Catchment Scale Evaluation of Multiple Global Hydrological Models from ISIMIP2a over North America
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Global Hydrological Simulations from the ISIMIP Database
2.3. Regional Hydrological Simulations Based on the HYSETS Database
2.4. Model Performance and Statistical Criteria
3. Results
3.1. gHM Performance in Simulating Discharge at the Catchment Scale
3.2. Detailed Analysis of four NA Catchments
3.3. Potential Factors Controlling gHM Performance
4. Discussion
4.1. On the Use of gHMs and rHMs Driven by Global Meteorological Datasets
4.2. gHMs’ Performance between Catchments
4.3. gHM versus rHM Approach at the Catchment Scale
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Global Data | Reanalysis | Bias Correction | Grid Spatial Resolution | Period | Reference |
---|---|---|---|---|---|
GSWP3 | 20th Centurya | GPCC V6, GPCP, CRU and SRB | 0.5° (~50km) | 1901–2010 | [43] |
Princeton PGMFD v2 | NCEP/NCAR Reanalysis 1 | CRU, SBM and TRMM | 0.5° (~50km) | 1901–2012 | [44] |
WATCH Forcing Data (WFD) | ERA-40 | GPCC v4 | 0.5° (~50km) | 1971–2001 | [45] |
WFDEI.GPCC | ERA-Interim | GPCC v5 and v6 | 0.5° (~50km) | 1979–2012 | [46] |
gHM | Spin-Up | River Routing | PET Method | Snowmelt Method | Calibration |
---|---|---|---|---|---|
DBH | 20-year | Linear reservoir based on DDM30 (a) | Energy balance [50] | Energy balance | No |
H08 | 70-year | Linear reservoir based on DDM30 (a) | Bulk formula [40] | Energy balance | No |
LPJml | 5000-year potential natural vegetation spin-up, followed by 390-year land-use spin-up, both recycling 120-year random climate sequence | Linear reservoir based on DDM30 (a) | Priestley-Taylor [51] | Degree-day with precipitation factor | No |
PCR–GLOBWB | 50-year | Travel-time routing | Hamon [52] | Degree-day with rain–snow transition | No |
rHM | Model Parameters (Nb.) | Input Data | Spin-Up | Flow Schemes | PET Method | Snowmelt Method | Calibration/Validation |
---|---|---|---|---|---|---|---|
GR4J | 4 | P, PET | 1-year | Production and routing components | Oudin [58] | Degree-day (CEMANEIGE; [59]) | Yes |
HMETS | 21 | P, T | 1-year | Two connected reservoirs for the saturated and vadose zones | Oudin [58] | Degree-day [60] | Yes |
River Basin | Province or State (Country) | Drainage Area (km2) | Mean Altitude (m) | Köppen Climate cClassification |
---|---|---|---|---|
Baleine | Quebec (Canada) | 32,500 | 380 | Continental—Subarctic climate (Dfc) |
Liard | Northwest Territories (Canada) | 275,000 | 980 | Continental—Subarctic climate (Dfc) |
Rio Grande | Oaxaca (Mexico) | 11,982 | 1869 | Tropical—Tropical rainforest/monsoon climate (Af/Am) |
Susquehanna | Pennsylvania (US) | 67,313 | 410 | Continental—Warm-summer humid continental climate (Dfb) |
River Basin | Global Meteorological Datasets | gHM | rHM | ||||||
---|---|---|---|---|---|---|---|---|---|
DBH | H08 | LPJml | PCR-GLOBWB | All gHMs | GR4J | HMETS | |||
Bias high flows (%)—50% of highest observed flows | |||||||||
Baleine (S = 32,500 km2) | GSWP3 | 52 | 38 | 18 | 24 | 33 | −11 | −5 | |
Princeton | 17 | 9 | −13 | −6 | 2 | ||||
WATCH | 69 | 48 | 31 | 7 | 39 | ||||
WFDEI | 53 | 14 | 25 | 34 | 32 | ||||
All datasets | 47.8 | 27.3 | 15.3 | 14.8 | |||||
Liard (S = 275,000 km2) | GSWP3 | 353 | 197 | 33 | 109 | 173 | −10 | −0.2 | |
Princeton | 331 | 187 | 18 | 99 | 159 | ||||
WATCH | 453 | 231 | 50 | 70 | 201 | ||||
WFDEI | 421 | 193 | 45 | 118 | 194 | ||||
All datasets | 390 | 202 | 37 | 99 | |||||
Rio Grande (S = 11,982 km2) | GSWP3 | −36 | −52 | −49 | 23 | −29 | −17 | −10 | |
Princeton | −52 | −48 | −56 | 19 | −34 | ||||
WATCH | −54 | −61 | −57 | 13 | −40 | ||||
WFDEI | −61 | −64 | −62 | 17 | −43 | ||||
All datasets | −51 | −56 | −56 | 18 | |||||
Susquehanna (S = 67,313 km2) | GSWP3 | −19 | −31 | −30 | −28 | −27 | −9 | −11 | |
Princeton | −30 | −40 | −37 | −35 | −36 | ||||
WATCH | −4 | −7 | −15 | −29 | −14 | ||||
WFDEI | −6 | −14 | −16 | −19 | −14 | ||||
All datasets | −15 | −23 | −25 | −28 | |||||
Bias low flows (%)—50% of lowest observed flows | |||||||||
Baleine (S = 32,500 km2) | GSWP3 | 0.4 | 13 | 7 | 38 | 15 | 20 | 4 | |
Princeton | −16 | 7 | 10 | 19 | 5 | ||||
WATCH | −6 | 16 | 62 | 27 | 25 | ||||
WFDEI | −0.5 | 51 | 78 | 46 | 43 | ||||
All datasets | −6 | 22 | 39 | 33 | |||||
Liard (S = 275,000 km2) | GSWP3 | 206 | 946 | 951 | 630 | 683 | 104 | −2 | |
Princeton | 186 | 949 | 810 | 594 | 6345 | ||||
WATCH | 235 | 982 | 1189 | 562 | 742 | ||||
WFDEI | 237 | 1181 | 1137 | 671 | 807 | ||||
All datasets | 216 | 1014 | 1022 | 614 | |||||
Rio Grande (S = 11,982 km2) | GSWP3 | −22 | −81 | −33 | 123 | −3 | 73 | 49 | |
Princeton | −24 | −78 | −44 | 89 | −14 | ||||
WATCH | −38 | −88 | −53 | 113 | −17 | ||||
WFDEI | −53 | −91 | −53 | 110 | −22 | ||||
All datasets | −34 | −85 | −46 | 109 | |||||
Susquehanna (S = 67,313 km2) | GSWP3 | 224 | −8 | 41 | 25 | 71 | 38 | 37 | |
Princeton | 220 | 0.06 | 45 | 24 | 72 | ||||
WATCH | 276 | 16 | 59 | 17 | 92 | ||||
WFDEI | 255 | 12 | 52 | 41 | 90 | ||||
All datasets | 244 | 5 | 49 | 27 |
River Basin | Global Meteorological Datasets | gHM | rHM | |||||
---|---|---|---|---|---|---|---|---|
DBH | H08 | LPJml | PCR-GLOBWB | All gHMs | GR4J | HMETS | ||
NSE high flows—50% of highest observed flows | ||||||||
Baleine (S = 32,500 km2) | GSWP3 | −8.2 | −11.7 | −30.5 | −2.1 | −13.1 | 0.01 | 0.4 |
Princeton | −1.7 | −2.5 | −16.7 | −0.9 | −5.5 | |||
WATCH | −13.7 | −18.0 | −31.9 | −0.6 | −16.1 | |||
WFDEI | −7.8 | −4.7 | −27.8 | −2.7 | −10.8 | |||
All datasets | −8 | −9 | −27 | −2 | ||||
Liard (S = 275,000 km2) | GSWP3 | −54.9 | −15.2 | −7.5 | −3.8 | −20.4 | 0.5 | 0.7 |
Princeton | −47.6 | −12.7 | −5.0 | −3.3 | −17.4 | |||
WATCH | −88.6 | −20.0 | −7.7 | −1.6 | −29.5 | |||
WFDEI | −80.6 | −14.0 | −7.5 | −4.9 | −26.8 | |||
All datasets | −67.9 | −15.5 | −6.9 | −3.4 | ||||
Rio Grande (S = 11,982 km2) | GSWP3 | −3.6 | −3.0 | −2.6 | −2.7 | −2.9 | −0.04 | 0.3 |
Princeton | −1.0 | −1.2 | −1.1 | −1.1 | −1.1 | |||
WATCH | −1.3 | −2.0 | −1.4 | −1.1 | −1.5 | |||
WFDEI | −1.5 | −2.0 | −1.3 | −1.0 | −1.45 | |||
All datasets | −1.9 | −2.1 | −1.6 | −1.5 | ||||
Susquehanna (S = 67,313 km2) | GSWP3 | −0.6 | −0.2 | 0.04 | −0.1 | −0.22 | 0.4 | 0.4 |
Princeton | −0.6 | −0.3 | −0.1 | −0.3 | −0.33 | |||
WATCH | −1.1 | −0.03 | 0.2 | −0.1 | −0.26 | |||
WFDEI | −1.1 | −0.1 | 0.2 | −0.2 | −0.3 | |||
All datasets | −0.9 | −0.2 | 0.1 | −0.2 | ||||
NSE low flows—50% of lowest observed flows | ||||||||
Baleine (S = 32,500 km2) | GSWP3 | −3.5 | −1.1 | −26.6 | −1.4 | −8.2 | 0.2 | 0.4 |
Princeton | −2.2 | −0.4 | −28.5 | −0.3 | −7.9 | |||
WATCH | −4.0 | −1.6 | −59.0 | −0.5 | −16.3 | |||
WFDEI | −3.2 | −2.3 | −66.3 | −1.9 | −18.4 | |||
All datasets | −3.2 | −1.4 | −45.1 | −1 | ||||
Liard (S = 275,000 km2) | GSWP3 | −222.8 | −1043.8 | −3438.1 | −360.6 | −1266 | −12 | −0.8 |
Princeton | −198.2 | −1028.8 | −2095.0 | −318.2 | −910 | |||
WATCH | −272.4 | −1112.9 | −3309.3 | −264.0 | −1239 | |||
WFDEI | −292.0 | −1483.4 | −3179.2 | −412.1 | −1341 | |||
All datasets | −246.4 | −1167.2 | −3005.4 | −338.7 | ||||
Rio Grande (S = 11,982 km2) | GSWP3 | −21.4 | −8.7 | −22.3 | −23.9 | −19.1 | −6.6 | −6.7 |
Princeton | −12.5 | −6.8 | −8.9 | −16.9 | −11.3 | |||
WATCH | −9.0 | −8.0 | −9.9 | −19.3 | −11.6 | |||
WFDEI | −6.7 | −6.8 | −9.2 | −15.0 | −9.4 | |||
All datasets | −12.4 | −7.6 | −12.6 | −18.8 | ||||
Susquehanna (S = 67,313 km2) | GSWP3 | −32.6 | −1.1 | −3.0 | −2.1 | −9.7 | −1.6 | −2.4 |
Princeton | −31.4 | −1.3 | −3.3 | −1.6 | −9.4 | |||
WATCH | −57.2 | −2.1 | −6.0 | −2.4 | −16.9 | |||
WFDEI | −47.3 | −2.4 | −5.3 | −4.0 | −14.8 | |||
All datasets | −42.1 | −1.7 | −4.4 | −2.5 |
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Troin, M.; Arsenault, R.; Fournier, E.; Brissette, F. Catchment Scale Evaluation of Multiple Global Hydrological Models from ISIMIP2a over North America. Water 2021, 13, 3112. https://doi.org/10.3390/w13213112
Troin M, Arsenault R, Fournier E, Brissette F. Catchment Scale Evaluation of Multiple Global Hydrological Models from ISIMIP2a over North America. Water. 2021; 13(21):3112. https://doi.org/10.3390/w13213112
Chicago/Turabian StyleTroin, Magali, Richard Arsenault, Elyse Fournier, and François Brissette. 2021. "Catchment Scale Evaluation of Multiple Global Hydrological Models from ISIMIP2a over North America" Water 13, no. 21: 3112. https://doi.org/10.3390/w13213112
APA StyleTroin, M., Arsenault, R., Fournier, E., & Brissette, F. (2021). Catchment Scale Evaluation of Multiple Global Hydrological Models from ISIMIP2a over North America. Water, 13(21), 3112. https://doi.org/10.3390/w13213112