Using Soil Moisture Data to Estimate Evapotranspiration and Development of a Physically Based Root Water Uptake Model

摘要: In humid regions such as west-central Florida, evapotranspiration (ET) is estimated to be 70% of precipitation on an average annual basis (Bidlake et al. 1993; Knowles 1996; Sumner 2001). ET traditionally inferred from values potential (PET) or reference (Doorenabos and Pruitt 1977). PET data are more readily available can computed either pan evaporation energy budget methods (Penman 1948; Thornthwaite Monteith 1965; Priestly Taylor 1972, etc.). The above methodology though simple, suffer the fact that meteorological collected in field for mostly under non-potential conditions, rendering estimates erroneous (Brutsaert 1982; 2006). Lysimeters used determine mass balance, however, shallow water table environments, they found give readings due air entrapment (Fayer Hillel 1986), well fluctuating (Yang 2000). Remote sensing techniques as, satellite-derived feedback model Surface Energy Balance Algorithm (SEBAL) reviewed by Kite Droogers (2000) remotely sensed Normalized Difference Vegetation Index (NDVI) Mo (2004) especially useful large scale studies. However, case highly heterogeneous landscapes , resolution may become problematic owing coarse (Nachabe 2005). eddy correlation methodologies also limited computing net cannot resolve contribution different sources. For continuous soil moisture measurements estimation have been accurately 2005; Fares Alva Past studies, e.g., Robock (2000), Mahmood Hubbard (2003), Nachabe (2005), clearly shown monitoring successfully a hydrologic balance. approach herein involves use measurements. Using point measurement observations individual determined. Additionally, if similar content set wells along flow transect other components budgets attempts comprehensively at study site. following section describes particular configuration instruments, development methodology, example where authors applied