Evapotranspiration in Agro-Ecosystems and Forestry: Spatio-temporal Applications presents the progress and advances made in terms of science and application of evaporation, transpiration, and evapotranspiration for various vegetation surfaces, water bodies, and bare soil under different soil and crop management (including different irrigation and tillage management) conditions. Sections on forest and wetlands evapotranspiration and grassland evaporative losses are included, as are the fundamentals of original Penman, Penman-Monteith, Shuttleworth-Wallace and ASCE-EWRI and FAO56 Penman-Monteith equations and their derivatives.
The book is an excellent resource to better understand the progression and applications and dynamics of most recent evapotranspiration, evaporation and transpiration measurement and modeling technologies. Case studies will be provided in terms of how different technologies are currently deployed, how data are used for providing information and management decisions to the users.
1. Title of Book - p. i 2. Cover image - p. i 3. Title page - p. ii 4. Table of Contents - p. iii 5. Copyright - p. iv 6. List of contributors - p. ix 7. Preface - p. xi 8. Chapter One. Original Penman–Monteith actual crop evapotranspiration and standardized Penman–Monteith Reference evapotranspiration models - p. 1 9. Chapter Two. Simulating forest evapotranspiration in hydrologic models: challenges and opportunities - p. 33 10. Chapter Three. Global SSEBop actual evapotranspiration modeling and mapping using the VIIRS data - p. 77 11. Chapter Four. Evapotranspiration-based smart controllers for landscape irrigation - p. 103 12. Chapter Five. Spatio-temporal attributes of evapotranspiration - p. 123 13. Chapter six. Crop evapotranspiration under changing climate - p. 151 14. Chapter Seven. A review of experimental evapotranspiration in mountain environments - p. 187 15. Chapter Eight. Remote measurement of potential water loss through evapotranspiration of kudzu during the growing season with artificial intelligence-based decision support - p. 221 16. Index - p. 241
Evapotranspiration in Agro-Ecosystems and Forestry: Spatio-temporal Applications presents the progress and advances made in terms of science and application of evaporation, transpiration, and evapotranspiration for various vegetation surfaces, water bodies, and bare soil under different soil and crop management (including different irrigation and tillage management) conditions. Sections on forest and wetlands evapotranspiration and grassland evaporative losses are included, as are the fundamentals of original Penman, Penman-Monteith, Shuttleworth-Wallace and ASCE-EWRI and FAO56 Penman-Monteith equations and their derivatives.
The book is an excellent resource to better understand the progression and applications and dynamics of most recent evapotranspiration, evaporation and transpiration measurement and modeling technologies. Case studies will be provided in terms of how different technologies are currently deployed, how data are used for providing information and management decisions to the users.
1. Title of Book - p. i 2. Cover image - p. i 3. Title page - p. ii 4. Table of Contents - p. iii 5. Copyright - p. iv 6. List of contributors - p. ix 7. Preface - p. xi 8. Chapter One. Original Penman–Monteith actual crop evapotranspiration and standardized Penman–Monteith Reference evapotranspiration models - p. 1 9. Chapter Two. Simulating forest evapotranspiration in hydrologic models: challenges and opportunities - p. 33 10. Chapter Three. Global SSEBop actual evapotranspiration modeling and mapping using the VIIRS data - p. 77 11. Chapter Four. Evapotranspiration-based smart controllers for landscape irrigation - p. 103 12. Chapter Five. Spatio-temporal attributes of evapotranspiration - p. 123 13. Chapter six. Crop evapotranspiration under changing climate - p. 151 14. Chapter Seven. A review of experimental evapotranspiration in mountain environments - p. 187 15. Chapter Eight. Remote measurement of potential water loss through evapotranspiration of kudzu during the growing season with artificial intelligence-based decision support - p. 221 16. Index - p. 241
