Process modeling for soil moisture using sensor network data |
| |
| Institution: | 1. Department of Mathematics and Statistics, Texas Tech University, Lubbock, TX 79409, USA;2. Department of Statistical Science, Duke University, Durham, NC 27708, USA;3. Department of Botany, University of Wyoming, Laramie, WY 82071, USA;4. Nicholas School of Environment, Duke University, Durham, NC 27708, USA;5. Department of Electrical Engineering, Northern Arizona University, Flagstaff, AZ 86011, USA;1. UMR 729 MISTEA, INRA-SupAgro, 2 place Pierre Viala, 34060 Montpellier, France;2. LMAP, UMR CNRS 5142, Université de Pau et des Pays de l’Adour, Avenue de l’Université, 64000 Pau, France;1. Laboratoire de Mathématiques Appliquées de Compiègne-L.M.A.C., Université de Technologie de Compiègne, B.P. 529, 60205 Compiègne Cedex, France;2. L.S.T.A., Université Pierre et Marie Curie, 4 place Jussieu, 75252 Paris Cedex 05, France;1. Purdue University, United States;2. North Carolina State University, United States;3. Newcastle University, UK |
| |
| Abstract: | The quantity of water contained in soil is referred to as the soil moisture. Soil moisture plays an important role in agriculture, percolation, and soil chemistry. Precipitation, temperature, atmospheric demand and topography are the primary processes that control soil moisture. Estimates of landscape variation in soil moisture are limited due to the complexity required to link high spatial variation in measurements with the aforesaid processes that vary in space and time. In this paper we develop an inferential framework that takes the form of data fusion using high temporal resolution environmental data from wireless networks along with sparse reflectometer data as inputs and yields inference on moisture variation as precipitation and temperature vary over time and drainage and canopy coverage vary in space. We specifically address soil moisture modeling in the context of wireless sensor networks. |
| |
| Keywords: | Data fusion Euler discretization Hierarchical nonlinear model Partial differential equation State space model |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
