By: Gary L. Christopherson & D. Phillip Guertin
The University of Arizona
The Annual Meeting of the
American Schools of Oriental Research
Soil and water conservation is an important factor affecting
the success of any agricultural endeavor. This is especially true for the
highland regions of the Levant, where it has long been maintained that the
introduction of intensive agriculture, including terraces, enabled human
penetration into these areas during the Iron Age. Unfortunately there are
few terrace systems which can be securely dated to the Iron Age, leaving
the researcher with few artifactual pegs upon which to hang this assertion.
This paper approaches the question not by looking for terraces, but by looking
for areas susceptible to soil erosion, i.e. areas where terrace walls would
be necessary to support agriculture. Concentrating on the region of Tall
al-'Umayri, Jordan, a series of models were built using a geographic information
system (GIS) and the Universal Soil Loss Equation (USLE) developed by the
USDA. These models estimate the erosion potential of the region under a
variety of conditions, including forested, deforested, and plowed. Iron
1 and Iron 2 archaeological sites from the region were then placed in the
models to discover the erosion potential at these sites. Results suggest
that agricultural terracing was utilized in the region throughout the Iron
The remains of ancient agricultural terraces are one of the most ubiquitous features of the Levantine hill country, but discovering the temporal context of these ancient terrace walls has proven to be nearly impossible. The nature of these remnants of past agricultural intensification is such that a recently built terrace may be identical in form to one built three thousand years ago, precluding most attempts at typological seriation. Further, in the life of a terrace, construction, destruction, and reconstruction, is a cycle which may be repeated many times. In the 'Umayri region, for example, terraces are currently being built atop the remains of their more ancient forebears, making a determination of their origins difficult. In this photograph, the ephemeral remains of an ancient terrace (forground) disappear beneath a terrace wall built in 1988. Finally, terraces defy traditional archaeological methods for dating. In general, terraces exhibit little or no stratigraphy. On a large terraced slope every wall will likely be a composite of original and reconstructed components, and an excavator can never be sure of anything beyond the portion of wall they have sectioned. Additionally, artifacts, such as pottery or coins, found in the walls may have as much to do with gravity induced percolation of water, soil, rocks, etc., down the slopes as they do with construction dates. About the only success at assigning a temporal context to terrace walls have been those few instances when they have been identified as complete units, associated with single period settlements or farmsteads (Edelstein & Gat, 1980-81; Edelstein & Gibson, 1982; Edelstein & Kislev, 1981). Unfortunately, most terrace walls do not arrive at the archaeologist's doorstep in such a neat package.
This difficulty in establishing a temporal context for agricultural terraces leaves room for many theories about the role they played in the settlement of the Levant. In the hill country of Judea, where most of the interest in terraces has been concentrated, they have been portrayed by many as the minimum technological requirement for the establishment of settlements during Iron Age I, yet few terraces can be securely dated to this period. Certainly the single most influential terrace wall in the region is the Iron Age I terrace from Site G of Calloway's excavation of 'Ai. One of the few terraces of the ancient world from a relatively secure stratigraphic context, this wall has become the foundation for many who see terracing as necessary for opening the hill-country to settlement.
This position has been most forcefully argued by Stager. Based on terraces at 'Ai and Radanna, Stager asserts:
Of all the technologies and techniques available to the Iron Age settlers, none served them better than agricultural terracing, which helped to open up the highland frontier to the Iron Age farmers. This technological advance dramatically altered the attractiveness of the Hill Country to the incoming agriculturists and increased its carrying capacity as never before. (Stager, 1985: 5)
Further, he maintains that this was a technology employed from the beginning by the new arrivals, stating, "The highland villagers were already well advanced in techniques of terrace agriculture when they established their settlements de novo on hilltops and laid out their terraced plots on the slopes below" (Stager, 1985: 6). Stager sees terrace farming as one of the hallmarks of Iron Age I in the Judean highlands, extending the influence of the 'Ai terrace to the "nearly 100 settlements founded in the hills at this time" (Stager, 1982: 116). Only the most forceful of many, Stager's assumption that terraces were necessary for penetration into the hill country during Iron Age I is echoed by a host of others. In one form or another and at various points in their careers, Ahlström, Calloway, De Geus, Dever, Gottwald, Meyers, and Thompson have all written that the Iron Age I economy of the Judean highlands was based in some measure on terrace agriculture (Ahlström, 1982: 183-184; Calloway, 1985: 41; De Geus, 1975: 70; Dever, 1990: 78; Gottwald, 1979: 658-659; Meyers, 1978: 95; Thompson, 1979: 66).
Although fewer in number, there are those who are not convinced that the terraces at 'Ai and Radanna are enough to posit an Iron Age I date for extensive terracing in the Judean hill-country. Hopkins in his work, The Highlands of Canaan, pursues an argument of logic in asserting that terraces were not used extensively during the initial stages of Iron Age settlement. Following Boserup, he contends that agricultural intensification occurs only when a growing population creates enough stress to make the extra effort necessary (Boserup, 1965: 41; Boserup, 1981: 31). Hopkins cites the tremendous amount of labor necessary to construct and maintain terraces (Hopkins, 1985: 177-178), the need for surplus labor and a level of community organization to carry out terracing projects (Hopkins, 1985: 178-179), and the fact that crops can be grown on slopes of up to 30 degrees without the aid of terraces (Hopkins, 1985: 180), to conclude that agricultural terraces were a "response of the Highland communities to exigencies encountered as the duration of their settlement progressed" (Hopkins, 1985: 181). This position gains support from Israel Finkelstein, who notes that "the earliest Israelite settlements turned out to be located in the very areas where terraces were less essential, while the classic terraced regions were practically devoid of settlement sites" (Finkelstein, 1988; Finkelstein, 1996).
This paper is proposing a new methodological approach to the question of when terrace agriculture was introduced. Based on the assumption that if archaeological sites are located in areas with low erosion potential, terracing would have been both unnecessary and improbable, the proposed methodology is not based on a new examination of terraces, or on an argument of logic, but on probabilities based on erosion potential. The vehicle by which these probabilities will be determined is a commonly used equation for determining soil loss, the Universal Soil Loss Equation (USLE), developed by the United States Department of Agriculture (USDA). Using this equation, in conjunction with a geographic information system (GIS), a series of models detailing erosion potential under a variety of conditions will be built for the region of Tall al-'Umayri, Jordan. Archaeological sites from the region will be placed in the models in order to discover the relative erosion potential for each site. It should be stated here, that the results of this paper are specific to the 'Umayri region, and do not apply to the Judean Highlands, or to other areas in the Near East; however, the methodology can be used anywhere.
The Madaba Plains Project (MPP) has been involved in Jordan since 1968, concentrating on the sites of Tall Hesban, Tall al-Umayri, and Tall Jalul. In addition to excavation, regional surveys were carried out in the vicinity of each of these sites. In the 'Umayri region, 133 archaeological sites were documented, ranging in size from large tells to small agricultural installations, and in age from Palaeolithic to late Islamic (Boling, 1989; Christopherson, forthcoming, 1997; Younker, 1991). For more information on the data collected by this survey, follow this link to a catalog of sites recorded by the 'Umayri survey.
Additionally, a GIS has been developed for the region using ARC/INFO software (ESRI, 1995). If the reader is not familiar with these spatial database systems, discussions can be found in many sources, including several with an archaeological emphasis (cf. Burrough, 1986; Christopherson, 1996; Kvamme, 1989; Kvamme, 1992). A short description can also be found by following this link to a GIS primer. For the Umayri GIS, data for hypsography, hydrography, physical, and cultural features were captured from the Jordan 1:25,000 series of topographic maps. Elevation, roads, and wadi channels were taken from the following sheets: Amman, Sheet 225/145 (D. Survey, 1958a), and Naur, Sheet 225/135 (D. Survey, 1958b). Additionally, geology and soil maps were created in 1992 by the MPP geologist, Douglas W. Schnurrenberger.
The coordinates for all GIS data were based on the Palestine Grid coordinate system and the Transverse Mercator projection of the Jordan 1:25,000 series maps. The unit of measure for this coordinate system is the meter, and the point of origin for this map series is 035° 12' 43.490" E. longitude, 31° 44' 02.749" N. latitude. The southwest corner of the digitized area was 228000 E, 136000 N; the northeast corner of the digitzed area was 240000 E, 148000 N. A raster grid, with a cell size of 50 X 50 meters, was imposed on the 144 square kilometers represented by these coordinates. This created a matrix of 240 rows and 240 columns, or 57,600 cells. Of the cells in the grid, 31,253 were contained within the five kilometer radius of the Umayri survey region. All anlysis in this study was confined to this five kilometer radius.
Surface erosion of soil is caused principally by rainfall dislodging soil particles from a surface. The energy of a single large rainstorm is enough to "splash over 200 metric tons of soil into the air on a single hectare of bare and loose soil. Individual particles can be splashed more than 0.5 m in height and 1.5 m sideways" (Brooks, Folliot, Gregersen, & Thames, 1991: 131). This concussive soil movement does not become a problem until the rate of rainfall exceeds the rate of infiltration into the soil. Once this rate is exceeded, water begins running across the surface, picking up the loosened soil particles and transporting them down slope. As it moves across the surface, the water forms rills, or gullies, picking up additional sediment as it goes. The sediment in the runoff water acts as an abrasive, tearing up additional sediment as it goes. Steep slopes and soils with low infiltration rates accelerate the process, making these two factors critical to the erosion process.
This study assumes that areas with high erosion rates (>50 metric tons/hectare/year) can not be successfully farmed using dryland farming practices without soil and water conservation structures. To model the rate of erosion, the Universal Soil Loss Equation (USLE), developed by the USDA Agricultural Research Service (Wischmeier & Smith, 1978), was used. The USLE is one of the most widely used methods for predicting erosion and has been successfully applied within a GIS framework (Cowen, 1993; Warren, Diersing, Thompson, & Goran, 1989). The major advantage of the USLE is that the data it requires are readily available. The USLE equation is:
A = R K L S V
where A, is the computed annual soil loss per acre (metric tons/hectare/year) and is the product of the following factors:
Rainfall Erosivity Factor (R): The R factor reflects the erosive energy of rainfall and is computed based on rainfall intensity. Using information developed by the United Nations Food and Agriculture Organization a R value of 75 was assigned to our study area.
Soil Erodibility Factor (K): The K factor reflects how erodible a soil would be under the worst conditions, that is, bare soil tilled up and down the slope. The K factor is computed as a function of soil texture and structure. The soils in the study region were all varieties of the Red Mediterranean Soils typical to the region. Based on texture, the Madaba Plains Project geologist identified three varieties of Red Mediterranean soil in the project area, referred to here as wadi soils, slope soils, and ridge soils. Wadi soils are found in the drainage bottoms and have a silty clay texture with less than 20% gravel or rock fragments. The slope soils are typically found on slopes and in small tributary wadis. They are a silty clay loam with a gravel or rock fragment content from 30% to 50%. The ridge soils, found along the ridge tops, have a silt loam texture and a gravel and rock fragment content between 30% and 70% (Schnurrenberger, personal communicaton). Historically, the ridge soils had the best water retention characteristics, and therefore were the better agricultural soils. With the combination of deforestation and discontinuity in terrace maintenance in the region, ridge soils have experienced high erosion levels and today are relatively shallow with significant levels of exposed bedrock. The erosion models developed here assume that this soil was deeper and had a lower percentage of gravel in antiquity than it does today. Using soil survey information from the study area, K values of 0.38, 0.35, and 0.69 were assigned to the wadi soils, slope soils, and ridge soils, respectively. The soil erodability factor (K) map was created by a reclassification of the soil map of the study area to reflect these values.
Slope Length and Slope Gradient
In the USLE equation, the slope length (L) and slope gradient (S) factors predict the effect of topography on erosion. The steeper and longer a slope, the higher its potential for erosion. The creation of the slope gradient and slope length factors was based on a procedure described by Cowen (1993) which uses rasterized facets from a triangulated irregular network, or TIN, to estimate slope gradient and length. This procedure yielded average slope gradients (in percent) and lengths (in meters) for each facet in the TIN surface which were then rasterized and the S and L factors computed. (Because of the resolution of our data a L factor of 1.0 was assumed across the study area.)
The V, or vegetative cover factor describes the impact of vegetation, or lack thereof, on potential erosion. Simply put the more cover you have the better the protection from erosion. Undisturbed natural systems are usually stable, with good vegetation cover characteristics and low erosion rates. As might be expected, tampering with the natural vegetation can seriously affect erosion rates. Deforestation will increase erosion potential by increasing a soil's exposure to wind and to water. More serious is farming, which usually increases erosion significantly by loosening and dislodging soil particles through the tilling of the soil. Using information from the United States Soil Conservation Service a V factor of 0.01 was assigned to natural conditions, 0.1 to deforested conditions and 0.3 to farmed conditions in the 'Umayri region.
In areas with high erosion rates structural control measures are needed, not only to control soil loss, but to capture enough surface runoff for successful crop production. This is especially true under dryland farming conditions in arid and semiarid environments. Control practices are those things that humans can do to promote water and soil retention. Generally this involves the building of terraces, check-dams, berms, embankments, and in modern times, reforestation.
Having constructed the model components, building the models themselves was a simple task. With each component map in a raster format, the model was built by instructing the GIS to multiply the USLE components to create new maps of erosion potential under certain conditions (Figure 1). Models for three different conditions were constructed, a model for the region with climax vegetation intact, a model for a deforested landscape, and a model for a deforested landscape being cultivated for agricultural purposes.
These models were then divided into three categories based on potential erosion. Areas with erosion potential of less than 10 metric tons/hectare/year, those with 10 to 50 metric tons/hectare/year, and those with 50 or more metric tons/hectare/year. At less than 10 tons, moisture retention is excellent with new soil forming fast enough to replenish that lost to erosion. At 10 to 50 tons, less water will percolate into the soil and the consequent runoff will cause soil depletion to occur, but at relatively low rates, often slow enough that soil loss would not necessarily be apparent to the farmer. Finally, at rates above 50 tons/hectare/year, soil loss would be readily apparent. Sheet wash and gullying of the soil would be problems for the farmer and remedial steps would be necessary for continued farming in these regions.
With examination of the three models, differences with regard to erosion potential became clear. Modeling erosion in the region with climax vegetation intact showed very little potential for erosion. In this model, 99% of the region lost less than 10 metric tons/hectare/year, and the remaining 1% lost between 10 and 50 tons/year (Figure 2). What this model demonstrated was that left in its natural state, the 'Umayri survey area would not experience significant erosion problems.
When the model removed vegetation from the region, erosion potential changed dramatically, with an increase in areas of high erosion at the expense of the low erosion zones. The area with less than 10 tons/hectare of erosion dropped from 99% to 64%, while the area with 10-50 tons/year rose from 1% to 31%. Additionally, 5% of the region was now losing more than 50 tons/hectare/year (Figure 3). Over the long run, deforestation would cause serious problems for the region, and is probably primarily responsible for the large areas of exposed bedrock today.
A more serious change occured when the model assumed that once the land had been cleared it was being tilled for agricultural purposes. This caused the percentage of high erosion zones to increase dramatically, with large portions of the area exhibiting serious erosion potential. In fact, the model estimated that 24% of the region was now losing more than 50 tons/hectare/year, and the areas losing less than 10 tons/year had decreased to just 33% of the region (Figure 4). Clearly, the coming of agriculture to the region would have had a dramatic impact on the landscape and it was likely a learning process for farmers as they sought to open new areas to cultivation. It is clear from this model that there were substantial portions of the landscape where terraces would have been necessary for agriculture to be successful.
Having built the erosion models, it was possible to establish the nature of the relationship between archaeological sites and the area's erosion potential. Approaching this question from the perspective of the farmer, our expectation was that they would prefer optimal agricultural zones, namely, those with ridge soils and low erosion potential. Wanting an accurate picture of conditions in the immediate vicinity of the sites, that is, those areas where most of the agricultural activity would be concentrated, Iron 1 and Iron 2 sites were buffered 100 meters in all directions, providing an area for examination of just over 3 hectares per site. Once these buffers were created, the soil and erosion potential maps were queried by the site maps and cross-tabulations of the results were prepared.
Looking first at the region as a whole (Table 1), these cross tabs establish the base from which comparisons will be made. In Table 1, erosion potential of less than 50 metric tons/hectare/year is labeled acceptable and erosion greater than 50 metric tons/hectare/year is labeled unacceptable. There are three numbers in this table that are particularly important. First, 26% of the region would be considered optimal for agriculture, having both acceptable erosion levels and ridge soils. The second important number is the total for unacceptable erosion potential. With only 23.8% of the region falling into this category, it is clear that there was adequate room for the establishment of farms in areas with low potential erosion. One final number to note is the total area taken up by ridge soils. At 44%, these soils constitute the best, but not the majority of soil in the region.
|Ridge Soils||Slope Soils||Wadi Soils||Total|
When these numbers are compared to the percentages for Iron Age I sites (Table 2), clear differences emerge. As expected a large percentage of the landscape surrounding these sites had both acceptable erosion levels and ridge soils. While this optimal agricultural zone was found in just 26% of the total project area, it constituted nearly 43.8% of the land in the vicinity of Iron Age I sites, making it the largest of the six possible categories. The second thing to notice is that 84.4% of the area surrounding Iron Age I sites is made up of ridge soils, substantially more than the 44% in the project area as a whole. Finally, note the difference between the totals for unacceptable erosion levels. While the region as a whole had only 23.8 % in unacceptable zones, the area surrounding Iron Age I sites is 42.2% and all but 1.6% of this is from areas with ridge soils. Based on these comparisons, the most important factor for Iron Age I settlers was ridge soils. If possible, areas with low erosion were utilized, but the principal factor was clearly soil type.
|Ridge Soils||Slope Soils||Wadi Soils||Total|
The significance of these differences was determined by conducting a one sample chi-square test. The differences between Tables 1 and 2 produced a chi-square statistic of 138.97. Based on this test statistic, the probability that the differences between these samples was a chance occurrence is less than 1 in 10,000. The implication of this statistic, and the percentages it was based on, is that in the 'Umayri region during the early Iron Age there is a very high probability that terrace agriculture was already being practiced. The strongest objection to this conclusion would be the nearly 60-40 split between unacceptable and acceptable levels of erosion. It could be argued that they were farming the 60 and using the 40 for their animals, but this argument runs into problems when individual sites are examined. Fifty-six percent of the Iron Age I sites had more than half of their surrounding area in high erosion zones, and a substantial number of these were almost totally surrounded by areas of unacceptable erosion. Clearly, at these sites terraces would have been essential for agriculture to succeed. The other possibility is that some of these were not agricultural sites, and this is probably true, but experience in the region has shown that agriculture was practiced at nearly every site.
This conclusion was supported by the results for Iron Age II sites in the 'Umayri region (Table 3). Terrace agriculture clearly played a significant role in the Iron Age II Levantine economy. If subsistence strategies were significantly different from Iron Age I to Iron Age II, this would be reflected by differences between the samples. Instead, the numbers indicate more similarity than dissimilarity. In Table 3, there is a shift to the right during the Iron Age II period, as other soil types were utilized more frequently, but the most important factor for Iron Age II sites remains ridge soils, now evenly split between acceptable and unacceptable erosion zones. Further, the totals for Iron Age II potential erosion are nearly identical to that for the Iron Age I sites, with 42.7% of the area surrounding Iron Age II sites in unacceptable zones. These relatively small differences indicate that the same agricultural zones were being utilized during Iron Age I and Iron Age II. Presumably, they were facing similar problems and utilizing similar strategies to solve these problems.
|Ridge Soils||Slope Soils||Wadi Soils||Total|
Based on these results, we would argue that four conclusions, tempered by three cautions, can be drawn regarding soil erosion and agricultural practices in the 'Umayri region. The first caution is a reminder that these are mathematical models. The author's believe them to be good models, but are aware that a different manipulation of the numbers might produce different results. Secondly, it is the nature of erosion to change the landscape, and these models were built on today's data. This means that no matter how carefully constructed, they can only approximate the ancient landscape. Third, labels of acceptable or unacceptable erosion in these models reflect modern values, not necessarily those of Iron Age farmers.
Aware of these cautions, we now propose the following conclusions. First,
with deforestation and the introduction of agriculture, soil erosion would
have been a serious problem in substantial portions of the 'Umayri survey
region. Second, Iron Age farmers clearly preferred ridge soils. Third, an
area's erosion potential was less important than soil type in selecting
locations for sites. Finally, it is highly probable that agricultural terraces
were utilized by both Iron Age I and Iron Age II farmers.
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The authors would like to thank the Madaba Plains Project for the archaeological data used in this paper, and the Advanced Resource Technology Group at the University of Arizona for access to ARC/INFO geographic information systems technology and expertise, and financial assistance in attending the meeting where the paper was presented.
Gary L. Christopherson is a Ph.D. candidate in the Near East Studies Department, and a Research Assistant in the Advanced Resource Technology Group at The University of Arizona. He has been associated with the Madaba Plains Project since 1987, where he is a Field Director in charge of archaeological survey. Correspondence may be sent to: ART Group (SRNR), 203 Biological Sciences East, The University of Arizona, Tucson, AZ, 85721, phone (520) 621-3045, or by email: Gary Christopherson -- email@example.com
D. Phillip Guertin is an Associate Professor within the School of Renewable Natural Resources, and leader of the Advanced Resource Technology Group, The University of Arizona. Correspondence may be sent to: ART Group (SRNR), 203 Biological Sciences East, The University of Arizona, Tucson, AZ, 85721, phone (520) 621-1723, or by email: Dr. Phil Guertin -- firstname.lastname@example.org