Comment on “Probabilistic approach to modeling of velocity distributions in fluid flows” by C.-L. Chiu and S.-M. Hsu, Journal of Hydrology 316:28–42

Dingman, Stephen

doi:10.1016/j.jhydrol.2006.09.006

Cited by 85 publications

(138 citation statements)

References 10 publications

(27 reference statements)

Supporting

Mentioning

107

Contrasting

Unclassified

Order By: Relevance

“…For the same reason, the overall calibration of a power function trends of U versus Q and S variables (U 5 k Q (j 1 m S) , adjusted R-squared 5 97.98%; k, j, and m are the calibration parameters reported in Figure 4) provides the highest values of the exponent of Q for TA and TB (0.46 and 0.59, respectively) and a much lower value for the TS reach (0.34). This finding is in agreement with previous observations, which emphasized how the energy-line slopes of rough morphologies change more rapidly when a macroroughness regime shifts to a microroughness or to a transition-to-microroughness regime [Bathurst, 1985;Smart, 1999;Dingman, 2007].…”

Section: 1002/2014wr016631supporting

confidence: 93%

On kinematics and flow velocity prediction in step‐pool channels

D’Agostino

Michelini

2015

Water Resources Research

View full text Add to dashboard Cite

This paper verifies methods for the prediction of mean flow velocity at the reach scale in mountain streams, investigating the kinematics of a series of two small-scale artificial step-pool sequences and a transitional reach between plane-bed and step-pool under well-controlled hydraulic conditions, and improving the estimation of the energy expenditure between the step crest and the downstream pool. Experimental data were collected using three fish ladder reaches with slopes between 2.6 and 10%. Four types of field measurements were conducted: topographical surveys to extract the thalweg profiles and cross-sectional geometry of reference cross sections; grain size analyses of the bed surface; steady state runs with a given flow rate (0.005-0.234 m 3 /s), and surveying of the water profile in the most significant cross sections. The following main conclusions were reached: (i) the dominance of spill resistance at the lowest discharge (pool water depth-step height ratios of 0.4) causes primary dimensionless head losses of up to 80%, and these losses progressively decrease to approximately 40% when the water discharge and related pool water depth submerge the upstream step height. A specific predictive equation for the head loss was calibrated and then verified via data from the Rio Cordon. (ii) The verification of literature-sourced equations to predict the reach-averaged flow velocity provided suitable results for several of these equations indicating that the use of a specific step-pool equation does not appear to be crucial to achieving accurate predictions.

show abstract

Section: 1002/2014wr016631supporting

confidence: 93%

On kinematics and flow velocity prediction in step‐pool channels

D’Agostino

Michelini

2015

Water Resources Research

View full text Add to dashboard Cite

show abstract

“…Otherwise, the value of the saturated conductivity in the other areas has been obtained under the constraint of fixed ratios between the saturated conductivity pertaining to different land use classes. Note that we rely on literature data for the establishment of the above ratios as a function of the various soil types and/or uses (Dingman, 1994). This has clear operational advantages.…”

Section: Source Area Geomorphic Transitions Legendmentioning

confidence: 99%

“…A continuously updated description of the instantaneous maximum infiltration rate within each source area A γ , say ϕ γ (t), is achieved by the use of the Green-Ampt model for shallow soils (e.g. Dingman, 1994) (see caption of Table 2). When the water-input rate J (γ , t) (see e.g.…”

Section: Runoff Productionmentioning

confidence: 99%

“…We adopted the Penman-Monteith equation (e.g. Dingman, 1994) integrated by the FAO approach (e.g. Allen et al, 2005), which allows a theoretically sound evaluation of evapotranspiration through (relatively) few micro-meteorological, soil and vegetation parameters whose spatial distribution is determined via remotely sensed image analysis.…”

Section: Runoff Productionmentioning

confidence: 99%

“…Actual infiltration rates within each subbasin, ϕ γ , are computed by the runoff production model via the equation (e.g. Dingman, 1994)…”

Section: Runoff Productionmentioning

confidence: 99%

See 2 more Smart Citations

Transport at basin scales: 2. Applications

Rinaldo

Botter

Bertuzzo

et al. 2006

Hydrol. Earth Syst. Sci.

View full text Add to dashboard Cite

Abstract. In this paper, the second of a series, we apply the models discussed in Part 1 to a significant case study. The nature of the catchment under study, the transport phenomena investigated (i.e. nitrates moving as solutes within runoff waters) and the scales involved in space and time, provide an elaborate test for theory and applications. Comparison of modeling predictions with field data (i.e. fluxes of carrier flow and solute nitrates) suggests that the framework proposed for geomorphic transport models is capable to describe well large-scale transport phenomena driven and/or controlled by spatially distributed hydrologic fields (e.g. rainfall patterns in space and time, drainage pathways, soil coverage and type, matter stored in immobile phases). A sample MonteCarlo mode of application of the model is also discussed where hydrologic forcings and external nitrate applications (through fertilization) are treated as random processes.

show abstract

Snowtography quantifies effects of forest cover on net water input to soil at sites with ephemeral or stable seasonal snowpack in Arizona, USA

et al. 2022

View full text Add to dashboard Cite

Forested, snow-dominated watersheds provide a range of ecosystem services including water supply, carbon sequestration, habitat and recreation. While hydrologic partitioning has been well-studied in watersheds with stable seasonal snowpack, less is known about watersheds with ephemeral snowpack. Furthermore, drought-related disturbances and/or management practices are altering vegetation cover in many forests, with unknown and potentially different, consequences for stable seasonal versus ephemeral snowpacks. This study quantifies net water input (NWI) to soil for two sites with contrasting stable seasonal and ephemeral snowpacks, respectively, for three water years in Arizona, USA. Observations include a network of automated cameras and graduated snow stakes (snowtography) deployed across gradients of forest structure, airborne lidar maps of topography and forests and SNOTEL station records. Given the importance of mixed-phase precipitation in ephemeral snowpack watersheds, an algorithm is developed to distinguish among snowfall and rainfall that does/does not contribute to snowpack mass. Finally, existing canopy interception and snowpack models are used to estimate how NWI varies with canopy cover. At the ephemeral snowpack site, increasing canopy cover reduces NWI amount and advances its seasonal timing less strongly than at the stable seasonal snowpack site.Interestingly, canopy reduces NWI duration at the ephemeral site but prolongs it at the stable seasonal snowpack site. These effects are more important in a cool/wet and average year than a warm/dry year. Understanding differences between canopy impacts on amount, timing and duration of NWI for areas with ephemeral versus stable seasonal snowpack is increasingly important as the number of watersheds with ephemeral snowpack grows.

show abstract

Comment on “Probabilistic approach to modeling of velocity distributions in fluid flows” by C.-L. Chiu and S.-M. Hsu, Journal of Hydrology 316:28–42

Cited by 85 publications

References 10 publications

On kinematics and flow velocity prediction in step‐pool channels

On kinematics and flow velocity prediction in step‐pool channels

Transport at basin scales: 2. Applications

Snowtography quantifies effects of forest cover on net water input to soil at sites with ephemeral or stable seasonal snowpack in Arizona, USA

Contact Info

Product

Resources

About