Understanding changes in lake water storage (LWS) and its attribution to climate change and human activities is essential for adaptive management of water resources in regulated lakes. Although altimetric measurements, whether ground- or satellite-based, can reproduce LWS dynamics, they do not provide sufficient information on why LWS is changing. Neither the water balance method nor detailed hydrological modeling can capture exactly LWS change in most regulated lakes largely because of the scarcity of water output observations. Here, a simple water balance model, following Budyko’s supply–demand framework, was proposed to estimate LWS change in regulated lakes without the need for water output information. The elasticity of LWS was theoretically derived from the Budyko-based model to attribute LWS change to its main driving factors. The annual LWS observed during 1964–2019 under three different regulation plans in Lake Dianchi, which is a typical regulated lake located in southwest China, was used to calibrate and test the proposed model. Comparison between the estimated results and observed data indicated that the model accurately captured the variations of annual LWS in Lake Dianchi with a relative root mean square error of 4.08%, and mean absolute percentage error of 2.88%. The attribution results suggested that lake regulation strategies were the primary cause of LWS change in Lake Dianchi, while water transfer had a limited contribution. This study suggests that complex hydrological behavior in regulated lakes can be explored using Budyko's supply–demand framework with a low requirement for data. This can provide effective guidance to lake managers and policymakers for adaptive management of water resources in regulated lakes.