Search Results

You are looking at 1 - 6 of 6 items for :

  • Model performance/evaluation x
  • Human Impact on Climate Extremes for Water Resources Infrastructure Design, Operations, and Risk Management x
  • All content x
Clear All
Mohammad Karamouz, Erfan Goharian, and Sara Nazif

metropolitan area is simulated to evaluate its overall reliability in supplying water under the extreme streamflow conditions. In this step, STELLA is used in order to model the contribution and connection of different elements of the Karaj Reservoir system. STELLA is an object-oriented simulation modeling software, which is produced by ISEE Systems (formerly High Performance Systems). The rest of this paper includes a brief description of the study area. Then the methodology and results are discussed

Full access
G. T. Aronica and B. Bonaccorso

investigation. Then, the results of models calibration and validation are shown for both the current and future scenarios. Hence, a comparison is presented between the resulting flow duration curves and utilization curves aimed at evaluating the effects of changes in temperature and precipitation on hydropower potential of the river basin. Finally, conclusions about the proposed methodology, based on the derived results, are drawn in the last section. 2. Data and methods 2.1. Study area and data The study

Full access
Tim Bardsley, Andrew Wood, Mike Hobbins, Tracie Kirkham, Laura Briefer, Jeff Niermeyer, and Steven Burian

: 1) hydrologic modeling of the SLC watersheds; 2) a watershed-specific analysis of sensitivity to changes in temperature, PET, and precipitation for the seven primary supply watersheds; 3) tests of scenarios of extremely low future water supply and droughts using results from the watershed sensitivity analyses in item 2 above; and 4) water demand analyses, which allowed for the generation and evaluation of future demand test cases. 3.1. Watershed modeling The colocation of WWA personnel (the lead

Full access
Wondmagegn Yigzaw, Faisal Hossain, and Alfred Kalyanapu

possible for this case because the routing model had the limiting temporal unit of 24 h ( Lohmann et al. 1996 ), which can be a limitation to demonstrate a clear sensitivity of hydrography for changing peak floods. The model was calibrated using observed flow at Fair Oaks, California (for details, see Yigzaw et al. 2012 ). The years of 1997 and 1999 are used for calibration and verification, respectively. Performance metrics of the calibrated and verified model are shown in Table 1 . Table 1. VIC

Full access
Brandon L. Parkes, Hannah L. Cloke, Florian Pappenberger, Jeff Neal, and David Demeritt

running a Monte Carlo simulation, the default values for the parameters given in Table 1 were deemed suitable for the Carlisle 2005 observational dataset. A first-order sensitivity analysis using the method described by Saltelli et al. ( Saltelli et al. 2008 ) suggest the performance of the algorithm is most sensitive to nn (see Table 2 ). Table 2. Sensitivity indices of the model to the four parameters varied on the Latin hypercube sample. 4. Results When this algorithm is applied to the dataset

Full access
Alfred J. Kalyanapu, A. K. M. Azad Hossain, Jinwoo Kim, Wondmagegn Yigzaw, Faisal Hossain, and C. K. Shum

in exaggerated flood depths and inundation extents (e.g., Figure 5a ). Second, after adjusting the DEMs, the Flood2D-GPU model is calibrated for Manning’s n by iteratively changing the parameter value and comparing the simulated flood extent and flood stages with the observed data. To estimate the performance of the flood simulation, two different metrics were used. The first metric used is to compare the simulated flood stages to the observed flood stage at the H Street Bridge, obtained from

Full access