Understanding the stable hydrogen and oxygen isotope composition of river water in the basin is of great significance for identifying the evolution mechanism of water cycle and the composition of water source. Based on the test results of δD and δ 18O of river water and precipitation samples collected from Shiyang River in August 2020, this paper analyzed the composition characteristics of δ 18O and δD of river water in Shiyang River Basin during rainy period, and further revealed the spatial evolution characteristics and influencing factors. The results show that the δ 18O and δD values of the main and tributaries of Shiyang River are gradually enriched along the river, showing an increasing trend, while the excess deuterium is decreasing along the river. The effect of δ 18O and δD in river water is significant, and the variation of δ 18O altitude gradient is smaller than that of local precipitation and global precipitation. Using the evaporation loss calculation model, it can be seen that evaporation fractionation has an obvious effect on the water isotope change of Shiyang River, and the main stream of Shiyang River has the greatest effect, followed by Jinta River and Zamu River. The evaporation of reservoir water is more intense than that of river water. Precipitation is the main source of river water, and the isotope is mainly affected by the isotopic composition of river water in tributaries, and is controlled by the elevation effect, the continuous evaporation effect along the direction of runoff, and the higher degree of evaporation effect in the rainy season.

Satellite-based solar-induced chlorophyll fluorescence (SIF) has the potential for an early detection and accurate impact assessment of meteorological drought on vegetation photosynthesis. However, how the response of satellite SIF to meteorological drought varies under different climatic conditions and biome types remains poorly understood. In this study, we determined the drought time-scale at which the vegetation photosynthesis response was highest based on the standardized precipitation evapotranspiration index (SPEI) and satellite SIF, and examined how the sensitivity of SIF signals from different ecosystems to drought varied along an aridity gradient in northern China. The results showed that spatial variability of the annual maximum SIF was constrained by wetness conditions and biome types. Annual maximum SIF was positively correlated with SPEI in 57.9% of vegetated lands (P < 0.05). 34.8% of humid ecosystems were characterized by a significant SIF-SPEI correlation (P < 0.05). This percentage reached 44%, 71.4% and 86.2% for arid, sub-humid and semi-arid ecosystems, respectively. The variation of SIF-SPEI correlations was a Gaussian function of the aridity index (AI), with the highest SIF-SPEI correlation appearing in the AI bin of 0.4 (0.37-0.46). The drivers for this pattern were vegetation composition and water availability. The variation of SIF time-scales in response to SPEI was a linear function of the AI, but the slope varied among biomes. To summarize with increasing aridity drought-induced declines in vegetation photosynthesis will be quicker and more significant.