The magnitude of your peak flow is regularly underestimated (Figure S
The magnitude of the peak flow is consistently underestimated (Figure S3 and Table 5).Water 2021, 13,15 ofTable six. NSE Betamethasone disodium MedChemExpress values of higher and low flows computed for each gHM limate ataset combination and the two rHMs for the 4 catchments more than the 1971010 period. The satisfactory NSE values are in bold (NSE 0.five; see Section two.4).River Basin Global Meteorological Datasets GSWP3 Princeton WATCH WFDEI All datasets GSWP3 Princeton WATCH WFDEI All datasets GSWP3 Princeton WATCH WFDEI All datasets GSWP3 Princeton WATCH WFDEI All datasets GSWP3 Princeton WATCH WFDEI All datasets GSWP3 Princeton WATCH WFDEI All datasets GSWP3 Princeton WATCH WFDEI All datasets GSWP3 Princeton WATCH WFDEI All datasets gHM DBH H08 LPJml PCRGLOBWB All gHMs GR4J rHM HMETSBaleine (S = 32,500 km2 ) Liard (S = 275,000 km2 ) Rio Grande (S = 11,982 km2 ) Susquehanna (S = 67,313 km2 )Baleine (S = 32,500 km2 ) Liard (S = 275,000 km2 ) Rio Grande (S = 11,982 km2 ) Susquehanna (S = 67,313 km2 )NSE high flows–50 of highest observed flows -8.two -11.7 -30.five -2.1 -1.7 -2.five -16.7 -0.9 -13.7 -18.0 -31.9 -0.six -7.eight -4.7 -27.8 -2.7 -8 -9 -27 -2 -54.9 -15.2 -7.5 -3.eight -47.6 -12.7 -5.0 -3.3 -88.6 -20.0 -7.7 -1.six -80.six -14.0 -7.5 -4.9 -67.9 -15.five -6.9 -3.4 -3.6 -3.0 -2.six -2.7 -1.0 -1.two -1.1 -1.1 -1.3 -2.0 -1.four -1.1 -1.five -2.0 -1.three -1.0 -1.9 -2.1 -1.six -1.five -0.six -0.two 0.04 -0.1 -0.6 -0.3 -0.1 -0.three -1.1 -0.03 0.2 -0.1 -1.1 -0.1 0.2 -0.two -0.9 -0.2 0.1 -0.two NSE low flows–50 of lowest observed flows -3.5 -1.1 -26.6 -1.four -2.two -0.four -28.5 -0.three -4.0 -1.six -59.0 -0.5 -3.two -2.3 -66.3 -1.9 -3.2 -1.4 -45.1 -1 -222.8 -1043.eight -3438.1 -360.6 -198.2 -1028.8 -2095.0 -318.two -272.4 -1112.9 -3309.three -264.0 -292.0 -1483.4 -3179.two -412.1 -246.4 -1167.2 -3005.4 -338.7 -21.4 -8.7 -22.three -23.9 -12.five -6.eight -8.9 -16.9 -9.0 -8.0 -9.9 -19.three -6.7 -6.eight -9.two -15.0 -12.four -7.six -12.6 -18.eight -32.6 -1.1 -3.0 -2.1 -31.four -1.three -3.three -1.six -57.2 -2.1 -6.0 -2.four -47.3 -2.4 -5.three -4.0 -42.1 -1.7 -4.four -2.-13.1 -5.5 -16.1 -10.eight -20.four -17.4 -29.5 -26.eight -2.9 -1.1 -1.five -1.45 -0.22 -0.33 -0.26 -0.three -8.2 -7.9 -16.three -18.4 -1266 -910 -1239 -1341 -19.1 -11.3 -11.six -9.four -9.7 -9.four -16.9 -14.0.0.0.0.-0.0.0.0.0.0.–0.-6.-6.-1.-2.Relating to the Susquehanna River Basin, the gHM limate ataset combinations execute poorly in reproducing seasonal discharge (Figure S5) and systematically offer a time offset with the spring peak flow. That is confirmed together with the analysis of the Taylor diagram with robust RMSD values (Figure S6). H08, DBH, and PCR LOBWB usually far better capture the mean interannual cycles of discharge, with a excellent simulation of low flows with minimal bias values, specially for the H08 ataset and PCR LOBWB ataset combinations (Table 5). Only H08, when driven by WATCH and WFDEI, exhibits realistic peak flow simulations which can be the closest to the rHM simulations. As for the gHM HM comparison, the rHM rinceton combinations yield a lot more constant discharge simulations more than the catchments than the gHM rinceton combinations, with a a lot more trusted reproduction in the observed magnitude and timing of peak flow (Figure 9 and Figures S1, S3 and S5), and far better model ability. The normal deviation values of the rHMs are similar to the observations, with higher correlation coefficient values and reduce RMSD values than the gHMs (Figure ten and Figures S2, S4 and S6). This confirms the truth that the gHMs, with their coarse resolution plus the associated limitations with regards to the Safranin supplier misrepresentation of regional topography, translate into some unrealistic simulations of disch.
