Groundwater level declines in Tianjin, North China: climatic variations and human activities

2022 ◽  
Author(s):  
Renjie Qin ◽  
Qiuyang Song ◽  
Yonghong Hao ◽  
Guanghong Wu
Keyword(s):  
Groundwater Level ◽  
Human Activities ◽  
North China ◽  
Climatic Variations

scholarly journals Improving the Resolution and Accuracy of Groundwater Level Anomalies Using the Machine Learning-Based Fusion Model in the North China Plain

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 46
Author(s):  
Gangqiang Zhang ◽  
Wei Zheng ◽  
Wenjie Yin ◽  
Weiwei Lei
Keyword(s):  
Machine Learning ◽  
Data Fusion ◽  
Groundwater Level ◽  
North China Plain ◽  
North China ◽  
Gradient Boosting ◽  
Fusion Model ◽  
The North ◽  
The North China Plain ◽  
Prediction Module

The launch of GRACE satellites has provided a new avenue for studying the terrestrial water storage anomalies (TWSA) with unprecedented accuracy. However, the coarse spatial resolution greatly limits its application in hydrology researches on local scales. To overcome this limitation, this study develops a machine learning-based fusion model to obtain high-resolution (0.25°) groundwater level anomalies (GWLA) by integrating GRACE observations in the North China Plain. Specifically, the fusion model consists of three modules, namely the downscaling module, the data fusion module, and the prediction module, respectively. In terms of the downscaling module, the GRACE-Noah model outperforms traditional data-driven models (multiple linear regression and gradient boosting decision tree (GBDT)) with the correlation coefficient (CC) values from 0.24 to 0.78. With respect to the data fusion module, the groundwater level from 12 monitoring wells is incorporated with climate variables (precipitation, runoff, and evapotranspiration) using the GBDT algorithm, achieving satisfactory performance (mean values: CC: 0.97, RMSE: 1.10 m, and MAE: 0.87 m). By merging the downscaled TWSA and fused groundwater level based on the GBDT algorithm, the prediction module can predict the water level in specified pixels. The predicted groundwater level is validated against 6 in-situ groundwater level data sets in the study area. Compare to the downscaling module, there is a significant improvement in terms of CC metrics, on average, from 0.43 to 0.71. This study provides a feasible and accurate fusion model for downscaling GRACE observations and predicting groundwater level with improved accuracy.

scholarly journals Spatial and temporal variations of CO<sub>2</sub> mole fractions observed at Beijing, Xianghe and Xinglong in North China

2021 ◽  
Author(s):  
Yang Yang ◽  
Minqiang Zhou ◽  
Ting Wang ◽  
Bo Yao ◽  
Pengfei Han ◽  
...  
Keyword(s):  
Seasonal Variations ◽  
Human Activities ◽  
North China ◽  
Terrestrial Ecosystem ◽  
Temporal Variations ◽  
Spatial And Temporal Variations ◽  
Boundary Layer Height ◽  
The Mean ◽  
The Impact ◽  
First Time

Abstract. Atmospheric CO2 mole fractions are observed at Beijing (BJ), Xianghe (XH), and Xinglong (XL) in North China using the Picarro G2301 Cavity Ring-Down Spectroscopy instruments. The measurement system is described comprehensively for the first time. The geo-distances among these three sites are within 200 km, but they have very different surrounding environments: BJ is inside the megacity; XH is in the suburban area; XL is in the countryside on a mountain. The mean and standard deviation of CO2 mole fractions at BJ, XH, and XL between October 2018 and September 2019 are 448.4 ± 12.8 ppm, 436.0 ± 9.2 ppm and 420.6 ± 8.2 ppm, respectively. The seasonal variations of CO2 at these three sites are similar, with a maximum in winter and a minimum in summer, which is dominated by the terrestrial ecosystem. However, the seasonal variations of CO2 at BJ and XH are more affected by human activities as compared to XL. By using CO2 at XL as the background, CO2 enhancements are observed simultaneously at BJ and XH. The diurnal variations of CO2 are driven by the boundary layer height, photosynthesis and human activities at BJ, XH and XL. Moreover, we address the impact of the wind on the CO2 mole fractions at BJ and XL. This study provides an insight into the spatial and temporal variations of CO2 mole fractions in North China.

scholarly journals Response of a Coastal Groundwater System to Natural and Anthropogenic Factors: Case Study on East Coast of Laizhou Bay, China

2020 ◽  
Vol 17 (14) ◽  
pp. 5204
Author(s):  
Ya Sun ◽  
Shiguo Xu ◽  
Qin Wang ◽  
Suduan Hu ◽  
Guoshuai Qin ◽  
...  
Keyword(s):  
Human Factors ◽  
Groundwater Level ◽  
Human Activities ◽  
Research Area ◽  
Laizhou Bay ◽  
Natural Background ◽  
Groundwater System ◽  
Irrigated Area ◽  
Groundwater Environment ◽  
Groundwater Samples

With a shifting climate pattern and enhancement of human activities, coastal areas are exposed to threats of groundwater environmental issues. This work takes the eastern coast of Laizhou Bay as a research area to study the response of a coastal groundwater system to natural and human impacts with a combination of statistical, hydrogeochemical, and fuzzy classification methods. First, the groundwater level dynamics from 1980 to 2017 were analyzed. The average annual groundwater level dropped 13.16 m with a descent rate of 0.379 m/a. The main external environmental factors that affected the groundwater level were extracted, including natural factors (rainfall and temperature), as well as human activities (irrigated area, water-saving irrigated area, sown area of high-water-consumption crops, etc.). Back-propagation artificial neural network was used to model the response of groundwater level to the above driving factors, and sensitivity analysis was conducted to measure the extent of impact of these factors on groundwater level. The results verified that human factors including irrigated area and water-saving irrigated area were the most important influencing factors on groundwater level dynamics, followed by annual precipitation. Further, groundwater samples were collected over the study area to analyze the groundwater hydrogeochemical signatures. With the hydrochemical diagrams and ion ratios, the formation of groundwater, the sources of groundwater components, and the main hydrogeochemical processes controlling the groundwater evolution were discussed to understand the natural background of groundwater environment. The fuzzy C-means clustering method was adopted to classify the groundwater samples into four clusters based on their hydrochemical characteristics to reveal the spatial variation of groundwater quality in the research area. Each cluster was spatially continuous, and there were great differences in groundwater hydrochemical and pollution characteristics between different clusters. The natural and human factors resulted in this difference were discussed based on the natural background of the groundwater environment, and the types and intensity of human activity.

scholarly journals Quantitative Detection and Attribution of Groundwater Level Variations in the Amu Darya Delta

Water ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 2869
Author(s):  
Xiaohui Pan ◽  
Weishi Wang ◽  
Tie Liu ◽  
Yue Huang ◽  
Philippe De Maeyer ◽  
...  
Keyword(s):  
Climate Change ◽  
Correlation Analysis ◽  
Groundwater Level ◽  
Human Activities ◽  
Pearson Correlation ◽  
Aral Sea ◽  
Irrigation Area ◽  
Amu Darya ◽  
Pearson Correlation Analysis ◽  
Groundwater Dynamic

In the past few decades, the shrinkage of the Aral Sea is one of the biggest ecological catastrophes caused by human activity. To quantify the joint impact of both human activities and climate change on groundwater, the spatiotemporal groundwater dynamic characteristics in the Amu Darya Delta of the Aral Sea from 1999 to 2017 were analyzed, using the groundwater level, climate conditions, remote sensing data, and irrigation information. Statistics analysis was adopted to analyze the trend of groundwater variation, including intensity, periodicity, spatial structure, while the Pearson correlation analysis and principal component analysis (PCA) were used to quantify the impact of climate change and human activities on the variabilities of the groundwater level. Results reveal that the local groundwater dynamic has varied considerably. From 1999 to 2002, the groundwater level dropped from −189 cm to −350 cm. Until 2017, the groundwater level rose back to −211 cm with fluctuation. Seasonally, the fluctuation period of groundwater level and irrigation water was similar, both were about 18 months. Spatially, the groundwater level kept stable within the irrigation area and bare land but fluctuated drastically around the irrigation area. The Pearson correlation analysis reveals that the dynamic of the groundwater level is closely related to irrigation activity within the irrigation area (Nukus: −0.583), while for the place adjacent to the Aral Sea, the groundwater level is closely related to the Large Aral Sea water level (Muynak: 0.355). The results of PCA showed that the cumulative contribution rate of the first three components exceeds 85%. The study reveals that human activities have a great impact on groundwater, effective management, and the development of water resources in arid areas is an essential prerequisite for ecological protection.

Monitoring Models for Plastic Debris

2010 ◽  
Vol 29-32 ◽  
pp. 479-483
Author(s):  
Ting Ting Wang ◽  
Yuan Biao Zhang ◽  
Zhi Ning Liang ◽  
Wei Huang
Keyword(s):  
North Pacific ◽  
Human Activities ◽  
Kuroshio Current ◽  
Marine Litter ◽  
Plastic Debris ◽  
Climatic Variations ◽  
The North ◽  
Computer Based ◽  
Current Area ◽  
The North Pacific

To strengthen monitoring for plastic debris in the ocean, our paper compared debris distributions of 2 special Garbage Patches (The North Pacific Central Gyre and Kuroshio Current area). And then we developed a computer-based optimal searching model to monitor formation and changes of debris in the oceans. We found that winds belts, currents, and regional human activities along with seasonal climatic variations can influence marine litter patterns and trends in deposition.

Assessing the relative role of climate change and human activities in desertification of North China from 1981 to 2010

2018 ◽  
Vol 13 (1) ◽  
pp. 43-54 ◽  
Author(s):  
Duanyang Xu ◽  
Alin Song ◽  
Dajing Li ◽  
Xue Ding ◽  
Ziyu Wang
Keyword(s):  
Climate Change ◽  
Human Activities ◽  
North China ◽  
Relative Role

scholarly journals Groundwater Vulnerability to Pollution in Kediri City, East Java Province, Indonesia

2021 ◽  
Vol 930 (1) ◽  
pp. 012012
Author(s):  
T Widodo ◽  
W Wilopo ◽  
A Setianto
Keyword(s):  
Water Resource ◽  
Groundwater Level ◽  
Groundwater Pollution ◽  
Human Activities ◽  
Shallow Groundwater ◽  
Groundwater Vulnerability ◽  
Shallow Aquifers ◽  
Groundwater Occurrence ◽  
High Level ◽  
Overlying Strata

Abstract Groundwater is a water resource that is still a mainstay for humans. The need for groundwater increases with the growth of population and the development of the industrial and agricultural sectors. The residents of Kediri City still use wells from shallow aquifers to fulfill their water needs. Shallow aquifers are prone to pollution due to the influence of shallow groundwater depths and human activities. The purpose of this study is to determine the vulnerability of groundwater pollution in Kediri City. Groundwater vulnerability was conducted by the GOD method (Groundwater Occurrence, Overlaying Lithology, and Depth of Groundwater) that consists of 3 parameters, namely the groundwater confinement, the type of overlying strata, and the depth of the groundwater level. The analysis results show that the level of groundwater vulnerability according to the GOD method in Kediri City consists of moderate and high classes. The western and the eastern part of Kediri City is classified as a high level of vulnerability. In contrast, in the middle of Kediri City, it tends to experience a moderate level of vulnerability.

scholarly journals Characteristics and causes of groundwater dynamic changes in Naoli River Plain, Northeast China

2020 ◽  
Vol 20 (7) ◽  
pp. 2603-2615
Author(s):  
Du Xinqiang ◽  
Chang Kaiyang ◽  
Lu Xiangqin
Keyword(s):  
Groundwater Level ◽  
Human Activities ◽  
Dynamic Change ◽  
Kendall Test ◽  
Hydrodynamic Characteristics ◽  
Groundwater Exploitation ◽  
River Plain ◽  
Observation Wells ◽  
Year 2000 ◽  
Groundwater Dynamic

Abstract Identification of groundwater dynamic behavior and its mechanism is the basis of groundwater protection and management. In Naoli River Plain (NRP), an important agricultural cultivation base and wetland in China, the trend of groundwater dynamic change is complicated under natural climate and human activities. Based on the methods of the Mann–Kendall test, Sen's slope estimation and correlation analysis, groundwater hydrodynamic characteristics and causes were identified. Within 68 observation wells from year 2000 to 2015, there are 28, 30 and 10 wells, accounting for 41.2%, 44.1% and 14.7%, that belong to rising, declining and relatively stable change trends, respectively. The average groundwater rising and declining rates are 0.19 m/year and 0.26 m/year respectively. The groundwater level was increasing or stable in the areas where there was no intensive groundwater exploitation, such as wetland, mountain foregrounds, residential lands and dry farmland. The groundwater level was declining obviously in the paddy fields with groundwater as the source of irrigation water. Thus, the groundwater dynamics in NRP were affected both by human activities of groundwater irrigation and climate change. The carrying capacity of groundwater for agricultural cultivation has been overloaded in some areas, and a conjunctive utilization of surface water and groundwater is needed urgently in NRP.

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