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Precision Characterization of Soil-Groundwater Contamination in an Industrial Park, North China: Bp-Ann Model Prediction and Migration Mechanism

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SSRN 2023年

作者： Liu, Siyan Yang, Xiao Liu, Zhaoshu Yan, Xiulan Jin, Xiaoli Zhou, Yaoyu Liang, Tao Key Laboratory of Land Surface Pattern and Simulation Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing100101 China College of Resources and Environment University of Chinese Academy of Sciences Beijing100190 China College of Resources and Environment Hunan Agricultural University Changsha410128 China

Intensive industrial activities cause soil contamination with wide variations and even perturb groundwater safety. The links between contamination and geochemical features, however, have not been established yet due to the intricate hydrogeology and industrial processes. In this study, 880 soil samples and 8 groundwater samples were collected in an industrial park in China to precisely characterize the contamination levels of soil-groundwater system and migration mechanisms. Our research delineated the spatial distribution pattern of contaminants via the back propagation neural network algorithm (BP-ANN) prediction and visualization of a three-dimensional contamination plume model, and clarified the migration mechanisms in both soil and groundwater systems. Arsenic (As) and 1,2-dichloroethane (1,2-DCA) were identified as the primary contaminants in the site soil, and their vertical migration depth arrived to 6-8 m, however, a distinct migration behavior was found in between the two contaminants. Correlation analysis revealed that hydrogeological characteristics were recognized critical for the migration of As, while the migration of 1,2-DCA depended on soil lithology and water content. Contaminants migrate vertically downwards with soil water under gravity-driven conditions and penetrate through the soil barrier to reach the saturated aquifer, forming a contamination plume with groundwater flow. The migration behaviors and influencing mechanisms in the soil-groundwater system of an industrial park were confirmed for the first time through field tests combining machine learning algorithms. Our findings are imperative to build capabilities in monitoring the contamination status of industrial sites and provide valuable technical support for maintaining sustainable industry. © 2023, The Authors. All rights reserved.

关键词： Contamination

Precision Characterization of Soil-Groundwater Contamination in an Industrial Park, North China: Bp-Ann Model Prediction and Migration Mechanism

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SSRN 2023年

Intensive industrial activities cause soil contamination with wide variations and even perturb groundwater safety. The links between contamination and geochemical features, however, have not been established yet due to the intricate hydrogeology and industrial processes. In this study, 880 soil samples and 8 groundwater samples were collected in an industrial park in China, and the spatial distribution patterns of contaminants were delineated via the back propagation neural network algorithm prediction and visualization of a three-dimensional contamination plume model, and clarified the migration mechanisms in both soil and groundwater systems. Arsenic and 1,2-dichloroethane were identified as the primary contaminants in the site soil, and their vertical migration depth arrived to 6-8 m, however, a distinct migration behavior was found in the two contaminants. Correlation analysis revealed that hydrogeological characteristics were recognized critical for the migration of arsenic, while the migration of 1,2-dichloroethane depended on soil lithology and water content. Contaminants migrate vertically downwards with soil water under gravity-driven conditions and penetrate through the soil barrier to reach the saturated aquifer, forming a contamination plume with groundwater flow. Our findings are imperative to build capabilities in monitoring the contamination status of industrial sites and provide valuable technical support for maintaining sustainable industry. © 2023, The Authors. All rights reserved.

关键词： Spatial distribution

Benefits of Adaptive Managements on Wheat Yield in China Outweigh the Impact of Climate Change

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SSRN 2024年

作者： Liu, Yujie Chen, Jiahao Tan, Qinghua Wang, Xuhui Pan, Tao Key Laboratory of Land Surface Pattern and Simulation Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China The Administrative Bureau of Chinese Academy of Sciences Beijing China Sino-French Institute for Earth System Science College of Urban and Environmental Sciences Peking University Beijing China

Agricultural adaptive management practices, such as nutrient and water management, have been widely recognized as crucial in adaptation to climate change and increasing crop yields. However, the role of adaptive management has not been fully considered. The contribution of adaptative management to crop yield remains unclear, whose regional differences have been largely neglected. To address this gap, this study proposes a multi-model ensemble (MME) combining six machine learning algorithms by Bayesian model averaging method to evaluate the contribution of adaptive management to wheat yield based on county-scale observations in China from 1981 to 2011. Results show that China’s wheat yield has increased 1.93 times since 1981, with an average change rate of 55.90 kg ha-1 a-1. The intensity of adaptive managements including fertilizer application, irrigation rate and power of machinery showed an overall upward trend. All six machine learning methods outperformed multiple linear regression, and MME has improved the accuracy of the simulation. Overall, improvements in adaptive managements contributed to 28.95% to 52.52% of wheat yield change, outweigh the contribution of climate change (12.96%~24.78%). While fertilization and irrigation contributed almost equally to yield change in national level, their influence varied depending on the cultivation region. The study sheds light on the importance of adaptive management practices in contributing to increased crop yields, and the findings underscore the need for large-scale quantification and region-specific strategies to promote sustainable agriculture. © 2024, The Authors. All rights reserved.

关键词： Climate change

A Robust But Straightforward Phenology-Based Ginger Mapping Algorithm by Using Unique Phenology Features, Time-Series Sentinel-2 Images, and Google Earth Engine

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SSRN 2022年

作者： Di, Yuanyuan Dong, Jinwei Zhu, Fangfang Fu, Ping Faculty of Science and Engineering University of Nottingham Ningbo China Ningbo315100 China Key Laboratory of Land Surface Pattern and Simulation Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing100101 China

Ginger (Zingiber officinale), a commonly used spice, dietary supplement, and medical plant, is expanding rapidly in China due to its increasing demands and price in the international market. However, the existing information on its area and spatial distribution can only be derived from statistical data, and spatially explicit maps of ginger planting areas are unavailable. We proposed a simple but robust ginger planting area mapping algorithm using the time-series Sentinel-2 images and Google Earth Engine (GEE) platform. Changyi city, the hotspot city with the highest ginger production in China, was selected as our study area. Two ginger indices (GIs) were generated based on the four unique phenology features: 1) high reflectance at the start of the season due to white agricultural mulching films, 2) a slower green-up feature in the early season, 3) low reflectance in summer due to black sunshade nets cover, 4) a unique green feature at the end of the growing season. The accuracy assessment based on the ground truth data showed fairly reasonable overall accuracies of 96.7%–97.3%, while the Matthews correlation coefficients (MCC) were 0.871–0.924. We found a rapid ginger expansion from 63.0 km2 in 2019 to 101.5 km2 in 2021 in the study area, by 61% from 2019 to 2021. Moreover, about 78% of ginger land in the study area had crop rotation every two years to boost yield and prevent bacterial diseases in the soil. Our study identified four critical features of ginger and demonstrated the potential of the phenology-based approach, Sentinel-2 data, and GEE platform for ginger mapping. This study is expected to apply to regional or national ginger mapping to provide valuable information for the ginger planting plan and guide the international ginger trade. © 2022, The Authors. All rights reserved.

关键词： Engines

Planting area and production decreased for winter-triticeae crops but increased for rapeseed in Ukraine with climatic impacts dominating

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Geography and Sustainability 2025年第2期6卷 108-116页

作者： Jichong Han Yuchuan Luo Zhao Zhang Jialu Xu Yi Chen Senthold Asseng Jonas Jägermeyr Christoph Müller Jørgen E Olesen Reimund Rötter Fulu Tao Joint International Research Laboratory of Catastrophe Simulation and Systemic Risk Governance School of National Safety and Emergency ManagementBeijing Normal UniversityZhuhai 519087China School of Systems science Beijing Normal UniversityBeijing 100875China Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station School of Geographical SciencesSouthwest UniversityChongqing 400715China Key Laboratory of Land Surface Pattern and Simulation Institute of Geographical Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101China Technical University of Munich Department of Life Science EngineeringDigital AgricultureHEF World Agricultural Systems CenterFreisingGermany NASA Goddard Institute for Space Studies New YorkNYUSA Columbia University Center for Climate Systems ResearchNew YorkNYUSA Potsdam Institute for Climate Impacts Research(PIK) Member of the Leibniz AssociationPotsdamGermany Department of Agroecology Aarhus UniversityTjeleDenmark University of Götingen Tropical Plant Production and Agricultural Systems Modelling(TROPAGS)GötingenGermany University of Götingen Centre for Biodiversity and Sustainable Land Use(CBL)GötingenGermany College of Resources and Environment University of Chinese Academy of SciencesBeijing 100049China

On-time mapping dynamics of crop area,yield,and production is important for global food *** information,however,is often not ***,we used satellite information,a spectral-phenology integration approach for mapping crop area,and a machine learning model for predicting yield in the war-stricken *** found that in Ukraine crop area and production declined in 2022 relative to 2017–2021 and 2021 for wintertriticeae crops,which was invaded before the cropping season in February of that *** the same time,crop area and production for rapeseed increased in Ukraine,with yields consistently lower by 6.5%relative to *** low precipitation and the Russian-Ukrainian conflict-related factors contributed to such yield variations by-1.3%and-0.9%for winter-triticeae crops and-4.2%and-0.5%for rapeseed in *** demonstrate a robust framework for monitoring country-wide crop production dynamics in near real-time,serving as an early-foodsecurity-warning system.

关键词： Food security Conflict Machine learning Production Satellite

Recent Soybean Subsidy Policy Did Not Recover Soybean Planting Areas in Northeast China

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SSRN 2023年

作者： Di, Yuanyuan You, Nanshan Dong, Jinwei Liao, Xiaoyong Song, Kaishan Fu, Ping Key Laboratory of Land Surface Pattern and Simulation Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing100101 China Faculty of Science and Engineering University of Nottingham Ningbo China Ningbo315100 China Northeast Institute of Geography and Agroecology Chinese Academy of Sciences Changchun130102 China

The COVID-19 pandemic and the Sino-US trade friction changed the international trade pattern and affected global food security. With over 80% of China’s soybean demand being dependent on imports, China has implemented multiple agricultural policies to stimulate soybean production, such as the soybean producer subsidies. Northeast (NE) China is the leading soybean-producing region in China and produces more than half of the soybean in the country. However, it is unclear how the soybean production policies affected soybean planting area and cropping patterns in NE China. Here, we generated annual crop maps at 10-m resolution in NE China from 2017 to 2021 using a well-established crop mapping framework. We found that soybean area in NE China contracted following the soybean producer subsidies released in 2017, with a decline (-27.9%) in the soybean planting area from 2020 to 2021 due to the high comparative benefits of planting maize. We also found that the routine rotation system dominated the soybean planting areas instead of the soybean producer subsidy. The effects of the routine rotation system were more conspicuous in the 2300-2700 ℃ d accumulated temperature zone of Heilongjiang Province. The lower net profit of soybean cultivation than maize cultivation could be the major reason for the reduction in soybean planting area. Our study provides objective satellite evidence to track the inter-annual variability of cropping patterns and assess the effectiveness of the soybean producer subsidy policy in NE China. © 2023, The Authors. All rights reserved.

关键词： Cultivation

Assessing Environmental Thresholds in Relation to Plant Structure and Nutritional Value for Improved Maize Calendar Ensuring Food Security

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SSRN 2021年

作者： Ahmad, Aqeel Liu, Yujie Key Laboratory of Land Surface Pattern and Simulation Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing100101 China

The environment has been continuously changed, and it’s a bitter truth that we can’t minimize anthropogenic activities to mitigate harmful impacts of the environment. The changing environment is a great threat to food security by affecting crop yields. However, there is no comprehensive study to assess the environmental impact on the nutritional quality of the crops. In this study, we have investigated the nutritional and yield of maize crops around the globe and synchronized the finding with physiological reasoning. The study enlightens the time-course pathway for maize plant enzymes and describes their behavior toward changing environments. The study also explained time-scale-based changes in the physiological conditions of maize crops against environmental dynamics around the globe. It also detected the impact of climate change on the deterioration of the nutritional quality of maize. The current reports activities of three different enzyme classes. It was noted that the photosynthesis-related enzyme activities were boosted after a sudden increase in carbon dioxide concentration. However, the drought years (2005-2010) decreased photosynthesis and increased oxidative activities. Overall, the glycemic index of the maize crop has been increased during the last four decades. However, the crop production threshold levels have been raised more quickly. The nutritional index values possess an alarming situation and are frequently recorded under the threshold levels in recent years. The study paves a path for maize toward nutritional contents richness, ensuring food security and nutritional security in the future. © 2021, The Authors. All rights reserved.

关键词： Crops

Changes in vegetation and moisture in the northern Tianshan of China over the past 450 years

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Frontiers of Earth Science 2020年第2期14卷 479-491页

作者： Weihe REN Yan ZHAO Quan LI Jianhui CHEN Key Laboratory of Land Surface Pattern and Simulation Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101China University of Chinese Academy of Sciences Beijing 100049China Key Laboratory of West China’s Environmental System(Ministry of Education) College of Earth and Environmental SciencesLanzhou UniversityLanzhou 730000China

Knowledge of historical changes in moisture within semi-arid and arid regions is the basis of climatic change predictions and strategies in response to long-term *** this study,a multiproxy peat record with highresolution from Sichanghu in the northern Tianshan was used to document the changes in vegetation and climate over the past 450 years in the arid Central *** pollen,grain size,and loss on ignition(LOI)records indicate that the productivity of local peat began to increase at^1730 *** vegetation in the Sichanghu area experienced several transitions,from temperate desert to dense desert,marsh meadow,and steppe desert *** climate in the study area was extremely dry during the early stages of the Little Ice Age(LIA)(before 1730 AD)and relatively wet during the late stages(1730–1880 AD).The inferred changes in the moisture conditions of the Sichanghu peatland since the LIA may have been controlled by the extent of Arctic sea ice,the North Atlantic Oscillation,and the Siberian High via the connections of large-scale atmospheric circulations such as the Westerlies.

关键词： Little Ice Age pollen vegetation change moisture condition Tianshan arid Central Asia

Study of the intensity and driving factors of land use/cover change in the Yarlung Zangbo River, Nyang Qu River, and Lhasa River region, Qinghai-Tibet Plateau of China

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Journal of Arid land 2022年第4期14卷 411-425页

作者： LUO Jing XIN Liangjie LIU Fenggui CHEN Qiong ZHOU Qiang ZHANG Yili College of Geographic Sciences Qinghai Normal UniversityXining 810008China Academy of Plateau Science and Sustainability Xining 810008China Key Laboratory of Land Surface Pattern and Simulation Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101China Center for Excellence in Tibetan Plateau Earth Sciences Chinese Academy of SciencesBeijing 100101China

land use/land cover(LULC) is an important part of exploring the interaction between natural environment and human activities and achieving regional sustainable development. Based on the data of LULC types(cropland, forest land, grassland, built-up land, and unused land) from 1990 to 2015, we analysed the intensity and driving factors of land use/cover change(LUCC) in the Yarlung Zangbo River,Nyang Qu River, and Lhasa River(YNL) region, Qinghai-Tibet Plateau of China, using intensity analysis method, cross-linking table method, and spatial econometric model. The results showed that LUCC in the YNL region was nonstationary from 1990 to 2015, showing a change pattern with "fast-slow-fast" and "U-shaped". Built-up land showed a steady increase pattern, while cropland showed a steady decrease pattern. The gain of built-up land mainly came from the loss of cropland. The transition pattern of LUCC in the YNL region was relatively single and stable during 1990–2015. The transition pattern from cropland and forest land to built-up land was a systematic change process of tendency and the transition pattern from grassland and unused land to cropland was a systematic change process of avoidance. The transition process of LUCC was the result of the combined effect of natural environment and social economic development in the YNL region. This study reveals the impact of ecological environment problems caused by human activities on the land resource system and provides scientific support for the study of ecological environment change and sustainable development of the Qinghai-Tibet Plateau.

关键词： land use/cover change intensity analysis driving factors Yarlung Zangbo River Nyang Qu River Lhasa River Qinghai-Tibet Plateau