What is the near-natural catchment? An application of hydrological signatures assessment
Many studies classify catchments with little human activity (HA) as near-natural catchments to increase the number of studied catchments. However, how much HA can be negligible is still unclear. In this study, catchments with little HA are classified as near-natural catchments when their hydrologica...
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| Language: | English |
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Elsevier
2025-02-01
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| Series: | Ecological Indicators |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1470160X25001384 |
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| author | Huan Xu Hao Wang Pan Liu Xiaojing Zhang Weibo Liu Chutian Zhou Hao Ye Hongxuan Lei Yang Liu |
| author_facet | Huan Xu Hao Wang Pan Liu Xiaojing Zhang Weibo Liu Chutian Zhou Hao Ye Hongxuan Lei Yang Liu |
| author_sort | Huan Xu |
| collection | DOAJ |
| description | Many studies classify catchments with little human activity (HA) as near-natural catchments to increase the number of studied catchments. However, how much HA can be negligible is still unclear. In this study, catchments with little HA are classified as near-natural catchments when their hydrological behavior is similar to that of natural catchments. To determine whether a catchment can be considered near-natural, we derive several key hydrological signatures that characterize catchment behavior among numerous hydrological signatures. This is done by condensing a large set of 222 into eight signatures that are computable, representative, robust, and predictable. The sensitivity of the eight signatures to HA are calculated using a causal inference method instead of directly calculating linear correlation coefficients to avoid spurious relationships. The product of sensitivity and HA represents the HA impact on the catchment. By limiting the impact to a small proportion of the average hydrological signature, the HA threshold is determined. Results in the global catchments show that HA thresholds are 0.8%, 1.2%, and 15.4% of the city area, cropland area, and reservoir regulation degree, respectively. Both hypothesis testing and visual inspection indicate that catchments with the determined thresholds exhibit hydrological behavior identical to that of natural catchments. Based on these thresholds, approximately 68% of the world’s land area, excluding Antarctica, is classified as near-natural catchments. This study established a method to identify the negligible degree of HA using causal relationships. It contributes to the understanding of the HA impact on hydrological systems. |
| format | Article |
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| institution | Kabale University |
| issn | 1470-160X |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Elsevier |
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| series | Ecological Indicators |
| spelling | doaj-art-d8d328455389490e96481d9150f9d9df2025-02-10T04:34:17ZengElsevierEcological Indicators1470-160X2025-02-01171113209What is the near-natural catchment? An application of hydrological signatures assessmentHuan Xu0Hao Wang1Pan Liu2Xiaojing Zhang3Weibo Liu4Chutian Zhou5Hao Ye6Hongxuan Lei7Yang Liu8State Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan 430072 China; Research Institute for Water Security (RIWS), Wuhan University, Wuhan 430072 China; Hubei Provincial Key Lab of Water System Science for Sponge City Construction, Wuhan University, Wuhan 430072 ChinaState Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan 430072 China; State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038 China; Corresponding authors at: State Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan 430072, China.State Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan 430072 China; Research Institute for Water Security (RIWS), Wuhan University, Wuhan 430072 China; Hubei Provincial Key Lab of Water System Science for Sponge City Construction, Wuhan University, Wuhan 430072 China; Corresponding authors at: State Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan 430072, China.State Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan 430072 China; Research Institute for Water Security (RIWS), Wuhan University, Wuhan 430072 China; Hubei Provincial Key Lab of Water System Science for Sponge City Construction, Wuhan University, Wuhan 430072 ChinaState Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan 430072 China; Research Institute for Water Security (RIWS), Wuhan University, Wuhan 430072 China; Hubei Provincial Key Lab of Water System Science for Sponge City Construction, Wuhan University, Wuhan 430072 ChinaState Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan 430072 China; Research Institute for Water Security (RIWS), Wuhan University, Wuhan 430072 China; Hubei Provincial Key Lab of Water System Science for Sponge City Construction, Wuhan University, Wuhan 430072 ChinaState Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan 430072 China; Research Institute for Water Security (RIWS), Wuhan University, Wuhan 430072 China; Hubei Provincial Key Lab of Water System Science for Sponge City Construction, Wuhan University, Wuhan 430072 ChinaState Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan 430072 China; Research Institute for Water Security (RIWS), Wuhan University, Wuhan 430072 China; Hubei Provincial Key Lab of Water System Science for Sponge City Construction, Wuhan University, Wuhan 430072 ChinaState Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan 430072 China; Research Institute for Water Security (RIWS), Wuhan University, Wuhan 430072 China; Hubei Provincial Key Lab of Water System Science for Sponge City Construction, Wuhan University, Wuhan 430072 ChinaMany studies classify catchments with little human activity (HA) as near-natural catchments to increase the number of studied catchments. However, how much HA can be negligible is still unclear. In this study, catchments with little HA are classified as near-natural catchments when their hydrological behavior is similar to that of natural catchments. To determine whether a catchment can be considered near-natural, we derive several key hydrological signatures that characterize catchment behavior among numerous hydrological signatures. This is done by condensing a large set of 222 into eight signatures that are computable, representative, robust, and predictable. The sensitivity of the eight signatures to HA are calculated using a causal inference method instead of directly calculating linear correlation coefficients to avoid spurious relationships. The product of sensitivity and HA represents the HA impact on the catchment. By limiting the impact to a small proportion of the average hydrological signature, the HA threshold is determined. Results in the global catchments show that HA thresholds are 0.8%, 1.2%, and 15.4% of the city area, cropland area, and reservoir regulation degree, respectively. Both hypothesis testing and visual inspection indicate that catchments with the determined thresholds exhibit hydrological behavior identical to that of natural catchments. Based on these thresholds, approximately 68% of the world’s land area, excluding Antarctica, is classified as near-natural catchments. This study established a method to identify the negligible degree of HA using causal relationships. It contributes to the understanding of the HA impact on hydrological systems.http://www.sciencedirect.com/science/article/pii/S1470160X25001384Natural watershedHydrologic signatureHuman activityDouble/debiased machine learningLarge-sample hydrology |
| spellingShingle | Huan Xu Hao Wang Pan Liu Xiaojing Zhang Weibo Liu Chutian Zhou Hao Ye Hongxuan Lei Yang Liu What is the near-natural catchment? An application of hydrological signatures assessment Ecological Indicators Natural watershed Hydrologic signature Human activity Double/debiased machine learning Large-sample hydrology |
| title | What is the near-natural catchment? An application of hydrological signatures assessment |
| title_full | What is the near-natural catchment? An application of hydrological signatures assessment |
| title_fullStr | What is the near-natural catchment? An application of hydrological signatures assessment |
| title_full_unstemmed | What is the near-natural catchment? An application of hydrological signatures assessment |
| title_short | What is the near-natural catchment? An application of hydrological signatures assessment |
| title_sort | what is the near natural catchment an application of hydrological signatures assessment |
| topic | Natural watershed Hydrologic signature Human activity Double/debiased machine learning Large-sample hydrology |
| url | http://www.sciencedirect.com/science/article/pii/S1470160X25001384 |
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