In this study, an FDR allocation scheme based on synergetic theory was designed to alleviate the drainage conflicts caused by the grabbing of flood drainage rights (FDR) in each region of the basin. An FDR allocation index system was constructed by employing synergetic theory and following the principles of safety, equity, efficiency, and sustainability. A new multi-criteria decision-making method, called FBWM-Grey-TOPSIS, was developed, which is based on the integration of the fuzzy best–worst method (FBWM) and Grey-TOPSIS. Among them, the FBWM method was used to distinguish the importance of subsystems and order parameters, and the Grey-TOPSIS method is applied to obtain the optimal FDR assignment results. Taking the Jiangsu section of the Sunan Canal as an example, the FDRs of the four regions in the basin were allocated. The results reveal that the proportion of FDRs obtained in descending order is Changzhou (32.69%), Suzhou (24.88%), Wuxi (23.01%), and Zhenjiang (19.42%). In addition, the performance of the proposed method is demonstrated by sensitivity analysis and comparative analysis with the existing methods. The methodology and research results presented in this paper can help governments and agencies achieve a scientific allocation of FDR in watersheds, thus promoting harmonious watershed development.

Analyzing the spatial and temporal evolution of ecosystem service value (ESV) and the driving mechanisms of spatial differentiation are fundamental to exploring the sustainable development of regional ecosystems. This article selected a coastal region in southeastern China with rapid economic development as the study object. Based on the five land-use remote sensing data sets from 2000 to 2019, the benefit transfer method was used to evaluate the ESV in the coastal zone of Jiangsu Province, revealing the spatial and temporal evolution characteristics of ESV more accurately. Meanwhile, using the panel data regression model delved into the driving mechanisms of ESV spatial heterogeneity. The results showed the following: (1) There was a marked change in land use types from 2000 to 2019, with significant reductions in cropland and water areas and continued urban land expansion. The overall ESV in the study area exhibited a downward trend (8.41%), with regulation and support services being its core functions. (2) The ESV distribution had a distinct spatial differentiation, with hotspots mainly located near the coastal zone and cold spots in towns and surrounding areas. (3) There were considerable differences in the degree of impact of each influencing factor on different types of ESVs. On the whole, land use intensity had the most significant impact and was the first driver, followed by climate change and socioeconomic factors. The findings indicate that future ecosystem management decision-making should involve the conservation and intensive use of land resources and guide human livelihood and production activities toward ESV preservation and appreciation.

Identifying and assessing the drivers of change in ecosystem service value (ESV) is critical for integrated management and human well-being in coastal zone areas. This paper took a typical coastal zone in eastern China as the research object. Based on five periods of remote sensing monitoring data of land use status from 2000 to 2020, the ESV of Yancheng was estimated by adopting the equivalence factor method. Spatial statistical analysis and GeoDetector were applied to reveal the heterogeneous features of ESV and its driving mechanism. The results suggested that: (1) From 2000–2020, each land use type in the study area changed to different degrees, among which the most drastic change was in the construction land, which increased continuously by 962.69 km², the cultivated land area decreased continuously by 784.1 km², and the area of water body decreased by 163.34 km². (2) ESV experienced a process of increasing and then decreasing, from 547.84 × 10⁸ yuan to 570.86 × 10⁸ yuan and then decreasing to 507.62 × 10⁸ yuan, with farmland ecosystems having the largest ESV, accounting for more than 60%. Regulatory services were the core function of ecosystem services, accounting for more than 60%. (3) There was significant spatial-temporal differentiation in ESV, with extremely low ESV expanding in rapidly developing urbanized areas. The ESV distribution exhibited significant spatial autocorrelation and local spatial clustering, with the gravity center showing a general trend from north to southwest. (4) The ESV spatial and temporal evolutionary characteristics were the result of a multifactorial integration of land use, topography, socio-economics, and climate factors. The explanatory power of each factor in descending order was LDI > DEM > POP > GDP > RAI > TEM, and any two-factor interaction had higher explanatory power than the single factor.