River discharge monitoring is an important component of the hydrology objectives of Surface Water and Ocean Topography mission (SWOT). River discharge can be estimated Solely using river widths and At Many-stations Hydraulic Geometry (AMHG), but the accuracy is low due to the parameters of At a-station Hydraulic Geometry (AHG) given by AMHG deviate from the truth. In view of this, a Constrained At-Many-Stations Hydraulic Geometry (CAMHG) is proposed to optimize AHG parameters. The performance of CAMHG is verified in three reaches of the Yangtze River using river widths derived from SWOT. After using CAMHG, the relative root mean square error (RRMSE) of estimated discharge reduce 100.1% to 24.4%, 1137.1% to 49.9% and 48.6% to 45.5% for Hankou, Shashi and Luoshan respectively. In addition, CAMHG can also weaken the accuracy difference of estimated discharge in dry and wet seasons benefited from its more reliable AHG parameters. Thus, the proposed CAMHG can dramatically improves the accuracy of discharge estimations and it is meaningful for the discharge calculation after SWOT data release.

The annual variation trend of the gravity and lithospheric magnetic field for adjacent periods are analyzed by using the observation of rover gravity and geomagnetic fields in Yunnan from 2011 to 2021, which tend to be consistent every year during the seismogenic process of a strong earthquake. Thus, this study normalizes the annual value of the adjacent periods for the gravity and lithospheric magnetic field. The normalized values are converted into two classifications that can be compared within [−1,1]. In Yunnan Province, a grid of 0.1° × 0.1° was used to compare the data correlation between the variation of gravity and the variation in the lithospheric magnetic field at the same location. The results are as follows. First, the variation trend of the gravity field and total magnetic field tend to be synchronous year to year in strong earthquake years. The range of consistency increases gradually with the approach of the earthquake year reaching its maximum one year before the earthquake. Throughout the region, the overlap number of normalized annual variations in gravity and magnetic field reaches its maximum, and the peak difference of kernel density curve reaches its minimum. Second, the correlation coefficient of the annual variation in the gravity and magnetic field increases year to year during the development of a strong earthquake within a smaller region surrounding the event. The maximum appears one year before the earthquake, and after the earthquake, the correlation decreases. The analysis of gravity and magnetic fusion characteristics can be employed for the prediction of strong earthquakes.