Soil Water Retention Curve
Abstract
Potential water retention, S, is one of parameters commonly used in hydrologic modeling for soil moisture accounting. Physically, S indicates total amount of water which can be stored in soil and is expressed in units of depth. S can be represented as a change of soil moisture content and in this context is commonly used to estimate direct runoff, especially in the Soil Conservation Service (SCS) curve number (CN) method. Generally, the lumped and the distributed hydrologic models can easily use the SCS-CN method to estimate direct runoff. Changes in potential water retention have been used in previous SCS-CN studies; however, these studies have focused on long-term hydrologic simulations where S is allowed to vary at the daily time scale. While useful for hydrologic events that span multiple days, the resolution is too coarse for short-term applications such as flash flood events where S may not recover its full potential. In this study, a new method for estimating a time-variable potential water retention at hourly time-scales is presented. The methodology is applied for the Napa River basin, California. The streamflow gage at St Helena, located in the upper reaches of the basin, is used as the control gage site to evaluate the model performance as it is has minimal influences by reservoirs and diversions. Rainfall events from 2011 to 2012 are used for estimating the event-based SCS CN to transfer to S. As a result, we have derived the potential water retention curve and it is classified into three sections depending on the relative change in S. The first is a negative slope section arising from the difference in the rate of moving water through the soil column, the second is a zero change section representing the initial recovery the potential water retention, and the third is a positive change section representing the full recovery of the potential water retention. Also, we found that the soil water moving has traffic jam within 24 hours after finished first rainfall because of the difference between infiltration and percolation rates.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2016
- Bibcode:
- 2016AGUFM.H21C1420J
- Keywords:
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- 1805 Computational hydrology;
- HYDROLOGYDE: 1847 Modeling;
- HYDROLOGYDE: 1865 Soils;
- HYDROLOGY