PPT-The potential to reduce uncertainty in regional runoff projections from climate models
Author : reportperfect | Published Date : 2020-10-22
Flavio Lehner Andrew W Wood Julie A Vano David M Lawrence Martyn P Clark Justin S Mankin Nature Climate Change 9 926933 2019 doi101038s415580190639x APPROACH
Presentation Embed Code
Download Presentation
Download Presentation The PPT/PDF document "The potential to reduce uncertainty in r..." is the property of its rightful owner. Permission is granted to download and print the materials on this website for personal, non-commercial use only, and to display it on your personal computer provided you do not modify the materials and that you retain all copyright notices contained in the materials. By downloading content from our website, you accept the terms of this agreement.
The potential to reduce uncertainty in regional runoff projections from climate models: Transcript
Flavio Lehner Andrew W Wood Julie A Vano David M Lawrence Martyn P Clark Justin S Mankin Nature Climate Change 9 926933 2019 doi101038s415580190639x APPROACH. for S2D forecasting. EUPORIAS wp31. Nov 2012, Ronald Hutjes. Background. S2D impact prediction. Uncertainty explosion / Skill implosion ??. SST. Weather. (Downscaling). Soil moisture. Plant productivity. Stormwater. Runoff, and Protect . the Waterfront. by Julio Perez. . Horticultural Technician. University of Florida, IFAS/Broward County . Extension Education Section. Parks and Recreation Division. Dane Hurst. GIS in Water Resources. Utah State University. Fall 2014. Project Objective. Develop . a model . to forecast total seasonal snowmelt runoff for two major reservoirs downstream of the Abajo Mountain range in San Juan County, UT. Dr. Chris Murray,. Department of Interdisciplinary Studies. Outline. What motivated this project?. Runoff and pollution. Turfgrass as a water quality management tool. Experiments and studies of the effect of fertilization. Dave Morgan, Paul Johnston and Laurence Gill. Trinity College Dublin. Phil Collins. HRD Technologies Ltd. Kwabena Osei . Hydro International. morgandt@tcd.ie. Department of Civil, Structural & Environmental Engineering. LECTURE OBJECTIVES. Understand the . runoff generation processes. Know measures that can be used to regulate . runoff . rate. LECTURE OBJECTIVES. Know the applications of . runoff data in . hydrology, water management and agriculture. Stormwater. Runoff, and Protect . the Waterfront. by Julio Perez. . University of Florida, IFAS/Broward County . Extension Education Section. Parks and Recreation Division. j. ulperez@broward.org . Seas (CLIMSEA). Helén Andersson, Markus Meier, Matthias Gröger, Christian Dieterich. RCP8.5. RCP4.5. 2. o. C. Temperature. . change. in the Baltic Sea . Ice. . extent. Modell . Observations. EC-EARTH RCP4.5. Platform . (NCPP) . Introduction, Status, Plans. August 23, 2011. NCPP Core Organizing Team. (Richard B. Rood, . presenting. ). Core Organizing Team . (20110823). Ammann. , Caspar. Anderson, Donald. Runoff may be defined as that part of precipitation as well as any other flow contributions which appear in surface streams of either perennial or seasonal nature.. It is the flow collected from a drainage basin appearing at the outlet of the basin or catchment. Usman Mohseni1, Sai Bargav Muskula2. 1,2Research Scholar, Department of Civil Engineering, IIT Roorkee, Roorkee, INDIA. INTRODUCTION. Rainfall-runoff modelling is one of the most prominent hydrological models used to examine the relation between rainfall and runoff . Learning objectives. Be able to define and compute the topographic wetness index and describe its role and use in TOPMODEL runoff calculations. Be able to use TOPMODEL principles to calculate the spatial distribution of soil moisture deficit and use this information in the calculation of runoff using appropriate GIS tools. Hydrology and Water Resources, RG744. Institute of Space Technology. November 02-06, 2015. Runoff models. Peak runoff models. Provide only the estimates of peak discharge from the watershed. Continuous runoff models. Andrew Levan. For fans of probability, confidence intervals and margins of error, climate change is a dream come true. For everyone else, the fact that uncertainty (inherent in any complex area of science) has gradually become one of climate change's defining features is a constant headache. Because uncertainty – real or manufactured – is a well-rehearsed reason for inaction.
Download Document
Here is the link to download the presentation.
"The potential to reduce uncertainty in regional runoff projections from climate models"The content belongs to its owner. You may download and print it for personal use, without modification, and keep all copyright notices. By downloading, you agree to these terms.
Related Documents