Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1029/2020WR029310 |
Integrating remote sensing and numerical modeling to quantify the water balance of climate-induced intermittent wetlands | |
Shengyang Chen; Fiona Johnson; William Glamore | |
2021-09-22 | |
发表期刊 | Water Resources Research
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出版年 | 2021 |
英文摘要 | Wetlands are an important habitat for many species but over the past few decades ecosystem biodiversity and function have been threatened. Due to their shallow and fluctuating water levels, wetlands are particularly vulnerable to climate variability. This is especially a risk for ephemeral and intermittent wetlands with limited hydrologic connections to deep aquifers, designated herein as Climate-induced Intermittent Wetlands (CiIWs). However, the response of CiIW systems to long-term climate variability has received limited research attention, partly because continuous ground surface monitoring data is rarely available over inter-decadal periods. An alternative to ground surface data is the use of satellite imagery to estimate the temporal water extent variability. An integrated remote sensing and modeling approach is presented here to provide a novel method for investigating historical water storage variations in a CiIW system. The new method estimates water levels in a shallow wetland using Landsat data and was successfully validated against field water level data. The new method performed better than five existing algorithms. A water balance model was calibrated using the combined remotely sensed and local field data to derive daily water level time series since 1900. The validated water balance model results indicated that most of the water level fluctuations in the intermittent wetland can be explained by climatic drivers and subsurface flow interactions. Overall, this study demonstrates the importance of an integrated remote sensing and water balance modeling approach for hydroclimatic analysis of intermittent wetlands. This article is protected by copyright. All rights reserved. |
领域 | 资源环境 |
URL | 查看原文 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/338761 |
专题 | 资源环境科学 |
推荐引用方式 GB/T 7714 | Shengyang Chen,Fiona Johnson,William Glamore. Integrating remote sensing and numerical modeling to quantify the water balance of climate-induced intermittent wetlands[J]. Water Resources Research,2021. |
APA | Shengyang Chen,Fiona Johnson,&William Glamore.(2021).Integrating remote sensing and numerical modeling to quantify the water balance of climate-induced intermittent wetlands.Water Resources Research. |
MLA | Shengyang Chen,et al."Integrating remote sensing and numerical modeling to quantify the water balance of climate-induced intermittent wetlands".Water Resources Research (2021). |
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