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With global climate change and increasingly extreme weather conditions, the water quality of the Lijiang River Basin (LRB) is facing huge threats. At present, there is still a lack of systematic research on water quality indicators and the influence of indirect factors such as meteorological factors on it in the LRB. Therefore, this study is based on the meteorological, hydrological, and water quality data of the LRB from 2012 to 2018, using the Mann–Kendall test, Morlet wavelet method, Spearman's rank correlation coefficient, sensitivity, and contribution rate to quantitative analysis of the relationship between climate conditions and water quality indicators. The results show that the change trends of these hydrological and climatic conditions have almost no significant sudden change; precipitation and streamflow are decreasing each year; the streamflow trend exhibits time hysteresis; precipitation has a stronger influence downstream than on the local area; water quality indicators of both stations exhibited a change period of around 18 to 20 months, with the exception of pH. Water quality indicators are insensitive to precipitation and streamflow, and sensitive to humidity and wind speed; DO was negatively correlated with climate indicators apart from wind speed; almost all water quality indicators in Yangshuo are highly sensitive to air temperature, and the contribution rate of air temperature to ORP and TP reached 4.81% and 3.56%, respectively; sunshine duration has a positive impact on reducing NH4-N and TP. The difference between Yangshuo and Guilin is mostly due to the input of external sources on both sides of the Lijiang River, which results in variations in climate conditions sensitivities. [ABSTRACT FROM AUTHOR]

Landscape patterns have a substantial effect on non-point source (NPS) pollution in watersheds. Facilitating sustainable development of mountain-rural areas is a major priority for China. Knowledge of the impacts of various landscapes on water quality in these areas is critical to meeting environmental goals. This study applied the Soil and Water Assessment Tool (SWAT) to create a hydrologic and water quality model of the study watershed; then, the relationship between water quality and landscape patterns was investigated using multiple linear regression and redundancy analysis. The results show that the western sub-basins had higher nitrogen pollution loads, and the total nitrogen concentration reached a maximum value of 3.91 mg/L; the eastern sub-basins had a higher pollution load of phosphorous featured by maximum total phosphorous concentration of 2.15 mg/L. The water quality of the entire watershed in all scenarios tended to deteriorate over time. Landscape metrics accounted for 81.7% of the total variation in pollutant indicators. The percentage of forest landscape was negatively correlated with NPS pollution, while other types of landscape showed a positive correlation. The patch density, landscape shape index, and largest patch index of urban and agricultural lands were negatively correlated with pollutant concentrations. Upland landscapes contributed more pollutants than paddy fields. Some measures, e.g., returning grassland and farmland to forest in steep regions and replacing upland crops with paddy fields, were recommended for mitigating NPS pollution in the study watershed. [ABSTRACT FROM AUTHOR]

Talent programmes are treated as a strategic foundation for social–economic development in China. With increasing levels of funding for basic research, talent programmes in basic research are becoming more complex. This increased complexity leads to inefficiencies because it is difficult to coordinate and manage these talent programmes effectively. This paper reports a survey of talent programmes in basic research in China. The results show that talent programmes in basic research have not yet formed an integrated system and that there exist some weaknesses in integration, structure, hierarchy and chronological order. Based on these conclusions, this paper proposes a framework for the talent programme system in basic research using system theory. Furthermore, measures to address weaknesses in the existing talent programme system are provided and analysed according to China's national talent strategy. These measures should be helpful for promoting the operation of talent programmes and optimising their overall performance. [ABSTRACT FROM AUTHOR]

Water vapor is one of the most important parameters in climatic studies. MODerate-resolution Imaging Spectroradiometer (MODIS) is a key instrument and can provide spatially continuous precipitable water vapor (PWV) products. This study was focused on the performance evaluation of the MODIS near-infrared PWV product (MOD-NIR-PWV) over China. For a comprehensive assessment of the performance of MOD-NIR-PWV, PWV retrieved from the measurements at the global navigation satellite systems (GNSS) stations (i.e., GNSS-PWV) and the ERA5 reanalysis dataset (ERA-PWV) from 2013 to 2018 were used as the reference. To investigate the suitability of using ERA-PWV as the reference for the evaluation, ERA-PWV was compared to the high-accuracy GNSS-PWV at 246 GNSS stations and PWV retrieved from radiosonde observations (RS-PWV) at 78 radiosonde stations over China. The results showed that the mean bias and mean root-mean-square (RMS) of the differences between ERA-PWV and GNSS-PWV across all the stations were 0.5 and 1.7 mm, respectively, and the mean correlation coefficient of the two datasets was above 0.96. The values were 0.4 and 1.9 mm and 0.97, respectively, for the differences between ERA-PWV and RS-PWV. This suggests the suitability of ERA-PWV as the reference for the evaluation of MOD-NIR-PWV. In addition, MOD-NIR-PWV was compared with both GNSS-PWV and ERA-PWV, and their mean bias and mean RMS were 2.9 and 3.8 mm (compared to GNSS-PWV) and 2.1 and 3.0 mm (compared to ERA-PWV), respectively. The positive bias values and the non-normal distribution of the differences between MOD-NIR-PWV and both reference datasets imply that a considerable systematic overestimation of MOD-NIR-PWV over China may exist. To mitigate the systematic bias, ERA-PWV was utilized as the sample data due to its spatial continuities, and a grid-based calibration model was developed based on the annual and semiannual periodicities in the differences between MOD-NIR-PWV and ERA-PWV at each grid point. After applying the calibration model to correct MOD-NIR-PWV, the calibrated MOD-NIR-PWV was compared with ERA-PWV and GNSS-PWV for precision and accuracy analysis, respectively. The comparison showed that the model could significantly improve the precision by 94% and accuracy by 53%, which manifested the effectiveness of the calibration model in improving the performance of MOD-NIR-PWV over China. [ABSTRACT FROM AUTHOR]

As one of the atmosphere propagation delays, the tropospheric delay is a significant error source that should be properly handled in high-precision global navigation satellite system (GNSS) applications. We propose an improved zenith tropospheric delay (ZTD) modeling method whereby the piecewise model of the atmospheric refractivity is introduced. Compared with using the exponential model to fit ZTD in vertical direction, the ZTD piecewise model has a better performance. Based on ERA5 2.5° × 2.5° reanalysis data produced by the European Centre for Medium-Range Weather Forecasting (ECMWF) from 2013 to 2017, we establish the regional gridded ZTD model (RGZTD) using a trigonometric function for China and the surrounding areas, which ranges from 70° E to 135° E in longitude and from 15° N to 55° N in latitude. To verify the performance of RGZTD model, the ERA5 ZTD data in 2017–2018, the radiosonde ZTD data from 86 radiosonde stations over China in 2017–2018, and the tropospheric delay products on 251 GNSS stations from Crustal Movement Observation Network of China (CMONOC) in 2016–2017 are used as external compliance check data. The results show that the overall accuracy of RGZTD model is better than that of exponential model, UNB3m model, and GPT3 model. Moreover, the accuracy can be improved by about 13.4%, 7.1%, and 6.2% when ERA5 reanalysis data, radiosonde data, and CMONOC data are used as reference values, respectively. High-accuracy ZTD data can be provided because the RGZTD model takes into account the vertical variation of ZTD through the new piecewise model. [ABSTRACT FROM AUTHOR]

• SWAT has good applicability to the hydrological simulation of the karst area. • Severe storms primarily occur during April to July and November. • The risk of flooding is projected to increase under the five SSP-based future land use scenarios. • The severity of flood events is expected to escalate during the dry season, with runoff coefficients potentially increasing by up to 16%. With economic and social development, the inevitable conflict between growing populations and land use change has become increasingly prominent. In karst areas, such as the Lijiang River Basin (LRB) in South China, land use has undergone rapid and intense changes over the past few decades due to urbanization and agricultural development. Assessing the hydrological effects of future land use change scenarios in karst areas is essential for estimating potential flood risks. In this study, we constructed hydrological models for the LRB based on a widely used hydrological model (SWAT, Soil and Water Assessment Tool), analyzed the runoff coefficient (R c) at event scale, and evaluated the hydrological effects under future land use scenarios in 2100 based on five shared socio-economic pathways (SSPs). The results indicate that the simulated streamflow effectively replicated the hydrographs of the LRB. The model exhibited good performance, as evidenced by daily streamflow simulation with NSE greater than 0.65 and PBIAS within the range of ± 15 %. This demonstrates the applicability of SWAT in karst areas. The analysis of storm events revealed that severe storms in the LRB mainly took place between April and July and in November, with relatively long durations and high R c values. Under all five SSP-based future land use scenarios, it is predicted that flood risk will increase in the LRB. Notably, the severity of flood events during the dry season is expected to escalate, with R c potentially increasing by up to 16 %. To address environmental degradation and achieve sustainable development, it is imperative to adopt appropriate environment-friendly land use practices and implement effective land management strategies. [ABSTRACT FROM AUTHOR]

As the climate and the external environment have changed, the environmental factors of the Lijiang River Basin (LRB) have changed, posing new threats to the environmental quality, ecosystem balance, and management and protection of the water environment of the Lijiang River. Water quality indicators and environmental factors vary spatially along the Lijiang River, which runs through urban areas, farmland, and karst areas. However, research on the response of water quality to water environmental factors is still lacking. Within this context, this study considered statistical methods and hydrological, meteorological, and water quality data of the middle and lower reaches of the Lijiang River from 2012 to 2018, expounded on the temporal and spatial change characteristics and evolution trends of water quality indicators; we analyzed the correlation between water quality indicators and environmental factors; we quantitatively assessed the sensitivity and contribution rate of water quality indicators to environmental factors. The results demonstrated that rainfall feedback on the river streamflow was lagging, and upstream precipitation often affected downstream streamflow. The water quality in the upper reaches of Guilin has improved year by year, and pollution levels have increased slightly when flowing through the urban area of Guilin. In spite of this, it still falls within the range of self-purification. River characteristics heavily influence the impact of environmental factors on water quality indicators; in contrast, the effects of different locations along the same river are more similar. Four water quality indicators are negatively correlated with water temperature, pH, and dissolved oxygen (DO). The sensitivities of ammonia nitrogen (NH 4 -N) and chemical oxygen demand (COD Mn ) to streamflow increase with the flow direction. The contribution rates of DO-to-total phosphorus (TP) and pH-to-TP are over -6%. Water temperature is the major contributing factor in the Lijiang River, while DO has a higher contribution in tributaries. The external sources affect the concentration of various water quality indicators and the sensitivity of water quality indicators to the external environment. There should be a series of measures implemented to reduce pollution, such as using oxygenation or chemical means to increase pH in Dahe and Yangshuo to control water pollutants. Tourism and particular karst topography make LRB's calculations unique, but the research method can be applied to other watersheds as well.