Zobrazeno 1 - 10
of 38
pro vyhledávání: '"W. T. Crow"'
Publikováno v:
Hydrology and Earth System Sciences, Vol 25, Pp 1569-1586 (2021)
The Soil Moisture Active Passive (SMAP) Level-4 (L4) product provides global estimates of surface soil moisture (SSM) and root-zone soil moisture (RZSM) via the assimilation of SMAP brightness temperature (Tb) observations into the NASA Catchment Lan
Externí odkaz:
https://doaj.org/article/f954a6c16fb94233ab42019bd82e1c2d
Publikováno v:
Hydrology and Earth System Sciences, Vol 24, Pp 581-594 (2020)
Soil water content (θ) influences the climate system by controlling the fraction of incoming solar and longwave energy that is converted into evapotranspiration (ET). Therefore, investigating the coupling strength between θ and ET is important for
Externí odkaz:
https://doaj.org/article/9967151340c243f1b151c7c35631a994
Publikováno v:
Hydrology and Earth System Sciences, Vol 24, Pp 615-631 (2020)
Soil moisture (SM) measurements contain information about both pre-storm hydrologic states and within-storm rainfall estimates, both of which are required inputs for event-based streamflow simulations. In this study, an existing dual state/rainfall c
Externí odkaz:
https://doaj.org/article/21b58f2741ba47ea8eb4c51efcb3931e
Publikováno v:
Hydrology and Earth System Sciences, Vol 22, Pp 1351-1369 (2018)
A newly developed microwave (MW) land surface temperature (LST) product is used to substitute thermal infrared (TIR)-based LST in the Atmosphere–Land Exchange Inverse (ALEXI) modeling framework for estimating evapotranspiration (ET) from space.
Externí odkaz:
https://doaj.org/article/4fabe971143f43bebbd8dd898335bd36
Publikováno v:
Hydrology and Earth System Sciences, Vol 21, Pp 4403-4417 (2017)
This study applied the exponential filter to produce an estimate of root-zone soil moisture (RZSM). Four types of microwave-based, surface satellite soil moisture were used. The core remotely sensed data for this study came from NASA's long-lastin
Externí odkaz:
https://doaj.org/article/093754675c9340cd8abe45d860ffc272
Publikováno v:
Hydrology and Earth System Sciences, Vol 21, Iss 3, Pp 1849-1862 (2017)
Due to their shallow vertical support, remotely sensed surface soil moisture retrievals are commonly regarded as being of limited value for water budget applications requiring the characterization of temporal variations in total terrestrial water sto
Externí odkaz:
https://doaj.org/article/ea208b6654b54c15801c9813ac008955
Publikováno v:
Hydrology and Earth System Sciences, Vol 20, Iss 8, Pp 3263-3275 (2016)
Conventional methods to estimate land surface temperature (LST) from space rely on the thermal infrared (TIR) spectral window and is limited to cloud-free scenes. To also provide LST estimates during periods with clouds, a new method was developed to
Externí odkaz:
https://doaj.org/article/ead1cc23d9ca46f799b0344b324e2dcf
Publikováno v:
Hydrology and Earth System Sciences, Vol 19, Iss 4, Pp 1659-1676 (2015)
Assimilation of remotely sensed soil moisture data (SM-DA) to correct soil water stores of rainfall-runoff models has shown skill in improving streamflow prediction. In the case of large and sparsely monitored catchments, SM-DA is a particularly attr
Externí odkaz:
https://doaj.org/article/7d22d55bc06b402986ec05bb31bbcf27
Publikováno v:
Hydrology and Earth System Sciences, Vol 17, Iss 10, Pp 3695-3706 (2013)
This paper investigates the structural difference in timing of the diurnal temperature cycle (DTC) over land resulting from choice of measuring device or model framework. It is shown that the timing can be reliably estimated from temporally sparse ob
Externí odkaz:
https://doaj.org/article/51e001158e5c4ae68ebe60d9dfc00ca4
Publikováno v:
Hydrology and Earth System Sciences, Vol 16, Iss 9, Pp 3451-3460 (2012)
The lagged rank cross-correlation between model-derived root-zone soil moisture estimates and remotely sensed vegetation indices (VI) is examined between January 2000 and December 2010 to quantify the skill of various soil moisture models for agricul
Externí odkaz:
https://doaj.org/article/2db8e17d96bf4f82a297456c71a6f6de