Advances in Evaporation and Evaporative Demand
The importance of evapotranspiration is well-established in different disciplines such as hydrology, agronomy, climatology, and other geosciences. Reliable estimates of evapotranspiration are also vital to develop criteria for in-season irrigation management, water resource allocation, long-term est...
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| Year of Publication: | 2022 |
| Language: | English |
| Physical Description: | 1 electronic resource (214 p.) |
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| 245 | 1 | 0 | |a Advances in Evaporation and Evaporative Demand |
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| 520 | |a The importance of evapotranspiration is well-established in different disciplines such as hydrology, agronomy, climatology, and other geosciences. Reliable estimates of evapotranspiration are also vital to develop criteria for in-season irrigation management, water resource allocation, long-term estimates of water supply, demand and use, design and management of water resources infrastructure, and evaluation of the effect of land use and management changes on the water balance. The objective of this Special Issue is to define and discuss several ET terms, including potential, reference, and actual (crop) ET, and present a wide spectrum of innovative research papers and case studies. | ||
| 546 | |a English | ||
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| 653 | |a evapotranspiration | ||
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| 653 | |a spatial | ||
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| 653 | |a agricultural drought | ||
| 653 | |a drought characteristics | ||
| 653 | |a evapotranspiration deficit index | ||
| 653 | |a parameter sensitivity | ||
| 653 | |a temporal scale sensitivity | ||
| 653 | |a water stress anomaly | ||
| 653 | |a interception | ||
| 653 | |a linear storage model | ||
| 653 | |a evaporation | ||
| 653 | |a cover crop | ||
| 653 | |a water balance | ||
| 653 | |a faba bean | ||
| 653 | |a GK2A/AMI | ||
| 653 | |a artificial neural network | ||
| 653 | |a Korean Peninsula | ||
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| 653 | |a UAV | ||
| 653 | |a remote sensing | ||
| 653 | |a micrometeorological data | ||
| 653 | |a spatial IRT measurements | ||
| 653 | |a crop irrigation scheduling and management | ||
| 653 | |a infrared radiometer sensors | ||
| 653 | |a real-time data analysis | ||
| 653 | |a water reservoir | ||
| 653 | |a regression | ||
| 653 | |a observed data | ||
| 653 | |a ERA5-Land data | ||
| 653 | |a R language | ||
| 653 | |a precipitation | ||
| 653 | |a drought | ||
| 653 | |a Mann-Kendall | ||
| 653 | |a trend analysis | ||
| 653 | |a actual evapotranspiration | ||
| 653 | |a potential evapotranspiration | ||
| 653 | |a reference evapotranspiration | ||
| 653 | |a evaporation paradox | ||
| 653 | |a global dimming | ||
| 653 | |a wind stilling | ||
| 653 | |a forest fires | ||
| 653 | |a groundwater | ||
| 653 | |a stochastic simulation | ||
| 653 | |a marginal structure | ||
| 653 | |a long-range dependence | ||
| 653 | |a Hurst-Kolmogorov dynamics | ||
| 653 | |a RASPOTION | ||
| 653 | |a parametric model | ||
| 653 | |a hydrological calibration | ||
| 653 | |a evapotranspiration estimation | ||
| 653 | |a urban rain gardens | ||
| 653 | |a lysimeters | ||
| 653 | |a evapotranspiration models | ||
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