Search

Water clarity, commonly determined by Secchi disk depth (SDD), is a critical water quality parameter for assessing estuarine ecosystems heath. Since the 1980s, significant changes in SDD have been observed in the Pearl River Estuary (PRE), a robust, economical, and densely populated estuary in southern China. However, its long-term patterns and associated drivers have not yet been systematically investigated. In this study, three novel semi-analytical algorithms suitable for Landsat 5, 7, and 8 images were applied to 36-year (1987–2022) Landsat series data to explored the spatiotemporal heterogeneity of SDD in the PRE. The results indicated that the proposed SDD estimation algorithms yielded well-accepted performances and few errors, with mean absolute percentage errors <27% and root mean square errors <0.105 m. Spatially, the SDDs in the Western regions of the PRE (0.25 ± 0.1 m) were significantly lower than that in the Open areas (0.55 ± 0.15 m). In addition, the SDD showed an overall increasing trend from 1987 to 2022 with a rate of 0.032 m/y over the entire area, indicating gradually improved water quality in the PRE, owing to the less anthropogenic perturbations and landscape change. This research not only produces a 36-year historical SDD dataset for estuarine areas, but also imparts new insights into the complex mechanisms involved in watershed management. • The water clarity (SDD) in Pearl River Estuary was tracked with Landsat from 1987 to 2022. • Significantly spatiotemporal patterns and overall upward trend of SDD were unveiled. • The SDD were found to be strongly linked to dominated anthropogenic factors over time. • Our study has implications for future precise eutrophication control and efficient water resources management. [ABSTRACT FROM AUTHOR]

Due to the uneven distribution of renewable resources and electricity load centers in China, renewable energy usually needs to be delivered a long distance from the generation base to the load center. However, wind power and photovoltaic (PV) have to be bundled with flexible resources, such as thermal generators, to compensate for the generation uncertainty and variability. Concentrating solar power (CSP) is a controllable generation technology, and it is receiving great attention in the northwest China to be constructed in the 100% renewable energy generation base. This paper proposes a generation portfolio optimization model of a 100% renewable energy base supported by CSP. Firstly, a flexible operation model of CSP based on the interval theory is proposed. Then, a coordinated operation strategy of a 100% renewable energy base organized by CSP, wind power, PV and also energy storage is formulated. On this basis, a generation portfolio optimization model is established with the target of minimizing an extended levelized cost of energy (LCOE) considering the transmission cost. A case study of 100% renewable energy base in Qinghai Province, China, is conducted to verify the effectiveness of the proposed model. It is depicted that CSP plays an important role in the cost-effective portfolio and can be a better alternative to the combination of PV and storage. For the 100% renewable energy base in Qinghai, the LCOE with an optimal CSP, PV, wind, and storage combination is 0.5785 CNY/kWh, which is 20.3% lower than the case without the installation of a CSP station. • Building a 100% renewable energy generation base with a CSP, PV, wind, and storage combination. • A planning model with the target of minimizing an extended LCOE considering transmission cost. • A coordinated operation strategy of a 100% renewable energy base considering CSP's flexibility. • The LCOE of a 100% renewable energy base can drop 20.3% when equipped with CSP in Qinghai. [ABSTRACT FROM AUTHOR]

• Farmland has mainly been converted into construction land in the Huaihe River Basin. • The supply–demand for agroecosystem services are related to farmland loss rate (FLR). • Urbanization patterns strongly impact supply–demand relationship in different FLR area. China's urbanization has gradually become the dominant factor in farmland loss, but it remains unclear how urbanization impacts the supply–demand relationship of agroecosystem services at different rates of farmland loss, which in turn poses new challenges to the ecological security of farmland. Taking the Huaihe River Basin as a case, this paper analyzes farmland loss from 2000 to 2020, as well as changes in the supply–demand relationship of four types of agroecosystem services: food production, socio-economic security, carbon sequestration, and soil conservation, revealing the driving mechanisms of urbanization on the supply–demand relationship of agroecosystem services in sub-regions with different rates of farmland loss. The results show that: (1) A total of 13588.11 km2 of farmland was converted to construction land from 2000 to 2020, accounting for 75.62 % of the total amount of farmland converted to different land types, and 95.57 % of the total amount of farmland converted to construction land. (2) There was a surplus supply of grain production services and socio-economic security services, while there was a deficit in the supply of carbon sequestration services, and a balance in the supply–demand of soil conservation services. (3) The matching degree of supply–demand for agroecosystem services was lower in the Rapid Loss Area compared to the Medium Loss Area and Slow Loss Area. (4) Urbanization was divided into population, economic, and spatial urbanization. The supply–demand relationships of agroecosystem services were impacted greatly by spatial urbanization in the Rapid Loss Area and by economic urbanization in the Medium Loss Area and Slow Loss Area. [ABSTRACT FROM AUTHOR]