145px;">5.0</td>
			<td style="width:83px;">2.2</td>
			<td style="width:117px;">1,250</td>
		</tr>
		<tr height="29">
			<td height="29" style="height:29px;width:173px;">50 w Full Jet 1/2 HH</td>
			<td style="width:96px;">7.0</td>
			<td style="width:145px;">4.1</td>
			<td style="width:83px;">3.7</td>
			<td style="width:117px;">2,300</td>
		</tr>
	</tbody>
</table>
Table 1.&#160;Nozzle size chart. Nozzle sizes that have been identified for use with this rainfall simulator and their associated rainfall intensity, pressure and flow parameters are presented. Selection of nozzle size depends on the desired rainfall intensity. Rainfall intensity and duration correspond to a precipitation event of a certain return period for a specified study location. Nozzle size 17 wsq was used for this study. Rainfall of 40 min&#160;duration at an intensity of 3.2 cm/hr&#160;is equivalent to a natural precipitation event that commonly occurs on an annual basis on the Eastern Shore of the Chesapeake Bay in Maryland.
<table border="0" cellpadding="0" cellspacing="0" width="513">
	<colgroup>
		<col />
		<col span="2" />
		<col />
	</colgroup>
	<tbody>
		<tr height="26">
			<td height="26" style="height:27px;width:128px;">Soil moisture</td>
			<td style="width:129px;">Total runoff&#160;</td>
			<td style="width:129px;">Flow weighted</td>
			<td style="width:127px;">Total load&#160;</td>
		</tr>
		<tr height="26">
			<td height="26" style="height:27px;width:128px;">%</td>
			<td style="width:129px;">volume (L)</td>
			<td style="width:129px;">concentration&#160;</td>
			<td style="width:127px;">(mg urea-N)</td>
		</tr>
		<tr height="26">
			<td height="26" style="height:27px;width:128px;"></td>
			<td style="width:129px;"></td>
			<td style="width:129px;">(mg L-1 urea-N)</td>
			<td style="width:127px;"></td>
		</tr>
		<tr height="26">
			<td height="26" style="height:27px;width:128px;">&#160; 27&#8224;</td>
			<td style="width:129px;">2.96</td>
			<td style="width:129px;">4.99</td>
			<td style="width:127px;">13.66</td>
		</tr>
		<tr height="26">
			<td height="26" style="height:27px;width:128px;">27</td>
			<td style="width:129px;">2.87</td>
			<td style="width:129px;">4.37</td>
			<td style="width:127px;">12.55</td>
		</tr>
		<tr height="26">
			<td height="26" style="height:27px;width:128px;">25</td>
			<td style="width:129px;">2.52</td>
			<td style="width:129px;">3.57</td>
			<td style="width:127px;">8.62</td>
		</tr>
		<tr height="26">
			<td height="26" style="height:27px;width:128px;">25</td>
			<td style="width:129px;">1.81</td>
			<td style="width:129px;">2.33</td>
			<td style="width:127px;">4.21</td>
		</tr>
		<tr height="26">
			<td height="26" style="height:27px;width:128px;">22</td>
			<td style="width:129px;">2.52</td>
			<td style="width:129px;">2.18</td>
			<td style="width:127px;">5.50</td>
		</tr>
		<tr height="26">
			<td height="26" style="height:27px;width:128px;">22</td>
			<td style="width:129px;">2.47</td>
			<td style="width:129px;">1.54</td>
			<td style="width:127px;">3.81</td>
		</tr>
		<tr height="26">
			<td height="26" style="height:27px;width:128px;">19</td>
			<td style="width:129px;">1.99</td>
			<td style="width:129px;">1.72</td>
			<td style="width:127px;">3.41</td>
		</tr>
		<tr height="26">
			<td height="26" style="height:27px;width:128px;">19</td>
			<td style="width:129px;">2.35</td>
			<td style="width:129px;">3.70</td>
			<td style="width:127px;">8.68</td>
		</tr>
		<tr height="26">
			<td height="26" style="height:27px;width:128px;">17</td>
			<td style="width:129px;">1.91</td>
			<td style="width:129px;">1.69</td>
			<td style="width:127px;">3.22</td>
		</tr>
		<tr height="26">
			<td height="26" style="height:27px;width:128px;">17</td>
			<td style="width:129px;">1.66</td>
			<td style="width:129px;">0.90</td>
			<td style="width:127px;">1.50</td>
		</tr>
		<tr height="26">
			<td height="26" style="height:27px;width:128px;">14</td>
			<td style="width:129px;">1.51</td>
			<td style="width:129px;">0.78</td>
			<td style="width:127px;">1.18</td>
		</tr>
		<tr height="26">
			<td></td>
			<td></td>
			<td></td>
			<td height="26" style="height:27px;">&#8224; Duplicate numbers represent two replications for each moisture level</td>
		</tr>
	</tbody>
</table>
Table 2.&#160;Antecedent soil moisture content, total runoff volume, flow weighted urea-N concentration and total urea-N load after rainfall simulation. Duplicate numbers represent two replications for each moisture level

Watch this Scientific Journal Video about A Protocol for Conducting Rainfall Simulation to Study Soil Runoff at JoVE.com

A Protocol for Conducting Rainfall Simulation to Study Soil Runoff

A rainfall simulator was used to apply a consistent rate of uniform rainfall to packed soil boxes in a study of the fate and transport of urea, a nonpoint source environmental contaminant. Under uniform soil and rainfall conditions, antecedent soil moisture content exerted strong control over urea loss in surface runoff.

Rainfall is a driving force for the transport of environmental contaminants from agricultural soils to surficial water bodies via surface runoff. The ...

a-protocol-for-conducting-rainfall-simulation-to-study-soil-runoff

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Environment

20.5K ビュー.  University of Maryland Eastern Shore. 降雨シミュレータは、尿素、非点源の環境汚染物質の運命と輸送の研究にパックされた土壌のボックスへの一様な降雨の一貫した率を適用するために使用された。均一な土壌や降雨条件下では、前件土壌水分量は、表面流出中の尿素の損失に強い制御を発揮した。 

ビデオ: A Protocol for Conducting Rainfall Simulation to Study Soil Runoff

Design and Operation of a Continuous 13C and 15N Labeling Chamber for Uniform or Differential, Metabolic and Structural, Plant Isotope Labeling

Tracing rare stable isotopes from plant material through the ecosystem provides the most sensitive information about ecosystem processes; from CO2 fluxes and soil organic matter formation to small-scale stable-isotope biomarker probing. Coupling multiple stable isotopes such as 13C with 15N, 18O or&#160;2H has the potential to reveal even more information about complex stoichiometric relationships during biogeochemical transformations. Isotope labeled plant material has been used in various studies of litter decomposition and soil organic matter formation1-4. From these and other studies, however, it has become apparent that structural components of plant material behave differently than metabolic components (i.e. leachable low molecular weight compounds) in terms of microbial utilization and long-term carbon storage5-7. The ability to study structural and metabolic components separately provides a powerful new tool for advancing the forefront of ecosystem biogeochemical studies. Here we describe a method for producing 13C and 15N labeled plant material that is either uniformly labeled throughout the plant or differentially labeled in structural and metabolic plant components.
Here, we present the construction and operation of a continuous 13C and 15N labeling chamber that can be modified to meet various research needs. Uniformly labeled plant material is produced by continuous labeling from seedling to harvest, while differential labeling is achieved by removing the growing plants from the chamber weeks prior to harvest. Representative results from growing Andropogon gerardii Kaw demonstrate the system&#39;s ability to efficiently label plant material at the targeted levels. Through this method we have produced plant material with a 4.4 atom%13C and 6.7 atom%15N uniform plant label, or material that is differentially labeled by up to 1.29 atom%13C and 0.56 atom%15N in its metabolic and structural components (hot water extractable and hot water residual components, respectively). Challenges lie in maintaining proper temperature, humidity, CO2 concentration,&#160;and light levels in an airtight 13C-CO2 atmosphere for successful plant production. This chamber description represents a useful research tool to effectively produce uniformly or differentially multi-isotope labeled plant material for use in experiments on ecosystem biogeochemical cycling.

Design and Operation of a Continuous 13C and 15N Labeling Chamber for Uniform or Differential, Metabolic and Structural, Plant Isotope Labeling

This method explains how to build and operate a continuous 13C and 15N isotope labeling chamber for uniform or differential plant tissue labeling. Representative results from metabolic and structural labeling of Andropogon gerardii are discussed.

Tracing rare stable isotopes from plant material through the ecosystem provides the most sensitive information about ecosystem processes; from CO2 fluxes ...

Design and Construction of an Urban Runoff Research Facility

As the urban population increases, so does the area of irrigated urban landscape. Summer water use in urban areas can be 2-3x winter base line water use due to increased demand for landscape irrigation. Improper irrigation practices and large rainfall events can result in runoff from urban landscapes which has potential to carry nutrients and sediments into local streams and lakes where they may contribute to eutrophication. A 1,000 m2 facility was constructed which consists of 24 individual 33.6 m2 field plots, each equipped for measuring total runoff volumes with time and collection of runoff subsamples at selected intervals for quantification of chemical constituents in the runoff water from simulated urban landscapes. Runoff volumes from the first and second trials had coefficient of variability (CV) values of 38.2 and 28.7%, respectively. CV values for runoff pH, EC, and Na concentration for both trials were all under 10%. Concentrations of DOC, TDN, DON, PO4-P, K+, Mg2+, and Ca2+ had CV values less than 50% in both trials. Overall, the results of testing performed after sod installation at the facility indicated good uniformity between plots for runoff volumes and chemical constituents. The large plot size is sufficient to include much of the natural variability and therefore provides better simulation of urban landscape ecosystems.

This paper describes the design, construction, and function of a 1,000 m2 facility containing 24 individual 33.6 m2 field plots equipped for measuring total runoff volumes with time and collection of runoff subsamples at selected intervals for quantification of chemical constituents in the runoff water from simulated home lawns.

As the urban population increases, so does the area of irrigated urban landscape. Summer water use in urban areas can be 2-3x winter base line water use ...

Experimental Protocol for Manipulating Plant-induced Soil Heterogeneity

Coexistence theory has often treated environmental heterogeneity as being independent of the community composition; however biotic feedbacks such as plant-soil feedbacks (PSF) have large effects on plant performance, and create environmental heterogeneity that depends on the community composition. Understanding the importance of PSF for plant community assembly necessitates understanding of the role of heterogeneity in PSF, in addition to mean PSF effects. Here, we describe a protocol for manipulating plant-induced soil heterogeneity. Two example experiments are presented: (1) a field experiment with a 6-patch grid of soils to measure plant population responses and (2) a greenhouse experiment with 2-patch soils to measure individual plant responses. Soils can be collected from the zone of root influence (soils from the rhizosphere and directly adjacent to the rhizosphere) of plants in the field from conspecific and heterospecific plant species. Replicate collections are used to avoid pseudoreplicating soil samples. These soils are then placed into separate patches for heterogeneous treatments or mixed for a homogenized treatment. Care should be taken to ensure that heterogeneous and homogenized treatments experience the same degree of soil disturbance. Plants can then be placed in these soil treatments to determine the effect of plant-induced soil heterogeneity on plant performance. We demonstrate that plant-induced heterogeneity results in different outcomes than predicted by traditional coexistence models, perhaps because of the dynamic nature of these feedbacks. Theory that incorporates environmental heterogeneity influenced by the assembling community and additional empirical work is needed to determine when heterogeneity intrinsic to the assembling community will result in different assembly outcomes compared with heterogeneity extrinsic to the community composition.

Understanding the role of environmental heterogeneity in species coexistence has typically focused on types of heterogeneity that are extrinsic to the community&#8217;s species composition. We provide novel detailed methods for creating soil heterogeneity treatments using soils subject to plant-soil feedback conditioning, or heterogeneity intrinsic to the community composition.

Coexistence theory has often treated environmental heterogeneity as being independent of the community composition; however biotic feedbacks such as ...

Soil Sampling and Isolation of Entomopathogenic Nematodes (Steinernematidae, Heterorhabditidae)

Entomopathogenic nematodes (a.k.a. EPN) represent a group of soil-inhabiting nematodes that parasitize a wide range of insects. These nematodes belong to two families: Steinernematidae and Heterorhabditidae. Until now, more than 70 species have been described in the Steinernematidae and there are about 20 species in the Heterorhabditidae. The nematodes have a mutualistic partnership with Enterobacteriaceae bacteria and together they act as a potent insecticidal complex that kills a wide range of insect species.
Herein, we focus on the most common techniques considered for collecting EPN from soil. The second part of this presentation focuses on the insect-baiting technique, a widely used approach for the isolation of EPN from soil samples, and the modified White trap technique which is used for the recovery of these nematodes from infected insects. These methods and techniques are key steps for the successful establishment of EPN cultures in the laboratory and also form the basis for other bioassays that consider these nematodes as model organisms for research in other biological disciplines. The techniques shown in this presentation correspond to those performed and/or designed by members of S. P. Stock laboratory as well as those described by various authors.

Soil Sampling and Isolation of Entomopathogenic Nematodes Steinernematidae, Heterorhabditidae

Entomopathogenic nematodes are soil-inhabiting roundworms that parasitize a wide range of insects. We demonstrate sampling methods used for the isolation of these nematodes from the soil using two techniques: the insect baiting and the modified White trap, for the recovery of nematodes from soil samples and infected insect cadavers, respectively.

Entomopathogenic nematodes (a.k.a. EPN) represent a group of soil-inhabiting nematodes that parasitize a wide range of insects. These nematodes belong to ...

A Protocol for Collecting and Constructing Soil Core Lysimeters

Leaching of nutrients from land applied fertilizers and manure used in agriculture can lead to accelerated eutrophication of surface water. Because the landscape has complex and varied soil morphology, an accompanying disparity in flow paths for leachate through the soil macropore and matrix structure is present. The rate of flow through these paths is further affected by antecedent soil moisture. Lysimeters are used to quantify flow rate, volume of water and concentration of nutrients leaching downward through soils. While many lysimeter designs exist, accurately determining the volume of water and mass balance of nutrients is best accomplished with bounded lysimeters that leave the natural soil structure intact. 
Here we present a detailed method for the extraction and construction of soil core lysimeters equipped with soil moisture sensors at 5 cm and 25 cm depths. Lysimeters from four different Coastal Plain soils (Bojac, Evesboro, Quindocqua and Sassafras) were collected on the Delmarva Peninsula and moved to an indoor climate controlled facility. Soils were irrigated once weekly with the equivalent of 2 cm of rainfall to draw down soil nitrate-N concentrations. At the end of the draw down period, poultry litter was applied (162 kg TN ha-1) and leaching was resumed for an additional five weeks. Total recovery of applied irrigation water varied from 71% to 85%. Nitrate-N concentration varied over the course of the study from an average of 27.1 mg L-1 before litter application to 40.3 mg L-1 following litter application. While greatest flux of nutrients was measured in soils dominated by coarse sand (Sassafras) the greatest immediate flux occurred from the finest textured soil with pronounced macropore development (Quindocqua).

A detailed method for extraction and assembly of intact soil core lysimeters and their use for study of leachate and associated loss of nutrients from surface applied poultry litter is demonstrated.

Leaching of nutrients from land applied fertilizers and manure used in agriculture can lead to accelerated eutrophication of surface water. Because the ...

Soil Lysimeter Excavation for Coupled Hydrological, Geochemical, and Microbiological Investigations

Studying co-evolution of hydrological and biogeochemical processes in the subsurface of natural landscapes can enhance the understanding of coupled Earth-system processes. Such knowledge is imperative in improving predictions of hydro-biogeochemical cycles, especially under climate change scenarios. We present an experimental method, designed to capture sub-surface heterogeneity of an initially homogeneous soil system. This method is based on destructive sampling of a soil lysimeter designed to simulate a small-scale hillslope. A weighing lysimeter of one cubic meter capacity was divided into sections (voxels) and was excavated layer-by-layer, with sub samples being collected from each voxel. The excavation procedure was aimed at detecting the incipient heterogeneity of the system by focusing on the spatial assessment of hydrological, geochemical, and microbiological properties of the soil. Representative results of a few physicochemical variables tested show the development of heterogeneity. Additional work to test interactions between hydrological, geochemical, and microbiological signatures is planned to interpret the observed patterns. Our study also demonstrates the possibility of carrying out similar excavations in order to observe and quantify different aspects of soil-development under varying environmental conditions and scale.

This study presents an excavation method for investigating subsurface hydrological, geochemical, and microbiological heterogeneity of a soil lysimeter. The lysimeter simulates an artificial hillslope which was initially under homogeneous condition and had been subjected to approximately 5,000 mm of water over eight cycles of irrigation in an 18-month period.

Studying co-evolution of hydrological and biogeochemical processes in the subsurface of natural landscapes can enhance the understanding of coupled ...

A Gusseted Thermogradient Table to Control Soil Temperatures for Evaluating Plant Growth and Monitoring Soil Processes

Thermogradient tables were first developed in the 1950s primarily to test seed germination over a range of temperatures simultaneously without using a series of incubators. A temperature gradient is passively established across the surface of the table between the heated and cooled ends and is lost quickly at distances above the surface. Since temperature is only controlled on the table surface, experiments are restricted to shallow containers, such as Petri dishes, placed on the table. Welding continuous aluminum vertical strips or gussets perpendicular to the surface of a table enables temperature control in depth via convective heat flow. Soil in the channels between gussets was maintained across a gradient of temperatures allowing a greater diversity of experimentation. The gusseted design was evaluated by germinating oat, lettuce, tomato, and melon seeds. Soil temperatures were monitored using individual, battery-powered dataloggers positioned across the table. LED lights installed in the lids or along the sides of the gradient table create a controlled temperature chamber where seedlings can be grown over a range of temperatures. The gusseted design enabled accurate determination of optimum temperatures for fastest germination rate and the highest percentage germination for each species. Germination information from gradient table experiments can help predict seed germination and seedling growth under the adverse soil conditions often encountered during field crop production. Temperature effects on seed germination, seedling growth, and soil ecology can be tested under controlled conditions in a laboratory using a gusseted thermogradient table.

Traditional thermogradient tables create a range of temperatures across the surface. Welding gussets perpendicular to the surface of a thermogradient table will control temperature in depth increasing possible research applications.

Thermogradient tables were first developed in the 1950s primarily to test seed germination over a range of temperatures simultaneously without using a ...

Measuring and Mapping Patterns of Soil Erosion and Deposition Related to Soil Carbonate Concentrations Under Agricultural Management

Spatial patterns of soil erosion and deposition can be inferred from differences in ground elevation mapped at appropriate time increments. Such changes in elevation are related to changes in near-surface soil carbonate (CaCO3) profiles. The objective is to describe a simple conceptual model and detailed protocol for repeatable field and laboratory measurements of these quantities. Here, accurate elevation is measured using a ground-based differential global positioning system (GPS); other data acquisition methods could be applied to the same basic method. Soil samples are collected from prescribed depth intervals and analyzed in the lab using an efficient and precise modified pressure-calcimeter method for quantitative analysis of inorganic carbon concentration. Standard statistical methods are applied to point data, and representative results show significant correlations between changes in soil surface layer CaCO3 and changes in elevation consistent with the conceptual model; CaCO3 generally decreased in depositional areas and increased in erosional areas. Maps are derived from point measurements of elevation and soil CaCO3 to aid analyses. A map of erosional and depositional patterns at the study site, a rain-fed winter wheat field cropped in alternating wheat-fallow strips, shows the interacting effects of water and wind erosion affected by management and topography. Alternative sampling methods and depth intervals are discussed and recommended for future work relating soil erosion and deposition to soil CaCO3.

Spatial patterns of soil erosion and deposition can be inferred from differences in ground elevation mapped at appropriate time increments. Such changes in elevation are related to changes in near-surface soil carbonates. Repeatable methods for field and laboratory measurements of these quantities and data analysis methods are described here.

Spatial patterns of soil erosion and deposition can be inferred from differences in ground elevation mapped at appropriate time increments. Such changes ...

Use of Principal Components for Scaling Up Topographic Models to Map Soil Redistribution and Soil Organic Carbon

Landscape topography is a critical factor affecting soil formation and plays an important role in determining soil properties on the earth surface, as it regulates the gravity-driven soil movement induced by runoff and tillage activities. The recent application of Light Detection and Ranging (LiDAR) data holds promise for generating high spatial resolution topographic metrics that can be used to investigate soil property variability. In this study, fifteen topographic metrics derived from LiDAR data were used to investigate topographic impacts on redistribution of soil and spatial distribution of soil organic carbon (SOC). Specifically, we explored the use of topographic principal components (TPCs) for characterizing topography metrics and stepwise principal component regression (SPCR) to develop topography-based soil erosion and SOC models at site and watershed scales. Performance of SPCR models was evaluated against stepwise ordinary least square regression (SOLSR) models. Results showed that SPCR models outperformed SOLSR models in predicting soil redistribution rates and SOC density at different spatial scales. Use of TPCs removes potential collinearity between individual input variables, and dimensionality reduction by principal component analysis (PCA) diminishes the risk of overfitting the prediction models. This study proposes a new approach for modeling soil redistribution across various spatial scales. For one application, access to private lands is often limited, and the need to extrapolate findings from representative study sites to larger settings that include private lands can be important.

Landscape processes are critical components of soil formation and play important roles in determining soil properties and spatial structure in landscapes. We propose a new approach using stepwise principal component regression to predict soil redistribution and soil organic carbon across various spatial scales.

Landscape topography is a critical factor affecting soil formation and plays an important role in determining soil properties on the earth surface, as it ...

Microplot Design and Plant and Soil Sample Preparation for 15Nitrogen Analysis

Many&#160;nitrogen fertilizer studies evaluate the overall effect of a treatment on end-of-season measurements such as grain yield or cumulative N losses. A stable isotope approach is necessary to follow and quantify the fate of fertilizer derived N (FDN) through the soil-crop system. The purpose of this paper is to describe a small-plot research&#160;design utilizing non-confined 15N enriched microplots for multiple soil and plant sampling events over two growing seasons and provide sample collection, handling, and processing protocols for total 15N analysis. The methods were demonstrated using a replicated study from south-central Minnesota planted to corn (Zea mays L.). Each treatment consisted of six corn rows (76 cm row-spacing) 15.2 m long with a microplot (2.4 m by 3.8 m) embedded at one end. Fertilizer-grade urea was applied at 135 kg N&#8729;ha-1 at planting, while the microplot received urea enriched to 5 atom % 15N. Soil and plant samples were taken several times throughout the growing season, taking care to minimize cross-contamination by using separate tools and physically separating unenriched and enriched samples during all procedures. Soil and plant samples were dried, ground to pass through a 2 mm screen, and then ground to a flour-like consistency using a roller jar mill. Tracer studies require additional planning, sample processing time and manual labor, and incur higher costs for 15N enriched materials and sample analysis than traditional N studies. However, using the mass balance approach, tracer studies with multiple in-season sampling events allow the researcher to estimate FDN distribution through the soil-crop system and estimate unaccounted-for FDN from the system.

Microplot Design and Plant and Soil Sample Preparation for 15Nitrogen Analysis

A microplot design for 15N tracer research is described to accommodate multiple in-season plant and soil sampling events. Soil and plant sample collection and processing procedures, including grinding and weighing protocols, for 15N analysis are put forth.

Many&#160;nitrogen fertilizer studies evaluate the overall effect of a treatment on end-of-season measurements such as grain yield or cumulative N losses. ...