2016
DOI: 10.3390/w8080321
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Effects of Model Spatial Resolution on Ecohydrologic Predictions and Their Sensitivity to Inter-Annual Climate Variability

Abstract: Abstract:The effect of fine-scale topographic variability on model estimates of ecohydrologic responses to climate variability in California's Sierra Nevada watersheds has not been adequately quantified and may be important for supporting reliable climate-impact assessments. This study tested the effect of digital elevation model (DEM) resolution on model accuracy and estimates of the sensitivity of ecohydrologic responses to inter-annual climate variability. The Regional Hydro-Ecologic Simulation System (RHES… Show more

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Cited by 15 publications
(20 citation statements)
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“…Goulden and Bales () showed that the effect of local aspect on estimated ET (NDVI‐based ET) is more substantial in the lower elevation (<1,000 m) in King River Basin where the water limitation is a key controls on vegetation behaviours. Aspect within both watersheds tends to have a unimodal distribution rather than bimodal distribution (Son et al, ). These environmental limitations and spatial pattern of aspect explain the low correlation between aspect and spatial ET in this watershed.…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…Goulden and Bales () showed that the effect of local aspect on estimated ET (NDVI‐based ET) is more substantial in the lower elevation (<1,000 m) in King River Basin where the water limitation is a key controls on vegetation behaviours. Aspect within both watersheds tends to have a unimodal distribution rather than bimodal distribution (Son et al, ). These environmental limitations and spatial pattern of aspect explain the low correlation between aspect and spatial ET in this watershed.…”
Section: Discussionmentioning
confidence: 99%
“…Ksat_v and Ksat_h are vertical and horizontal saturated hydraulic, m is decline coefficient of Ksat with depth, gw1 is the percentage of preferential flow from the soil surface to deep groundwater storage, ae is air entry pressure, and po is pore size index. The predictive performance of the model is evaluated using a combination of three accuracy measures: (a) Nash–Sutcliffe efficiency coefficient, R eff (Nash & Sutcliffe, ), (b) Nash–Sutcliff efficiency coefficient with logarithmic values, R logeff , and (c) the percent volume error (Son, Tague, & Hunsaker, ). The value of the three accuracy measures range from 0 to 1 with the perfect fit at 1.…”
Section: Methodsmentioning
confidence: 99%
“…Compared to the original snowmelt model [ Coughlan and Running , ], temperature melt coefficients for Bear Trap and Frazier are lower, but Big Sandy and Speckerman have the same coefficient value. Another Sierra Nevada RHESSys study at a similar elevation range using LiDAR‐derived vegetation input reported a higher melt coefficient of 0.005 [ Son et al ., ].…”
Section: Methodsmentioning
confidence: 99%
“…Parameters controlling soil physical properties of pore‐size index ( po ) and air‐entry pressure ( pa ), along with parameters controlling flow properties of vertical and lateral hydraulic conductivity at the surface ( k , svk , respectively), decay of hydraulic conductivity with depth ( m ), and percent of infiltrated water lost through fracture flow to deep‐groundwater ( gw1 ) and deep‐groundwater drainage rate ( gw2 ) were optimized in the calibration process. Acceptable parameter sets were determined by comparing observed and modeled daily stream discharge, and we used multiple assessments to quantify model accuracy, similar to the calibration approach of previous studies [ Garcia et al ., ; Garcia and Tague , ; Son et al ., ]. Minimum calibration criteria included a Nash‐Sutcliffe Efficiency ( NS e ) [ Nash and Sutcliffe , ] of daily streamflow and Nash‐Sutcliffe Efficiency of log‐transformed daily streamflow ( logNS e ) that were required to be greater than 0.60, in order to capture both the daily discharge and seasonal trends of high winter flows and low summer flows that are typical of a Mediterranean climate.…”
Section: Methodsmentioning
confidence: 99%
“…Major SSCZO research questions focus on the links between climate, regolith properties, vegetation, biogeochemistry, hydrology, and the response of the mountain ecosystem and catchments to disturbance and climate change. Related studies include evaluation of the transect of eddy covariance and evapotranspiration (Goulden et al, 2012;Goulden and Bales 2014;Saksa et al, 2017;Bales et al, 2018), soil moisture (Oroza et al, 2018), hydrologic modeling (Tague and Peng, 2013;Bart et al, 2016;Son et al, 2016;Bart and Tague, 2017;Jepsen et al, 2016), biochemical studies (Liu et al, 2012;Carey et al, 2016;Aciego et al, 2017;Arvin et al, 2017;Hunsaker and Johnson, 2017), geophysical research (Hahm et al, 2014;Holbrook et al, 2014), and sediment composition (Stacy et al, 2015;McCorkle et al, 2016). Regolith water storage is further described in Klos et al (2018).…”
Section: Introductionmentioning
confidence: 99%