AUTHOR=Kang Hui , Dou Wenzhang , Chen Li , Han Lingyi , Sui Xinxin , Ding Ziyue 

TITLE=A surface water resource asset accounting method based on multi-source remote sensing data

JOURNAL=Frontiers in Environmental Science

VOLUME=12

YEAR=2024

URL=https://www.frontiersin.org/journals/environmental-science/articles/10.3389/fenvs.2024.1473419

DOI=10.3389/fenvs.2024.1473419

ISSN=2296-665X

ABSTRACT=<p>Water resource asset (WRA) accounting holds great importance in ecological civilization construction. Existing WRA accounting methods heavily rely on statistical data, resulting in issues such as missing and inaccessible data. Moreover, they only consider the value brought by the physical resources, such as water quantity and quality, while neglecting the value brought by the ecological functions. Therefore, by fully exploiting the rapid, objective, and efficient advantages of remote sensing (RS) in monitoring surface objects, this article develops a surface WRA (SWRA) accounting method based on multi-source RS data. First, a representation model is innovatively proposed, with full consideration of the ecological service functions offered by water resources. Specifically, the SWRAs are represented by two parts: tangible and intangible assets. The tangible asset refers to the quantifiable stock of water resources. Surface water volume is adopted as the indicator for tangible assets in this article. The intangible asset, which primarily embodies the ecological service functions provided by water resources, encompasses five major categories: flood regulation, carbon fixation, oxygen release, water purification, and water conservation. Furthermore, due to different units, the total amounts cannot be summed or compared directly. Therefore, this article utilizes price tools to convert SWRAs into price value, ultimately achieving SWRA accounting. The established method was tested in Miyun, Beijing, China, from 2013 to 2023. The findings demonstrate that the SWRA value reached its peak in 2023, amounting to <inline-formula id="inf1"><mml:math id="m1" xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mn>56,9368.6</mml:mn><mml:mo>×</mml:mo><mml:mn>1</mml:mn><mml:msup><mml:mrow><mml:mn>0</mml:mn></mml:mrow><mml:mrow><mml:mn>4</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> yuan, while it had its lowest point in 2014, standing at <inline-formula id="inf2"><mml:math id="m2" xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mn>14,7402.7</mml:mn><mml:mo>×</mml:mo><mml:mn>1</mml:mn><mml:msup><mml:mrow><mml:mn>0</mml:mn></mml:mrow><mml:mrow><mml:mn>4</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> yuan. The experimental results indicate that the proposed method can quickly provide the SWRA values for many years, offering a methodological foundation for SWRA asset auditing and enhancing the timeliness of the auditing work.</p>