Economic development and increasing population density along the lower reaches of the Yellow river have challenged the river’s ability to meet human and ecological demand. The evaluation of the sustainability of water resources in the lower reaches of the Yellow River is of great significance for the achievement of high-quality development in the region. Based on an improved ecological footprint method considering soil water, the spatial and temporal evolution of the water resources ecological footprint and water resources carrying capacity and evaluates the utilization of water resources in the lower Yellow River are comprehensively evaluated. The results show that agricultural water consumption in the urban agglomerations in the lower reaches of the Yellow River occupies a major position in water consumption, accounting for more than 70%. In 2013–2017, the per capita water resources ecological footprint of the cities along the lower reaches of the Yellow River decreases every year, while the water resources carrying capacity is slightly fluctuating, but remains in a relatively stable state. The deficit situation has eased, falling by 54.52% in the past five years. The water use efficiency of the lower reaches of the Yellow River has increased every year, and the water resources conflict improved significantly, after the implementation of the new environmental policy in 2015. In terms of space, the cities with the smallest per capita ecological deficits include Zibo, Zhengzhou, and Laiwu City, and Dezhou, and Kaifeng and Binzhou City have the largest. Strict water resources management measures and water pollution prevention and control regulations should be formulated to improve the water use efficiency in these areas in order to solve the problem of water shortage.

Grassland productivity is the most direct indicator of grassland’s ecological status; thus, precise and rapid estimation of grassland productivity has an important significance for evaluating regional ecological carrying capacity, utilizing and developing natural resources reasonably. In this study, based on Moderate Resolution Imaging Spectroradiometer remote-sensing data, meteorological data, and ground measured data, the light utilization efficiency parameter of Carnegie–Ames–Stanford Approach model was optimized, and the optimized model was used to estimate net primary productivity (NPP) and analyse its spatio-temporal distribution of Xilingol grassland between 2005 and 2014. In addition, we investigated the NPP response mechanism to climate factors from two aspects, i.e. the accumulation amount and time of NPP. The results indicated that (i) Maximum light utilization efficiency was calculated to be 0.539 g C MJ⁻¹ for Xilingol grassland according to the least error criterion. (ii) Validation against NPP observations from 30 sites showed good performance of the optimized model in the research area, with an overall coefficient of determination (R²) of 0.72 and mean relative estimation error of 0.29. (iii) The annual mean NPP of Xilingol grassland was 161.23 g C m^–2 year^–1, with a decreasing trend from the northeast to the southwest. (iv) NPP presented increasing trend with a rate of 3.89 g C m^–2 year^–1 overall during 20052014, and the largest increase in NPP was found in temperate meadow-steppe. However, desert ecosystems showed the largest increasing rate after NPP standardization. (v) Precipitation was the main factor for driving carbon accumulation at the inter-annual scale, and the time to maximum NPP was significantly correlated with spring precipitation (R² = 0.637), NPP peaked early as the spring precipitation increasing.

Natural and socioeconomic variables have an impact on ecosystem services (ESs). The ESs trade-offs/synergies are informed by the reality that the same inputs have varying impacts on different ESs. Changing scales and time can alter dominant drivers and biophysical linkages of ESs, affecting their relationships. Although it is often assumed that ES relationships vary across scales, quantitatively testing this assumption with multiple ES is rare. Therefore, this study evaluated the five key ESs in the Pearl River Delta (PRD) from 1990 to 2015. We also employed a statistical approach to investigate the temporal variations, scale dependency, and spatial heterogeneity of ES trade-offs and synergies. The results demonstrated that: (1) The PRD’s synergetic interaction among ESs has been steadily improving over time; (2) The interaction between ESs dramatically altered as the research scale increased; (3) We discovered that the linkages among the soil conservation (SC), carbon sequestration (CS), water yield (WY), and habitat quality (HQ) were primarily synergistic. ESs of SC, CS, WY, and HQ were found to have negative correlations with grain production. This study will strengthen the understanding of the temporal changes and spatial scales of ESs relationships for decision-makers, which is beneficial to ecosystem management.