Distributed hydrological model for mapping evapotranspiration using remote sensing inputs

Chen, Jing M.; Chen, Xiaoyong; Ju, Weimin; Geng, Xiaoyuan

doi:10.1016/j.jhydrol.2004.08.029

Cited by 233 publications

(209 citation statements)

References 75 publications

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“…This model needs some input data, including a DEM, daily values of precipitation and temperature, information about soil use, vertical gradient of temperature, and precipitation. The model may be viewed as a simplified version of a distributed hydrological model (Wigmosta et al 1994;Chen et al 2005), and it considers superficial and groundwater flow formation. Full model equations are reported, for example, in Groppelli et al (2011b) and Bocchiola et al (2011), and the reader is referred there for details.…”

Section: The Glaciohydrological Modelmentioning

confidence: 99%

“…Because of the lack of daily data for longer periods (only 2012 is available), it was not possible to pursue a calibration/validation strategy using data subsets. In Table 3 the parameters estimated via calibration are reported, together with those estimated a priori based on the available literature, for example, wilting point for vegetated areas u w 5 0.15 (Chen et al 2005;Wang et al 2009) and field capacity u l 5 0.35 (e.g., Ceres et al 2009). Reservoir number for overland flow (e.g., Rosso 1984) are set to n s 5 3 based on several studies.…”

Section: Hydrological Model Calibrationmentioning

confidence: 99%

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Future Hydrological Regimes in the Upper Indus Basin: A Case Study from a High-Altitude Glacierized Catchment

Soncini

Bocchiola

Confortola

et al. 2015

Journal of Hydrometeorology

100

124

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The mountain regions of the Hindu Kush, Karakoram, and Himalayas (HKH) are considered Earth's ''third pole,'' and water from there plays an essential role for downstream populations. The dynamics of glaciers in Karakoram are complex, and in recent decades the area has experienced unchanged ice cover, despite rapid decline elsewhere in the world (the Karakoram anomaly). Assessment of future water resources and hydrological variability under climate change in this area is greatly needed, but the hydrology of these high-altitude catchments is still poorly studied and little understood. This study focuses on a particular watershed, the Shigar River with the control section at Shigar (about 7000 km 2 ), nested within the upper Indus basin and fed by seasonal melt from two major glaciers (Baltoro and Biafo). Hydrological, meteorological, and glaciological data gathered during 3 years of field campaigns (2011-13) are used to set up a hydrological model, providing a depiction of instream flows, snowmelt, and ice cover thickness. The model is used to assess changes of the hydrological cycle until 2100, via climate projections provided by three state-of-the-art global climate models used in the recent IPCC Fifth Assessment Report under the representative concentration pathway (RCP) emission scenarios RCP2.6, RCP4.5, and RCP8.5. Under all RCPs, future flows are predicted to increase until midcentury and then to decrease, but remaining mostly higher than control run values. Snowmelt is projected to occur earlier, while the ice melt component is expected to increase, with ice thinning considerably and even disappearing below 4000 m MSL until 2100.

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Section: The Glaciohydrological Modelmentioning

confidence: 99%

Section: Hydrological Model Calibrationmentioning

confidence: 99%

Future Hydrological Regimes in the Upper Indus Basin: A Case Study from a High-Altitude Glacierized Catchment

Soncini

Bocchiola

Confortola

et al. 2015

Journal of Hydrometeorology

100

124

View full text Add to dashboard Cite

show abstract

“…Wania et al (2010) describe a model of wetland hydrology and biogeochemistry (LPJ-WHyMe), but do not include consideration of microtopography or lateral flows. Others, such as BEPS (Chen et al, 2005 and InTEC v3.0 (Ju et al, 2006) include sophisticated ecohydrological and biogeochemical sub-models capable of simulating threedimensional hydrology (for large-scale topography) coupled to peatland carbon dynamics. Sonnentag et al (2008) further adapted BEPS to model the effects of mesoscale (site level) topography on hydrology, and hence on CO 2 exchange at Mer Bleue bog.…”

Section: Introductionmentioning

confidence: 99%

Representing northern peatland microtopography and hydrology within the Community Land Model

et al. 2015

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Abstract. Predictive understanding of northern peatland hydrology is a necessary precursor to understanding the fate of massive carbon stores in these systems under the influence of present and future climate change. Current models have begun to address microtopographic controls on peatland hydrology, but none have included a prognostic calculation of peatland water table depth for a vegetated wetland, independent of prescribed regional water tables. We introduce here a new configuration of the Community Land Model (CLM) which includes a fully prognostic water table calculation for a vegetated peatland. Our structural and process changes to CLM focus on modifications needed to represent the hydrologic cycle of bogs environment with perched water tables, as well as distinct hydrologic dynamics and vegetation communities of the raised hummock and sunken hollow microtopography characteristic of peatland bogs. The modified model was parameterized and independently evaluated against observations from an ombrotrophic raised-dome bog in northern Minnesota (S1-Bog), the site for the Spruce and Peatland Responses Under Climatic and Environmental Change experiment (SPRUCE). Simulated water table levels compared well with site-level observations. The new model predicts hydrologic changes in response to planned warming at the SPRUCE site. At present, standing water is commonly observed in bog hollows after large rainfall events during the growing season, but simulations suggest a sharp decrease in water table levels due to increased evapotranspiration under the most extreme warming level, nearly eliminating the occurrence of standing water in the growing season. Simulated soil energy balance was strongly influenced by reduced winter snowpack under warming simulations, with the warming influence on soil temperature partly offset by the loss of insulating snowpack in early and late winter. The new model provides improved predictive capacity for seasonal hydrological dynamics in northern peatlands, and provides a useful foundation for investigation of northern peatland carbon exchange.

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“…Viney and Sivapalan (2001) applied a conceptual Large Scale Catchment Model (LASCAM) to the Swan-Avon catchment in Western Australia, and found that stream flow, sediment yield, and nutrient yields had all increased since European settlement in the catchment. Remote sensing techniques can benefit water flux related ecosystem service modeling in three ways (Kite and Pietroniro, 1996;Pietroniro and Prowse, 2002;Chen et al, 2005;Liu and Li, 2008): 1) by identifying significant areal phenomena such as snow cover, surface water (e.g. flooded areas, lake areas) or sediment plumes from original remote sensing image; 2) by developing relationships between remote sensing data and parameters of interest to provide model parameters such as soil moisture and water quality; and 3) by quantifying important surface parameters such as land cover types and the LAI from remote sensing data.…”

Section: Water Flux Related Ecosystem Servicesmentioning

confidence: 99%

Remote sensing of ecosystem services: An opportunity for spatially explicit assessment

Feng

Yang

et al. 2010

Chin. Geogr. Sci.

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Ecosystem service is an emerging concept that grows to be a hot research area in ecology. Spatially explicit ecosystem service values are important for ecosystem service management. However, it is difficult to quantify ecosystem services. Remote sensing provides images covering Earth surface, which by nature are spatially explicit. Thus, remote sensing can be useful for quantitative assessment of ecosystem services. This paper reviews spatially explicit ecosystem service studies conducted in ecology and remote sensing in order to find out how remote sensing can be used for ecosystem service assessment. Several important areas considered include land cover, biodiversity, and carbon, water and soil related ecosystem services. We found that remote sensing can be used for ecosystem service assessment in three different ways: direct monitoring, indirect monitoring, and combined use with ecosystem models. Some plant and water related ecosystem services can be directly monitored by remote sensing. Most commonly, remote sensing can provide surrogate information on plant and soil characteristics in an ecosystem. For ecosystem process related ecosystem services, remote sensing can help measure spatially explicit parameters. We conclude that acquiring good in-situ measurements and selecting appropriate remote sensor data in terms of resolution are critical for accurate assessment of ecosystem services.

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Distributed hydrological model for mapping evapotranspiration using remote sensing inputs

Cited by 233 publications

References 75 publications

Future Hydrological Regimes in the Upper Indus Basin: A Case Study from a High-Altitude Glacierized Catchment

Future Hydrological Regimes in the Upper Indus Basin: A Case Study from a High-Altitude Glacierized Catchment

Representing northern peatland microtopography and hydrology within the Community Land Model

Remote sensing of ecosystem services: An opportunity for spatially explicit assessment

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