Most large-scale evapotranspiration(ET)estimation methods require detailed information of land use,land cover,and/or soil type on top of various atmospheric measurements.The complementary relationship of evaporation(C...Most large-scale evapotranspiration(ET)estimation methods require detailed information of land use,land cover,and/or soil type on top of various atmospheric measurements.The complementary relationship of evaporation(CR)takes advantage of the inherent dynamic feedback mechanisms found in the soil−vegetation−atmosphere interface for its estimation of ET rates without the need of such biogeophysical data.ET estimates over the conterminous United States by a new,globally calibrated,static scaling(GCR-stat)of the generalized complementary relationship(GCR)of evaporation were compared to similar estimates of an existing,calibration-free version(GCR-dyn)of the GCR that employs a temporally varying dynamic scaling.Simplified annual water balances of 327 medium and 18 large watersheds served as ground-truth ET values.With long-term monthly mean forcing,GCR-stat(also utilizing precipitation measurements)outperforms GCR-dyn as the latter cannot fully take advantage of its dynamic scaling with such data of reduced temporal variability.However,in a continuous monthly simulation,GCR-dyn is on a par with GCR-stat,and especially excels in reproducing long-term tendencies in annual catchment ET rates even though it does not require precipitation information.The same GCR-dyn estimates were also compared to similar estimates of eight other popular ET products and they generally outperform all of them.For this reason,a dynamic scaling of the GCR is recommended over a static one for modeling long-term behavior of terrestrial ET.展开更多
Daily and monthly flow-rates of the Little Nemaha River in Nebraska were simulated by the lumped-parameter Jakeman-Hornberger as well as a distributed-parameter water-balance accounting procedure for the 2003-2008 and...Daily and monthly flow-rates of the Little Nemaha River in Nebraska were simulated by the lumped-parameter Jakeman-Hornberger as well as a distributed-parameter water-balance accounting procedure for the 2003-2008 and 2000-2009 periods, respectively, with and without the help of the MODIS-based monthly estimates of evapotranspiration (ET) rates. While the daily lumped-parameter model simulation accuracy remained practically unchanged with the inclusion of the monthly MODIS-based ET rates interpolated into daily values (R2 of 0.66 vs 0.68, simulated to measured runoff ratio remaining the same 96%), the monthly water-balance accounting model outcomes did improve to some extent (from an R2 of 0.67 to 0.7 with simulated to measured runoff ratio of 72% vs 115%). In both cases the models had to be slightly modified for accommodation of the ET rates as predefined input values, not present in the original model setups. These results indicate the potential practical usefulness of satellite-derived ET estimates (CREMAP values in the present case) in monthly water-balance modeling. CREMAP is a calibration-free ET estimation method based on MODIS-derived daytime surface temperature values in combination of basic climatic variables, such as air temperature, humidity and solar radiation within a Complementary Relationship framework of evaporation.展开更多
基金supported by a BMEWater Sciences and Disaster Prevention FIKP grant of EMMI(BME FIKP-VIZ).
文摘Most large-scale evapotranspiration(ET)estimation methods require detailed information of land use,land cover,and/or soil type on top of various atmospheric measurements.The complementary relationship of evaporation(CR)takes advantage of the inherent dynamic feedback mechanisms found in the soil−vegetation−atmosphere interface for its estimation of ET rates without the need of such biogeophysical data.ET estimates over the conterminous United States by a new,globally calibrated,static scaling(GCR-stat)of the generalized complementary relationship(GCR)of evaporation were compared to similar estimates of an existing,calibration-free version(GCR-dyn)of the GCR that employs a temporally varying dynamic scaling.Simplified annual water balances of 327 medium and 18 large watersheds served as ground-truth ET values.With long-term monthly mean forcing,GCR-stat(also utilizing precipitation measurements)outperforms GCR-dyn as the latter cannot fully take advantage of its dynamic scaling with such data of reduced temporal variability.However,in a continuous monthly simulation,GCR-dyn is on a par with GCR-stat,and especially excels in reproducing long-term tendencies in annual catchment ET rates even though it does not require precipitation information.The same GCR-dyn estimates were also compared to similar estimates of eight other popular ET products and they generally outperform all of them.For this reason,a dynamic scaling of the GCR is recommended over a static one for modeling long-term behavior of terrestrial ET.
文摘Daily and monthly flow-rates of the Little Nemaha River in Nebraska were simulated by the lumped-parameter Jakeman-Hornberger as well as a distributed-parameter water-balance accounting procedure for the 2003-2008 and 2000-2009 periods, respectively, with and without the help of the MODIS-based monthly estimates of evapotranspiration (ET) rates. While the daily lumped-parameter model simulation accuracy remained practically unchanged with the inclusion of the monthly MODIS-based ET rates interpolated into daily values (R2 of 0.66 vs 0.68, simulated to measured runoff ratio remaining the same 96%), the monthly water-balance accounting model outcomes did improve to some extent (from an R2 of 0.67 to 0.7 with simulated to measured runoff ratio of 72% vs 115%). In both cases the models had to be slightly modified for accommodation of the ET rates as predefined input values, not present in the original model setups. These results indicate the potential practical usefulness of satellite-derived ET estimates (CREMAP values in the present case) in monthly water-balance modeling. CREMAP is a calibration-free ET estimation method based on MODIS-derived daytime surface temperature values in combination of basic climatic variables, such as air temperature, humidity and solar radiation within a Complementary Relationship framework of evaporation.
