Coupling WRF and NRCS-CN Models for Flood Forecasting in Paraíba do Meio River Basin in Alagoas, Brazil

Santos, André Gonçalo dos; Campos, José Nilson Beserra; Silva Junior, Rosiberto Salustiano

doi:10.1590/0102-7786344068

André Gonçalo dos Santos Autor de correspondência: André Gonçalo dos Santos, andregs9@yahoo.com.br.

Departamento de Engenharia Hidráulica e Ambiental, Centro de Tecnologia, Universidade Federal do Ceará, Fortaleza, CE, Brasil.

http://orcid.org/0000-0003-1826-4787

José Nilson Beserra Campos

Departamento de Engenharia Hidráulica e Ambiental, Centro de Tecnologia, Universidade Federal do Ceará, Fortaleza, CE, Brasil.

http://orcid.org/0000-0001-6321-1284

Rosiberto Salustiano Silva Junior

Instituto de Ciências Atmosféricas, Universidade Federal de Alagoas, Maceió, AL, Brasil.

http://orcid.org/0000-0001-7152-0095

Autor de correspondência: André Gonçalo dos Santos, andregs9@yahoo.com.br.

Station - DCPs	Code	Station type	Latitude	Longitude
Viçosa/AL (SB9)	936119	Rainfall	–9 22’ 45.12”	–36 14’ 57.12”
Viçosa/AL (SB9)	39710000	Flowrate	–9 22’ 45.12”	–36 14’ 57.12”
Atalaia/AL (SB12)	936110	Rainfall	–9 30’ 4.12”	–36 1’ 22.08”
Atalaia/AL (SB12)	39870000	Flowrate	–9 30’ 4.12”	–36 1’ 22.08”

Scheme	Notation
Kessler (1969)KESSLER, E. On the distribution and continuity of water substance in atmospheric circulations, in: Proceedings of the Conference on the Distribution and Continuity of Water Substance in Atmospheric Circulations. American Meteorological Society, v.10, n. 32, p. 1-84, 1969. – microphysics	MPK
*Lin et al.* (1983)**LIN, Y.L.; RICHARD, D.F.; HAROLD, D.O. Bulk parameterization of the snow field in a cloud model. J. Climate Appl. Meteor., v. 22, p. 1065-1092, 1983. – microphysics	MPL
*Thompson et al. (2004)*THOMPSON, G.; RASMUSSEN, R.M.; MANNING, K. Explicit forecasts of winter precipitation using an improved bulk microphysics scheme. Part I: description and sensitivity analysis. Mon. Weather Rev., v. 132, n. 2, p. 519-542, 2004. – microphysics	MPT
Kain and Fritsch (1993)KAIN, J.S.; FRITSCH, J.M. The role of the convective “trigger function” in numerical forecasts of mesoscale convective systems. Meteor. Atmos. Phys., v. 49, p. 93-106, 1993. – convection	KF
Betts and Miller (1986)BETTS, A.K.; MILLER, M.J. A new convective adjustment scheme. Part II: single column tests using GATE wave, BOMEX, ATEX and arctic air-mass data sets. Q. J. R. Meteorolog. Soc., v. 112, p. 693-709, 1986. and Janjić (1994)JANJIć, Z.I. The step-mountain Eta coordinate model: Further developments of the convection closure schemes. Mon. Wea. Rev., v. 122, p. 927-945, 1994. – convection	BMJ
Grell and Dévényi (2002)GRELL, G.A.; DéVéNYI, D. A generalized approach to parameterizing convection combining ensemble and data assimilation techniques. Geophys. Res. Lett., v. 29, n. 14, p. 1693-1696, 2002. – convection	G3D

Configuration	Scheme	Reference
Microphysics	Purdue Lin	*Lin et al., 1983*LIN, Y.L.; RICHARD, D.F.; HAROLD, D.O. Bulk parameterization of the snow field in a cloud model. J. Climate Appl. Meteor., v. 22, p. 1065-1092, 1983.
Cumulus	Grell 3D	Grell and Dévényi, 2002GRELL, G.A.; DéVéNYI, D. A generalized approach to parameterizing convection combining ensemble and data assimilation techniques. Geophys. Res. Lett., v. 29, n. 14, p. 1693-1696, 2002.
Surface boundary layer	MM5 Similarity	Beljaars, 1995BELJAARS, A.C.M. The parametrization of surface fluxes in large-scale models under free convection. Q. J. R. Meteorolog. Soc., v. 121, p. 255-270, 1995.
Soil surface layer	Unified Noah Land Surface Model	*Tewari et al., 2004*TEWARI, M.F.; CHEN, W, WANG J.; DUDHIA, M.A.; LEMONE K, MITCHELL ME, GAYNO G, WEGIEL J, CUENCA R.H. Implementation and verification of the unified NOAH land surface model in the WRF model, in: Proceedings of the 20th Conference on Weather Analysis and Forecasting. 16th Conference on Numerical Weather Prediction, Seattle, p. 11-15, 2004. Disponível em: http://ams.confex.com/ams/84Annual/techprogram/paper_69061.htm. Acesso em: 15 de Maio de 2017. http://ams.confex.com/ams/84Annual/techp...
Planetary boundary layer	Asymmetric Convection Model	Pleim, 2007PLEIM, J.E. A combined local and nonlocal closure model for the atmospheric boundary layer. Part I: model description and testing. J. Appl. Meteor. Climatol., v. 46, p. 1383-1395, 2007.
Atmospheric radiation	Goddard Shortwave	Chou and Max, 1994CHOU, M.D.,;MAX J.S. An efficient thermal infrared radiation parameterization for use in general circulation models. NASA Tech. Memo: 104606, v. 3, p. 93, 1994.
Atmospheric radiation	RRTMG Longwave	*Iacono et al., 2008*IACONO, M.J., DELAMERE, J.S., MLAWER, E.J., SHEPHARD, M.W., CLOUGH, S.A., COLLINS, W.D. Radiative forcing by long-lived greenhouse gases: calculations with the AER radiative transfer models. J. Geophys. Res. Atmos., v. 113, D13103, 2008.

	Observed category
Predicted category	$i / j$	Class 1	Class 2	...	Class k	Total
	Class 1	$n (F_{1}, O_{1})$	$n (F_{1}, O_{2})$	...	$n (F_{1}, O_{k})$	$N (F_{1})$
	Class 2	$n (F_{2}, O_{1})$	$n (F_{2}, O_{2})$	...	$n (F_{2}, O_{k})$	$N (F_{2})$
	...	...	...	...	...	...
	Class k	$n (F_{k}, O_{1})$	$n (F_{k}, O_{2})$	...	$n (F_{k}, O_{k})$	$N (F_{K})$
	Total	$N (O_{1})$	$N (O_{2})$	...	$N (O_{K})$	$N$

Combination	r	Bias	RMSE
MPK-KF	0.55	–0.01	1.82
MPK-BMJ	0.31	–0.84	2.17
MPK-G3D	0.53	–0.55	1.87
MPL-KF	0.63	0.07	1.66
MPL-BMJ	0.44	–0.81	2.08
MPL-G3D	0.46	–0.27	2.03
MPT-KF	0.68	–0.07	1.55
MPT-BMJ	0.38	–0.82	2.12
MPT-G3D	0.61	–0.28	1.69

Combination	r	Bias	RMSE
MPK-KF	0.42	–0.97	2.05
MPK-BMJ	0.36	–0.93	2.04
MPK-G3D	0.29	–0.61	2.80
MPL-KF	0.46	–1.02	2.08
MPL-BMJ	0.42	–0.95	2.03
MPL-G3D	0.42	–0.50	2.19
MPT-KF	0.21	–0.99	2.14
MPT-BMJ	0.20	–0.95	2.14
MPT-G3D	0.40	–0.42	1.89

Station	r	Bias (mm/h)	RMSE (mm/h)	HSS
Atalaia	0.32	0.07	10.45	0.61
Viçosa	0.15	–0.09	2.92	0.37

Statistical criterion	Sub-basin SB9	Sub-basin SB12
Statistical criterion	Calibrated	Calibrated
NS	0.809	0.836
R	0.905	0.938
RMSE	0.073	1.067
Bias	–0.184	–5.837

Statistical criterion	Sub-basin SB9	Sub-basin SB12
Statistical criterion	Validated	Validated
NS	0.591	0.809
r	0.945	0.908
RMSE	0.295	1.251
Bias	–2.257	–3.866

Statistical criterion	Sub-basin SB9	Sub-basin SB12
Statistical criterion	Coupled	Coupled
NS	0.75	0.57
HSS	0.25	0.73
PA	61%	84%
r	0.76	0.75
RMSE (m³/s)	0.11	2.49
Bias (m³/s)	–0.24	13.15

H S S = \frac{\frac{1}{N} \sum_{i = 1}^{k} N (F_{i} O_{i}) - \frac{1}{N^{2}} \sum_{i = 1}^{k} N (F_{i}) N (O_{i})}{1 - \frac{1}{N^{2}} \sum_{i = 1}^{k} N (F_{i}) N (O_{i})}

[1] Autor de correspondência: André Gonçalo dos Santos, andregs9@yahoo.com.br.

Brasil

Brasil

Coupling WRF and NRCS-CN Models for Flood Forecasting in Paraíba do Meio River Basin in Alagoas, Brazil

Acoplamento dos modelos WRF e NRCS-CN para previsão de cheias na bacia do rio Paraíba do Meio em Alagoas, Brasil

Abstract