An Index of Susceptibility to Drought (<i>ISD</i>) for the Semiarid Brazilian Northeast

Neves, Josemir Araujo; Melo, Silvio de Barros; Sampaio, Everardo Valadares de Sá Barreto

doi:10.1590/0102-778631220140016

Josemir Araujo Neves

Empresa de Pesquisa Agropecuária do Rio Grande do Norte, Parnamirim, RN, Brazil

Silvio de Barros Melo Autor de correspondência: Silvio de Barros Melo, sbm@cin.ufpe.br.

Centro de Informática, Universidade Federal de Pernambuco, Recife, PE, Brazil

Everardo Valadares de Sá Barreto Sampaio

Departamento de Energia Nuclear, Universidade Federal de Pernambuco, Recife, PE, Brazil

Autor de correspondência: Silvio de Barros Melo, sbm@cin.ufpe.br.

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Figura 1
Location of the sites (rainfall and weather stations) in Rio Grande do Norte, Brazil, used in this work.

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Figura 2
ISD Structure. The term VP is the abbreviation for “viewpoint”. The numbers to the right of the sub-indicators indicate their levels of importance in the model.

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Figura 3
Flow chart of calculation - ISD.

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Figura 2
ISD Structure. The term VP is the abbreviation for “viewpoint”. The numbers to the right of the sub-indicators indicate their levels of importance in the model.

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Figura 3
Flow chart of calculation - ISD.

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Figura 4
Rain distribution in Rio Grande do Norte – 1998 (extremely dry).

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Figura 5
Rain distribution in Rio Grande do Norte – 2000 (normal).

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Figura 6
Rain distribution in Rio Grande do Norte – 2005 (dry).

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Figura 7
Rain distribution in Rio Grande do Norte – 2006 (rainy).

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Figura 8
Index of Susceptibility to Drought (ISD) – 1998.

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Figura 9
Index of Susceptibility to Drought (ISD) – 2000.

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Figura 10
Index of Susceptibility to Drought (ISD) – 2005.

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Figura 11
Index of Susceptibility to Drought (ISD) – 2006.

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Figura 12
Boxplot of the ISD classification results of the first simulation.

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Figura 13
Stochastic dominance of ISD classification according to the indexing of .

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Figura 14
Boxplot of the ISD classification resulting from the first approach of the second simulation. Year: 1998.

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Figura 15
Stochastic dominance of the ISD classification according to the indexing of , the first approach from the second simulation.

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Tabela 1
List of indicators for drought susceptibility, respective weights and levels of importance.

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Tabela 2
Degree of susceptibility to drought for the Rio Grande do Norte state.

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Tabela 3
ISD PCA results.

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Tabela 4
Matrix of factors of charges rotated of ISD sub-indicators.

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Tabela 5
Statistics of main ISD classification results from the first simulation.

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Tabela 6
Summary of the stochastic dominance results from the first approach of the second simulation.

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Tabela 7
Summary of the stochastic dominance results from the second approach of the second simulation.

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Indicators	Meaning	Weigths / levels of importance
VP11	Represent the physical characteristics of the municipalities and are obtained from the agricultural suitability of soils and use of land of the municipalities.	0.15
VP12	Represent the weather conditions by the historic mean rainfall of the municipalities.	0.12
VP131	Represent the basic rural characteristics by the rural population of the municipalities.	0.15
VP132	Represent the basic rural characteristics by the participation of the agricultural activities in GDP of the municipalities.	0.12
VP133	Represent the local conditions that can mitigate the drought effects based on the current municipality income per capita.	0.06
VP22	Indicate the risks associated with harvest lost and is based on the rain distribution in the municipalities.	0.20
VP21	Indicate the risks associated with shortages of human and animal drinking water of the municipalities.	0.20

Category	Variation
High susceptibility	ISD > 52.05174
Medium-high susceptibility	44.72983 < ISD ≤ 52.05174
Medium susceptibility	31.76541 < ISD ≤ 44.72983
Medium-low susceptibility	23.26673 < ISD ≤ 31.76541
Low susceptibility	ISD ≤ 23.26673

Year	Main components⁽¹⁾ (1) Indices in boldface represent components which are sufficient to explain more than 80% of the variation; their corresponding eigenvalues, explained variance and cumulative variance are also shown in boldface in the other columns.	Eigenvalue	Variance explained (%)	Cumulative variance (%)
1998	1	2.064	29.50	29.50
	2	1.478	21.10	50.60
	3	1.212	17.30	67.90
	4	0.813	11.60	79.60
	5	0.687	9.80	89.40
	6	0.501	7.17	96.58
	7	0.239	3.42	100.0
2000	1	1.806	25.80	25.80
	2	1.520	21.70	47.50
	3	1.138	16.30	63.80
	4	0.870	12.40	76.20
	5	0.710	10.20	86.40
	6	0.583	8.36	94.72
	7	0.369	5.29	100.0
2005	1	2.108	30.10	30.10
	2	1.592	22.80	52.90
	3	1.247	17.80	70.70
	4	0.793	11.30	82.10
	5	0.537	7.69	89.74
	6	0.440	6.30	96.00
	7	0.276	3.95	100.0
2006	1	1.752	25.10	25.10
	2	1.552	22.2	47.20
	3	1.157	16.5	63.70
	4	0.863	12.3	76.10
	5	0.844	12.1	88.10
	6	0.506	7.26	95.41
	7	0.321	4.59	100.0

Year	Sub-indicator	Components⁽¹⁾ (1) A factor that is shown in boldface represents a moderate or high charge, indicating that the corresponding sub-indicator is significant for the main component in the factor's column.
Year	Sub-indicator	1	2	3	4	5	6	7
1998	VP11	−0.1643	0.5885	−0.2534	0.0088	−0.6301	−0.3963	−0.0902
	VP12	−0.5966	0.1715	0.0343	−0.2281	0.2707	0.1971	−0.6702
	VP131	0.4382	0.4392	−0.0545	−0.1218	−0.1475	0.7546	−0.0767
	VP132	0.0245	0.2385	0.6428	0.7068	−0.0012	−0.0102	−0.1719
	VP133	0.2529	0.5629	0.0589	−0.220	0.6415	−0.3653	0.1486
	VP21	−0.5999	0.2373	0.0225	0.0920	0.0760	0.3114	0.6869
	VP22	0.0201	0.0343	−0.7172	0.6135	0.3008	0.0626	−0.1147
2000	VP11	−0.0025	0.5955	−0.0450	0.6156	0.2049	0.2776	0.3810
	VP12	0.5573	0.2951	−0.2263	0.1433	0.2259	−0.2810	−0.6327
	VP131	−0.4827	0.3338	−0.0878	0.1288	−0.3751	−0.6995	−0.0320
	VP132	−0.3766	0.0188	−0.5358	−0.2985	0.6830	−0.0889	0.0844
	VP133	−0.2364	0.5691	0.0413	−0.4727	−0.2150	0.4739	−0.3520
	VP21	0.5074	0.2608	−0.2620	−0.4580	−0.2258	−0.1816	0.5585
	VP22	0.0322	0.2332	0.7625	−0.2477	0.4499	−0.2982	0.1013
2005	VP11	−0.0391	0.6655	−0.0342	0.0073	−0.6979	0.2284	0.1222
	VP12	−0.5738	0.2440	0.0772	0.0729	0.3425	−0.1195	0.6842
	VP131	0.5048	0.3068	−0.0621	0.0936	0.4954	0.6037	0.1684
	VP132	−0.0377	−0.0115	0.6927	0.6997	−0.0377	0.0726	−0.1487
	VP133	0.3627	0.5331	0.1083	−0.0213	0.2270	−0.7089	−0.1334
	VP21	−0.5291	0.3423	−0.1619	−0.0073	0.3080	0.1866	−0.6684
	VP22	0.0356	−0.0418	−0.6863	0.7040	−0.0464	−0.1621	0.0422
2006	VP11	−0.2568	0.5314	−0.1771	−2.3×10⁻¹	0.5591	0.2923	0.4063
	VP12	0.5006	0.4150	−0.3390	−3.1×10⁻²	0.1202	0.1344	−0.6546
	VP131	−0.5671	0.1912	0.1458	−2.3×10⁻⁵	−0.4308	0.5571	−0.3528
	VP132	0.0903	0.1767	0.6945	−6.2×10⁻¹	0.0671	−0.2127	−0.1801
	VP133	−0.3333	0.5498	−0.0783	2.4×10⁻¹	−0.1928	−0.6914	−0.0549
	VP21	0.4638	0.3738	0.0466	−4.4×10⁻²	−0.6015	0.1806	0.4963
	VP22	−0.1650	−0.1880	−0.5844	−6.9×10⁻¹	−0.2891	−0.1732	0.0014

Class order	City	Mode	Min	25th Pctile	50th Pctile	75th Pctile	Max	Mean	Standard deviation
1	Acari⁽³⁾ (3) Municipalities belonging to the third group.	96	1	14	29	52	129	35.62	26.48
2	Assu⁽¹⁾ (1) Municipalities belonging to the first group;	1	1	2	4	11	62	7.69	8.64
6	Almino Afonso	90	60	135	153	163	167	146.33	20.64
10	Apodi⁽²⁾ (2) Municipalities belonging to the second group;	16	1	5	11	25	95	17.08	16.28
13	Campo_Grande⁽²⁾ (2) Municipalities belonging to the second group;	25	1	7	16	33	102	22.87	19.95
20	Brejinho	165	59	137	155	164	167	147.77	20.02
23	Caico⁽²⁾ (2) Municipalities belonging to the second group;	40	1	6	14	28	105	19.79	18.07
28	Carnaubais⁽³⁾ (3) Municipalities belonging to the third group.	4	1	10	21	41	122	27.96	22.94
34	Currais_Novos⁽³⁾ (3) Municipalities belonging to the third group.	20	1	9	19	38	110	25.59	21.47
40	Extremoz	153	64	137	154	163	167	147.08	20.68
44	Francisco_Dantas⁽³⁾ (3) Municipalities belonging to the third group.	18	1	15	32	56	131	38.11	27.57
48	Gov_Dix_Sept_Rosado⁽²⁾ (2) Municipalities belonging to the second group;	13	1	7	16	32	107	22.07	19.40
51	Ielmo_Marinho⁽²⁾ (2) Municipalities belonging to the second group;	5	1	5	11	24	88	16.57	15.76
53	Ipueira	83	30	98	126	148	167	120.69	32.12
55	Itau⁽³⁾ (3) Municipalities belonging to the third group.	12	1	14	28	51	129	34.91	26.38
57	Jandaira⁽³⁾ (3) Municipalities belonging to the third group.	55	1	15	30	52	131	36.20	26.75
67	Jucurutu⁽³⁾ (3) Municipalities belonging to the third group.	54	1	11	23	43	117	29.35	23.17
68	Jundia	167	71	146	159	166	167	153.12	16.48
79	Macau⁽²⁾ (2) Municipalities belonging to the second group;	5	1	5	12	25	94	17.39	16.51
81	Marcelino_Viera⁽³⁾ (3) Municipalities belonging to the third group.	27	1	12	25	45	121	31.00	24.19
88	Mossoro⁽¹⁾ (1) Municipalities belonging to the first group;	9	1	1	4	9	51	6.74	7.76
103	Pau_dos_Ferros⁽³⁾ (3) Municipalities belonging to the third group.	23	1	15	30	54	129	37.04	27.27
124	Santana_do_Matos⁽¹⁾ (1) Municipalities belonging to the first group;	5	1	3	6	15	75	10.69	11.32
130	Sao_Francisco_do_Oeste	159	55	131	151	162	167	143.16	23.00
140	Sao_Rafael⁽³⁾ (3) Municipalities belonging to the third group.	18	1	13	28	51	126	34.66	26.21
141	Sao_Tome⁽²⁾ (2) Municipalities belonging to the second group;	2	1	5	13	28	100	18.85	17.62
144	Senador_Georgino_Avelino	137	53	131	151	162	167	143.54	22.62
150	Severiano_Melo⁽²⁾ (2) Municipalities belonging to the second group;	4	1	6	14	28	98	19.69	17.96
155	Tenente_Ananias⁽³⁾ (3) Municipalities belonging to the third group.	17	1	11	23	42	128	29.53	23.34
165	Vera_Cruz	119	50	126	148	161	167	140.54	24.43
167	Vila_Flor	94	48	127	148	160	167	140.81	24.09

Year	Dominants	Dominated
1998	Santana do Matos (124) and Mossoró (88)	Brejinho (20), Natal (89), Maxaranguape (83) and São Gonçalo do Amarante (131)
2000	Currais Novos (34), Jandaíra (57) and São Tomé (141)	Brejinho (20), Almino Afonso (6), Maxaranguape (83) and Extremoz (40)
2005	Matos (124), São Tomé (141), Severiano Melo (150), Apodi (10), and Tenente Ananias (155)	Extremoz (40), Maxaranguape (83), Senador Georgino Avelino (144) and Almino Afonso (6)
2006	São Tomé (141), Marcelino Vieira (81), Ielmo Marinho (51), Bento Fernandes (17), João Câmara (64) and Monte das Gameleiras (87)	Almino Afonso (6), São Francisco do Oeste (130) and Extremoz (40)

Year	Dominants	Dominated
1998	Mossoró (88) and Santana do Matos (124)	Brejinho (20), Maxaranguape (83), Natal (89), São Gonçalo do Amarante (131), Extremoz (40), Pedro Velho (107), José da Penha (66), Doutor Severiano (35), Jundiá (68)
2000	São Tomé (141), Jandaíra (57), Currais Novos (34)	Brejinho (20), Almino Afonso (6), Jundiá (68), Extremoz (40), Maxaranguape (83)
2005	Santana do Matos (124), Severiano Melo (150), São Tomé (141), Apodi (10), Tenente Ananias (155), Macau (79), Assu (2), Currais Novos (28)	Extremoz (40), Jundiá (68), Almino Afonso (6), Viçosa (166), Encanto (37), Maxaranguape (83), Senador Georgino Avelino (144), Vera Cruz (165), Brejinho (20)
2006	Ielmo Marinho (51), São Tomé (141), Marcelino Vieira (81), Bento Fernandes (17), João Câmara (64)	Almino Afonso (6), São Francisco do Oeste (130), Extremoz (40), Jundiá (68), Viçosa (166), Encanto (37), Tabuleiro Grande (152), Maxaranguape (83) Triunfo Potiguar (160)

[1] Autor de correspondência: Silvio de Barros Melo, sbm@cin.ufpe.br.

Brasil

Brasil

An Index of Susceptibility to Drought (ISD) for the Semiarid Brazilian Northeast

Um Índice de Susceptibilidade ao Fenômeno da Seca (ISFS) para o Semiárido Nordestino

Abstract