Insights for empirically modeling evapotranspiration influenced by riparian and upland vegetation in semiarid regions

Bunting, Daniel P.; Kurc, S. A.; Glenn, Edward P.; Nagler, Pamela L.; Scott, Russell L.

doi:10.1016/j.jaridenv.2014.06.007

Cited by 11 publications

(15 citation statements)

References 57 publications

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“…Results of long-term trend and decadal changes in evapotranspiration (and Pcp) indicate whether the given region will be wetter or drier than its past climatic conditions. Findings of this study can be useful for a careful planning of water resources management, for instance, to determine how much water can be used to support environmental needs after safely being allocated for human use (Bunting et al, 2014). Long-term increase in PET and a negative trend in Pcp imply that the ratio of PET to Pcp was increasing over time.…”

Section: Implications Of Changes In Pet Temperature and Pcp For Aridmentioning

confidence: 90%

Trends and variability of temperature and evaporation over the African continent: Relationships with precipitation

Onyutha

2020

ATM

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Section: Implications Of Changes In Pet Temperature and Pcp For Aridmentioning

confidence: 90%

Trends and variability of temperature and evaporation over the African continent: Relationships with precipitation

Onyutha

2020

ATM

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“…While many empirical ET models exist [68][69][70][71], the current study utilizes a model introduced by Scott et al [45] and later adjusted by Bunting et al [46] due to its dependence on only satellite derived parameters. The model follows the form:…”

Section: Empirical Et Modelmentioning

confidence: 99%

“…Adjustments of Equation (1) by Bunting et al [46] led to numerous formulations requiring LST, a normalized version of EVI, and/or precipitation, depending on the site used for calibration. Models with best performance under either a riparian or upland classification, as determined by Bunting et al [46], were used in the current study (Equations (2) and (3)). …”

Section: Empirical Et Modelmentioning

confidence: 99%

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Evapotranspiration Estimates Derived Using Multi-Platform Remote Sensing in a Semiarid Region

et al. 2017

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Evapotranspiration (ET) is a key component of the water balance, especially in arid and semiarid regions. The current study takes advantage of spatially-distributed, near real-time information provided by satellite remote sensing to develop a regional scale ET product derived from remotely-sensed observations. ET is calculated by scaling PET estimated from Moderate Resolution Imaging Spectroradiometer (MODIS) products with downscaled soil moisture derived using the Soil Moisture Ocean Salinity (SMOS) satellite and a second order polynomial regression formula. The MODis-Soil Moisture ET (MOD-SMET) estimates are validated using four flux tower sites in southern Arizona USA, a calibrated empirical ET model, and model output from Version 2 of the North American Land Data Assimilation System (NLDAS-2). Validation against daily eddy covariance ET indicates correlations between 0.63 and 0.83 and root mean square errors (RMSE) between 40 and 96 W/m 2 . MOD-SMET estimates compare well to the calibrated empirical ET model, with a −0.14 difference in correlation between sites, on average. By comparison, NLDAS-2 models underestimate daily ET compared to both flux towers and MOD-SMET estimates. Our analysis shows the MOD-SMET approach to be effective for estimating ET. Because it requires limited ancillary ground-based data and no site-specific calibration, the method is applicable to regions where ground-based measurements are not available.

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“…Accurate estimates of regional scale ET are needed for sustainable water resource management, particularly for arid ecosystems due to competing demands for water resources among agricultural irrigation, public and domestic needs, industrial production, and ecological environments [4,5]. In recent decades, some empirical remotely sensed ET models have been developed [6][7][8][9][10][11][12][13][14] and their potential for regional scale ET estimation in arid ecosystems has been demonstrated [15][16][17][18][19][20][21][22][23][24][25][26]. These models extrapolate ET observed or estimated at the site scale to regional scale based on the empirical relationship constructed at the local site scale, which relates daily ET from the eddy covariance or Bowen ratio flux towers to vegetation indices (VIs) and meteorological data [27][28][29].…”

Section: Introductionmentioning

confidence: 99%

Effects of Distinguishing Vegetation Types on the Estimates of Remotely Sensed Evapotranspiration in Arid Regions

Wang

Yuan

et al. 2019

Remote Sensing

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Accurate estimates of evapotranspiration (ET) in arid ecosystems are important for sustainable water resource management due to competing water demands between human and ecological environments. Several empirical remotely sensed ET models have been constructed and their potential for regional scale ET estimation in arid ecosystems has been demonstrated. Generally, these models were built using combined measured ET and corresponding remotely sensed and meteorological data from diverse sites. However, there are usually different vegetation types or mixed vegetation types in these sites, and little information is available on the estimation uncertainty of these models induced by combining different vegetation types from diverse sites. In this study, we employed the most popular one of these models and recalibrated it using datasets from two typical vegetation types (shrub Tamarix ramosissima and arbor Populus euphratica) in arid ecosystems of northwestern China. The recalibration was performed in the following two ways: using combined datasets from the two vegetation types, and using a single dataset from specific vegetation type. By comparing the performance of the two methods in ET estimation for Tamarix ramosissima and Populus euphratica, we investigated and compared the accuracy of ET estimation at the site scale and the difference in annual ET estimation at the regional scale. The results showed that the estimation accuracy of daily, monthly, and yearly ET was improved by distinguishing the vegetation types. The method based on the combined vegetation types had a great influence on the estimation accuracy of annual ET, which overestimated annual ET about 9.19% for Tamarix ramosissima and underestimated annual ET about 11.50% for Populus euphratica. Furthermore, substantial difference in annual ET estimation at regional scale was found between the two methods. The higher the vegetation coverage, the greater the difference in annual ET. Our results provide valuable information on evaluating the estimation accuracy of regional scale ET using empirical remotely sensed ET models for arid ecosystems.

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Insights for empirically modeling evapotranspiration influenced by riparian and upland vegetation in semiarid regions

Cited by 11 publications

References 57 publications

Trends and variability of temperature and evaporation over the African continent: Relationships with precipitation

Trends and variability of temperature and evaporation over the African continent: Relationships with precipitation

Evapotranspiration Estimates Derived Using Multi-Platform Remote Sensing in a Semiarid Region

Effects of Distinguishing Vegetation Types on the Estimates of Remotely Sensed Evapotranspiration in Arid Regions

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