Groundwater Residue Sampling Design - American Chemical Society

Chapter 10

Soil Map Units Basis for Agrochemical-Residue Sampling 1

2

D. L Karlen and T. E. Fenton 1

National Soil Tilth Laboratory, Agricultural Research Service, U.S. Department of Agriculture, 2150 Pammel Drive, Ames, IA 50011 Department of Agronomy, Iowa State University, Ames, IA 50011

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Representative sample collection is the most critical step in any program designed to determine how soil and crop management affects the presence of agrochemical residues such as nitrate nitrogen or pesticides. Soil map units within the soil classification system, can be used to develop sampling plans with comparable soil bodies despite natural soil diversity. Soil map unit data can be analyzed statistically and used to provide information for geographic information systems (GIS). Use of soil map units for selecting sampling sites to evaluate current and alternate management practices on agrochemical residues is recommended. A n a l y t i c a l measurement of agrochemical residues such as n i t r a t e nitrogen (N0 -N) or pesticides i n s o i l samples must meet QAQC (quality assurance quality control) standards, but for useful and v a l i d interpretation of the analyses each sample must represent an i n d i v i d u a l and s p e c i f i c s o i l phase. This i s important because s o i l s have different b i o l o g i c a l , chemical, and physical properties. The ultimate fate of many agrochemicals w i l l be determined by interactions controlled by s o i l and agrochemical properties. Developing a sampling plan that provides representative samples i s a very c r i t i c a l process. It i s important to understand landscape v a r i a b i l i t y i n r e l a t i o n to the s o i l patterns, and to have elementary knowledge of current s o i l characterization and c l a s s i f i c a t i o n concepts. Our objective is to describe why s o i l s vary and to demonstrate how s o i l map units can be used to locate p a r t i c u l a r s o i l bodies from which representative samples can be collected to quantify agrochemical residue concentrations. 3

0097^156/91/0465-0182$06.00/0 © 1991 American Chemical Society

In Groundwater Residue Sampling Design; Nash, R., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1991.

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Drainage Systems Drainage systems have been defined as open or closed basins. Using an analogy of thermodynamic systems (I), an open system was theorized to have matter and energy imported and exported across boundaries and energy transformed uniformly to maintain a steady state. A drainage basin of any size i s a natural open system that i s confined at i t s head (origin) and along i t s sides by the perimeter (outermost) d i v i d e , but i t i s open at i t s mouth. Surface water from r a i n f a l l or melt water i s c o l l e c t e d by the drainage net that forms the basin and i s discharged through the outlet or mouth (2). In a natural closed system, there i s an i n t e r i o r basin and the drainage net descends i n a c e n t r i p e t a l pattern. Surface water o r i g i n a t i n g from atmospheric sources descends the drainageways and c o l l e c t s i n the basin. Loss of water i s only through evaporation, transpiration by plants, and subsurface percolation (2). Drainage patterns are important because movement of many agrochemical residues i s d i r e c t l y or i n d i r e c t l y related to the path of water and sediment movement. Identifying the drainage basin type and boundaries must be given high p r i o r i t y when selecting s i t e s and developing agrochemical sampling plans. Although the same s o i l map units can occur within either an open or closed drainage system, fate of agrochemicals applied to s o i l s w i l l d i f f e r . Materials that move with runoff or drainage water w i l l accumulate i n a closed basin, but continue to move away from application s i t e s i n an open basin. If samples representing a single map unit are c o l l e c t e d from different types of drainage basins, differences i n the amount of residues that are measured may erroneously be attributed to v a r i a b i l i t y among s o i l samples rather than to differences i n drainage patterns. Landscape Position The idea that s o i l s are landscapes as well as p r o f i l e s has been generally accepted for 40 years (3). Each s o i l occupies space, i s defined i n three dimensions, can be evaluated r e l a t i v e to evolution of elements within the landscape, and can be mapped. Recognition of this idea increased awareness of soil-geomorphic relationships and resulted i n development of several models to explain soil-landscape relationships (4-7). Each model can make important contributions toward understanding landscape p o s i t i o n , but the most important part i s recognizing that a l l s o i l s on the landscape are not the same age S o i l landscapes have been described as the geographic d i s t r i b u t i o n of s o i l s on landscapes (2). When this simple c l a s s i f i c a t i o n system i s combined with a model of landscape evolution, both s o i l materials and r e l a t i v e s o i l water relations can be accurately predicted. These factors are important for understanding processes and especially i n helping understand s o i l v a r i a b i l i t y within a l o c a l landscape (S). This knowledge i s important for developing representative agrochemical sampling plans because the fate of many chemicals w i l l be determined by interactions that occur because of i d e n t i f i a b l e s o i l and/or chemical properties.


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The current landscape terminology originated after previously suggested (9) segments of a " f u l l y developed h i l l s l o p e " were modified and renamed (10). A summit, shoulder, backslope, footslope, and toeslope are the five elements currently recognized. This slopep r o f i l e terminology can be applied to the geomorphic components of headslope, sideslope, and toeslope (Figure 1). Relative s t a b i l i t y and water movement for these s l o p e - p r o f i l e elements i n humid regions was discussed previously (II), but are summarized here because of t h e i r importance for understanding factors that influence s o i l v a r i a b i l i t y and t h e i r reaction with various agrochemicals. Summit. This p o s i t i o n i s considered to be the most stable element of the landscape. There i s l i t t l e runoff where the summit i s at least 30 m wide. Water movement i s predominantly v e r t i c a l except near the t r a n s i t i o n to the shoulder or on summit undulations. In these areas some l a t e r a l water movement and accompanying surface and deep percolation occur. Shoulder. This p o s i t i o n has slopes that are usually convex. Surface runoff i s maximized i n this element r e s u l t i n g i n a highly erosional and r e l a t i v e l y unstable surface. P r o b a b i l i t y of l a t e r a l subsurface flow i s high. Solum thickness and organic matter content are usually a minimum on this element. Backslope. Dominant processes on this p o s i t i o n include both surface and subsurface transportation of material and water. Slopes are nearly l i n e a r and steepest on this landscape p o s i t i o n . Surface transport of material may be i n the form of flow, slump, surface wash, or creep. This p o s i t i o n i s considered to be r e l a t i v e l y unstable. Footslope. Concavity i s c h a r a c t e r i s t i c of t h i s landscape p o s i t i o n . The concavity results i n deposition from upslope of p a r t i c u l a t e material as well as material c a r r i e d i n solution. The p o s i t i o n i s dominantly constructional and r e l a t i v e l y unstable. Seepage zones are common and the water content i s usually much higher than on shoulder or backslope positions. Cumulic s o i l s are associated with this p o s i t i o n i n the Midwest. Toeslope. This p o s i t i o n i s constructional and r e l a t i v e l y unstable. A l l u v i a l material i n the toeslope p o s i t i o n i s derived from up v a l l e y and from upslope elements. The slope shape and position c l a s s i f i c a t i o n system (2) i s a very useful t o o l for f i e l d investigations, because i t helps predict the s o i l composition, relationships to surrounding landscape features, and s o i l water regimes (8). However, for evaluating s o i l product i v i t y , i t has been suggested that the backslope should be divided into l i n e a r , nose and head slope positions (8). This recommendation was made because different water flow regimes among these positions can create large differences i n s o i l - p l a n t environments. A s i m i l a r argument can be made for evaluating agrochemical movement.


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10.

Figure 1. Landscape elements associated with a f u l l y developed hillslope. (Redrawn with permission from r e f . 5. Copyright 1969 Iowa State Univ. Press).


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What i s a S o i l ? S o i l i s defined as "the unconsolidated mineral matter on the surface of the earth that has been subjected to and influenced by genetic and environmental factors of: parent material, climate (including moisture and temperature e f f e c t s ) , macro- and microorganisms, and topography, a l l acting over a period of time and producing a product- s o i l - - t h a t d i f f e r s from the material from which i t i s derived i n many p h y s i c a l , chemical, b i o l o g i c a l and morphological properties and characteristics (12). The basic s o i l model i s a function of the five s o i l forming f a c t o r s , but occasionally the model has been modified to include man as a s i x t h s o i l forming factor. Unique combinations r e s u l t i n g from overlapping of these factors gives r i s e to different s o i l s (13). An alternate model views s o i l formation or genesis as consisting of two steps that i n some cases can be overlapping (14). The two steps are parent material accumulation and horizon d i f f e r e n t i a t i o n . Additions, removals, transfers, and transformations that occur over time cause horizon d i f f e r e n t i a t i o n . Various process combinations are operative i n a l l s o i l s , and the process balance determines the nature of the s o i l formed. S o i l Forming Factors Parent material (mineral content, p a r t i c l e s i z e , e t c . ) influences the inherent f e r t i l i t y , chemical reaction, and s o i l texture. The deposition method (residual, or transported by i c e , water, or wind) primarily affects s o i l texture and landscape topography. Formation time, i n conjunction with intensity (ie temperature, r a i n f a l l , e t c . ) , determines the degree of progress i n s o i l development. Topography influences s o i l water, temperature, and erosion. S o i l s on sloping land lose water as runoff and are generally d r i e r than non-sloping s o i l s i n the same area. Depressional s o i l s usually have higher water content than sloping s o i l s . Sloping topographies are subject to more erosion than f l a t t e r land under s i m i l a r land cover. Slope orientation and elevation are topographical factors that influence l o c a l microclimate and thus influence the s o i l forming processes. Climate influences s o i l type because p r e c i p i t a t i o n , temperature, and the amount of erosive wind and water action determine weathering rates of parent materials. Water and temperature influence b i o l o g i cal and chemical reaction rates including solution, hydration, and leaching. Climate also determines the kind and quantity of vegetat i o n found throughout various landscapes and the amount of organic material added each year. The b i o t a type and quantity determine the kind and amount of organic materials that are returned to the s o i l . Biota influence s p a t i a l organic material deposition, i e . , trees deposit most organic matter on the surface, while grasses d i s t r i b u t e organic matter v i a t h e i r root systems throughout large volumes of s o i l . Vegetation influences many other b i o l o g i c a l processes by providing energy sources for microbial processes including nitrogen mineralization,


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f i x a t i o n , and immobilization, as well as organic matter and crop residue decomposition processes that influence nutrient c y c l i n g .


Soil Variability Recognition of s p a t i a l v a r i a b i l i t y i n s o i l s i s important i n designing a sampling scheme. Two broad categories of s p a t i a l v a r i a b i l i t y , systematic and random, are commonly recognized (15). Systematic v a r i a b i l i t y i s a change i n s o i l properties as a function of landform, geomorphic component, or a s o i l forming factor. One example from northwest Iowa (Figure 2) shows the relationship between g l a c i a l t i l l and ground surface elevation i n a loess over g l a c i a l t i l l landscape. I f surface elevation i s known, the elevation at which g l a c i a l t i l l w i l l be encountered can be predicted quite accurately. Systematic change has been documented for h i l l s l o p e sediments (16) which are formed by processes including slope wash, faunal a c t i v i t y , creep, and frost heave. Water movement sorts the materials downs lope creating changes i n s o i l texture that are predictable. For an Iowa landscape (16) formed i n g l a c i a l t i l l , sorting resulted i n a systematic change i n p a r t i c l e size from the summit to a midslope point where a sand lens was encountered. However, this change could be described by equation 1, where L i s the distance from the summit. Below the intersection with the sand lens, mean sediment diameter increased abruptly and the relationship was described by a l o g a r i t h mic function presented i n equation 2. Y - 139.73 + 1.95L - 3.67L

2

Y - 325.25 - 228.12 log L

(1) (2)

Another h i l l s l o p e sediment study (4) showed that p a r t i c l e s i z e , organic carbon, cation exchange capacity, and extractable Ca and Mg were d i r e c t l y related to the upslope source. Being aware of these s o i l changes i s important when developing agrochemical sampling plans because of organic matter, pH, and other interactions between s o i l and agrochemical properties, and because most sloping landscapes have large areas of sediment reworked by one or more processes (8) . Even i n v i r g i n forest (17), and throughout the Southern Piedmont, about 50% of the landscape i s covered by material other than residuum (1819). The most d i f f i c u l t impediment to obtaining this information i s that only highly detailed s o i l morphology normally recognizes h i l l s l o p e sediments (8). I f changes i n s o i l properties can not be related to a known cause, the changes are c l a s s i f i e d as random or chance v a r i a t i o n s . The categorization of v a r i a b i l i t y , however, i s often dependent on observation spacing. V a r i a b i l i t y o r i g i n a l l y considered random may i n some cases be shown to be systematic i f the sampling intensity i s increased, or i f c o n t r o l l i n g mechanisms are i d e n t i f i e d . Anticipated v a r i a b i l i t y among s o i l s can be predicted based on selected parameters. By studying morphologically matched pedons (three-dimensional bodies of s o i l having an area ranging from 1 to 10 m and i d e n t i f i a b l e horizon shapes and r e l a t i o n s ) , the following 2



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1110

Ο

1070 Η 1080

.

1 1090

1

1 1100

1

1

1110

SURFACE ELEVATION (FEET) Figure 2. Systematic v a r i a b i l i t y as shown by s o i l surface and g l a c i a l t i l l elevations i n northwest Iowa.


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generalized order for v a r i a b i l i t y i n physical properties has been reported as a function of parent material: loess < g l a c i a l d r i f t < alluvium - residium (20). S i m i l a r l y , the following generalized array for s p a t i a l v a r i a b i l i t y i n p h y s i c a l , chemical and elemental s o i l properties was suggested (21):


Parent m a t e r i a l - - Loess < g l a c i a l t i l l < g l a c i a l outwash - g l a c i a l lacustrine - alluvium; Elements---

Κ - T i < Zr < Fe < Ca;

Horizons—

No consistent trend among A, B, and C horizons.

In an o v e r a l l sampling project, the magnitude of data v a r i a b i l i t y associated with various sources was probably greatest to l e a s t i n the following order (21): Landscape body » > choice laboratory analyses.

of pedon »

pedon sampling >

S o i l Map Units Natural s o i l v a r i a t i o n because of differences i n drainage, landscape p o s i t i o n , s o i l forming factors, or possibly long-term management practices may appear to make i t impossible to c o l l e c t a representa t i v e sample. However, by using s o i l map units the natural v a r i a t i o n can be grouped into i d e n t i f i a b l e sampling units that can be analyzed statistically. A s o i l map unit i s a c o l l e c t i o n of areas within a landscape that can be defined and named i n terms the same as t h e i r s o i l components (22). Each map unit i d e n t i f i e d on a s o i l survey represents an i n d i v i d u a l pedon, a c o l l e c t i o n of very s i m i l a r pedons (polypedon), or polypedon parts that consist of contiguous s i m i l a r pedons and thus represent a "specific s o i l " . Map units may consist of one or more components that are i d e n t i f i e d i n the name of the map u n i t . Minor components that are not i d e n t i f i e d i n a map u n i t name are considered inclusions. A l l components, whether dominant or i n clusions, considered to be important for interpretation and use or understanding of a s o i l map unit are included i n the s o i l map unit d e s c r i p t i o n . With regard to agrochemical sampling, i t i s important to know that different s o i l map units may respond d i f f e r e n t l y to various a g r i c u l t u r a l chemicals because of inherent differences i n properties such as pH or organic matter content. Each map unit d i f f e r s i n some respect from a l l others within a survey area, i s bounded on a l l sides by pedons of unlike character, and can be uniquely i d e n t i f i e d as a delineation on a s o i l map. An important aspect, however, i s that s o i l boundaries can seldom be shown with complete accuracy on s o i l s maps because many boundaries are gradational i n character. Therefore, parts and pieces of adjacent polypedons are sometimes inadvertently included (inclusions)


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or excluded (exclusions) from each s o i l map u n i t . The p u r i t y and kinds of map units depend primarily on the scale and purpose for which a s o i l survey map was developed and the pattern of s o i l s and miscellaneous areas within the landscape. When developing agrochemical sampling plans, i t i s important to recognize differences i n scale because s o i l survey maps have been prepared at r a t i o s of 1:12000, 1:15840, 1:20000, or 1:24000. These scales correspond to 8.33, 6.31, 5.00, and 4.17 cm km" (5.28, 4.00, 3.17, and 2.64 inches mile" ). Map scale determines the number of inclusions i n each s o i l map u n i t , because each section of land (640 acres or 259 hectares) i s drawn on 27.9, 16.0, 10.0, or 7.0 inches (180, 103, 65, or 45 cm ). Examples of map unit d e t a i l associated with scales of 1:1200 and 1:15840 are shown i n Figure 3 and Figure 4, respectively. Figure 3 i s drawn for an area of approximately 20 acres (8 hectares) and provides much greater d e t a i l than Figure 4 which shows two adjacent 40 acre (16 ha) areas. S o i l map units provide an excellent basis for developing an agrochemical sampling scheme for several reasons. F i r s t , taxonomic classes provide the basic sets of s o i l properties that define s o i l map u n i t s . The s o i l taxonomic classes provide predefined sets of s o i l properties that have been tested for genetic relationships and for interpretive value. Taxa provide stable and consistent c r i t e r i a for recognizing the components and most probable c h a r a c t e r i s t i c s of p o t e n t i a l map units i n an unfamiliar area. Established taxa also make i t much easier to identify s i m i l a r s o i l s for each s t a t i s t i c a l class designation. S o i l map units thus summarize an immense amount of research and experience related to the significance of i n d i v i d u a l and combinations of s o i l properties (23). S o i l map units also provide a basis for sampling and grouping the natural v a r i a t i o n caused by landscape p o s i t i o n (24). To support increasing interest i n s o i l map u n i t s , more research i s occurring to quantify morphological map unit differences or "purity". Presently, no more than 25% of a map unit should be comprised of d i s s i m i l a r s o i l s and no more than 10 to 15% should have c h a r a c t e r i s t i c s more l i m i t i n g than the named s o i l ( s ) (22). 1

1

2


2

Sampling Procedure To develop an agrochemical sampling scheme using s o i l map u n i t s , a s o i l survey map must be obtained from the S o i l Conservation Service or other agencies i n the National Cooperative S o i l Survey. If a different mapping scale i s needed, specialized maps must be developed for the s i t e by trained s o i l s c i e n t i s t s . After obtaining a map with appropriate d e t a i l (Figure 3 and Figure 4) samples can be c o l l e c t e d randomly from within a s o i l map u n i t , or along transects with random or fixed spacings. After establishing transects, samples are c o l l e c t e d and handled to prevent contamination, coordinates of each sampling s i t e are determined, s o i l map units are i d e n t i f i e d from d i g i t i z e d or hardcopy maps, and data are analyzed s t a t i s t i c a l l y using s o i l map units as class variables for s t a t i s t i c a l programs such as the SAS General Linear Model (25). This technique was recently used to demonstra-


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Figure 4. S o i l map unit delineation for two adjacent 16 ha (40 acre) areas associated with a mapping scale of 1:15840 which is equivalent to 6.3 cm km" or 4 inches mile" . 1

1


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te how s o i l map units could be used to quantify crop y i e l d v a r i a t i o n i n a Coastal P l a i n f i e l d (26). Identifying the exact s o i l map unit at each sampling s i t e i s currently the most tedious process, but as global positioning devices and d i g i t i z e d s o i l maps become more a v a i l a b l e , this task w i l l be s i m p l i f i e d .


Information Transfer Use of s o i l map units as a basis for sampling for agrochemical residues w i l l f a c i l i t a t e information transfer among experiments conducted at different geographical scales. Results obtained from p l o t - or f i e l d - s c a l e experiments can be compared with those measured for farm-, watershed- or basin-scale studies that represent areas of 10, 100, or 1000 ha by identifying common s o i l map units at each scale of experimentation. Geographical information systems (GIS) can transfer information c o l l e c t e d for i n d i v i d u a l map units across s p a t i a l or temporal scales. Techniques for using GIS and small-scale d i g i t a l s o i l maps to study natural resource problems have recently been reported (27). By using currently available data bases such as the S o i l Survey Geographic Data Base (SSURGO), the State S o i l Geographic Data Base (STATSGO), or the National S o i l Geographic Data Base (NATSGO) , interpretive maps can be made by overlaying s o i l data with other s p a t i a l resource data (28). Conclusion As s o i l survey maps throughout the U.S. and i n several countries around the world are completed and subsequently d i g i t i z e d , s o i l map units should be used to develop sampling schemes to measure agrochemi c a l residues i n various s o i l matrices throughout a l l agroecological zones.

Literature Cited 1. Strahler, A. N. Geol. Soc. Am. Bull. 1952, 63, pp. 923-938. 2. Rune, R. V. Geomorphology; Houghton Mifflin Co.: Boston, MA. 1975. pp. 246. 3. Soil Survey Staff. Soil Survey Manual, USDA Handbook 18. U.S. Gov. Print. Office, Washington, DC. 1951. pp. 503 4. Ruhe, R.V.; Daniels, R.B.; Cady, J.G. Landscape Evolution and Soil Formation in Southwestern Iowa. USDA Tech. Bull. 1349. 1967. pp. 242. 5. Ruhe, R. V. Quaternary Landscapes in Iowa. Iowa State Univ. Press., Ames, IA. 1969. pp. 255. 6. Hack, J.T. Am. J . Sci. 1960, 258A, pp. 80-97. 7. Conacher, A.J.; Dalrymple, J.B. Geoderma. 1977, 18, pp. 1-154. 8. Daniels, R.B.; Bubenzer, G.D. In Proceedings of soil erosion and productivity workshop. Larson, W.E.; Foster, G.R.; Allmaras, R.R.; Smith, C.M., Eds.; Univ. Minnesota: St. Paul, MN 1990. pp. 1-22. 9. Wood, A. Geol. Assoc. Proc. 1942, 53, pp. 128-138.



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10. Ruhe, R. V. Transactions 7th Intl. Congr. Soil Sci, Madison, WI. 1960; pp. 165-170. 11. Hall, G. F. In Pedogenesis and Soil Taxonomy I. Concepts and Interactions; Wilding, L.P.; Smeck, N.E.; Hall, G.F. Eds.; Elsevier Publishing Co., Amsterdam. 1983. pp. 303. 12. Soil Science Society of America. Glossary of soil science terms; Soil Sci. Soc. Am.: Madison, WI, 1979. 13. Arnold, R.W. In Pedogenesis and Soil Taxonomy I. Concepts and interactions; Wilding, L.P; Smeck, N.E.; Hall, G.F. Eds.; Elsevier Publishing Co., Amsterdam. 1983. pp. 303. 14. Simonson, R.W. Soil Sci. Soc. Am. Proc. 1959. 53, pp. 152-156. 15. Wilding, L.P.; Drees, L.R. In Pedogenesis and Soil Taxonomy I. Concepts and Interactions; Wilding, L.P.; Smeck, N.E.; Hall, G.F. Eds.; Elsevier Publishing Co., Amsterdam. 1983. pp. 303. 16. Kleiss, H.J. Soil Sci. Soc. Amer. Proc. 1970 34, pp. 287-290. 17. McCracken, R.J.; Daniels, R.B.; Fulcher, W.E. Soil Sci. Soc. Am. J. 1989, 53, pp. 1146-1152. 18. Eargle, D.H. Science 1940, 91, pp. 337-388. 19. Whittecar, G.R. S.E. Geol. 1985. 26, pp. 117-129. 20. Mausbach, M.J.; Brasher, B.R.; Yeck, R.D.; Nettleton, W.D. Soil Sci. Sci. Am. J., 1980, 44 pp. 358-363. 21. Drees, L.R.; Wilding, L.P. Soil Sci. Soc. Am. Proc., 1973. 37 pp. 82-87. 22. Soil Survey Staff. National Soils Handbook. U.S. Gov. Print. Office, Washington, DC. 1983. pp. 618. 23. Hudson, B.D. Soil Survey Horizons, 1990, 31, pp. 63-72. 24. Gilliam, J.W.; Cassel, D.K.; Daniels, R.B.; Stone, J.R. In Erosion and Soil Productivity; Proceedings ASAE National Symp. on Erosion and Soil Productivity, New Orleans, LA; Am. Soc. Agr. Eng., St. Joseph, MI. 1985. pp. 75-82. 25. SAS Institute Inc. SAS User's Guide: Statistics. Version 5 Edition. Cary, NC. 1985. pp. 956 26 Karlen, D.L.; Sadler, E . J . ; Busscher, W.J. Soil Sci. Soc. Am. J. 1990, 54, pp. 859-865. 27. Bliss, N.B.; Reybold, W.U. J. Soil Water Conserv. 1989, 44, pp. 30-34. 28. Reybold, W.U.; TeSelle, G.W. J . Soil Water Conserv. 1989, 44 pp. 28-29. RECEIVED

November 5, 1990


Groundwater Residue Sampling Design - American Chemical Society

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