Nitrogen Inversion Model in a Wetland Environment Based on the Canopy Reflectance of Emergent Plants

Author:

Wu Dongli1ORCID,Zhao Dongliang2,Zhu Yongchao1,Shen Chao1,Xue Hongxi3ORCID

Affiliation:

1. Meteorological Observation Center of China Meteorological Administration, Beijing 100081, China

2. College of Resources Environment and Tourism, Capital Normal University, Beijing 100048, China

3. National Meteorological Center, Beijing 100081, China

Abstract

Reuse of reclaimed water in constructed wetlands is a promising way to conserve water resources and improve water quality, and it is playing a very important role in wetland restoration and reconstruction. This study utilized reflectance spectra of wetland vegetation to estimate nitrogen content in water in the Beijing Bai River constructed wetland, a typically constructed wetland that uses reclaimed water. Canopy reflectance spectra of two dominant plants in the wetland, including reed and cattail, were acquired using a spectrometer (350–2500 nm). Simultaneously, water samples were collected to measure water quality. To establish the appreciate relationship between total nitrogen content (TN) and reflectance spectra, both simple and multiple regression models, including simple ration spectral index (SR), normalized difference spectral index (ND), stepwise multiple linear regression (SMLR) model, and partial least squares regression (PLSR), were adopted in this study. The results showed that (1) compared with simple regression models (SR and ND), multiple regressions models (SMLR and PLSR) could provide a more accurate estimation of TN concentration in the wetland environment. Among these models, the PLSR model had the highest accuracy and was proven to be the most useful tool to reveal the relationship between the spectral reflectance of wetland plants and the total nitrogen consistency of wetland at the canopy scale. (2) The inversion effect of TN concentration in water is slightly better than that of wetland vegetation, and the reflection spectrum of the reed can predict TN concentration more accurately than that of cattail. The finding not only provides solid evidence for the potential application of remote sensing to detect water eutrophication but also enhances our understanding of the monitoring and management of water quality in urban wetlands using recycled water.

Funder

Scientific and Technological Breakthroughs in Henan Province

Publisher

Hindawi Limited

Subject

Atmospheric Science,Pollution,Geophysics

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