Using satellite-based precipitation for developing intense rainfall equations for ungauged areas of the Southern Bahia Mesoregion

Garrido, Renan Bitencourt; Fontes, Andrea Sousa; Silva, Samara Fernanda da; Souza, Naiah Caroline Rodrigues de; Assis, Janaina Maria Oliveira de

doi:10.1590/2318-0331.302520240092

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Scientific/Technical Article • RBRH 30 • 2025 • https://doi.org/10.1590/2318-0331.302520240092 linkcopy

Using satellite-based precipitation for developing intense rainfall equations for ungauged areas of the Southern Bahia Mesoregion

Estimativas de precipitação por satélite para definição de equações de chuvas intensas em áreas não monitoradas da Mesorregião Sul Baiano

Authorship SCIMAGO INSTITUTIONS RANKINGS

ABSTRACT

Satellite-based precipitation products can be an important alternative for developing IDF equations in ungauged regions, in search for more flood-resilient hydraulic systems. This study evaluated precipitation estimates from the product CHIRPS for developing IDF equations in the Southern Bahia Mesoregion. The statistical metrics used were Percent Bias (PBIAS), Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and the Nash-Sutcliffe Efficiency coefficient (NSE). The results indicate that CHIRPS does not perform satisfactorily in its original state, but it can provide reasonable IDF equations if the data bias is corrected. Based on a linear regression model, a bias correction method was proposed, which can be applied in ungauged areas of the studied region, showing better performance than IDF equations provided by the software Pluvio 2.1 (RMSE 45.27% lower; MAE 46.31% lower).

Keywords:
IDF curves; CHIRPS; Bias correction

Classes	PBIAS	NSE
Very good	< 5	0.75 - 1.00
Good	5 - 10	0.65 - 0.75
Satisfactory	10 - 15	0.50 - 0.65
Acceptable	-	0.40 - 0.50
Unsatisfactory	≥ 15	≤ 0.40

Model	Variables	Type	R²	SE
Reg1	Longitude	Simple	0.795	0.1255
Reg2	Latitude	Simple	0.557	0.1638
Reg3	PRCPTOT	Simple	0.462	0.1868
Reg4	Longitude and Latitude	Multiple	0.926	0.1030
Reg5	Longitude, Latitude and PRCPTOT	Multiple	0.928	0.1076

Name	Intersection		Longitude		Latitude		PRCPTOT
Name	Standard error	P-value	Standard error	P-value	Standard error	P-value	Standard error	P-value
Reg 1	2.129	2.483E-11	0.0537	1.033E-11
Reg 2	0.325	0.00127			0.0206	8.753E-07
Reg 3	0.143	7.481E-12					0.000112	1.547E-05
Reg 4	2.255	1.140E-08	0.0608	3.863E-08	0.0158	0.00279
Reg 5	2.957	9.796E-06	0.0758	1.074E-05	0.0158	0.00320	8.491E-05	0.325

N	Code	PBIAS			RMSE (mm/h)			MAE (mm/h)			NSE
N	Code	Orig.	BC.1	BC.2	Orig.	BC.1	BC.2	Orig.	BC.1	BC.2	Orig.	BC.1	BC.2
1	1439023	31.48%	-4.26%	-8.97%	41.22	5.91	12.04	41.02	5.54	11.69	-4.02	0.90	0.57
2	1439044	-11.74%	-11.91%	-20.79%	14.79	14.98	24.87	13.39	13.59	23.72	0.62	0.61	-0.07
3	1439089	23.60%	-1.71%	-2.25%	26.43	1.91	2.48	25.90	1.88	2.46	0.10	1.00	0.99
4	1539002	59.53%	2.47%	10.51%	69.72	2.87	12.27	69.10	2.87	12.20	-9.08	0.98	0.69
5	1539006	14.58%	3.46%	-6.09%	18.34	5.72	7.54	17.29	4.91	7.22	0.14	0.92	0.85
6	1539010	57.04%	-8.65%	9.73%	61.92	13.67	12.70	61.91	11.54	10.56	-2.60	0.82	0.85
7	1539014	19.32%	-5.74%	-5.31%	21.22	6.46	5.99	21.16	6.29	5.82	0.23	0.93	0.94
8	1639000	-0.37%	-2.72%	-14.18%	3.42	5.22	19.64	2.98	4.47	18.79	0.97	0.93	0.06
9	1739001	28.00%	-7.81%	-3.69%	46.19	12.56	6.53	44.62	12.45	5.87	-0.46	0.89	0.97
10	1739005	14.96%	6.16%	1.73%	20.47	9.80	5.40	19.01	8.47	4.85	-0.82	0.58	0.87
11	1739010	4.72%	-5.88%	-19.80%	7.29	9.06	30.54	7.25	9.03	30.40	0.93	0.89	-0.21
12	1740001	-17.99%	1.26%	6.97%	24.33	6.86	12.43	24.24	6.10	10.68	-0.73	0.86	0.55
13	1740005	-11.38%	0.16%	7.67%	14.43	2.75	9.41	13.74	2.36	9.26	0.46	0.98	0.77
14	1740006	-13.26%	-2.60%	-5.41%	16.52	3.79	6.97	16.11	3.27	6.57	0.21	0.96	0.86
15	1740008	-26.71%	-5.70%	-8.61%	34.38	9.68	12.75	33.12	8.38	10.99	-2.16	0.75	0.56
16	1839000	-1.40%	-3.99%	12.21%	6.52	7.95	20.93	5.45	6.34	17.84	0.96	0.94	0.57
17	1840012	-22.57%	-1.29%	-5.83%	35.28	9.91	12.29	35.12	8.46	9.64	-0.15	0.91	0.86
18	1539016	-21.50%	-14.08%	-30.45%	28.70	20.05	39.50	26.57	17.40	37.64	-0.82	0.11	-2.44
19	1439002	47.48%	1.51%	21.17%	43.45	2.00	19.52	42.59	1.70	18.99	-0.02	1.00	0.79
20	1539008	-24.15%	-15.62%	-34.00%	31.49	21.29	43.63	29.69	19.21	41.81	-0.45	0.34	-1.78
21	1339000	47.64%	-3.84%	0.63%	55.06	4.47	0.73	54.47	4.39	0.72	-4.45	0.96	1.00
22	1339012	57.78%	-0.81%	-13.50%	87.52	3.91	21.45	86.76	3.48	20.27	-5.08	0.99	0.63
23	1339027	69.21%	-7.46%	15.52%	79.24	8.75	17.69	78.60	8.48	17.63	-10.03	0.87	0.45
24	1339038	98.86%	7.25%	-4.27%	156.53	11.58	6.69	154.42	11.32	6.67	-18.12	0.90	0.97
25	1339044	116.51%	-21.93%	11.73%	160.62	35.14	19.16	160.00	30.11	16.12	-17.99	0.09	0.73
26	1439006	23.13%	-19.70%	-12.75%	27.57	26.16	18.96	26.70	22.74	16.26	0.06	0.16	0.56
Average		21.64%	-4.75%	-3.77%	43.56	10.09	15.46	42.74	9.03	14.41	-2.78	0.78	0.45

Classes	PBIAS			NSE
Classes	Orig.	BC.1	BC.2	Orig.	BC.1	BC.2
Very good	3	13	5	3	19	12
Good	0	8	9	0	1	2
Satisfactory	5	2	6	1	2	6
Acceptable	-	-	-	1	0	1
Unsatisfactory	18	3	6	21	4	5

N	Code	PBIAS		RMSE (mm/h)		MAE (mm/h)		NSE
N	Code	Pluvio	BC.2	Pluvio	BC.2	Pluvio	BC.2	Pluvio	BC.2
1	1439023	10.63%	-8.97%	16.71	12.04	14.29	11.69	0.17	0.57
2	1439044	25.30%	-20.79%	30.49	24.87	28.87	23.72	-0.61	-0.07
3	1439089	30.27%	-2.25%	34.37	2.48	33.22	2.46	-0.52	0.99
4	1539002	23.10%	10.51%	28.93	12.27	26.82	12.20	-0.74	0.69
5	1539006	4.11%	-6.09%	6.75	7.54	5.80	7.22	0.88	0.85
6	1539010	13.80%	9.73%	15.44	12.70	14.97	10.56	0.78	0.85
7	1539014	12.74%	-5.31%	16.12	5.99	13.96	5.82	0.56	0.94
8	1639000	-6.83%	-14.18%	9.07	19.64	9.06	18.79	0.80	0.06
9	1739001	-13.91%	-3.69%	22.21	6.53	22.18	5.87	0.66	0.97
10	1739005	7.98%	1.73%	13.41	5.40	11.57	4.85	0.22	0.87
11	1739010	-10.55%	-19.80%	18.32	30.54	16.20	30.40	0.56	-0.21
12	1740001	18.04%	6.97%	26.72	12.43	24.31	10.68	-1.08	0.55
13	1740005	25.26%	7.67%	32.32	9.41	30.50	9.26	-1.71	0.77
14	1740006	24.65%	-5.41%	32.09	6.97	29.96	6.57	-1.98	0.86
15	1740008	21.98%	-8.61%	28.88	12.75	27.25	10.99	-1.23	0.56
16	1839000	45.66%	12.21%	67.25	20.93	66.72	17.84	-3.48	0.57
17	1840012	68.04%	-5.83%	108.93	12.29	105.84	9.64	-10.01	0.86
18	1539016	15.67%	-30.45%	20.73	39.50	19.37	37.64	0.05	-2.44
19	1439002	59.41%	21.17%	54.92	19.52	53.29	18.99	-0.63	0.79
20	1539008	16.28%	-34.00%	20.17	43.63	20.01	41.81	0.40	-1.78
21	1339000	2.04%	0.63%	3.29	0.73	2.81	0.72	0.98	1.00
22	1339012	-22.52%	-13.50%	35.20	21.45	33.81	20.27	0.02	0.63
23	1339027	2.74%	15.52%	4.13	17.69	3.55	17.63	0.97	0.45
24	1339038	-25.02%	-4.27%	39.39	6.69	39.08	6.67	-0.21	0.97
25	1339044	-15.29%	11.73%	26.75	19.16	22.65	16.12	0.47	0.73
26	1439006	18.85%	-12.75%	21.81	18.96	21.76	16.26	0.41	0.56
Average		13.56%	-3.77%	28.25	15.46	26.84	14.41	-0.55	0.45

Classes	PBIAS		NSE
Classes	Pluvio	BC.2	Pluvio	BC.2
Very good	3	5	5	12
Good	2	9	1	2
Satisfactory	5	6	2	6
Acceptable	-	-	3	1
Unsatisfactory	16	6	15	5

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[1] Source: Adapted from Rauf & Ghumman (2018); Anjinho et al. (2021).