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Dai H, Zhang Y, Fang W, Liu J, Hong J, Zou C, Zhang J. Microbial community structural response to variations in physicochemical features of different aquifers. Front Microbiol 2023; 14:1025964. [PMID: 36865779 PMCID: PMC9971630 DOI: 10.3389/fmicb.2023.1025964] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Accepted: 01/23/2023] [Indexed: 02/11/2023] Open
Abstract
Introduction The community structure of groundwater microorganisms has a significant impact on groundwater quality. However, the relationships between the microbial communities and environmental variables in groundwater of different recharge and disturbance types are not fully understood. Methods In this study, measurements of groundwater physicochemical parameters and 16S rDNA high-throughput sequencing technology were used to assess the interactions between hydrogeochemical conditions and microbial diversity in Longkou coastal aquifer (LK), Cele arid zone aquifer (CL), and Wuhan riverside hyporheic zone aquifer (WH). Redundancy analysis indicated that the primary chemical parameters affecting the microbial community composition were NO3 -, Cl-, and HCO3 -. Results The species and quantity of microorganisms in the river-groundwater interaction area were considerably higher than those in areas with high salinity [Shannon: WH (6.28) > LK (4.11) > CL (3.96); Chao1: WH (4,868) > CL (1510) > LK (1,222)]. Molecular ecological network analysis demonstrated that the change in microbial interactions caused by evaporation was less than that caused by seawater invasion under high-salinity conditions [(nodes, links): LK (71,192) > CL (51,198)], whereas the scale and nodes of the microbial network were greatly expanded under low-salinity conditions [(nodes, links): WH (279,694)]. Microbial community analysis revealed that distinct differences existed in the classification levels of the different dominant microorganism species in the three aquifers. Discussion Environmental physical and chemical conditions selected the dominant species according to microbial functions. Gallionellaceae, which is associated with iron oxidation, dominated in the arid zones, while Rhodocyclaceae, which is related to denitrification, led in the coastal zones, and Desulfurivibrio, which is related to sulfur conversion, prevailed in the hyporheic zones. Therefore, dominant local bacterial communities can be used as indicators of local environmental conditions.
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Affiliation(s)
- Heng Dai
- State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences, Wuhan, China
- School of Environmental Studies, Hubei Key Laboratory of Yangtze Catchment Environmental Aquatic Science, China University of Geosciences, Wuhan, China
| | - Yiyu Zhang
- State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences, Wuhan, China
- School of Environmental Studies, Hubei Key Laboratory of Yangtze Catchment Environmental Aquatic Science, China University of Geosciences, Wuhan, China
| | - Wen Fang
- State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences, Wuhan, China
- School of Environmental Studies, Hubei Key Laboratory of Yangtze Catchment Environmental Aquatic Science, China University of Geosciences, Wuhan, China
| | - Juan Liu
- State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences, Wuhan, China
- School of Environmental Studies, Hubei Key Laboratory of Yangtze Catchment Environmental Aquatic Science, China University of Geosciences, Wuhan, China
| | - Jun Hong
- School of Environmental Studies, China University of Geosciences, Wuhan, China
| | - Chaowang Zou
- Hubei Shuili Hydro Power Reconnaissance Design Institute, Wuhan, China
| | - Jin Zhang
- State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Yangtze Institute for Conservation and Development, Hohai University, Nanjing, China
- Chinese Academy of Sciences, Xinjiang Institute of Ecology and Geography, Ürümqi, China
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Tu Z, Zhou Y, Zhou J, Han S, Liu J, Liu J, Sun Y, Yang F. Identification and Risk Assessment of Priority Control Organic Pollutants in Groundwater in the Junggar Basin in Xinjiang, P.R. China. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:2051. [PMID: 36767417 PMCID: PMC9915296 DOI: 10.3390/ijerph20032051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 01/14/2023] [Accepted: 01/19/2023] [Indexed: 06/18/2023]
Abstract
The Junggar Basin in Xinjiang is located in the hinterland of Eurasia, where the groundwater is a significant resource and has important ecological functions. The introduction of harmful organic pollutants into groundwater from increasing human activities and rapid socioeconomic development may lead to groundwater pollution at various levels. Therefore, to develop an effective regulatory framework, establishing a list of priority control organic pollutants (PCOPs) is in urgent need. In this study, a method of ranking the priority of pollutants based on their prevalence (Pv), occurrence (O) and persistent bioaccumulative toxicity (PBT) has been developed. PvOPBT in the environment was applied in the screening of PCOPs among 34 organic pollutants and the risk assessment of screened PCOPs in groundwater in the Junggar Basin. The results show that the PCOPs in groundwater were benzo[a]pyrene, 1,2-dichloroethane, trichloromethane and DDT. Among the pollutants, benzo[a]pyrene, 1,2-dichloroethane and DDT showed high potential ecological risk, whilst trichloromethane represented low potential ecological risk. With the exception of benzo[a]pyrene, which had high potential health risks, the other screened PCOPs had low potential health risks. Unlike the scatter distribution of groundwater benzo[a]pyrene, the 1,2-dichloroethane and trichloromethane in groundwater were mainly concentrated in the central part of the southern margin and the northern margin of the Junggar Basin, while the DDT in groundwater was only distributed in Jinghe County (in the southwest) and Beitun City (in the north). Industrial and agricultural activities were the main controlling factors that affected the distribution of PCOPs.
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Affiliation(s)
- Zhi Tu
- College of Water Conservancy and Civil Engineering, Xinjiang Agricultural University, Urumqi 830052, China
- Xinjiang Hydrology and Water Resources Engineering Research Center, Urumqi 830052, China
- Xinjiang Key Laboratory of Hydraulic Engineering Security and Water Disasters Prevention, Urumqi 830052, China
| | - Yinzhu Zhou
- Center for Hydrogeology and Environmental Geology Survey, CGS, Baoding 071051, China
| | - Jinlong Zhou
- College of Water Conservancy and Civil Engineering, Xinjiang Agricultural University, Urumqi 830052, China
- Xinjiang Hydrology and Water Resources Engineering Research Center, Urumqi 830052, China
- Xinjiang Key Laboratory of Hydraulic Engineering Security and Water Disasters Prevention, Urumqi 830052, China
| | - Shuangbao Han
- Center for Hydrogeology and Environmental Geology Survey, CGS, Baoding 071051, China
| | - Jinwei Liu
- Center for Hydrogeology and Environmental Geology Survey, CGS, Baoding 071051, China
| | - Jiangtao Liu
- Center for Hydrogeology and Environmental Geology Survey, CGS, Baoding 071051, China
| | - Ying Sun
- College of Water Conservancy and Civil Engineering, Xinjiang Agricultural University, Urumqi 830052, China
- Xinjiang Hydrology and Water Resources Engineering Research Center, Urumqi 830052, China
- Xinjiang Key Laboratory of Hydraulic Engineering Security and Water Disasters Prevention, Urumqi 830052, China
| | - Fangyuan Yang
- College of Mathematics and Physics, Xinjiang Agricultural University, Urumqi 830052, China
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Zhang Q, Wang H, Xu Z, Li G, Yang M, Liu J. Quantitative identification of groundwater contamination sources by combining isotope tracer technique with PMF model in an arid area of northwestern China. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2023; 325:116588. [PMID: 36308954 DOI: 10.1016/j.jenvman.2022.116588] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Revised: 10/16/2022] [Accepted: 10/19/2022] [Indexed: 06/16/2023]
Abstract
Nowadays, groundwater quality has deteriorated because of intensive human activities. It is important to accurately identify the pollution source for controlling the deterioration of groundwater quality. However, the accuracy of the current source analysis method needs to be improved. In this study, we combined hydrochemical method, isotope tracing technique and PMF model, for the first time, to trace the source of groundwater pollution in Beichuan River basin, Qinghai Province, China. According to the results, there were 35.8% of Fe, 34.1% of total hardness, 24.3% of SO42- and 8.09% of NO3- samples exceeded the Grade III standards for Groundwater quality in China, which indicated that the groundwater in the study area has been significantly affected by human activities. Hydrochemical method suggested that the chemical component originated from rock weathering, cation exchange and mineral dissolution. Based on isotope tracing technique (δ15N-NO3-, δ18O-NO3-, δ34S-SO42- and δ18O-SO42-), the primary sources of nitrate and sulfate in groundwater were soil nitrogen and oxidation of sulfide minerals in the forest area, domestic sewage and oxidation of sulfide minerals in the urban and industrial area, and mixed sources in the village and agricultural area. Finally, the pollution source of groundwater was distinguished by combining the PMF model, isotope tracing technique and hydrochemical method. Results showed that the main pollutant of groundwater is domestic sewage in the urban, village and industrial area. The contribution rates to groundwater pollution were 60.7%, 60.8% and 57.8%, respectively. However, in the forest and agricultural area, the main source changed to water-rock interaction and chemical fertilizer, and the contribution rates to groundwater quality were 53.5% and 61.0%, respectively. Our results suggested that the coupling tracing methodology can improve the accuracy of source resolution in the water environment and it can be applied to other areas of the world.
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Affiliation(s)
- Qianqian Zhang
- Hebei and China Geological Survey Key Laboratory of Groundwater Remediation, Institute of Hydrogeology and Environmental Geology, Chinese Academy of Geological Sciences, Shijiazhuang, 050061, China; Key Laboratory of Cenozoic Geology and Environment, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing, 100029, China.
| | - Huiwei Wang
- Hebei and China Geological Survey Key Laboratory of Groundwater Remediation, Institute of Hydrogeology and Environmental Geology, Chinese Academy of Geological Sciences, Shijiazhuang, 050061, China
| | - Zhifang Xu
- Key Laboratory of Cenozoic Geology and Environment, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing, 100029, China
| | - Gan Li
- College of Forestry, Southwest Forestry University, Kunming, 650233, China
| | - Mingnan Yang
- Hebei and China Geological Survey Key Laboratory of Groundwater Remediation, Institute of Hydrogeology and Environmental Geology, Chinese Academy of Geological Sciences, Shijiazhuang, 050061, China
| | - Jingtao Liu
- Hebei and China Geological Survey Key Laboratory of Groundwater Remediation, Institute of Hydrogeology and Environmental Geology, Chinese Academy of Geological Sciences, Shijiazhuang, 050061, China
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Rashid T, Sabarathinam C, Al-Qallaf H, Bhandary H, Al-Jumaa M, Shishter A, Al-Salman B. Evolution of hydrogeochemistry in groundwater production fields of Kuwait - Inferences from long-term data. CHEMOSPHERE 2022; 307:135734. [PMID: 35926745 DOI: 10.1016/j.chemosphere.2022.135734] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Revised: 07/04/2022] [Accepted: 07/12/2022] [Indexed: 06/15/2023]
Abstract
Kuwait Group aquifers and Dammam Formation are the two prominent aquifers, the wells tapping Dammam Formation and Dual completion wells are used for groundwater production. The current study investigates the spatiotemporal evolution of hydrochemical characteristics of the Shagaya water field utilizing long-term (1975-2019) hydrochemical data from 116 water wells. The Shagaya water well field has been differentiated into A to F sub-Fields. Mann-Kendall and Sen's Slope method along with spatial interpolation of change in TDS with time identified a significant decrease in TDS with time in the major portions of the Shagaya B, C, D, and E Fields. The study infers that 82% of wells extracting water from the Dammam Formation and 42% of Dual completion wells show a decrease in TDS concentration. The most plausible explanation for this phenomenon was the inflow of better-quality water from the up gradient parts of the Kuwait Group and the Dammam Formation aquifers due to the fall in the potentiometric head with high volume production in the well field. The results of ionic ratios (Na/Cl, Ca/Mg, Ca/SO4, Ca + Mg/SO4+HCO3), isotopes (34S, 87Sr/86Sr), relationships between 2H and 18O, and Ne/He and 3He/4He ratios identified that salinization was due to the result of rock-water interaction, ion exchange, mixing between groundwater of Kuwait Group and Dammam Formation and with groundwater from deeper parts of the aquifer. The long-term analysis of the data shows a notable variation of chemistry in a few locations and thus the study helps to manage, sustain groundwater resources, and protection of host aquifers.
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Affiliation(s)
- Tariq Rashid
- Water Resources Development Management Program Water Research Center, Kuwait Institute for Scientific Research P. O. Box: 24885, Safat, 13109, Kuwait.
| | - Chidambaram Sabarathinam
- Water Resources Development Management Program Water Research Center, Kuwait Institute for Scientific Research P. O. Box: 24885, Safat, 13109, Kuwait.
| | - Habib Al-Qallaf
- Water Resources Development Management Program Water Research Center, Kuwait Institute for Scientific Research P. O. Box: 24885, Safat, 13109, Kuwait.
| | - Harish Bhandary
- Water Resources Development Management Program Water Research Center, Kuwait Institute for Scientific Research P. O. Box: 24885, Safat, 13109, Kuwait.
| | - Mariam Al-Jumaa
- Water Resources Development Management Program Water Research Center, Kuwait Institute for Scientific Research P. O. Box: 24885, Safat, 13109, Kuwait.
| | - Ahmed Shishter
- Water Resources Development Management Program Water Research Center, Kuwait Institute for Scientific Research P. O. Box: 24885, Safat, 13109, Kuwait.
| | - Bandar Al-Salman
- Water Resources Development Management Program Water Research Center, Kuwait Institute for Scientific Research P. O. Box: 24885, Safat, 13109, Kuwait.
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Zhao X, Liu X, Xing Y, Wang L, Wang Y. Evaluation of water quality using a Takagi-Sugeno fuzzy neural network and determination of heavy metal pollution index in a typical site upstream of the Yellow River. ENVIRONMENTAL RESEARCH 2022; 211:113058. [PMID: 35255414 DOI: 10.1016/j.envres.2022.113058] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/17/2022] [Revised: 02/25/2022] [Accepted: 02/27/2022] [Indexed: 06/14/2023]
Abstract
Assessment of river water quality is very important for understanding the impact of human activities on aquatic ecosystems. As the second-largest river in China, the Yellow River's water environment is closely related to the social development and water security of northern China. The Huangshui River is a major tributary of the upper Yellow River, and it supplies water to cities in the lower reaches. In this study, a Takagi-Sugeno (T-S) fuzzy neural network was used to evaluate water quality of the Huangshui River, and pollutant sources were analyzed. The heavy metal pollution index (HPI) was calculated to assess the heavy metal pollution level, and the health risks posed by heavy metal elements were assessed. The results indicated that the main contaminants in the Huangshui River were ammonia nitrogen (NH3-N) and total phosphorus (TP), which was affected by various activities of industry, agriculture, and urbanization, and the maximum concentration of NH3-N and TP was 5.90 mg/L and 0.36 mg/L, respectively. The T-S evaluation results of some points in the middle reaches were 3.317 and 3.197, which belonged to Level Ⅳ and the water quality was poor. The concentrations of Cu, Zn and Cr in the river were 0.57-44.58 μg/L, 10-122.50 μg/L and 2-28.67 μg/L, respectively, and they were relatively large. The T-S fuzzy neural network could evaluate water quality, avoiding extreme evaluation results by using fuzzy rules to reduce the influence of pollutant concentrations that are too high or too low. In addition to qualitative categorization of water quality, this approach can also quantitatively assess water quality within a single category. The results of water quality assessment could provide a scientific data support for river management.
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Affiliation(s)
- Xiaohong Zhao
- School of Civil Engineering, Chang'an University, Xi'an, 710061, China
| | - Xiaojie Liu
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China
| | - Yue Xing
- School of Civil Engineering, Chang'an University, Xi'an, 710061, China
| | - Lingqing Wang
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Yong Wang
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China
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Effects of Agriculture and Animal Husbandry on Heavy Metal Contamination in the Aquatic Environment and Human Health in Huangshui River Basin. WATER 2022. [DOI: 10.3390/w14040549] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Huangshui River (HSR) is the mother river of Qinghai province. Croplands and grasslands cover more than 76% of the total area, and highland agriculture and animal husbandry are the dominant industries. The use of pesticides, fertilizers, and feed additives increases the risk of heavy metal (HM) contamination. In this study, the concentration of HMs in the main stream and tributaries of HSR were investigated. The Positive Matrix Factorization model was used for source apportionment, and Health Risk Assessment method was used to assess the human health risks. To further analyze the effect of agriculture and animal husbandry on aquatic environment and human health, we considered agriculture and animal husbandry as two factors in the source apportionment process, defined the effect of the factors, established the calculation formula, and quantified the effects. The results show that the overall situation of aquatic environment in HSR is good; natural processes, traffic tail gas and atmospheric deposition, agricultural planting, industrial wastewater discharge, and animal husbandry are the main sources of HMs in the water. These HMs present noncarcinogenic and carcinogenic risks for infants. A total effect of agricultural and animal husbandry on HMs or HI in HSRB is approximately 20%, while on TCR is 40%. However, the effects of agriculture on the hazard quotient of arsenic, carcinogenic risk of nickel and lead, and that of animal husbandry on carcinogenic risk of cadmium were significant. This study can provide a theoretical basis for local managers of agriculture and animal husbandry to perform their work effectively.
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Hajji S, Allouche N, Bouri S, Aljuaid AM, Hachicha W. Assessment of Seawater Intrusion in Coastal Aquifers Using Multivariate Statistical Analyses and Hydrochemical Facies Evolution-Based Model. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 19:155. [PMID: 35010415 PMCID: PMC8751113 DOI: 10.3390/ijerph19010155] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Revised: 12/15/2021] [Accepted: 12/17/2021] [Indexed: 06/14/2023]
Abstract
Groundwater (GW) studies have been conducted worldwide with regard to several pressures, including climate change, seawater intrusion, and water overexploitation. GW quality is a very important sector for several countries in the world, in particular for Tunisia. The shallow coastal aquifer of Sfax (located in Tunisia) was found to be under the combined conditions of continuous drop in GW and further deterioration of the groundwater quality (GWQ). This study was conducted to identify the processes that control GWQ mainly in relation to mineralization sources in the shallow Sfax coastal aquifer. To perform this task, 37 wells are considered. Data include 10 physico-chemical properties of groundwater analyzed in water samples: pH, EC, calcium (Ca), sodium (Na), magnesium (Mg), potassium (K), chloride (Cl), sulfate (SO4), bicarbonate (HCO3), and nitrate (NO3), i.e., investigation was based on a database of 370 observations. Principal component analysis (PCA) and hydrochemical facies evolution (HFE) were conducted to extract the main factors affecting GW chemistry. The results obtained using the PCA model show that GWQ is mainly controlled by either natural factors (rock-water interactions) or anthropogenic ones (agricultural and domestic activities). Indeed, the GW overexploitation generated not only the GWQ degradation but also the SWI. The inverse distance weighted (IDW) method, integrated in a geographic information system (GIS), is employed to achieve spatial mapping of seawater intrusion locations. Hydrochemical facies evolution (HFE) results corroborate the seawater intrusion and its spatial distribution. Furthermore, the mixing ratio showed that Jebeniana and Chaffar-Mahares localities are characterized by high SWI hazard. This research should be done to better manage GW resources and help to develop a suitable plan for the exploitation and protection of water resources.
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Affiliation(s)
- Soumaya Hajji
- Laboratory of Water, Energy and Environment, National School of Engineers of Sfax, University of Sfax, B.P. 1173, Sfax 3083, Tunisia; (S.H.); (N.A.); (S.B.)
| | - Nabila Allouche
- Laboratory of Water, Energy and Environment, National School of Engineers of Sfax, University of Sfax, B.P. 1173, Sfax 3083, Tunisia; (S.H.); (N.A.); (S.B.)
| | - Salem Bouri
- Laboratory of Water, Energy and Environment, National School of Engineers of Sfax, University of Sfax, B.P. 1173, Sfax 3083, Tunisia; (S.H.); (N.A.); (S.B.)
| | - Awad M. Aljuaid
- Department of Industrial Engineering, College of Engineering, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia;
| | - Wafik Hachicha
- Department of Industrial Engineering, College of Engineering, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia;
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Abstract
The Huangshui River Basin (HRB) is the main grain production and key implementation region of the “Grain for Green Program” (GGP) of Qinghai Province, and has experienced a quick urbanization during the last 20 years. Therefore, identifying the farmland change and its ecological effects is significant for farmland and ecological protection in the HRB. To this end, this study analyzed the farmland change between 2000 and 2018, based on 1 m spatial resolution farmland data visually interpreted from Google Earth high-resolution images, and then estimated its ecological impact based on the Normalized Difference Vegetation Index (NDVI) data of MODIS, using an ecological impact index of farmland change. The study found that: (1) The farmland area in the HRB decreased from 320.15 k ha in 2000 to 245.01 k ha in 2018, reduced by 23.47% or 1.48% per year, as mainly caused by ecological restoration and built-up land occupation; (2) from 2000 to 2018, the natural environment showed a greening trend in the HRB, with the mean NDVI increasing by 0.74% per year; (3) the farmland changes had a positive ecological effect, contributing 6.67% to the regional increase in the NDVI, but had a negative impact on grain production; (4) it is suggested to strengthen farmland protection by strictly controlling the urban land occupation and over-conversion of farmland in the HRB.
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