Net primary productivity response to precipitation varied with different ecosystems in the Tibetan Plateau over the past two millennia DOI
Anning Cui, Houyuan Lü, Juzhi Hou

и другие.

Palaeogeography Palaeoclimatology Palaeoecology, Год журнала: 2024, Номер 649, С. 112343 - 112343

Опубликована: Июнь 21, 2024

Язык: Английский

Reconstructing aeolian activities and borders shifts of the Gonghe Sandy Lands since the last Glacial Maximum DOI
Yunkun Shi, E Chongyi,

Chunxia Xu

и другие.

Geomorphology, Год журнала: 2025, Номер unknown, С. 109706 - 109706

Опубликована: Март 1, 2025

Язык: Английский

Процитировано

2

Precipitation seasonality in controlling the north‒south dipolar pattern of effective moisture variations on the eastern margin of the Tibetan Plateau during the Holocene DOI Creative Commons
Duo Wu,

Qili Xiao,

Shilong Guo

и другие.

Quaternary Science Reviews, Год журнала: 2024, Номер 345, С. 109030 - 109030

Опубликована: Окт. 30, 2024

Язык: Английский

Процитировано

7

Last 15 ka record of water column changes associated with Indian summer monsoon variability from the northeastern Bay of Bengal DOI

N.M. Gayathri,

E. Sreevidya, A.V. Sijinkumar

и другие.

Quaternary International, Год журнала: 2025, Номер 723, С. 109713 - 109713

Опубликована: Фев. 28, 2025

Язык: Английский

Процитировано

0

Changes in the prehistoric human living environment on the Tibetan Plateau and their societal impacts: Research progress and perspectives DOI

Qili Xiao,

Duo Wu, Tao Wang

и другие.

Science China Earth Sciences, Год журнала: 2025, Номер unknown

Опубликована: Апрель 17, 2025

Язык: Английский

Процитировано

0

Late Holocene human population change revealed by fecal stanol records and its response to environmental evolution at Xiada Co on the western Tibetan Plateau DOI
Xiumei Li, Sutao Liu, Kejia Ji

и другие.

Palaeogeography Palaeoclimatology Palaeoecology, Год журнала: 2023, Номер 636, С. 111993 - 111993

Опубликована: Дек. 20, 2023

Язык: Английский

Процитировано

7

Modern pollen thresholds for tree presence on the eastern Tibetan Plateau and their potential application DOI
Chaoqun Cao, Nannan Wang, Wenjia Li

и другие.

Palaeogeography Palaeoclimatology Palaeoecology, Год журнала: 2024, Номер 639, С. 112066 - 112066

Опубликована: Фев. 3, 2024

Язык: Английский

Процитировано

2

Late Miocene palynological records of vegetation and climate changes in the Otindag Dune field DOI
Jiale Wang, Yali Zhou, Jiangli Pang

и другие.

Palaeogeography Palaeoclimatology Palaeoecology, Год журнала: 2024, Номер 643, С. 112198 - 112198

Опубликована: Апрель 15, 2024

Язык: Английский

Процитировано

2

SedaDNA reveals mid-to late Holocene aquatic plant and algae changes in Luanhaizi Lake on the Tibetan Plateau DOI
Hanqiu Xu,

Lian‐Fang Feng,

Naimeng Zhang

и другие.

Palaeogeography Palaeoclimatology Palaeoecology, Год журнала: 2024, Номер 650, С. 112344 - 112344

Опубликована: Июнь 22, 2024

Язык: Английский

Процитировано

2

Holocene rangeland characteristics on the northeastern Tibetan Plateau in relation to climate and pastoralism from sedimentary ancient DNA DOI Creative Commons
Ying Liu, Kathleen R. Stoof‐Leichsenring, Bernhard Diekmann

и другие.

Quaternary Science Reviews, Год журнала: 2024, Номер 339, С. 108850 - 108850

Опубликована: Июль 24, 2024

Язык: Английский

Процитировано

2

Deep learning-based GLOF modelling for hazard assessment and risk management DOI
Rana Muhammad Ali Washakh, Xiaoduo Pan,

Sundas Almas

и другие.

Georisk Assessment and Management of Risk for Engineered Systems and Geohazards, Год журнала: 2024, Номер unknown, С. 1 - 18

Опубликована: Июль 30, 2024

Glacial Lake Outburst Flood (GLOF) has become a crucial aspect as the increase in meltdown of glaciers results breach unstable debris dams. Hence, it is essential to understand nature glacial lakes for proper planning and development region long term. In this paper, deep learning network developed GLOF hazard risk assessment. The Shepard Convolutional Neural Network Fused Deep Maxout (ShCNNFDMN) by fusing Networks (ShCNN) (DMN) based on regression analysis. Here, various data feature attributes, like geometric properties, location lake-based global properties are determined from lake data. Afterthat, assessment carried out these parameters ShCNNFDMN. Then, performed levels attributes. ShCNNFDMN analyzed metrics, such Hazard modelling error, Risk prediction Mean Average Error (MAE), R-Squared found produce values 0.462, 0.423, 0.358, 0.288, respectively. proposed method useful applications, infrastructure planning, taking preventive mitigative actions downstream areas glacier lakes.

Язык: Английский

Процитировано

2