Zhang, 2011


Integrated Approach to Identifying Subsurface Flow in a Forest Catchment

Zhang, J. (2011)
Doctor of Philosophy, Soil Science, The Pennsylvania State University, p. 186  


During the last three decades, significant progress has been made in understanding the mechanism of subsurface lateral flow (SLF). However, the spatial and temporal occurrence of SLF remains poorly understood because of the complex subsurface heterogeneity and the lack of appropriate tools to identify such heterogeneity. The overall goal of this study is to develop an integrated hydrologic and geophysical database that can elucidate spatial and temporal patterns of SLF at the Shale Hills Critical Zone Observatory (CZO). Specifically, this study assembles a large database of Ground Penetrating Radar (GPR) images and real-time soil moisture monitoring, which is used to address the following four research objectives: 1) to identify spatial and temporal occurrence of SLF, 2) to investigate flow patterns in two contrasting soils-landform units, 3) to study the effect of soil horizonation on the seasonal change of GPR signals, and 4) to develop a new software to process, display, and interpret time-lapsed GPR data. Under objective 1), the direct evidence of SLF was revealed by comparing real-time soil moisture storage change in each monitored soil horizon at each site with rainfall inputs. Results indicated that SLF was ubiquitous across all the monitoring sites and 52% of 97 rainfall events from 2007 to 2009 produced SLF. However, individual monitoring site showed spatial and temporal variation in the occurrence of SLF, which was related to soil type, hillslope location, rainfall characteristics, and initial soil moisture. The results also clearly showed a rainfall threshold to initiate SLF, which increased from 1.1 to 2.3 mm from wet to dry seasons. Although SLF occurred at each site, only 9 out of the 97 rainfall events analyzed showed the connectivity from the hilltop to the valley floor. Under wet condition, only 1.1~ 2.3 mm rain could connect SLF from the hilltop to the valley floor, while under dry condition, 14.6 mm rain was needed to deliver water from the hilltop down to the valley floor. In addition, we found that the layers where SLF most likely to occur also varied among different hillslope locations that had different soil types: SLF in the shallow Weikert soil occurred mostly in the R horizon, while in the deep Rushtown soil SLF frequently occurred in the Bw and C horizons. This study enhanced the understanding of the mechanism, actual location, and potential flow pathway of SLF in a forested catchment and can improve process-based hydrological modeling. Under objective 2), time-lapsed GPR imaging was combined with real-time soil moisture monitoring to identify SLF pathways in two contrasting transects of soils. The real-time soil moisture monitoring showed that SLF occurred in top 20-cm soil after artificial water infiltration into the shallow Weikert soil in a planar hillslope (30% slope), whereas vertical flow dominated in the deep Rushtown soil located in a concave hillslope (swale) with 15% slope. The time-lapse GPR radargrams revealed the general infiltration wetting front and preferential flow pattern that were significantly different between the two types of soils and hillslopes, which were then confirmed by simulation modeling results. Through comparing simulated radargrams generated from four conceptual flow models with the field observed GPR data, we were able to confirm that subsurface lateral macropore flow was dominant in the shallow Weikert soil, while a combination of vertical macropore flow and lateral matrix flow was dominant in the deep Rushtown soil under the experimental conditions of this study. Time-lapsed GPR is proved to be a useful methodology for improved understanding of hydrologic connectivity in the subsurface, which can facilitate the formulation and test of different conceptualizations of subsurface network modeling. Under objective 3), GPR was combined with high resolution real-time soil moisture monitoring to examine seasonal changes of GPR signals at the interfaces of soil layers in two different soils. The results indicate that in the deep Rushtown soil reflection in the BC-C horizon interface became clearer as soil became wetter. High resolution real-time soil water monitoring and field observations indicated that this increased reflection may be due to SLF above and below the BC horizon, which increased the contrast along the interface. In contrast, in the shallow Weikert soil, reflections at the soil -bedrock interface and weathered-unweathered rock interface became intermittent as soil became wetter. This was likely caused by non-uniform distribution of water into the fractures of the shale bedrock, which created locally strong contrasts between soil and bedrock thus leading to point scatter of GPR reflection. The results also indicated optimal time to detect soil horizons in the two soils studied. Wet condition without rainfall event is optimal for detecting the BC-C interface in the Rushtown soil, while dry condition is optimal for detecting the soil-bedrock and weathered-unweathered interface in the Weikert soil. Our results also indicated that seasonal GPR survey with high resolution real-time soil water content monitoring is a promising methodology for understanding, explaining and conceptualizing hydrologic processes in the hillslope. Under objective 4), MATLAB-based software called Time-lapsed GPR (TGPR) has been developed as an alternative to expansive commercial software to process, display, and interpret GPR data collected in the Shale hills catchment. The TGPR can process both 2D and 3D GPR survey data and has ability to batch process surveys containing several profiles instead of single file as the commercial software usually does. With user-friendly interfaces, the TGPR can allow users to interactively edit radargrams and manually or automatically correct topography. The TGPR also provides several utilities to enhance 2D and 3D visualizations of GPR data. These utilities include trace view, wiggle view, and image view of 2D data; slice view, cube view, and transparent view of 3D data; ten built-in color table to enhance image display quality; layer editing on 2D image. Furthermore, with structured programming, TGPR can be easily expanded and customized. Overall, high temporal resolution real-time soil moisture monitoring data can be used to identify the occurrence of SLF, analyze SLF processes, and seasonal soil moisture change at the point scale. Combined with high spatial resolution GPR survey, spatial flow pattern can be identified, flow mechanism can be confirmed, and flow pathways can be traced at the hillslope scale. Such an integrated approach that combines the point and hillslope scales investigations provides valuable insights into the understanding of the complex and dynamic subsurface heterogeneity and how it impacts hydrologic processes.


Zhang, J. (2011): Integrated Approach to Identifying Subsurface Flow in a Forest Catchment . Doctor of Philosophy, Soil Science, The Pennsylvania State University, p. 186.

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Zhang, 2011
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