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Lake Biwa, Japan represents a crucial example of the complex climatic and anthropogenic drivers influencing lake ecological transformations, vital to informing Sustainable Development Goals globally. This study utilizes 20022022 Landsat, MODIS and in situ Lake Biwa monitoring data to analyze surface layer spatiotemporal dynamics across interrelated vegetation, water quality and meteorological indicators -- encompassing Normalized Difference Vegetation Index (NDVI), nitrogen (N), phosphorus (P), chlorophyll-a (Chi) and water temperature (W-TEM). Upward NDVI raster trends were found over 20 years alongside prevalent N, P and Chl declines -- although some increases did occur spatially in P and Chl -- while W-TEM mostly rose lakewide. Southwest-northeast gradients typified distributions. Further attribution analyses revealed W-TEM as the primary N, P and Chl driver, while agricultural expansion and urbanization mediated crucial N and P changes. Moreover, wind speed (WS), Crop, W-TEM, minimum temperature (TMMN), Chl and N constituted top NDVI raster influence factors respectively. These novel integrated models quantifying Lake Biwa ecological responses to multifaceted environmental change provide new perspectives to inform sustainable management of Lake Biwa itself and critical freshwater resources worldwide. [ABSTRACT FROM AUTHOR]

In a lake catchment system, we analyzed the lake water-level responses to precipitation. Moreover, we identified the average precipitation retention time—due to subsurface flows—from the delay time calculated using the response function with data of water level and catchment precipitation (both rainfall and snowfall) collected over 30 years of continuous observations of Lake Biwa, Japan. We focused on the snow reserves and the water-level response delay due to the snowmelt of Lake Biwa catchment. We concluded that the average precipitation retention time of the catchment subsurface flow (i.e., above the impermeable layer) in Lake Biwa was approximately 45 days. Additionally, the precipitation retention time during snowmelt was shorter than that during the dry season. Overall, the shape of the response function reflects the lake system. This knowledge improves the understanding of lake systems and can be helpful for lake resource managers. Furthermore, finding the delay time from the response function may be useful for determining the contribution of rainfall to increasing the water levels of other lakes. Therefore, our results can contribute to the development of management strategies to address inland aquatic ecosystems and conservation. [ABSTRACT FROM AUTHOR]