Multi-scale response relationship between water quality of rivers entering lakes from different pollution source areas and land use intensity: a case study of the three lakes in central Yunnan.

As the main supply source of lakes, the water quality of the rivers entering the lakes directly determines the water safety and sustainable development of the lakes. Human activities are the direct cause of changes in the water quality of rivers entering lakes, and land use intensity is the direct manifestation of human activities on the land surface. Although significant progress has been made in studying the relationship between land use changes and water quality in lakes, there is still a lack of research on exploring the relationship between land use intensity and water quality at multiple scales, especially in comparative studies of different pollution source areas. To address this problem, this study used Pearson's correlation analysis and land use intensity index method to explore the response relationship between river water quality and land use intensity at different spatial and temporal scales and different pollution source areas using three lakes in central Yunnan as examples. The results showed that land use intensity was generally positively correlated with water quality, but the response relationship between land use intensity and different water quality indicators was significantly different at different scales and for different pollution source areas. Compared to non-urban areas, the impact of land use intensity on water quality is more significant in urban areas. Compared to the rainy season, the correlation between CODNa, TP, and NH3-N values and land use intensity is stronger during the dry season, while the correlation between COD, TN, and land use intensity is weaker during the dry season. When viewed at different scales, different water quality indicators have different scale effects, but overall, the larger the scale, the stronger the correlation. Therefore, in the work of lake water environmental governance, it is necessary to consider comprehensively from multiple scales and perspectives and adopt measures that are more suitable for regional water pollution prevention and control.

[Spatial heterogeneity and driving factors of ecosystem water yield service in Yunnan Province, China based on Geodetector]. / åŸºäºŽåœ°ç†æŽ¢æµ‹å™¨çš„äº‘å—çœç”Ÿæ€ç³»ç»Ÿäº§æ°´æœåŠ¡çš„ç©ºé—´å¼‚è´¨æ€§åŠé©±åŠ¨å› ç´ .

Water yield is an important ecosystem service. It is the key to maintain ecological security and sustainable development to accurately grasp the spatial heterogeneity characteristics and identify the key driving factors of water yield in different regions. Taking Yunnan Province with significant geospatial heterogeneity as the research area, we used InVEST model to simulate the temporal and spatial variations of water yield in Yunnan Province from 1992 to 2019. The spatial characteristics of driving factors, such as climate, vegetation, soil, terrain, land use, on water yield service were analyzed through Geodetector. The results showed that water yield of Yunnan Province showed a fluctuating trend of increasing at first and decreasing later from 1992 to 2019, with a similar spatial distribution pattern in each year, and an overall trend of gradually decreasing from northwest, west and southwest to central and east. Climatic factors (precipitation and actual evapotranspiration) were the main driving factors leading to spatial differentiation of water yield. In different watershed divisions, the impact of each driving factor on water yield had significant spatial heterogeneity: the watersheds dominated by precipitation were mainly distributed in the west of Yunling-Yuanjiang line, the Irrawaddy River, the upper reaches of Nujiang River, the lower reaches of Nujiang River, the upper reaches of Lancang River, the upper reaches of Jinsha River, Yuanjiang River and Lixian River areas. As for the east of Yunling-Yuanjiang line, in karst landform areas (Nanguang River, Chishui River, Wujiang River, Youjiang River and Panlong River) and the lower reaches of Jinsha River with high population density and shortage of cultivated land, actual evapotranspiration and land use type were the leading factors controlling the spatial pattern of water yield. The results could provide a reference for water resources management policy and ecological civilization construction in Yunnan Province, with a certain guiding significance to promote the optimization and sustainable development of ecosystem services in complex plateau-mountain area.

Research on the spatiotemporal coupling relationships between land use/land cover compositions or patterns and the surface urban heat island effect.

Urbanization leads to changes in landscape configuration and land use/land cover (LULC) patterns, and these changes are important factors affecting the surface urban heat island (SUHI) effect. However, from the perspective of spatiotemporal changes, quantitative analytical results regarding the impacts of the LULC composition, configuration, and pattern in inland plateau lakeside cities on the SUHI effect, and the responsive relationships among these factors remain unclear. By combining satellite remote sensing data with analytical methods, such as urban-rural gradients, spatial statistics, and landscape pattern indices, the impacts of LULC changes on the SUHI effect in Kunming, China, are revealed. The results show the following. (1) The explosive growth in impervious surfaces (ISs) caused by urbanization, leading to changes in the LULC composition, configuration and pattern, is the main reason for the deterioration of the SUHI effect. Over the past 30 years, Kunming's ISs have increased by 304.58 km2, SUHI has expanded by 764.26 km2, and the regional average land surface temperature (LST) has increased by 1 °C. (2) This study also found that a large area of bare ground is another important reason for the sharp rise in LST, explaining why bare land (BL) has the highest average LST (28.72 °C). (3) The pattern of LULC can well explain the spatial distribution characteristics of SUHIs. The normalized difference built-up index (NDBI), normalized difference bareness index (NDBaI), and LST have the same change curve along the urban-rural gradient, while the normalized difference vegetation index (NDVI), modified normalized difference water index (MNDWI), and LST have opposite trends. (4) ISs and water body (WB) are the main types of warming and cooling, respectively, but the warming effect of ISs is greater than the cooling effect of WB. From the average value of the correlation coefficient with LST, NDBI (0.84) > MNDWI (-0.63). (5) Kunming's remote sensing index values do not have simple linear relationships with the LST. NDBaI, NDBI, and LST show significant exponential relationships, and NDVI, MNDWI, and LST show significant quadratic polynomial relationships. (6) The dominant landscape type determines the correlation between the landscape shape index (LSI) and the LST of green spaces (GSs). (7) Adopting a simple and regular landscape layout can effectively reduce the SUHI effect. These research results could provide a scientific decision-making basis for the spatial urban planning and ecological construction of Kunming and could have practical significance for guiding the green, healthy, and sustainable development of the city.

[Identification of important biodiversity areas by InVEST model considering opographic relief: A case study of Yunnan Province, China]. / 顾及地形起伏的InVESTæ¨¡åž‹çš„ç”Ÿç‰©å¤šæ ·æ€§é‡è¦åŒºè¯†åˆ«­­ä»¥äº‘南省为例.

Accurately identifying important areas of biodiversity is one of the key issues in ecology and biodiversity research, as well as an important basis for the delineation of the red line for ecologi-cal protection and territorial spatial planning. With China's typical plateau mountainous area (Yunnan Province) as a research case, we used the net primary productivity (NPP) quantitative index method, InVEST model and InVEST model focusing on topographic relief to identify biodiversity important areas. The results showed that NPP quantitative index method was not suitable for the plateau mountainous areas with obvious vertical zonal development. The identified area contained only 26.1% of the protected areas. The InVEST model had higher identification accuracy than the NPP quantitative index method in Yunnan Province. The identified area covered 49.4% of the protected natural areas. Fragmentation was obvious in northwest Yunnan. The InVEST model focusing on topographic relief improved the identification accuracy of important areas of biodiversity, including 71.7% of nature reserves. The deficiency of NPP quantitative index method in water area identification was made up and the fragmentation problem of InVEST model was solved. The area of biodiversity important areas was 119466.94 km2, accounting for 30.3% of the total land area of Yunnan Province. The spatial distribution showed a pattern of "three barriers, two zones and one region for multi-point development".

Assessing the quantitative relationships between the impervious surface area and surface heat island effect during urban expansion.

As an important component of underlying urban surfaces, the distribution pattern and density of the impervious surface area (ISA) play an important role in the generation of surface urban heat island (SUHI) effects. However, the quantitative and localized exploration of the ISA's influence on SUHIs in the process of urban expansion from the perspective of temporal and spatial changes is still not clear. Based on multisource remote sensing data, the SUHI effect of urban expansion is revealed by using geospatial analysis methods such as profile, difference and regression analysis. The results show the following: (1) urban expansion plays a significant role in aggravating SUHIs. Overall, the ISA and land surface temperature (LST) have obvious consistency in terms of spatial distribution patterns. However, local spatial differentiation is significant. The areas with the highest LST were not concentrated in the downtown area with the highest ISA but were scattered in the cultivated land and exposed surface areas under development in the northern part of the city. (2) In general, the ISA can explain the spatial distribution of LST well, there is an obvious positive correlation between them, and the quadratic polynomial function is the best fitting model between them. (3) The density and spatial allocation of ecological elements, such as green space and water bodies, play an important role in alleviating SUHIs. This study found that the urban center with the highest ISA coverage rate has no significant SUHI due to the reasonable allocation of green space and water bodies. The research results can provide a scientific basis for future urban planning and ecological environment construction.

Monitoring the trends of water-erosion desertification on the Yunnan-Guizhou Plateau, China from 1989 to 2016 using time-series Landsat images.

The Yunnan-Guizhou Plateau (YGP) is a typical ecologically fragile region in southwest China. Water-erosion desertification (WED) is one of the most significant environmental and socio-economic issues on the YGP and has seriously restricted the socio-economic development of this region. However, the research on monitoring of the desertification trends in this region has been limited to long time-series Landsat imagery. The objectives of this research were to monitor the WED trends on the YGP using time-series Landsat imagery data from 1989 to 2016. In this paper, we present a multi-indicator rule-based method, which was used to map the WED on the YGP during this period. The results show that the addition of multiple indicators improved the WED classification accuracy to 90.61%. Overall, the following results were obtained by using the proposed method. (1) The slight desertification area on the YGP increased from 89,617.09 km2 in 1989 to 100,976.47 km2 in 2016 with an annual growth ratio (AGR) of 0.48%, the moderate desertification area increased from 80,276.65 km2 in 1989 to 90,768.39 km2 in 2016 with an AGR of 0.50%, and the severe desertification area increased from 8149.3 km2 in 1989 to 13,220.16 km2 in 2016 with an AGR of 2.39%. (2) The WED expansion on the YGP can be divided into three stages. Firstly, the total WED area increased slowly from 17.80×104 km2 in 1989 to 17.98×104 km2 in 2010 with an AGR of 0.05%. Then, the WED rapidly expanded from 17.98×104 km2 in 2010 to 20.28×104 km2 in 2013 with an AGR of 4.26%. Finally, the WED increased slightly from 20.28×104 km2 in 2013 to 20.50×104 km2 in 2016 with an AGR of 0.36%. The total areas of the different degrees of WED decreased in 1992, 1998, 2001, and 2004. (3) The driving factors of WED were analyzed based on the Geographically Weighted Regression (GWR) model. We found that precipitation, vegetation area, and gross domestic product have key roles in the processes of desertification reversion and development. However, the regression coefficients between WED and these factors exhibited considerable spatial variations. The regression coefficients of the key driving factors showed different spatial distributions based on the GWR model in the YGP. The research results can provide scientific reference information for the prevention and control of WED in the YGP.

Multi-scale relationship between land use/land cover types and water quality in different pollution source areas in Fuxian Lake Basin.

The spatial-temporal evolution of land use and land cover (LULC) and its multi-scale impact on the water environment is becoming highly significant in the LULC research field. The current research results show that the more significant scale impact on LULC and water quality in the whole basin and the riparian buffer scale is unclear. A consensus has not been reached about the optimal spatial scale problem in the relationship between the LULC and water quality. The typical lake basin of the Fuxian Lake watershed was used as the research area and the scale relationship between the LULC and water quality was taken as the research object. High resolution remote sensing images, archival resources of surveying, mapping and geographic information, and the monitoring data of water quality were utilized as the main data sources. Remote sensing and Geometric Information Technology were applied. A multi-scale object random forest algorithm (MSORF) was used to raise the classification accuracy of the high resolution remote sensing images from 2005 to 2017 in the basin and the multi-scale relationship between the two was discussed using the Pearson correlation analysis method. From 2005 to 2017, the water quality indicators (Chemical Oxygen Demand (COD), Total Phosphorous (TP), Total Nitrogen (TN)) of nine rivers in the lake's basin and the Fuxian Lake center were used as response variables and the LULC type in the basin was interpreted as the explanation variable. The stepwise selection method was used to establish a relationship model for the water quality of the water entering the lake and the significance of the LULC type was established at p < 0.05.The results show that in the seven spatial scales, including the whole watershed, sub-basin, and the riparian buffer zone (100 m, 300 m, 500 m, 700 m, and 1,000 m): (1) whether it is in the whole basin or buffer zone of different pollution source areas, impervious surface area (ISA), or other land and is positively correlated with the water quality and promotes it; (2) forestry and grass cover is another important factor and is negatively correlated with water quality; (3) cropping land is not a major factor explaining the decline in water quality; (4) the 300 m buffer zone of the river is the strongest spatial scale for the LULC type to affect the Chemical Oxygen Demand (COD). Reasonable planning for the proportion of land types in the riparian zone and control over the development of urban land in the river basin is necessary for the improvement of the urban river water quality. Some studies have found that the relationship between LULC and water quality in the 100 m buffer zone is more significant than the whole basin scale. While our study is consistent with the results of research conducted by relevant scholars in Aibi Lake in Xinjiang, and Erhai and Fuxian Lakes in Yunnan. Thus, it may be inferred that for the plateau lake basin, the 300 m riparian buffer is the strongest spatial scale for the LULC type to affect COD.