Digital twin technology, which reproduces real phenomena in virtual spaces, is becoming increasingly important in various fields of civil engineering. Especially for the future prediction of rivers, which are long natural structures, the availability of information that canbeprocessedautomatically iscrucial for sustainable infrastructure maintenanceamidstadeclineinengineers. This paper demonstrates a module developed towards realizing digital twins, focusing on riverbed variation analysis used for medium to long-term monitoring and trend prediction within river channels. As a practical application example, the module was demonstrated using various river data of the Kamanashi River, including 3D terrain data, to automate acquisition, conversion, analysis, and distribution. The module is designed to be customizable and replaceable in response to technological advances, making it a characteristic contribution to the automation of data processing in the future.