Identification of spatial and temporal contributions of rainfalls to flash  floods using neural network modelling: case study on the Lez basin (southern  France)

Darras, T.; Borrell Estupina, V.; Kong-A-Siou, L.; Vayssade, B.; Johannet, A.; Pistre, S.

doi:10.5194/hess-19-4397-2015

Articles | Volume 19, issue 10

https://doi.org/10.5194/hess-19-4397-2015

© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

https://doi.org/10.5194/hess-19-4397-2015

© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 19, issue 10

Research article

|

30 Oct 2015

Research article |

| 30 Oct 2015

Identification of spatial and temporal contributions of rainfalls to flash floods using neural network modelling: case study on the Lez basin (southern France)

T. Darras, V. Borrell Estupina, L. Kong-A-Siou, B. Vayssade, A. Johannet, and S. Pistre

Viewed

Total article views: 3,335 (including HTML, PDF, and XML)

HTML	PDF	XML	Total	BibTeX	EndNote
1,670	1,536	129	3,335	156	179

HTML: 1,670
PDF: 1,536
XML: 129
Total: 3,335
BibTeX: 156
EndNote: 179

Views and downloads (calculated since 08 Apr 2015)

Month	HTML	PDF	XML	Total
Apr 2015	60	56	3	119
May 2015	21	24	0	45
Jun 2015	8	7	1	16
Jul 2015	11	16	1	28
Aug 2015	3	8	0	11
Sep 2015	4	10	0	14
Oct 2015	41	32	1	74
Nov 2015	73	72	0	145
Dec 2015	9	28	0	37
Jan 2016	39	22	1	62
Feb 2016	22	12	3	37
Mar 2016	32	15	16	63
Apr 2016	9	11	1	21
May 2016	5	6	0	11
Jun 2016	4	7	0	11
Jul 2016	5	2	1	8
Aug 2016	9	4	1	14
Sep 2016	9	7	0	16
Oct 2016	9	7	2	18
Nov 2016	7	1	0	8
Dec 2016	2	2	0	4
Jan 2017	13	5	0	18
Feb 2017	9	5	1	15
Mar 2017	18	9	2	29
Apr 2017	25	14	1	40
May 2017	20	5	0	25
Jun 2017	29	8	2	39
Jul 2017	14	8	0	22
Aug 2017	7	5	0	12
Sep 2017	10	9	1	20
Oct 2017	1	4	0	5
Nov 2017	4	12	0	16
Dec 2017	11	13	0	24
Jan 2018	3	6	0	9
Feb 2018	10	8	0	18
Mar 2018	10	15	0	25
Apr 2018	8	9	0	17
May 2018	6	8	1	15
Jun 2018	4	9	0	13
Jul 2018	6	11	0	17
Aug 2018	6	8	0	14
Sep 2018	9	17	0	26
Oct 2018	6	16	0	22
Nov 2018	8	15	1	24
Dec 2018	4	15	0	19
Jan 2019	7	9	1	17
Feb 2019	4	10	0	14
Mar 2019	5	12	0	17
Apr 2019	9	4	0	13
May 2019	5	11	0	16
Jun 2019	9	18	0	27
Jul 2019	6	10	0	16
Aug 2019	4	7	0	11
Sep 2019	8	9	0	17
Oct 2019	7	5	2	14
Nov 2019	11	6	0	17
Dec 2019	3	20	1	24
Jan 2020	10	8	4	22
Feb 2020	7	5	0	12
Mar 2020	3	9	0	12
Apr 2020	4	12	1	17
May 2020	4	8	0	12
Jun 2020	15	9	0	24
Jul 2020	23	16	12	51
Aug 2020	9	9	5	23
Sep 2020	15	13	0	28
Oct 2020	9	7	0	16
Nov 2020	9	5	0	14
Dec 2020	10	14	0	24
Jan 2021	22	21	0	43
Feb 2021	11	5	0	16
Mar 2021	5	14	1	20
Apr 2021	8	16	3	27
May 2021	7	13	0	20
Jun 2021	12	15	0	27
Jul 2021	5	9	0	14
Aug 2021	10	13	0	23
Sep 2021	11	6	0	17
Oct 2021	6	29	0	35
Nov 2021	7	37	0	44
Dec 2021	17	13	0	30
Jan 2022	15	12	1	28
Feb 2022	11	15	1	27
Mar 2022	13	14	1	28
Apr 2022	7	4	2	13
May 2022	12	17	1	30
Jun 2022	3	7	1	11
Jul 2022	8	6	0	14
Aug 2022	15	12	0	27
Sep 2022	7	9	0	16
Oct 2022	7	12	0	19
Nov 2022	13	7	0	20
Dec 2022	11	13	1	25
Jan 2023	9	12	1	22
Feb 2023	9	5	1	15
Mar 2023	19	5	0	24
Apr 2023	7	5	1	13
May 2023	11	13	0	24
Jun 2023	7	6	0	13
Jul 2023	8	9	1	18
Aug 2023	10	6	1	17
Sep 2023	2	3	0	5
Oct 2023	8	4	0	12
Nov 2023	4	1	0	5
Dec 2023	7	2	1	10
Jan 2024	7	7	0	14
Feb 2024	4	3	0	7
Mar 2024	11	6	1	18
Apr 2024	7	8	1	16
May 2024	20	9	3	32
Jun 2024	15	6	3	24
Jul 2024	8	12	2	22
Aug 2024	26	6	0	32
Sep 2024	10	8	0	18
Oct 2024	17	6	0	23
Nov 2024	8	6	1	15
Dec 2024	7	4	1	12
Jan 2025	16	11	0	27
Feb 2025	23	6	1	30
Mar 2025	21	14	0	35
Apr 2025	25	13	1	39
May 2025	22	18	0	40
Jun 2025	47	12	0	59
Jul 2025	21	17	1	39
Aug 2025	15	16	1	32
Sep 2025	28	14	0	42
Oct 2025	25	25	2	52
Nov 2025	29	22	4	55
Dec 2025	30	22	3	55
Jan 2026	29	20	13	62
Feb 2026	18	17	1	36
Mar 2026	18	19	6	43

Cumulative views and downloads (calculated since 08 Apr 2015)

Month	HTML	PDF	XML	Total
Apr 2015	60	56	3	119
May 2015	21	24	0	45
Jun 2015	8	7	1	16
Jul 2015	11	16	1	28
Aug 2015	3	8	0	11
Sep 2015	4	10	0	14
Oct 2015	41	32	1	74
Nov 2015	73	72	0	145
Dec 2015	9	28	0	37
Jan 2016	39	22	1	62
Feb 2016	22	12	3	37
Mar 2016	32	15	16	63
Apr 2016	9	11	1	21
May 2016	5	6	0	11
Jun 2016	4	7	0	11
Jul 2016	5	2	1	8
Aug 2016	9	4	1	14
Sep 2016	9	7	0	16
Oct 2016	9	7	2	18
Nov 2016	7	1	0	8
Dec 2016	2	2	0	4
Jan 2017	13	5	0	18
Feb 2017	9	5	1	15
Mar 2017	18	9	2	29
Apr 2017	25	14	1	40
May 2017	20	5	0	25
Jun 2017	29	8	2	39
Jul 2017	14	8	0	22
Aug 2017	7	5	0	12
Sep 2017	10	9	1	20
Oct 2017	1	4	0	5
Nov 2017	4	12	0	16
Dec 2017	11	13	0	24
Jan 2018	3	6	0	9
Feb 2018	10	8	0	18
Mar 2018	10	15	0	25
Apr 2018	8	9	0	17
May 2018	6	8	1	15
Jun 2018	4	9	0	13
Jul 2018	6	11	0	17
Aug 2018	6	8	0	14
Sep 2018	9	17	0	26
Oct 2018	6	16	0	22
Nov 2018	8	15	1	24
Dec 2018	4	15	0	19
Jan 2019	7	9	1	17
Feb 2019	4	10	0	14
Mar 2019	5	12	0	17
Apr 2019	9	4	0	13
May 2019	5	11	0	16
Jun 2019	9	18	0	27
Jul 2019	6	10	0	16
Aug 2019	4	7	0	11
Sep 2019	8	9	0	17
Oct 2019	7	5	2	14
Nov 2019	11	6	0	17
Dec 2019	3	20	1	24
Jan 2020	10	8	4	22
Feb 2020	7	5	0	12
Mar 2020	3	9	0	12
Apr 2020	4	12	1	17
May 2020	4	8	0	12
Jun 2020	15	9	0	24
Jul 2020	23	16	12	51
Aug 2020	9	9	5	23
Sep 2020	15	13	0	28
Oct 2020	9	7	0	16
Nov 2020	9	5	0	14
Dec 2020	10	14	0	24
Jan 2021	22	21	0	43
Feb 2021	11	5	0	16
Mar 2021	5	14	1	20
Apr 2021	8	16	3	27
May 2021	7	13	0	20
Jun 2021	12	15	0	27
Jul 2021	5	9	0	14
Aug 2021	10	13	0	23
Sep 2021	11	6	0	17
Oct 2021	6	29	0	35
Nov 2021	7	37	0	44
Dec 2021	17	13	0	30
Jan 2022	15	12	1	28
Feb 2022	11	15	1	27
Mar 2022	13	14	1	28
Apr 2022	7	4	2	13
May 2022	12	17	1	30
Jun 2022	3	7	1	11
Jul 2022	8	6	0	14
Aug 2022	15	12	0	27
Sep 2022	7	9	0	16
Oct 2022	7	12	0	19
Nov 2022	13	7	0	20
Dec 2022	11	13	1	25
Jan 2023	9	12	1	22
Feb 2023	9	5	1	15
Mar 2023	19	5	0	24
Apr 2023	7	5	1	13
May 2023	11	13	0	24
Jun 2023	7	6	0	13
Jul 2023	8	9	1	18
Aug 2023	10	6	1	17
Sep 2023	2	3	0	5
Oct 2023	8	4	0	12
Nov 2023	4	1	0	5
Dec 2023	7	2	1	10
Jan 2024	7	7	0	14
Feb 2024	4	3	0	7
Mar 2024	11	6	1	18
Apr 2024	7	8	1	16
May 2024	20	9	3	32
Jun 2024	15	6	3	24
Jul 2024	8	12	2	22
Aug 2024	26	6	0	32
Sep 2024	10	8	0	18
Oct 2024	17	6	0	23
Nov 2024	8	6	1	15
Dec 2024	7	4	1	12
Jan 2025	16	11	0	27
Feb 2025	23	6	1	30
Mar 2025	21	14	0	35
Apr 2025	25	13	1	39
May 2025	22	18	0	40
Jun 2025	47	12	0	59
Jul 2025	21	17	1	39
Aug 2025	15	16	1	32
Sep 2025	28	14	0	42
Oct 2025	25	25	2	52
Nov 2025	29	22	4	55
Dec 2025	30	22	3	55
Jan 2026	29	20	13	62
Feb 2026	18	17	1	36
Mar 2026	18	19	6	43

Latest update: 24 Mar 2026

Short summary

Flash floods are important hazards in urbanised zone and constitute important human and financial stakes. This paper applies a novel methodology, KnoX, dedicated to extract knowledge from a neural network model. It was shown that KnoX method could help to better characterize processes of both surface and underground floods. A case study is chosen in France: the Lez karst hydrosystem whose river crosses the city of Montpellier (400 000 inhabitants). Results will help flood warning services.