Hysteresis response of groundwater depth on the influencing factors using an explainable learning model framework with Shapley values.

Machine learning has been widely used for groundwater prediction. However, the hysteresis response of groundwater depth (GD) to input features has not been fully investigated. This study uses an interpretation method to reveal the interplay between climate, human activity, and GD while considering the response of groundwater to multiple factors. Six factors [precipitation (P), wind speed (WS), temperature (T), population (POP), gross domestic product (GDP), and effective irrigated area (EIA)] were selected to analyze the hysteresis response of GD in terms of the lag correlation coefficient and lag time. The correlation between climatic variables and GD was weaker than that of anthropogenic variables. The lag time between variables and different types of GD was less than four months at most sites, except for EIA and WS in deep groundwater. The SVM model achieved satisfactory performance in 89 % of the sites. If there were sharp changes in GD during the testing period or significant variations in its seasonal patterns at different times, the SVM model performed poorly. The model was interpreted using the Shapley additive explanation method. The impact of POP and GDP on deep groundwater in irrigated areas was higher than that of shallow groundwater. In urban areas with intensive human activities, anthropogenic variables were the main factors affecting shallow groundwater while the impact of climate was gradually increasing in the suburbs. The influence of precipitation on shallow groundwater was decreased after water transfer from the South-to-North Water Diversion project. Furthermore, this study proposed a multifactor-driven conceptual model that can provide recommendations for analyzing groundwater dynamics in similar areas.

Optimization of Sperm Cryopreservation Formulation in Portunus trituberculatus.

Portunus trituberculatus is a very important marine economic species, and its aquaculture industry has been developing rapidly. However, the phenomenon of marine wild capture of P. trituberculatus and germplasm degradation has become increasingly serious. It is necessary to develop the artificial farming industry and carry out germplasm resource protection, for which sperm cryopreservation technology is an effective method. This research compared three methods (mesh-rubbing, trypsin digestion, and mechanical grinding) for acquiring free sperm, and the best method was mesh-rubbing. Then, the optimal cryopreservation conditions were selected, and the optimal formulation was sterile calcium-free artificial seawater, the optimal cryoprotectant was 20% glycerol, and the best equilibrium time was 15 min at 4 °C. The optimal cooling program was suspending the straws at 3.5 cm on the liquid nitrogen surface for 5 min and then storing them in liquid nitrogen. Finally, the sperm were thawed at 42 °C. However, the expression of sperm-related genes and the total enzymatic activities of frozen sperm were significantly decreased (p < 0.05), which showed that sperm cryopreservation damaged the sperm. Our study improves the sperm cryopreservation technology and the yield of aquaculture in P. trituberculatus. Additionally, the study provides a certain technical basis for the establishment of a sperm cryopreservation library of crustaceans.

Influence of land use changes on the remaining available aquifer storage (RAAS): A case study of the Taoerhe alluvial-proluvial fan.

Groundwater resources are important water sources for people living in arid-semiarid China. To solve the problem of continuously declining groundwater levels, groundwater artificial recharge has been widely conducted by using available aquifers. However, the effects of land use changes on the available aquifer storage, especially on the remaining available aquifer storage (RAAS), have not been fully explored. Here, we quantitatively evaluated the effects of land use changes on the RAAS, exemplifying the Taoerhe alluvial-proluvial fan. Independent component analysis (ICA) is used to determine precipitation- and groundwater extraction-affected RAASs, and regression equations are established for land use type areas and precipitation- and groundwater extraction-affected RAASs through stepwise regression and all-subsets regression. An integrated model combining the future land use simulation (FLUS) model and Markov-chain model is established to predict three land use change scenarios in 2036, and the impacts of land use changes on the precipitation- and groundwater extraction-affected RAASs are evaluated. The results show that land use changes were generally active from 2000 to 2018; during this time, the RAAS showed a fluctuating upward trend. Rational land use changes are critical to the RAAS. In the 2036 baseline scenario, the precipitation-affected RAAS is the smallest and the groundwater extraction-affected RAAS is the largest among the three scenarios, contrary to the economic development scenario results. The woodland conservation scenario shows that the groundwater level can be maintained at a stable level with appropriate woodland protection measures to ensure the stability of the RAAS, providing the most promising results for groundwater development and utilization in the study area. These results temporally quantify the effects of land use changes on the precipitation- and groundwater extraction-affected RAASs and provide a reference for developing artificial recharge schemes in arid-semiarid regions and studying the effects of land use changes on available aquifer storages.

Groundwater level modeling framework by combining the wavelet transform with a long short-term memory data-driven model.

Developing models that can accurately simulate groundwater level is important for water resource management and aquifer protection. In particular, machine learning tools provide a new and promising approach to efficiently forecast long-term groundwater table fluctuations without the computational burden of building a detailed flow model. This study proposes a multistep modeling framework for simulating groundwater levels by combining the wavelet transform (WT) with the long short-term memory (LSTM) network; the framework is named the combined WT-multivariate LSTM (WT-MLSTM) method. First, the WT decomposes the groundwater level time series (i.e., the training stage) into a self-control term and a set of external-control terms. Second, Pearson correlation analysis reveals the correlations between the influencing factors (i.e., river stage) and the groundwater table, and the multivariate LSTM model incorporating external factors is built to simulate the external-control terms. Third, the spatiotemporal evolution of the groundwater level is modeled by reconstructing the sequence of each term of the groundwater level time series. Methodological applications in the Liangshui River Basin, Beijing, China and the Cibola National Wildlife Refuge along the lower Colorado River, United States, show that the combined WT-MLSTM model has a higher simulation accuracy than the standard LSTM, MLSTM, and WT-LSTM models. A comparison between the combined WT-MLSTM model and support vector machine (SVM) also demonstrates the advantage of the proposed model. Additional comparison between model forecasts and observed groundwater levels shows the model predictability for short-term time series. Further analysis reveals that the applicability of the combined WT-MLSTM model decreases with increasing distance between the groundwater well and adjacent river channel, or with the increasing complexity of the changing groundwater level patterns, which may be driven by additional controlling factors. This study therefore provides a new methodology/approach for the rapid and accurate simulation and prediction of groundwater level.

Effects of COVID-19 on Urban Population Flow in China.

The COVID-19 epidemic has become a Public Health Emergency of International Concern. Thus, this sudden health incident has brought great risk and pressure to the city with dense population flow. A deep understanding of the migration characteristics and laws of the urban population in China will play a very positive role in the prevention and control of the epidemic situation. Based on Baidu location-based service (LBS) big data, using complex networks method and geographic visualization tools, this paper explores the spatial structure evolution of population flow network (PFN) in 368 cities of China under different traffic control situations. Effective distance models and linear regression models were established to analyze how the population flow across cities affects the spread of the epidemic. Our findings show that: (1) the scope of population flow is closely related to the administrative level of the city and the traffic control policies in various cities which adjust with the epidemic situation; The PFN mainly presents the hierarchical structure dominated by the urban hierarchy and the regional isolation structure adjacent to the geographical location.(2) through the analysis network topology structure of PFN, it is found that only the first stage has a large clustering coefficient and a relatively short average path length, which conforms to the characteristics of small world network. The epidemic situation has a great impact on the network topology in other stages, and the network structure tends to be centralized. (3) The overall migration scale of the whole country decreased by 36.85% compared with the same period of last year's lunar calendar, and a further reduction of 78.52% in the nationwide traffic control stage after the festival. (4) Finally, based on the comparison of the effective distance and the spatial distance from the Wuhan to other destination cities, it is demonstrated that there is a higher correlation between the effective distance and the epidemic spread both in Hubei province and the whole country.

Effects of Urban Producer Service Industry Agglomeration on Export Technological Complexity of Manufacturing in China.

Based on the measurement of producer service industry agglomeration and export technological complexity of manufactured products in 288 Chinese cities from 2000 to 2015, this paper illustrates the evolvement and spatial characteristics of the two factors through visualization figures, and discusses the effects of producer services agglomeration on export technological complexity of manufacturing through robust panel data models. The findings are as follows: as with the influence of industrial connection, empirical outcomes indicate that urban producer service agglomeration can promote technological complexity of export manufacturing on the full-sample level. Visualization analysis shows that the scale of producer service industry agglomeration and the export technological complexity of manufactured products around Chinese cities kept rising constantly during the study period. However, although the export technological complexity displayed a trickle-down effect, the producer service industry agglomeration experienced continuous polarization both on the national and the regional levels. Accordingly, as is shown in the empirical analysis by areas, regions with strong support from producer service industry saw a remarkable promotion in the export manufacturing technology, while the northwest and the northeast gradually lagged behind. Such results sufficiently prove that heterogeneity does exist in the performances of industrial connection between producer service industry and export manufacturing in cities of different regions in China.

Regional Differences and Dynamic Evolution of Carbon Emission Intensity of Agriculture Production in China.

The study of the carbon emission intensity of agricultural production is of great significance for the formulation of a rational agricultural carbon reduction policy. This paper examines the regional differences, spatial-temporal pattern and dynamic evolution of the carbon emission intensity of agriculture production from 1991 to 2018 through the Theil index and spatial data analysis. The results are shown as follows: The overall differences in carbon emission intensity of agriculture production presents a slightly enlarging trend, while the inter-regional differences in carbon emissions intensity is decreasing, but the intra-regional difference of carbon emissions intensity presented an expanding trend. The difference in carbon emission intensity between the eastern and central regions is not obvious, and the difference in carbon emission intensity in the western region shows a fluctuating and increasing trend. The overall differences caused by intra-regional differences; the average annual contribution of intra-regional differences is 67.84%, of which the average annual contribution of western region differences is 64.24%. The carbon emission intensity of agricultural production in China shows a downward trend, with provinces with high carbon emission intensity remaining stable, while provinces with low intensity are expanding. The Global Moran's I index indicates that China's carbon emission intensity of agricultural production shows a clear trend of spatial aggregation. The agglomeration trend of high agricultural carbon emission remains stable, and the overall pattern of agricultural carbon emission intensity shows a pattern of increasing differentiation from east to west.

Spatio-Temporal Comprehensive Measurements of Chinese Citizens' Health Levels and Associated Influencing Factors.

Health is the basis of a good life and a guarantee of a high quality of life. Furthermore, it is a symbol of social development and progress. How to further improve the health levels of citizens and reduce regional differences in citizens' health status has become a research topic of great interest that is attracting attention globally. This study takes 31 provinces (municipalities and autonomous regions) of China as the research object. Through using GIS (Geographic Information System) technology, the entropy method, spatial autocorrelation, stepwise regression, and other quantitative analysis methods, measurement models and index systems are developed in order to perform an analysis of the spatio-temporal comprehensive measurements of Chinese citizens' health levels. Furthermore, the associated influencing factors are analyzed. It has important theoretical and practical significance. The conclusions are as follows: (1) Between 2002 and 2018, the overall health levels of Chinese citizens have generally exhibited an upward trend. Moreover, for most provinces, the health levels of their citizens have improved dramatically, although some provinces, such as Tianjin and Henan, showed a fluctuating downward trend, suggesting that the health levels of citizens in these regions displayed a tendency to deteriorate. (2) The health levels of citizens from China's various provinces showed clear spatial distribution characteristics of clustering, as well as an obvious spatial dependence and spatial heterogeneity. As time goes by, the degree of spatial clustering with regard to citizens' health levels tends to weaken. The health levels of Chinese citizens have developed a certain temporal stability, the overall health status of Chinese citizens shows a spatial differentiation of a northeast-southwest distribution pattern. (3) The average years of education and urbanization rate have a significant positive effect on the improvement of citizens' health levels. The increase of average years of education and urbanization rate can promote the per capita income, which certainly could help improve citizens' health status. The Engel coefficient, urban-rural income ratio, and amount of wastewater discharge all pose a significant negative effect on the improvement of citizens' health levels, these three factors have played important roles in hindering the improvements of citizen health.

Dynamic analysis of agricultural carbon emissions efficiency in Chinese provinces along the Belt and Road.

To better understand the agricultural resources and environmental problems of the provinces along The Belt and Road in China, it is critical to investigate their agricultural carbon emission efficiency and evolutionary trends. Based on the panel data of 18 key provinces and cities between 2006 and 2015, this paper evaluated the agricultural carbon emission efficiency with the data envelopment analysis-Malmquist model and further explored their dynamic evolutionary trends. There were several main findings. First, the efficiency levels of agricultural carbon emissions showed significant regional differentiation among the areas, with that along the 21st-Century Maritime Silk Road being much higher than that along the Silk Road Economic Belt. Second, technical efficiency was the key factor that restricted the improvement of the comprehensive efficiency of agricultural carbon. Third, most provinces invested in too many redundant and unreasonably allocated resources, showing a trend of diminishing returns to scale. Last, According to dynamic evolution analysis, the total productivity still demonstrated a diminishing trend. This paper provides some suggestions for effectively improve the efficiency of agricultural carbon emissions in China, such as optimize the agricultural industrial structure, increasing the investment of carbon emission reduction technology, and implementing a carbon emission quota clearing system. This paper contributes to the improvement of the environment in China.

Prohibitin-mediated mitochondrial ubiquitination during spermiogenesis in Chinese mitten crab Eriocheir sinensis.

The sperm of Eriocheir sinensis has a cup-shaped nucleus that contains several mitochondria embedded at the opening of the cup. The acrosome vesicle also contains derivants of mitochondria. The mitochondria distribution pattern involves a decrease in the number and changes in the structure and transportation of these organelles. The decreased number of sperm mitochondria is achieved through autophagy or the ubiquitination pathway. Prohibitin (PHB), the mitochondria inner membrane protein, is an evolutionarily highly conserved protein, is closely associated with spermatogenesis and sperm quality control and is also a potential substrate of ubiquitination. However, whether PHB protein mediates the ubiquitination pathway of sperm mitochondria in crustacean animals remains poorly understood. In the present study, we revealed that PHB, a substrate of ubiquitin, participates in the ubiquitination and degradation of mitochondria during spermiogenesis in E. sinensis. To confirm this finding, we used shRNA interference to reduce PHB expression and an overexpression technique to increase PHB expression in vitro. The interference experiment showed that the reduced PHB expression directly affected the polyubiquitination level and mitochondria status, whereas PHB overexpression markedly increased the polyubiquitination level. In vitro experiments also showed that PHB and its ubiquitination decide the fate of mitochondria.