Analytical framework for screening long-time and large-scale soil moisture variability and its comparison with GRACE satellite data

Lucile Verrot, Georgia Destouni

Research output: Contribution to conferenceAbstract

Abstract

Soil moisture is a central component of the hydrologic cycle and its spatiotemporal variability offers a great
challenge in assessing large-scale hydrological processes. As this variability depends greatly on prevailing
hydro-climate, along with soil texture and its primarily spatial heterogeneity, soil moisture may be relatively
easily constrained by large-scale water balance consideration in time and knowledge of soil property distribution
in space. We have developed a relatively simple soil moisture model that relies on explicit account
of spatial soil hydraulics parameters and catchment-wise organized hydro-climatic data and their variation in
time. The current state of field techniques does not allow the retrieval of large-scale soil moisture data for
direct comparison with model results. However, the recent GRACE satellite data provides for the first time
large-scale directly comparative of large-scale water storage variability. This study compares the developed soil
moisture model’s ability to reproduce main variability dynamics in long-term data series of unsaturated water content
and groundwater table position at the catchment scale with GRACE data, for a set of large tropical catchments.
Original languageEnglish
Publication statusPublished - 2016
EventEGU General Assembly 2016 - Vienna, Austria
Duration: 17 Apr 201622 Apr 2016

Conference

ConferenceEGU General Assembly 2016
CountryAustria
CityVienna
Period17/04/1622/04/16

Fingerprint

GRACE
analytical framework
satellite data
soil moisture
catchment
soil texture
water storage
water budget
soil property
hydraulics
groundwater
screening
comparison
climate
soil
water

Cite this

Verrot, L., & Destouni, G. (2016). Analytical framework for screening long-time and large-scale soil moisture variability and its comparison with GRACE satellite data. Abstract from EGU General Assembly 2016, Vienna, Austria.

Analytical framework for screening long-time and large-scale soil moisture variability and its comparison with GRACE satellite data. / Verrot, Lucile; Destouni, Georgia.

2016. Abstract from EGU General Assembly 2016, Vienna, Austria.

Research output: Contribution to conferenceAbstract

Verrot, L & Destouni, G 2016, 'Analytical framework for screening long-time and large-scale soil moisture variability and its comparison with GRACE satellite data' EGU General Assembly 2016, Vienna, Austria, 17/04/16 - 22/04/16, .
Verrot, Lucile ; Destouni, Georgia. / Analytical framework for screening long-time and large-scale soil moisture variability and its comparison with GRACE satellite data. Abstract from EGU General Assembly 2016, Vienna, Austria.
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title = "Analytical framework for screening long-time and large-scale soil moisture variability and its comparison with GRACE satellite data",
abstract = "Soil moisture is a central component of the hydrologic cycle and its spatiotemporal variability offers a greatchallenge in assessing large-scale hydrological processes. As this variability depends greatly on prevailinghydro-climate, along with soil texture and its primarily spatial heterogeneity, soil moisture may be relativelyeasily constrained by large-scale water balance consideration in time and knowledge of soil property distributionin space. We have developed a relatively simple soil moisture model that relies on explicit accountof spatial soil hydraulics parameters and catchment-wise organized hydro-climatic data and their variation intime. The current state of field techniques does not allow the retrieval of large-scale soil moisture data fordirect comparison with model results. However, the recent GRACE satellite data provides for the first timelarge-scale directly comparative of large-scale water storage variability. This study compares the developed soilmoisture model’s ability to reproduce main variability dynamics in long-term data series of unsaturated water contentand groundwater table position at the catchment scale with GRACE data, for a set of large tropical catchments.",
author = "Lucile Verrot and Georgia Destouni",
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language = "English",
note = "EGU General Assembly 2016 ; Conference date: 17-04-2016 Through 22-04-2016",

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T1 - Analytical framework for screening long-time and large-scale soil moisture variability and its comparison with GRACE satellite data

AU - Verrot, Lucile

AU - Destouni, Georgia

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N2 - Soil moisture is a central component of the hydrologic cycle and its spatiotemporal variability offers a greatchallenge in assessing large-scale hydrological processes. As this variability depends greatly on prevailinghydro-climate, along with soil texture and its primarily spatial heterogeneity, soil moisture may be relativelyeasily constrained by large-scale water balance consideration in time and knowledge of soil property distributionin space. We have developed a relatively simple soil moisture model that relies on explicit accountof spatial soil hydraulics parameters and catchment-wise organized hydro-climatic data and their variation intime. The current state of field techniques does not allow the retrieval of large-scale soil moisture data fordirect comparison with model results. However, the recent GRACE satellite data provides for the first timelarge-scale directly comparative of large-scale water storage variability. This study compares the developed soilmoisture model’s ability to reproduce main variability dynamics in long-term data series of unsaturated water contentand groundwater table position at the catchment scale with GRACE data, for a set of large tropical catchments.

AB - Soil moisture is a central component of the hydrologic cycle and its spatiotemporal variability offers a greatchallenge in assessing large-scale hydrological processes. As this variability depends greatly on prevailinghydro-climate, along with soil texture and its primarily spatial heterogeneity, soil moisture may be relativelyeasily constrained by large-scale water balance consideration in time and knowledge of soil property distributionin space. We have developed a relatively simple soil moisture model that relies on explicit accountof spatial soil hydraulics parameters and catchment-wise organized hydro-climatic data and their variation intime. The current state of field techniques does not allow the retrieval of large-scale soil moisture data fordirect comparison with model results. However, the recent GRACE satellite data provides for the first timelarge-scale directly comparative of large-scale water storage variability. This study compares the developed soilmoisture model’s ability to reproduce main variability dynamics in long-term data series of unsaturated water contentand groundwater table position at the catchment scale with GRACE data, for a set of large tropical catchments.

M3 - Abstract

ER -