Citation:

PANGAEA.808328

Name: Thickness and frequency of erosive events observed in Lake Anterne
Published: 2011
License: https://creativecommons.org/licenses/by/3.0/

Always quote citation above when using data! You can download the citation in several formats below.

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Related to:

Giguet-Covex, Charline; Arnaud, Fabien; Enters, Dirk; Poulenard, Jérôme; Millet, Laurent; Francus, Pierre; David, Fernand; Rey, Pierre-Jérôme; Wilhelm, Bruno; Delannoy, Jean-Jacques (2012): Frequency and intensity of high-altitude floods over the last 3.5ka in northwestern French Alps (Lake Anterne). Quaternary Research, 77(1), 12-22, https://doi.org/10.1016/j.yqres.2011.11.003

Coverage:

Latitude: 46.000000 * Longitude: 6.800000

Minimum Elevation: 2063.0 m * Maximum Elevation: 2063.0 m

Event(s):

Lake_Anterne * Latitude: 46.000000 * Longitude: 6.800000 * Elevation: 2063.0 m * Location: Lac d Anterne, Haute-Savoie, Northern Alps, France

Parameter(s):

#	Name	Short Name	Unit	Principal Investigator	Comment
1	AGE	Age	ka BP		Geocode
2	Thickness	Thick	mm	Giguet-Covex, Charline	of erosive event deposits
3	Occurrence	Occur	#	Giguet-Covex, Charline	of erosive event deposits
4	Frequency	Frequency	#	Giguet-Covex, Charline	of erosive events: 100 years
5	Frequency	Frequency	#	Giguet-Covex, Charline	of erosive events: 10 years

Change history:

2021-03-29T06:37:49 – This data publication is a stand-alone publication and has been deleted from the "Supplement to" doi:10.1594/PANGAEA.842828

License:

Creative Commons Attribution 3.0 Unported (CC-BY-3.0)

Size:

41067 data points

Data

Download dataset as tab-delimited text — use the following character encoding:

1 Age [ka BP]	2 Thick [mm] (of erosive event deposits)	3 Occur [#] (of erosive event deposits)	4 Frequency [#] (of erosive events: 100 years)	5 Frequency [#] (of erosive events: 10 years)
-0.057	26	1
-0.056	0	0
-0.055	0	0
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1.159	20	1	2	1
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1.761	0	0	14	0
1.762	0	0	14	0
1.763	0	0	14	1
1.764	0	0	15	2
1.765	0	0	15	2
1.766	0	0	15	2
1.767	0	0	14	2
1.769	5	1	14	2
1.769	9	1	15	3
1.770	0	0	15	3
1.771	0	0	14	3
1.772	0	0	15	3
1.773	0	0	15	2
1.774	7	1	15	1
1.775	0	0	16	1
1.776	0	0	16	1
1.777	0	0	16	2
1.778	0	0	16	3
1.779	0	0	16	2
1.780	0	0	16	2
1.781	0	0	16	2
1.782	6	1	16	2
1.783	7	1	16	2
1.784	0	0	17	2
1.785	0	0	17	2
1.786	0	0	17	3
1.787	0	0	17	2
1.788	0	0	17	1
1.789	0	0	17	1
1.790	0	0	17	2
1.792	12	1	18	3
1.792	0	0	18	3
1.793	0	0	19	3
1.794	0	0	19	3
1.796	44	1	19	4
1.797	5	1	19	3
1.797	0	0	19	3
1.798	0	0	20	3
1.799	0	0	20	3
1.800	10	1	19	2
1.801	0	0	19	1
1.802	0	0	19	1
1.803	0	0	19	2
1.804	0	0	19	2
1.805	0	0	20	1
1.806	0	0	20	1
1.807	0	0	20	2
1.808	5	1	20	2
1.809	0	0	20	2
1.810	0	0	20	2
1.811	0	0	20	2
1.813	9	1	20	3
1.813	0	0	21	2
1.814	0	0	21	2
1.815	0	0	21	3
1.816	0	0	21	3
1.817	10	1	21	2
1.818	0	0	20	3
1.819	0	0	19	3
1.820	17	1	19	3
1.820	0	0	19	3
1.821	0	0	20	2
1.823	5	1	21	2
1.823	0	0	20	2
1.824	0	0	20	1
1.825	0	0	20	1
1.826	0	0	20	2
1.827	0	0	21	1
1.828	0	0	21	2
1.829	0	0	21	2
1.830	0	0	21	2
1.831	5	1	20	2
1.832	0	0	19	2
1.834	8	1	19	3
1.834	0	0	20	3
1.835	0	0	21	4
1.836	0	0	21	3
1.837	0	0	21	3
1.838	13	1	22	2
1.839	0	0	23	2
1.840	11	1	22	3
1.841	0	0	22	3
1.842	0	0	22	3
1.843	0	0	22	2
1.844	0	0	21	2
1.845	6	1	20	1
1.846	0	0	20	1
1.847	0	0	20	2
1.848	0	0	20	2
1.849	0	0	20	2
1.850	0	0	20	1
1.851	0	0	20	1
1.853	152	1	20	1
1.853	0	0	20	1
1.854	0	0	20	1
1.855	0	0	20	2
1.856	0	0	20	2
1.857	0	0	19	1
1.858	0	0	20	1
1.859	0	0	20	1
1.861	5	1	21	1
1.861	0	0	20	1
1.862	0	0	21	1
1.863	0	0	22	1
1.864	0	0	22	2
1.865	0	0	23	2
1.866	0	0	22	2
1.867	0	0	22	2
1.868	0	0	22	2
1.870	11	1	21	2
1.870	22	1	21	3
1.871	0	0	21	3
1.872	0	0	20	3
1.873	0	0	20	3
1.874	0	0	20	2
1.875	7	1	20	1
1.876	0	0	21	1
1.877	0	0	22	2
1.878	0	0	23	3
1.879	0	0	24	3
1.880	0	0	24	2
1.881	0	0	23	3
1.883	7	1	23	4
1.883	20	1	22	4
1.884	0	0	22	4
1.885	0	0	22	4
1.886	5	1	22	4
1.886	13	1	22	3
1.888	0	0	21	2
1.889	0	0	21	2
1.890	0	0	20	2
1.891	0	0	20	1
1.892	0	0	20	1
1.893	0	0	20	1
1.894	0	0	20	1
1.895	0	0	20	1
1.896	0	0	20	1
1.897	7	1	20	1
1.898	0	0	20	1
1.899	0	0	20	1
1.900	0	0	20	1
1.901	0	0	20	2
1.902	0	0	19	1
1.903	0	0	19	2
1.904	0	0	19	2
1.905	0	0	19	3
1.907	31	1	19	4
1.907	0	0	19	4
1.909	9	1	19	5
1.909	0	0	20	5
1.910	5	1	19	5
1.912	7	1	19	4
1.912	0	0	19	4
1.913	37	1	19	3
1.914	0	0	19	3
1.915	0	0	19	2
1.916	0	0	20	1
1.917	0	0	20	1
1.918	0	0	20	0
1.919	0	0	19	1
1.920	0	0	18	2
1.921	0	0	18	3
1.922	0	0	18	4
1.923	0	0	18	4
1.925	6	1	18	4
1.926	10	1	17	4
1.926	8	1	17	4
1.926	8	1	17	4
1.928	0	0	17	4
1.929	0	0	17	3
1.930	0	0	17	2
1.931	0	0	17	1
1.932	0	0	16	0
1.933	0	0	15	0
1.934	0	0	15	0
1.935	0	0	15	0
1.936	0	0	15	0
1.937	0	0	14	0
1.938	0	0	14	1
1.939	0	0	14	1
1.940	0	0	14	1

Only the first 2000 rows were shown. To view the complete dataset, download it as tab-delimited text. You can still view the full matrix in your browser, but be aware that this may crash the browser due to the huge size.