Evaluating the role of evapotranspiration remote sensing data in improving hydrological modeling predictability

Herman, Matthew R.; Nejadhashemi, A. Pouyan; Abouali, Mohammad; Hernandez‐Suarez, J. Sebastian; Daneshvar, Fariborz; Zhang, Zhen; Anderson, Martha C.; Sadeghi, Ali; Hain, Christopher; Sharifi, Amir

doi:10.1016/j.jhydrol.2017.11.009

Cited by 127 publications

(79 citation statements)

References 40 publications

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“…Others that could be used in wetland connectivity simulations include daily evapotranspiration estimates (e.g., Herman et al. ; Rajib et al. ) and qualitative data (e.g., Seibert and McDonnell ).…”

Section: Best Practices For Modeling Wetland Connectivitymentioning

confidence: 99%

“…Examples of nontraditional, but potentially useful sources of calibration/validation data for wetland connectivity simulations include distributed hydrometric data (e.g., and remotely sensed inundation data (e.g., Evenson et al 2019). Others that could be used in wetland connectivity simulations include daily evapotranspiration estimates (e.g., Herman et al 2018;Rajib et al 2018) and qualitative data (e.g., Seibert and McDonnell 2002). Further, similar to the uncertainty analysis utilized by Evenson et al (2016), there are increasingly accessible techniques researchers and practitioners can employ to quantify and bound uncertainty associated with calibration and validation results (e.g., Abbaspour 2013; Beven and Binley 2013).…”

Section: Use Innovative Calibration/validation Techniques For Simulatmentioning

confidence: 99%

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Modeling Connectivity of Non‐floodplain Wetlands: Insights, Approaches, and Recommendations

Jones

Ameli

Neff

et al. 2019

J American Water Resour Assoc

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Representing hydrologic connectivity of non‐floodplain wetlands (NFWs) to downstream waters in process‐based models is an emerging challenge relevant to many research, regulatory, and management activities. We review four case studies that utilize process‐based models developed to simulate NFW hydrology. Models range from a simple, lumped parameter model to a highly complex, fully distributed model. Across case studies, we highlight appropriate application of each model, emphasizing spatial scale, computational demands, process representation, and model limitations. We end with a synthesis of recommended “best modeling practices” to guide model application. These recommendations include: (1) clearly articulate modeling objectives, and revisit and adjust those objectives regularly; (2) develop a conceptualization of NFW connectivity using qualitative observations, empirical data, and process‐based modeling; (3) select a model to represent NFW connectivity by balancing both modeling objectives and available resources; (4) use innovative techniques and data sources to validate and calibrate NFW connectivity simulations; and (5) clearly articulate the limits of the resulting NFW connectivity representation. Our review and synthesis of these case studies highlights modeling approaches that incorporate NFW connectivity, demonstrates tradeoffs in model selection, and ultimately provides actionable guidance for future model application and development.

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Section: Best Practices For Modeling Wetland Connectivitymentioning

confidence: 99%

Section: Use Innovative Calibration/validation Techniques For Simulatmentioning

confidence: 99%

Modeling Connectivity of Non‐floodplain Wetlands: Insights, Approaches, and Recommendations

Jones

Ameli

Neff

et al. 2019

J American Water Resour Assoc

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“…Hydrological models are used to simulate different components of the hydrologic cycle including streamflow, evapotranspiration, soil moisture, groundwater, and surface water (Herman et al, 2018). Additionally, hydrological models are often used in climate change studies and in operational settings to develop safe and sustainable water resource strategies (Hrachowitz & Clark, 2017;Minville et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

“…Hydrological models are commonly calibrated against observed discharge and often fail to consider major hydrological components including actual evapotranspiration (AET) and soil moisture (Wanders, Bierkens, de Jong, de Roo, & Karssenberg, 2014). These classic approaches are inadequate to appropriately simulate other hydrologic components (Herman et al, 2018), mainly due to model structure errors, input data, observed variables, and covariation of parameters (Beven & Freer, 2001). Recent research also revealed an epistemic uncertainty link to the noninformativeness of calibration data (Beven & Westerberg, 2011;Efstratiadis & Koutsoyiannis, 2010).…”

Section: Introductionmentioning

confidence: 99%

Effectiveness of introducing crop coefficient and leaf area index to enhance evapotranspiration simulations in hydrologic models

Birhanu

Kim

Jang

2019

Hydrological Processes

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Evapotranspiration (ET) is an essential component of the hydrological cycle and plays a critical role in water resource management. However, ET is often overlooked in order to transform rainfall to runoff for better streamflow simulation. Hydrological models are commonly used to estimate areal actual evapotranspiration (AET) after calibration against observed discharge. However, classical approaches are often inadequate to appropriately simulate other hydrologic components. Hence, it is important to introduce natural heterogeneity to enhance hydrological processes and reduce water balance errors. In this study, the effectiveness of introducing a constant crop coefficient (Kc), flux tower‐based Kc, and leaf area index (LAI) to three hydrological models (Three‐Parametric Hydrologic Model [TPHM], Génie Rural à 4 paramètres Journalier [GR4J], and Catchment hydrologic cycle Assessment Tool [CAT]) is assessed for the simulation of daily streamflow and AET in a mountainous mixed forest watershed (8.54 km2) in South Korea. The results show that the streamflow simulations after introduction of Kc and LAI to the original models are quite similar. However, the effectiveness of the AET estimation was significantly enhanced after introduction of the flux tower‐based Kc and LAI. The information criterion computed to compare the models reveals that the flux tower‐based Kc‐simulated AET demonstrated better agreement with the observed AET. The Pearson's correlation coefficients (R2) of the TPHM (8%), GR4J (55%), and CAT (55%) models also showed improvements that were greater than the constant based Kc simulation. Similarly, the limitations of the three models with respect to capturing seasonal variation as well as high and low flows were enhanced after the introduction of the flux tower‐based Kc, which adequately reproduced hydrological processes with minimum water balance errors and bias. A regression analysis revealed the potential of estimating Kc as a linear function of LAI (R2 = 0.84). The results of this study indicate that introduction of Kc and LAI to the conceptual rainfall–runoff models can be considered an effective approach to reduce water balance errors and uncertainties in hydrological models and improve the reliability of climate change studies and water resource management.

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“…Hence, the selected soil moisture-based approach showed an acceptable performance in terms of discharges, presenting a negligible decrease in the validation period (∆NSE = 0.1) and greater sensitivity to the spatio-temporal variables' spatial representation.Currently there is a high availability of satellite data, almost in real time, with sufficient spatio-temporal resolutions (30 m-25 km) for ecohydrology in most cases and with a spatial distribution covering the entire earth. Among the sources of satellite information that can be used in ecohydrology, the following stand out: real evapotranspiration [19][20][21][22], land surface temperature [23,24], different vegetation indices [25][26][27], near-surface soil moisture (hereafter SM), [28][29][30][31][32] and more recently total water storage anomaly [33].Soil moisture plays a key role in the hydrological cycle, due to its influence on many processes that directly or indirectly affect the water balance, such as: vegetation growth, hydraulic properties of the ground, evapotranspiration, runoff generation and the processes of infiltration and deep percolation [13,30,[34][35][36][37]. Despite their importance, SM in-situ measurements are still uncommon in time and space [38,39].…”

mentioning

confidence: 99%

Assessment of Remotely Sensed Near-Surface Soil Moisture for Distributed Eco-Hydrological Model Implementation

Echeverría

Ruiz-Pérez

Puertes

et al. 2019

Water

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The aim of this study was to implement an eco-hydrological distributed model using only remotely sensed information (soil moisture and leaf area index) during the calibration phase. Four soil moisture-based metrics were assessed, and the best alternative was chosen, which was a metric based on the similarity between the principal components that explained at least 95% of the soil moisture variation and the Nash-Sutcliffe Efficiency (NSE) index between simulated and observed surface soil moisture. The selected alternative was compared with a streamflow-based calibration approach. The results showed that the streamflow-based calibration approach, even presenting satisfactory results in the calibration period (NSE = 0.91), performed poorly in the validation period (NSE = 0.47) and Leaf Area Index (LAI) and soil moisture were neither sensitive to the spatio-temporal pattern nor to the spatial correlation in both calibration and validation periods. Hence, the selected soil moisture-based approach showed an acceptable performance in terms of discharges, presenting a negligible decrease in the validation period (ΔNSE = 0.1) and greater sensitivity to the spatio-temporal variables’ spatial representation.

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Evaluating the role of evapotranspiration remote sensing data in improving hydrological modeling predictability

Cited by 127 publications

References 40 publications

Modeling Connectivity of Non‐floodplain Wetlands: Insights, Approaches, and Recommendations

Modeling Connectivity of Non‐floodplain Wetlands: Insights, Approaches, and Recommendations

Effectiveness of introducing crop coefficient and leaf area index to enhance evapotranspiration simulations in hydrologic models

Assessment of Remotely Sensed Near-Surface Soil Moisture for Distributed Eco-Hydrological Model Implementation

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