|Lei, T - PURDUE UNIV., WLAF, IN|
|Haghighi, K - PURDUE UNIV., WLAF, IN|
|Bralts, V - PURDUE UNIV., WLAF, IN|
Submitted to: Water Resources Research
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: June 26, 1998
Publication Date: N/A
Interpretive Summary: This study presents the results from a computer model which mimics the way in which rills form and change over time. The model presented in this study uses more advanced physics with a much higher level of complexity than has been used in previous scientific investigations. Most scientists, and perhaps most people, have the impression that if we know enough about a system, if we can describe it in enough detail, and if we understand erosion processes, we can calculate soil erosion rates. This study would indicate otherwise. The results shown here would indicate that there is a level of randomness in sediment loads which is inherent in nature. As the rill forms, it "self-generates" alternating regions of detachment and deposition in narrower and wider rill sections, respectively, and so the sediment load in the rill may naturally increase and decrease in an unpredictable manner as it meanders downshope. Depending then on where in the rill one takes erosion measurements, the sediment load has a natural component of variability associated with this widening and narrowing of the rill. This means that one might need to make more replications of erosion experiments than one might otherwise suppose in order to quantify or substantiate difference between treatments. By studying the behavior of this model, scientists can better understand how erosion occurs, but perhaps more importantly, it helps us understand how better to measure soil erosion and how to build better models for soil conservation purposes.
Technical Abstract: A series of laboratory flume experiments were performed to evaluate a mathematical model which simulates the dynamic process of rill evolution, including temporal changes in the spatial heterogeneity of rill flow width, depth, and velocity caused by varying rates of erosion and deposition along the bed. Initial bed slopes were 3, 5, and 7 percent with step increases of water inflow rates of 7.6, 11.4, and 15.2 liters per minute (2, 3 and 4 gallons per minute) at each slope grade. The soil material used in the flume was a kaolinitic, sandy-clay loam. The rill model equations were solved for each of the experimental flow conditions for four increasingly complex cases: A). time invariant and spatially uniform rill widths and bed slopes (elevations); B). time invariant and spatially uniform widths, time variable and spatially non-uniform slopes; C). time invariant but spatially non-uniform widths, time variable and spatially non-uniform slopes; D). time variant and spatially non-uniform rill widths and bed slopes. The model followed measured patterns of morphological changes as the rill evolved, which suggests that the feedback loops in the model between erosion, bed morphological changes, and hydraulics were adequate to capture the essence of rill evolution.