Sustainable governance of drinking water conservation areas based on adaptive thresholds.

Drinking water quality is integral to the Sustainable Development Goals framework. At the present, China's drinking water conservation faces a number of challenges that are partially brought on by strict conservation measures that don't fully take into account human-land conflict and sustainable development. Taking the idea of adaptive governance, this study seeks to identify adaptive thresholds and adaptive solutions for compatible drinking water conservation and local development. Pressure and resistance to drinking water quality in its status, future potential, and adaptive thresholds were explored to identify sustainable governance for the Baimei Conservation Area, Fujian Province. Field research, local governance forums, and the Soil and Water Assessment Tool (SWAT) model were utilized to explore the drinking water quality pressure and resistance to drinking water quality. In order to uncover potential future changes in pressure and resistance, suitability analyses and multi-scenario simulations were used to examine the status quo, pressure, and resistance scenarios. Adaptive thresholds were then identified through SWAT modeling of each scenario to guarantee the drinking water quality is greater than Class II in the Core Conservation Area and Class Ⅲ in 2nd-grade Conservation Area, respectively. The research finds that construction land development and farming are the key pressures on drinking water quality, and forests and wetlands are the primary resistances. The expansion of construction lands and the increased wetlands was centered on potential future scenarios because farming has no room for growth and forests are already heavily covered. The adaptive threshold of construction land expansion is identified to be 10% without new wetlands but can be 20% by adding 10% wetlands in subbasins, 5, 8, and 9. This study confirms the potential of adaptive sustainability for drinking water conservation areas. A similar analysis procedure can also be adapted to enhance adaptive governance for the sustainability of other conservation areas nationally and globally.

[Review of change detection methods using multi-temporal remotely sensed images].

With the development of platforms and sensors, continuous repetition of remote sensing observation of the earth surface has been realized, and a mass of multi-source, multi-scale, multi-resolution remote sensing data has been accumulated. Those images have detailedly recorded the changing process of ground objects on the earth, which makes the long term global change research, such as change detection, based on remote sensing become possible, and greatly push forward the research on image processing and application. Although plenty of successful research has been reported, there are still enormous challenges in multi-temporal imagery change detection. A relatively complete mature theoretical system has not formed, and there is still a lack of systematic summary of research progress. Firstly, the current progress in change detection methods using multi-temporal remotely sensed imagery has been reviewed in this paper. Then, the methods are classified into three categories and summarized according to the type and amount of the input data, single-phase post-classification comparison, two-phase comparison, and time series analysis. After that, the possible existing problems in the current development of multi-temporal change detection are analyzed, and the development trend is discussed finally.

[Research on spatial characteristic of non-point source pollution in Liaohe River basin].

The spatial characteristic of non-point source pollution in the Liaohe River was studied. Coupling the remote sensing data and non-point source (NPS) models, a method of assessing NPS pollution by pixel unit was developed, aiming to analyse the NPS pollution characteristic of Liaohe River basin in 2010, in turn to identify the main polluted areas and prevention measures. The work will provide technical supports for pollution prevention in Liaohe River basin. The results showed that in 2010, the total discharge of total nitrogen (TN) was 1.03 x 10(5) t, the total phosphorus (TP) was 6.8 x 10(3) t, the chemical oxygen demand (COD) was 1.31 x 10(5) t and the ammonia nitrogen (NH+4 -N) was 1. 8 x 10(4) t. The main pollution source of NPS was from agriculture. The contributions of NPS pollution to water quality were 67.4% , 76.4% , 39.4% and 21.9% for TN, TP, COD and NH+4 -N, respectively. The south of Liaohe River basin was the most serious polluted area, followed by the northeast areas. In this research, a method was build to estimate the NPS loads based on remote sensing pixel and the spatial characteristic of non-point source pollution in Liaohe River in 2010 was analysed, which will provide support for pollution prevention in Liaohe River.