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Article ; Online: Assessment of agricultural drought based on multi-source remote sensing data in a major grain producing area of Northwest China

Cai, Siyang / Zuo, Depeng / Wang, Huixiao / Xu, Zongxue / Wang, Guoqing / Yang, Hong

Agricultural Water Management. 2023 Mar., v. 278 p.108142-

2023

Abstract: Drought is considered to be one of the most serious natural disasters in China, which can result in enormous damage to nature and socio-economy. Compared to traditional ground-based monitoring techniques, remote sensing can effectively compensate for ... ...

Abstract	Drought is considered to be one of the most serious natural disasters in China, which can result in enormous damage to nature and socio-economy. Compared to traditional ground-based monitoring techniques, remote sensing can effectively compensate for spatial discontinuities at ground stations. The use of remote sensing technology for drought monitoring has irreplaceable advantages. The applicability of the TRMM3B43 dataset for precipitation was firstly verified in the Wei River basin, and the spatiotemporal characteristics of precipitation were analyzed. Based on the TRMM3B43, MODIS NDVI, and MODIS LST datasets, the spatiotemporal variations of drought were secondly investigated by calculating the Precipitation Condition Index (PCI), Vegetation Condition Index (VCI), and Temporal Condition Index (TCI). Crop yield was employed as the reference of drought impact for evaluating the applicability of the Scaled Drought Condition Index (SDCI) based on the combination of the PCI, VCI, and VCI by four kinds of weight determination methods, i.e. Analytic Hierarchy Process (AHP), Entropy method, Criteria Importance Through Intercriteria Correlation (CRITIC), and Fuzzy Comprehensive Evaluation (FCE). Finally, the agricultural drought calculated by the SDCI was evaluated against drought area, disaster area, and crop failure area to verify the applicability of the SDCI for agricultural drought disaster assessment in the Wei River basin. The results showed that the SDCI determined by FCE has better correlations with crop yield (R² =0.45) than the other methods. The SDCI values exhibited a "W" shape from 2003 to 2010 during the growing seasons and agricultural drought showed an increasing trend after 2013. The drought-prone areas shifted from north to south, with the degree of drought firstly decreasing and then increasing. In addition, the SDCI has better correlations with the disaster area (R² =0.35) than the drought area (R² = 0.16). At the municipal level, the SDCI could well assess agricultural drought. The results demonstrated that the SDCI can effectively monitor and assess drought impacts on agriculture and may provide helpful information for agricultural drought disaster prevention.
Keywords	crop failure ; crop yield ; data collection ; disaster preparedness ; drought ; entropy ; vegetation ; water management ; watersheds ; China ; Agricultural drought ; Scaled Drought Condition Index ; Multi-drought indices ; Drought disaster
Language	English
Dates of publication	2023-03
Publishing place	Elsevier B.V.
Document type	Article ; Online
Note	Use and reproduction
ZDB-ID	751144-9
ISSN	1873-2283 ; 0378-3774
ISSN (online)	1873-2283
ISSN	0378-3774
DOI	10.1016/j.agwat.2023.108142
Database	NAL-Catalogue (AGRICOLA)

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Article: Response of macroinvertebrate community to water quality factors and aquatic ecosystem health assessment in a typical river in Beijing, China

Hu, Xiaohong / Zuo, Depeng / Xu, Zongxue / Huang, Zhenfang / Liu, Bo / Han, Yuna / Bi, Yiqing

Environmental research. 2022 Sept., v. 212

2022

Abstract: Healthy aquatic ecosystems can offer basic ecological services for the sustainable development of humans and society. Water quality greatly influences the macroinvertebrate community in aquatic ecosystems and can alter the aquatic ecosystem's health ... ...

Abstract	Healthy aquatic ecosystems can offer basic ecological services for the sustainable development of humans and society. Water quality greatly influences the macroinvertebrate community in aquatic ecosystems and can alter the aquatic ecosystem's health status. However, the quantitative relationship between macroinvertebrate community and water quality factors in rivers remains unclear, particularly in urban rivers, which are strongly affected by human activities. Therefore, a new framework for the quantitative analysis between macroinvertebrate community and key water quality driving factors was developed in the study, meanwhile, the aquatic ecosystem health conditions were evaluated and validated by different methods. The framework was applied to a typical urban river, the North Canal River, which is regarded as the “mother river” of Beijing. Combined with the redundancy analysis (RDA) and the threshold indicator taxa analysis (TITAN), the water quality driving factors and their indicator species were identified and the corresponding response threshold was determined. Based on the benthic index of biotic integrity (B-IBI), the multi-metric rapid bioassessment method, and the biological monitoring working party (BMWP) score, the aquatic ecosystem health condition in the basin was comprehensively evaluated. The results show that fluoride, biochemical oxygen demand, ammonia-nitrogen and total phosphorus were the key water quality driving factors influencing the community structure of macroinvertebrates. Four indicator species of ammonia-nitrogen were identified by the TITAN method with a threshold range of 1.09–6.94 mg L⁻¹, and three indicator species of total phosphorus were identified with a threshold range of 0.48–1.27 mg L⁻¹. According to the results of the aquatic ecosystem health assessment, the river ecosystem was generally unhealthy and the upstream was better than downstream; the health condition in the mountainous areas of Changping district was the best, while that in Chaoyang district and the central city area was the worst. The framework could provide a strong basis for ecological restoration and pollution control of the urban rivers and become an important tool for the rehabilitation of aquatic ecosystems.
Keywords	ammonium nitrogen ; aquatic ecosystems ; basins ; biochemical oxygen demand ; biological assessment ; community structure ; ecological restoration ; environmental health ; fluorides ; health effects assessments ; health status ; humans ; indicator species ; macroinvertebrates ; mountains ; pollution control ; quantitative analysis ; research ; rivers ; sustainable development ; total phosphorus ; water quality ; China
Language	English
Dates of publication	2022-09
Publishing place	Elsevier Inc.
Document type	Article
ZDB-ID	205699-9
ISSN	1096-0953 ; 0013-9351
ISSN (online)	1096-0953
ISSN	0013-9351
DOI	10.1016/j.envres.2022.113474
Database	NAL-Catalogue (AGRICOLA)

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Article: Hydro-Meteorological Trends in the Yarlung Zangbo River Basin and Possible Associations with Large-Scale Circulation

Zhang, Rui / Xu, Zongxue / Zuo, Depeng / Ban, Chunguang

Water. 2020 Jan. 02, v. 12, no. 1

2020

Abstract: Climate change poses potential challenges to sensitive areas, such as high-elevation regions. The Yarlung Zangbo River (YLZR) basin is located in the southeast of the Qinghai-Tibetan Plateau. It contains large amounts of snow and numerous glaciers that ... ...

Abstract	Climate change poses potential challenges to sensitive areas, such as high-elevation regions. The Yarlung Zangbo River (YLZR) basin is located in the southeast of the Qinghai-Tibetan Plateau. It contains large amounts of snow and numerous glaciers that are vulnerable to climate change. Based on daily observational data at 17 meteorological stations in and around the YLZR basin during 1957–2015, the variability of precipitation, air temperature, and streamflow were analyzed. The nonparametric Mann–Kendall test, Sen’s slope estimate method, cross wavelet transform (XWT), and wavelet coherence (WTC) were used to identify the annual seasonal trends. the abrupt changes of precipitation and air temperature, and their associations with large-scale circulation. The results showed that the YLZR basin experienced an overall rapid warming and wetting during the study period, with an average warming rate of 0.33 °C/10 a and wetting rate of 4.25 mm/10a, respectively. Abrupt change points in precipitation and air temperature occurred around the 1970s and 1990s, respectively. The abrupt change points of three hydrological stations occurred around the late 1960s and the late 1990s, respectively. The precipitation, annual average temperature, and the streamflow of the three hydrological stations were negatively correlated with the Pacific decadal oscillation (PDO) and the multivariate El Niño-Southern Oscillation (ENSO) index (MEI), reaching a significant level of 0.05.
Keywords	air temperature ; atmospheric circulation ; basins ; climate change ; glaciers ; hydrometeorology ; river flow ; seasonal variation ; snow ; stream flow ; watershed hydrology ; watersheds ; China
Language	English
Dates of publication	2020-0102
Publishing place	Multidisciplinary Digital Publishing Institute
Document type	Article
Note	golden set
ZDB-ID	2521238-2
ISSN	2073-4441
ISSN	2073-4441
DOI	10.3390/w12010144
Database	NAL-Catalogue (AGRICOLA)

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Article: [Quantitative Analysis of the Correlation Between Macrobenthos Community and Water Environmental Factors and Aquatic Ecosystem Health Assessment in the North Canal River Basin of Beijing].

Hu, Xiao-Hong / Zuo, De-Peng / Liu, Bo / Huang, Zhen-Fang / Xu, Zong-Xue

Huan jing ke xue= Huanjing kexue

2022 Volume 43, Issue 1, Page(s) 247–255

Abstract: Macrobenthos can reflect the cumulative effect of various ecological threats on the water environment and are closely related to the health of river ecosystems. In this study, taking the North Canal River basin, a typical basin in Beijing, as an example, ...

Abstract	Macrobenthos can reflect the cumulative effect of various ecological threats on the water environment and are closely related to the health of river ecosystems. In this study, taking the North Canal River basin, a typical basin in Beijing, as an example, ecological data from 34 stations were investigated in the summer of 2015. Characteristics of the macrobenthos communities were analyzed, and driving environmental factors were identified using typical correspondence analysis. Thresholds and response species of those driving environmental factors were conducted using the thresholds indicator taxa analysis (TITAN). In this study, the health status of the river ecosystem was evaluated by the multi-metrics method and benthic index of biotic integrity (B-IBI). The benthic community was dominated by pollution-tolerant aquatic insects and mollusks, with a low-level Shannon-wiener diversity index between 0-1.01; fluoride, biochemical oxygen demand, ammonia-nitrogen, and total phosphorus were driving environmental factors influencing the community structure of macrobenthos. Indicator species of ammonia-nitrogen were identified by the TITAN in the North Canal River basin with a threshold range of 1.09-6.94 mg·L
MeSH term(s)	Beijing ; China ; Ecosystem ; Environmental Monitoring ; Rivers ; Water
Chemical Substances	Water (059QF0KO0R)
Language	Chinese
Publishing date	2022-01-06
Publishing country	China
Document type	Journal Article
ISSN	0250-3301
ISSN	0250-3301
DOI	10.13227/j.hjkx.202104158
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Response of macroinvertebrate community to water quality factors and aquatic ecosystem health assessment in a typical river in Beijing, China.

Hu, Xiaohong / Zuo, Depeng / Xu, Zongxue / Huang, Zhenfang / Liu, Bo / Han, Yuna / Bi, Yiqing

Environmental research

2022 Volume 212, Issue Pt D, Page(s) 113474

Abstract	Healthy aquatic ecosystems can offer basic ecological services for the sustainable development of humans and society. Water quality greatly influences the macroinvertebrate community in aquatic ecosystems and can alter the aquatic ecosystem's health status. However, the quantitative relationship between macroinvertebrate community and water quality factors in rivers remains unclear, particularly in urban rivers, which are strongly affected by human activities. Therefore, a new framework for the quantitative analysis between macroinvertebrate community and key water quality driving factors was developed in the study, meanwhile, the aquatic ecosystem health conditions were evaluated and validated by different methods. The framework was applied to a typical urban river, the North Canal River, which is regarded as the "mother river" of Beijing. Combined with the redundancy analysis (RDA) and the threshold indicator taxa analysis (TITAN), the water quality driving factors and their indicator species were identified and the corresponding response threshold was determined. Based on the benthic index of biotic integrity (B-IBI), the multi-metric rapid bioassessment method, and the biological monitoring working party (BMWP) score, the aquatic ecosystem health condition in the basin was comprehensively evaluated. The results show that fluoride, biochemical oxygen demand, ammonia-nitrogen and total phosphorus were the key water quality driving factors influencing the community structure of macroinvertebrates. Four indicator species of ammonia-nitrogen were identified by the TITAN method with a threshold range of 1.09-6.94 mg L
MeSH term(s)	Ammonia ; Animals ; Beijing ; China ; Ecosystem ; Environmental Monitoring/methods ; Humans ; Invertebrates ; Nitrogen ; Phosphorus ; Water Quality
Chemical Substances	Phosphorus (27YLU75U4W) ; Ammonia (7664-41-7) ; Nitrogen (N762921K75)
Language	English
Publishing date	2022-05-17
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	205699-9
ISSN	1096-0953 ; 0013-9351
ISSN (online)	1096-0953
ISSN	0013-9351
DOI	10.1016/j.envres.2022.113474
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Identification of priority management areas for non-point source pollution based on critical source areas in an agricultural watershed of Northeast China

Zuo, Depeng / Han, Yuna / Gao, Xiaoxi / Ma, Guangwen / Xu, Zongxue / Bi, Yiqing / Abbaspour, Karim C. / Yang, Hong

Environmental research. 2022 July 09,

2022

Abstract: Identification of critical source areas (CSAs) for non-point source (NPS) pollution is of great significance for environment governance and prevention. However, the CSAs are generally characterized as great spatial dispersion, and spatially heterogeneous ...

Abstract	Identification of critical source areas (CSAs) for non-point source (NPS) pollution is of great significance for environment governance and prevention. However, the CSAs are generally characterized as great spatial dispersion, and spatially heterogeneous precipitation has a great influence on the spatial distribution of nutrient yields. Therefore, we identify the CSAs for nutrient yields in an agricultural watershed of Northeast China at hydrological response units (HRUs) scale based on the Soil and Water Assessment Tool (SWAT), assess the impacts of spatially heterogeneity of precipitation on the identification of the CSAs, analyze the sensitivity of nutrient yields to precipitation by scenarios analysis method, and further identify priority management areas (PMAs) that have poor ability to retain nutrients. The results showed that the CSAs for nutrient yields identified by uniform precipitation showed greater fluctuation range and coverage area than actual precipitation; the major prevention areas of total nitrogen (TN) yield were mainly distributed in regions nearby main stem of lower reaches, while that of total phosphorus (TP) yield were mostly located in urban area nearby outlet of the watershed; the identification of the PMAs significantly decreased the CSAs for TN yield, whereas that for TP yield was no significant difference with the CSAs. This study could provide scientific guidance for the NPS pollution governance and prevention.
Keywords	Soil and Water Assessment Tool model ; agricultural watersheds ; governance ; nonpoint source pollution ; research ; total nitrogen ; total phosphorus ; urban areas ; China
Language	English
Dates of publication	2022-0709
Publishing place	Elsevier Inc.
Document type	Article
Note	Pre-press version
ZDB-ID	205699-9
ISSN	1096-0953 ; 0013-9351
ISSN (online)	1096-0953
ISSN	0013-9351
DOI	10.1016/j.envres.2022.113892
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Assessment of changes in water conservation capacity under land degradation neutrality effects in a typical watershed of Yellow River Basin, China

Zuo, Depeng / Chen, Guo / Wang, Guoqing / Xu, Zongxue / Han, Yuna / Peng, Dingzhi / Pang, Bo / Abbaspour, Karim C. / Yang, Hong

Ecological Indicators. 2023 Apr., v. 148 p.110145-

2023

Abstract: Large-scale implementation of the Grain for Green Project since 1999, which took the Yellow River Basin (YRB) as the core ecological restoration area, has had an important impact on the hydrological processes and ecological environment. Whether such ... ...

Abstract	Large-scale implementation of the Grain for Green Project since 1999, which took the Yellow River Basin (YRB) as the core ecological restoration area, has had an important impact on the hydrological processes and ecological environment. Whether such forest restoration construction is conducive to achieving land degradation neutrality as well as improving water conservation capacity has become a hot research topic. The Yiluo River basin (YLRB), one of the most important water conservation areas in the YRB, was selected as the study area. Firstly, the transfer matrix was used to analyze the changes in the two land use maps in 1990 and 2015 and to determine the transformation relationship between different land use types. Furthermore, land degradation was also investigated for further exploration of the correlation between land degradation neutrality and water conservation. The effects of land use and cover changes (LUCC) on the water conservation capacity across the YLRB were investigated by combining the Soil and Water Assessment Tool (SWAT) model, water conservation assessment method and land use change scenarios method. The results showed that the land degradation area was mainly located in the residential area and agricultural land in the downstream of the YLRB, and the execution of the Grain for Green Project is beneficial in promoting land degradation neutrality and increasing the water conservation capacity. The water conservation capacity across the YLRB approximately increased by 19.30 mm yr⁻¹ as every 10% of agricultural land converted to forest, showing a greater increase in the upstream than that in the downstream. Rainfall, Normalized Difference Vegetation Index (NDVI), and temperature were the primary factors affecting water conservation in the YLRB, while geological lithology also affects the spatial distribution of water conservation. The findings of this study could provide a theoretical basis for water resources and ecological environment protection.
Keywords	Soil and Water Assessment Tool model ; agricultural land ; forest restoration ; land degradation ; land use change ; lithology ; rain ; residential areas ; temperature ; vegetation index ; water conservation ; watersheds ; China ; Yellow River ; Water conservation capacity ; LUCC ; Land degradation neutrality ; The Grain for Green Project ; SWAT
Language	English
Dates of publication	2023-04
Publishing place	Elsevier Ltd
Document type	Article ; Online
Note	Use and reproduction
ZDB-ID	2036774-0
ISSN	1872-7034 ; 1470-160X
ISSN (online)	1872-7034
ISSN	1470-160X
DOI	10.1016/j.ecolind.2023.110145
Database	NAL-Catalogue (AGRICOLA)

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Article: Improving urban flood susceptibility mapping using transfer learning

Zhao, Gang / Pang, Bo / Xu, Zongxue / Cui, Lizhuang / Wang, Jingjing / Zuo, Depeng / Peng, Dingzhi

Journal of hydrology. 2021 Nov., v. 602

2021

Abstract: The flood inventory in urban areas is often difficult to collect and therefore inadequate for training a machine learning (ML)-based assessment model. In this study, we investigated the utility of transfer learning (TL) to improve urban flood ... ...

Abstract	The flood inventory in urban areas is often difficult to collect and therefore inadequate for training a machine learning (ML)-based assessment model. In this study, we investigated the utility of transfer learning (TL) to improve urban flood susceptibility assessment using knowledge outside the training domain. Specifically, we pre-trained a convolutional neural network-based assessment model in one catchment and then tried to improve the model performance of two other catchments by transferring knowledge from the pre-trained model. The results showed that (1) with the help of TL, the model performance of the two transferred catchments improved by 10%–25% in different data-rich and data-sparse scenarios; and (2) TL typically provided positive effects when we transferred knowledge from a well pretrained model in data-rich catchment. However, it may induce negative effects when the pre-trained model has poor accuracy. This study provides a promising approach to improve ML-based hazard assessment by sharing knowledge from different regions.
Keywords	hazard characterization ; hydrology ; inventories ; model validation ; models ; watersheds
Language	English
Dates of publication	2021-11
Publishing place	Elsevier B.V.
Document type	Article
ZDB-ID	1473173-3
ISSN	1879-2707 ; 0022-1694
ISSN (online)	1879-2707
ISSN	0022-1694
DOI	10.1016/j.jhydrol.2021.126777
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Identification of priority management areas for non-point source pollution based on critical source areas in an agricultural watershed of Northeast China.

Zuo, Depeng / Han, Yuna / Gao, Xiaoxi / Ma, Guangwen / Xu, Zongxue / Bi, Yiqing / Abbaspour, Karim C / Yang, Hong

Environmental research

2022 Volume 214, Issue Pt 2, Page(s) 113892

Abstract	Identification of critical source areas (CSAs) for non-point source (NPS) pollution is of great significance for environment governance and prevention. However, the CSAs are generally characterized as great spatial dispersion, and spatially heterogeneous precipitation has a great influence on the spatial distribution of nutrient yields. Therefore, we identify the CSAs for nutrient yields in an agricultural watershed of Northeast China at hydrological response units (HRUs) scale based on the Soil and Water Assessment Tool (SWAT), assess the impacts of spatially heterogeneity of precipitation on the identification of the CSAs, analyze the sensitivity of nutrient yields to precipitation by scenarios analysis method, and further identify priority management areas (PMAs) that have poor ability to retain nutrients. The results showed that the CSAs for nutrient yields identified by uniform precipitation showed greater fluctuation range and coverage area than actual precipitation; the major prevention areas of total nitrogen (TN) yield were mainly distributed in regions nearby main stem of lower reaches, while that of total phosphorus (TP) yield were mostly located in urban area nearby outlet of the watershed; the identification of the PMAs significantly decreased the CSAs for TN yield, whereas that for TP yield was no significant difference with the CSAs. This study could provide scientific guidance for the NPS pollution governance and prevention.
MeSH term(s)	Agriculture/methods ; China ; Environmental Monitoring/methods ; Nitrogen/analysis ; Non-Point Source Pollution/analysis ; Phosphorus/analysis ; Rivers ; Water Pollutants, Chemical/analysis
Chemical Substances	Water Pollutants, Chemical ; Phosphorus (27YLU75U4W) ; Nitrogen (N762921K75)
Language	English
Publishing date	2022-07-19
Publishing country	Netherlands
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	205699-9
ISSN	1096-0953 ; 0013-9351
ISSN (online)	1096-0953
ISSN	0013-9351
DOI	10.1016/j.envres.2022.113892
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Urban flood susceptibility assessment based on convolutional neural networks

Zhao, Gang / Pang, Bo / Xu, Zongxue / Peng, Dingzhi / Zuo, Depeng

Journal of hydrology. 2020 Nov., v. 590

2020

Abstract: In this study, a convolutional neural network (CNN)-based approach is proposed to assess flood susceptibility for urban catchment. Nine explanatory factors covering precipitation, topographical, and anthropogenic aspects were selected and two CNNs, SCNN ... ...

Abstract	In this study, a convolutional neural network (CNN)-based approach is proposed to assess flood susceptibility for urban catchment. Nine explanatory factors covering precipitation, topographical, and anthropogenic aspects were selected and two CNNs, SCNN and LeNet-5, were implemented to identify the relationship between the explanatory factors and flood inventory between 2004 and 2014 in the Dahongmen catchment in Beijing, China. The performance of the CNNs was compared with that of support vector machine (SVM) and random forest (RF) models for three model input strategies (point-based, array-based and imaged-based strategies). The results showed that: (1) The two CNNs performed better than the SVM and RF, with an accuracy of 0.90 for SCNN and 0.88 for Lenet-5 in the testing period. (2) The CNN-based approach provided more reliable flood susceptibility maps than the comparative models with the highest area under the curve (AUC) index of 0.9 validating by another flood inventory. (3) The upstream inundations induced by pluvial flood cannot be accurately identified by using point-based and array-based strategies. These errors were corrected by considering topographical information using the imaged-based CNN approach. (4) The fixed architecture LeNet-5 produced satisfactory results and avoided the time-consuming process of architecture selection of CNN. We conclude that the proposed CNN-based approach is a valid approach and provides a high-quality susceptibility map for urban mitigation and flood management.
Keywords	flood control ; hydrology ; inventories ; neural networks ; support vector machines ; watersheds ; China
Language	English
Dates of publication	2020-11
Publishing place	Elsevier B.V.
Document type	Article
Note	NAL-AP-2-clean
ZDB-ID	1473173-3
ISSN	1879-2707 ; 0022-1694
ISSN (online)	1879-2707
ISSN	0022-1694
DOI	10.1016/j.jhydrol.2020.125235
Database	NAL-Catalogue (AGRICOLA)

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