Evapotranspiration on western U.S. rivers estimated using the Enhanced Vegetation Index from MODIS and data from eddy covariance and Bowen ratio flux towers

Nagler, Pamela L.; Scott, Russell L.; Westenburg, Craig L.; Cleverly, James; Glenn, Edward P.; Huete, Alfredo

doi:10.1016/j.rse.2005.05.011

Cited by 268 publications

(237 citation statements)

References 39 publications

(103 reference statements)

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“…In their study, which included part of the Gobi desert where annual rainfall was about 40 mm, vegetation was absent in regions where groundwater depth exceeded 5.5 m. They also used NDVI and 13 groundwater bores, from which relationships between NDVI and groundwater depth for three vegetation classes (grassland, woodland and scrubland) were established. Maximal values of NDVI occurred at sites with intermediate (2.5-3.5 m) depth-to-groundwater rather than at sites with shallower groundwater, a result often ascribed to the effect of anoxia arising from root flooding when the water table is too shallow (Naumburg et al, 2005).…”

Section: Satellite-based Approachesmentioning

confidence: 97%

“…Naumburg et al (2005) provide a review of the impact of both declining and increasing depth to the water table on phreatophytic vegetation in arid zones and provide two conceptual models describing ecosystem responses to these changes in depth. They note that information on root depth and the impact this may have on responses to changes in depth-to-groundwater as a key knowledge gap.…”

Section: Eamus Et Al: Groundwater-dependent Ecosystems: Recent Inmentioning

confidence: 99%

“…phenology, LAI) and function (e.g. ET, gross primary productivity) has become increasingly sophisticated (Glenn et al, 2010;Yuan et al, 2010;Jung et al, 2011;Rossini et al, 2012;Kanniah et al, 2013;Ma et al, 2013;Nagler et al, 2013) and increasingly applied to realworld applications of water resources management (Scott et al, 2008;Glenn et al, 2010;Barron et al, 2014;Doody et al, 2014). Remote sensing (RS) provides a robust and spatially explicit means to assess not only vegetation structure and function but also relationships amongst these and climate variables.…”

Section: Satellite-based Approachesmentioning

confidence: 99%

“…Accurate and spatially distributed estimates of discharge through vegetation are difficult to obtain through field measurements. Recently, RS methods have been calibrated against Penman-Monteith estimates of ET (Glenn et al, 2010;Nagler et al, 2013;Doody et al, 2014), which requires only standard weather data (net radiation, wind speed and vapour pressure deficit) and thus increases the coverage of calibration sites. Because ET in GDEs is generally not limited by soil moisture when groundwater is of high quality (i.e.…”

Section: Estimating Groundwater Use By Remote Sensingmentioning

confidence: 99%

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Groundwater-dependent ecosystems: recent insights from satellite and field-based studies

Eamus

Zolfaghar

Villalobos‐Vega

et al. 2015

Hydrol. Earth Syst. Sci.

128

112

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Abstract. Groundwater-dependent ecosystems (GDEs) are at risk globally due to unsustainable levels of groundwater extraction, especially in arid and semi-arid regions. In this review, we examine recent developments in the ecohydrology of GDEs with a focus on three knowledge gaps: (1) how do we locate GDEs, (2) how much water is transpired from shallow aquifers by GDEs and (3) what are the responses of GDEs to excessive groundwater extraction? The answers to these questions will determine water allocations that are required to sustain functioning of GDEs and to guide regulations on groundwater extraction to avoid negative impacts on GDEs.We discuss three methods for identifying GDEs: (1) techniques relying on remotely sensed information; (2) fluctuations in depth-to-groundwater that are associated with diurnal variations in transpiration; and (3) stable isotope analysis of water sources in the transpiration stream.We then discuss several methods for estimating rates of GW use, including direct measurement using sapflux or eddy covariance technologies, estimation of a climate wetness index within a Budyko framework, spatial distribution of evapotranspiration (ET) using remote sensing, groundwater modelling and stable isotopes. Remote sensing methods often rely on direct measurements to calibrate the relationship between vegetation indices and ET. ET from GDEs is also determined using hydrologic models of varying complexity, from the White method to fully coupled, variable saturation models. Combinations of methods are typically employed to obtain clearer insight into the components of groundwater discharge in GDEs, such as the proportional importance of transpiration versus evaporation (e.g. using stable isotopes) or from groundwater versus rainwater sources.Groundwater extraction can have severe consequences for the structure and function of GDEs. In the most extreme cases, phreatophytes experience crown dieback and death following groundwater drawdown. We provide a brief review of two case studies of the impacts of GW extraction and then provide an ecosystem-scale, multiple trait, integrated metric of the impact of differences in groundwater depth on the structure and function of eucalypt forests growing along a natural gradient in depth-to-groundwater. We conclude with a discussion of a depth-to-groundwater threshold in this mesic GDE. Beyond this threshold, significant changes occur in ecosystem structure and function.

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Section: Satellite-based Approachesmentioning

confidence: 97%

Section: Eamus Et Al: Groundwater-dependent Ecosystems: Recent Inmentioning

confidence: 99%

Section: Satellite-based Approachesmentioning

confidence: 99%

Section: Estimating Groundwater Use By Remote Sensingmentioning

confidence: 99%

See 2 more Smart Citations

Groundwater-dependent ecosystems: recent insights from satellite and field-based studies

Eamus

Zolfaghar

Villalobos‐Vega

et al. 2015

Hydrol. Earth Syst. Sci.

128

112

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“…Plant reflectance properties in the red and near infrared regions are especially recruited for differentiating soil, water and vegetation with vegetation indices (Glenn et al, 2008). Vegetation indices can be used to estimate vegetation water content (Cheng et al, 2006, based on gravimetric or leaf water content (Cheng et al, 2011, Cheng et al, 2013, equivalent water thickness (EWT; water depth/per pixel; knowledge of pixel area provides the volume estimate), changes which are detectable in the short wave infrared region (1.1-2.5 μm), and evapotranspiration processes by including temperature from thermal infrared measurements (Glenn et al, 2010, Nagler et al, 2005a, Nagler et al, 2005b, thus together, identifying agricultural regions receiving excess or insufficient water supplies. Plant physiology and thus reflectance properties respond differently depending upon the time of year, crop type, and management strategies.…”

Section: Monitoring Crop Canopies and Water Stressmentioning

confidence: 99%

Food, water, and fault lines: Remote sensing opportunities for earthquake-response management of agricultural water

Rodriguez

Ustin

Sandoval-Solís

et al. 2016

Science of The Total Environment

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Earthquakes often cause destructive and unpredictable changes that can affect local hydrology (e.g. groundwater elevation or reduction) and thus disrupt land uses and human activities. Prolific agricultural regions overlie seismically active areas, emphasizing the importance to improve our understanding and monitoring of hydrologic and agricultural systems following a seismic event. A thorough data collection is necessary for adequate postearthquake crop management response; however, the large spatial extent of earthquake's impact makes challenging the collection of robust data sets for identifying locations and magnitude of these impacts. Observing hydrologic responses to earthquakes is not a novel concept, yet there is a lack of methods and tools for assessing earthquake's impacts upon the regional hydrology and agricultural systems. The objective of this paper is to describe how remote sensing imagery, methods and tools allow detecting crop responses and damage incurred after earthquakes because a change in the regional hydrology. Many remote sensing datasets are long archived with extensive coverage and with well-documented methods to assess plant-water relations. We thus connect remote sensing of plant water relations to its utility in agriculture using a post-earthquake agrohydrologic remote sensing (PEARS) framework; specifically in agro-hydrologic relationships associated with recent earthquake events that will lead to improved water management.© 2016 Elsevier B.V. All rights reserved. Keywords:Agro-hydrology Disaster management Monitoring Plant-water relations Post-earthquake agrohydrologic remote sensing (PEARS) Remote sensing Background, scope & needEarthquake events threaten food security, resource management and human life, and are observed to be steadily increasing (Ellsworth, 2013). As observed earthquake events continue to increase, it is important to explore and improve response and recovery strategies. Infrastructural damages, especially in urban environments, are at the forefront of research in remote sensing of earthquake-associated damage. Agricultural environments also face catastrophic impacts, often due to adverse hydrologic behavior following the event. The earthquake-water linkage poses particular threats to agricultural productivity, yet difficulty lies in predicting the location, destructiveness, and extent of damage. While effects of earthquake-induced hydrologic changes on crops remain largely unexplored, remote sensing of crop water relations provide a suite of tools to monitor responses and to mitigate crop loss. Remote sensing can address these challenges with archived imagery that has extensive spatial coverage. There are conceptual models that explicitly walk through remote sensing in disaster management (Joyce et al., 2009b) and remote sensing of post-earthquake urban damage (Eguchi et al., 2003) -leaving a gap at the interface of post-earthquake remote sensing of agricultural impacts. We therefore draw attention to current research in understanding earthquake impacts on agric...

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Mapping evapotranspiration trends using MODIS and SEBAL model in a data scarce and heterogeneous landscape in Eastern Africa

et al. 2013

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[1] Evapotranspiration (ET) accounts for a substantial amount of the water use in river basins particular in the tropics and arid regions. However, accurate estimation still remains a challenge especially in large spatially heterogeneous and data scarce areas including the Upper Pangani River Basin in Eastern Africa. Using multitemporal Moderate-resolution Imaging Spectroradiometer (MODIS) and Surface Energy Balance Algorithm of Land (SEBAL) model, 138 images were analyzed at 250 m, 8 day scales to estimate actual ET for 16 land use types for the period 2008-2010. A good agreement was attained for the SEBAL results from various validations. For open water evaporation, the estimated ET for Nyumba ya Mungu (NyM) reservoir showed a good correlations (R 5 0.95; R 2 5 0.91; Mean Absolute Error (MAE) and Root Means Square Error (RMSE) of less than 5%) to pan evaporation using an optimized pan coefficient of 0.81. An absolute relative error of 2% was also achieved from the mean annual water balance estimates of the reservoir. The estimated ET for various agricultural land uses indicated a consistent pattern with the seasonal variability of the crop coefficient (K c ) based on Penman-Monteith equation. In addition, ET estimates for the mountainous areas has been significantly suppressed at the higher elevations (above 2300 m a.s.l.), which is consistent with the decrease in potential evaporation. The calculated surface outflow (Q s ) through a water balance analysis resulted in a bias of 12% to the observed discharge at the outlet of the river basin. The bias was within 13% uncertainty range at 95% confidence interval for Q s . SEBAL ET estimates were also compared with global ET from MODIS 16 algorithm (R 5 0.74; R 2 5 0.32; RMSE of 34% and MAE of 28%) and comparatively significant in variance at 95% confidence level. The interseasonal and intraseasonal ET fluxes derived have shown the level of water use for various land use types under different climate conditions. The evaporative water use in the river basin accounted for 94% to the annual precipitation for the period of study. The results have a potential for use in hydrological analysis and water accounting.Citation: Kiptala, J. K., Y. Mohamed, M. L. Mul, and P. Van der Zaag (2013), Mapping evapotranspiration trends using MODIS and SEBAL model in a data scarce and heterogeneous landscape in Eastern Africa, Water Resour. Res., 49,[8495][8496][8497][8498][8499][8500][8501][8502][8503][8504][8505][8506][8507][8508][8509][8510]

show abstract

Evapotranspiration on western U.S. rivers estimated using the Enhanced Vegetation Index from MODIS and data from eddy covariance and Bowen ratio flux towers

Cited by 268 publications

References 39 publications

Groundwater-dependent ecosystems: recent insights from satellite and field-based studies

Groundwater-dependent ecosystems: recent insights from satellite and field-based studies

Food, water, and fault lines: Remote sensing opportunities for earthquake-response management of agricultural water

Mapping evapotranspiration trends using MODIS and SEBAL model in a data scarce and heterogeneous landscape in Eastern Africa

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