Submitted to: Transactions in Geographic Information Systems
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: January 25, 1997
Publication Date: N/A
Interpretive Summary: Macropores are large soil pores which, if continuous and connected to deeper portions of the soil profile, can materially influence the speed at which rain water will infiltrate into the soil and the amount of runoff an area may produce. Areas most likely to produce runoff or contribute to infiltration are called the contributing areas and may require special attention because they could serve as a primary conduit for chemicals to the groundwater (infiltration contributing areas), or as a source of sediment and surface flow to streams (runoff contributing areas). The objective of the study was to illustrate how to delineate contributing areas and how to relate them to measured values of macroporosity. To begin with spatial distribution of infiltration was predicted from an equation based on how fast water infiltrated at selected locations within an area. Points in between the measured locations were interpolated. When compared to similarly calculated distributions of rain, areas contributing to runoff and infiltration could be delineated. Macroporosity, based on pores larger than 3/100 of an inch in diameter, were estimated using infiltration rates measured at selected points and then spatially distributed in a similar fashion. In general high values of macroporosity corresponded to areas with higher infiltration, although not necessarily to primary... necessarily to primary contributing areas.
Technical Abstract: Topics considered in this study, which is cast in a geographical information systems (GIS) context, are spatial distribution of infiltration on an agricultural catchment and the manner in which macroporosity affects infiltration and infiltration related variables such as sorptivity and conductivity. The goal is to illustrate how to delineate areas contributing to runoff and infiltration and how to relate them to measured values of macroporosity. To accomplish this goal infiltration parameters sorptivity (S) and percolation rate (A) were evaluated in the field with a 0.3 m diameter infiltrometer, while macroporosity estimates at the same locations were based on the distribution of negative head (-40 mm) infiltration flux (Rogowski and Hoover 1996). Distributions of field measured parameters were used to prepare catchment wide attribute overlays in a GIS IDRISI1(Eastman 1992) format. Overlays of precipitation (P) and infiltration (I) were then intersected with one another for conditions of (P-I)<0 or (P-I)>/=0. This created alternate masks targeting specific portions of the watershed. In areas where (P-I)>/=0, locations with excess rain were designated as potential runoff contributing zones. Elsewhere, infiltration (I) was predicted in time (t) by a simple (I=St0.5+At) two parameter model (Philip 1957), or proceeded at a rate equal to the rainfall rate if (P-I)<0. We used kriging and sequential indicator simulation to model spatial patterns of infiltration and macropore continuity respectively. When modeling in GIS, cell size and time interval define the scale of averaging. Geostatistical structural analysis can justify scale selection, kriging displays the distribution, whereas conditional simulation will yield multiple equiprobable realizations which honor data