PMID- 30078915
OWN - NLM
STAT- PubMed-not-MEDLINE
LR  - 20230926
IS  - 0043-1397 (Print)
IS  - 1944-7973 (Electronic)
IS  - 0043-1397 (Linking)
VI  - 53
IP  - 6
DP  - 2017 Jun
TI  - Tradeoff between cost and accuracy in large-scale surface water dynamic modeling.
PG  - 4942-4955
LID - 10.1002/2017WR020519 [doi]
AB  - Recent efforts have led to the development of the local inertia formulation 
      (INER) for an accurate but still cost-efficient representation of surface water 
      dynamics, compared to the widely used kinematic wave equation (KINE). In this 
      study, both formulations are evaluated over the Amazon basin in terms of 
      computational costs and accuracy in simulating streamflows and water levels 
      through synthetic experiments and comparisons against ground-based observations. 
      Varying time steps are considered as part of the evaluation and INER at 60-second 
      time step is adopted as the reference for synthetic experiments. Five hybrid 
      (HYBR) realizations are performed based on maps representing the spatial 
      distribution of the two formulations that physically represent river reach flow 
      dynamics within the domain. Maps have fractions of KINE varying from 35.6% to 
      82.8%. KINE runs show clear deterioration along the Amazon river and main 
      tributaries, with maximum RMSE values for streamflow and water level reaching 
      7827m(3).s(-1) and 1379cm near the basin's outlet. However, KINE is at least 25% 
      more efficient than INER with low model sensitivity to longer time steps. A 
      significant improvement is achieved with HYBR, resulting in maximum RMSE values 
      of 3.9-292m(3).s(-1) for streamflows and 1.1-28.5cm for water levels, and cost 
      reduction of 6-16%, depending on the map used. Optimal results using HYBR are 
      obtained when the local inertia formulation is used in about one third of the 
      Amazon basin, reducing computational costs in simulations while preserving 
      accuracy. However, that threshold may vary when applied to different regions, 
      according to their hydrodynamics and geomorphological characteristics.
FAU - Getirana, Augusto
AU  - Getirana A
AD  - Hydrological Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, 
      MD.
AD  - Earth System Science Interdisciplinary Center, University of Maryland, College 
      Park, MD.
FAU - Peters-Lidard, Christa
AU  - Peters-Lidard C
AD  - Hydrological Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, 
      MD.
FAU - Rodell, Matthew
AU  - Rodell M
AD  - Hydrological Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, 
      MD.
FAU - Bates, Paul D
AU  - Bates PD
AD  - School of Geographical Sciences, University of Bristol, Bristol, UK.
LA  - eng
GR  - N-999999/Intramural NASA/United States
PT  - Journal Article
DEP - 20170524
PL  - United States
TA  - Water Resour Res
JT  - Water resources research
JID - 7501965
PMC - PMC6069676
MID - NIHMS980488
EDAT- 2017/06/01 00:00
MHDA- 2017/06/01 00:01
PMCR- 2018/08/01
CRDT- 2018/08/07 06:00
PHST- 2018/08/07 06:00 [entrez]
PHST- 2017/06/01 00:00 [pubmed]
PHST- 2017/06/01 00:01 [medline]
PHST- 2018/08/01 00:00 [pmc-release]
AID - 10.1002/2017WR020519 [doi]
PST - ppublish
SO  - Water Resour Res. 2017 Jun;53(6):4942-4955. doi: 10.1002/2017WR020519. Epub 2017 
      May 24.