Identification of the large-area and long-duration drought and its evolutionary characteristics in Nenjiang River basin

环境科学 气候变化 构造盆地 流域 水资源 自然灾害 持续时间(音乐) 自然地理学 气候学 水文学(农业) 地理 生态学 地质学 气象学 生物 艺术 古生物学 地图学 文学类 岩土工程
作者
Shanjun Zhang,Jia Liu,Chuanzhe Li,Fuliang Yu,Lanshu Jing,Yizhi Wang
出处
期刊:Journal of Hydrology [Elsevier]
卷期号:626: 130218-130218 被引量:3
标识
DOI:10.1016/j.jhydrol.2023.130218
摘要

The effects of droughts on food, economic, and social security have long been a worldwide significant issue. Recently droughts have showed a development trendency with a longer duration and a wider impact area due to the climate change and the human activities. In this study, the Gravity Recovery and Climate Experiment (GRACE) satellite data were used to develop the water storage deficit index, based on which the large-area and long-duration drought (LLD) were identified using the theory of runs and the copula functions. In the Nenjiang River basin, two drought events with a joint distribution frequency of greater than 75 % were identified as LLD events, with a drought area of 29.7 × 104 km2 and a drought duration of 27 and 33 months respectively. In terms of drought characteristic indicators, the average values of drought intensity, drought severity, and extreme intensity for LLD events were 1.04, 31.71, and 2.30, which is significantly higher than for other types of drought events. The LLD events take a longer time to develop to the peak intensity than other types of drought events, but their drought centroid migration is more widespread. This suggests that the propagation process of the LLD events is more complex and the spatial and temporal distribution of drought is more uneven. Thus, we recommended that appropriate actions and regulations be adopted for different regions in different periods to reallocate water resources according to the drought-related losses and management expenses. This study introduces an identification method of the LLD events, combined with the analyses of evolutionary charaterisitics in space and time. It is hoped that the outcomes of the study can help watershed managers to clearly and conveniently identify the LLD events based on the predicted drought duration and area.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
lewis17发布了新的文献求助10
刚刚
卢秋宇发布了新的文献求助10
刚刚
1秒前
1秒前
小豆发布了新的文献求助10
1秒前
所所应助伯赏夜南采纳,获得10
1秒前
2秒前
Orange应助冷酷的尔琴采纳,获得10
2秒前
英姑应助从容问雁采纳,获得10
2秒前
2秒前
暖秋发布了新的文献求助10
3秒前
3秒前
3秒前
3秒前
原野小年完成签到,获得积分10
4秒前
稳重蜗牛完成签到,获得积分10
4秒前
帅气书白完成签到,获得积分10
5秒前
edtaa发布了新的文献求助10
5秒前
DamonChen发布了新的文献求助10
5秒前
无心的砖家完成签到,获得积分10
5秒前
落后十八发布了新的文献求助20
5秒前
sheep完成签到,获得积分10
5秒前
SciGPT应助雨雨雨采纳,获得10
6秒前
直率诗柳完成签到,获得积分10
6秒前
刚国忠完成签到,获得积分20
6秒前
屈昭阳完成签到,获得积分20
6秒前
Lawenced发布了新的文献求助10
7秒前
何文发布了新的文献求助10
8秒前
尤寄风发布了新的文献求助10
8秒前
悬夜发布了新的文献求助10
9秒前
量子星尘发布了新的文献求助10
10秒前
11秒前
11秒前
Sunny完成签到 ,获得积分10
11秒前
12秒前
每天一篇文献的小王完成签到 ,获得积分10
12秒前
一十六完成签到,获得积分10
12秒前
aikeyan完成签到,获得积分10
12秒前
我是老大应助L山间葱采纳,获得10
13秒前
13秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Basic And Clinical Science Course 2025-2026 3000
Encyclopedia of Agriculture and Food Systems Third Edition 2000
人脑智能与人工智能 1000
花の香りの秘密―遺伝子情報から機能性まで 800
Principles of Plasma Discharges and Materials Processing, 3rd Edition 400
Pharmacology for Chemists: Drug Discovery in Context 400
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5608504
求助须知:如何正确求助?哪些是违规求助? 4693127
关于积分的说明 14876947
捐赠科研通 4717761
什么是DOI,文献DOI怎么找? 2544250
邀请新用户注册赠送积分活动 1509316
关于科研通互助平台的介绍 1472836