PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
January 9, 2008Sensors364 citationsOpen Access

Assessment of Evapotranspiration and Soil Moisture Content Across Different Scales of Observation

WVWillem W. VerstraetenRoyal Meteorological Institute of BelgiumFVFrank VeroustraeteShasta Bible College and Graduate SchoolJFJan FeyenRega Institute for Medical Research

Key Points

Key points are not available for this paper at this time.

Abstract

The proper assessment of evapotranspiration and soil moisture content arefundamental in food security research, land management, pollution detection, nutrient flows,(wild-) fire detection, (desert) locust, carbon balance as well as hydrological modelling; etc.This paper takes an extensive, though not exhaustive sample of international scientificliterature to discuss different approaches to estimate land surface and ecosystem relatedevapotranspiration and soil moisture content. This review presents:(i) a summary of the generally accepted cohesion theory of plant water uptake andtransport including a shortlist of meteorological and plant factors influencing planttranspiration;(ii) a summary on evapotranspiration assessment at different scales of observation (sapflow,porometer, lysimeter, field and catchment water balance, Bowen ratio,scintillometer, eddy correlation, Penman-Monteith and related approaches);(iii) a summary on data assimilation schemes conceived to estimate evapotranspirationusing optical and thermal remote sensing; and(iv) for soil moisture content, a summary on soil moisture retrieval techniques atdifferent spatial and temporal scales is presented.Concluding remarks on the best available approaches to assess evapotranspiration and soilmoisture content with and emphasis on remote sensing data assimilation, are provided.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Verstraeten et al. (2008) studied this question.

synapsesocial.com/papers/6a1fd2f5158420365711799ahttps://doi.org/10.3390/s8010070
Ask AI
Helpful
Bookmark
Share
View Full Paper