[1] Long-term climate is the first-order control on mean annual water balance, and vegetation and the interactions between climate seasonality and soil water storage change have also been found to play important roles. The purpose of this paper is to extend the Budyko hypothesis to the seasonal scale and to develop a model for interannual variability of seasonal evaporation and storage change. A seasonal aridity index is defined as the ratio of potential evaporation to effective precipitation, where effective precipitation is the difference between rainfall and storage change. Correspondingly, evaporation ratio is defined as the ratio of evaporation to effective precipitation. A modified Turc-Pike equation with a horizontal shift is proposed to model interannual variability of seasonal evaporation ratio as a function of seasonal aridity index, which includes rainfall seasonality and soil water change. The performance of the seasonal water balance model is evaluated for 277 watersheds in the United States. The 99% of wet seasons and 90% of dry seasons have Nash-Sutcliffe efficiency coefficients larger than 0.5. The developed seasonal model can be applied for constructing long-term evaporation and storage change data when rainfall, potential evaporation, and runoff observations are available. On the other hand, vegetation affects seasonal water balance by controlling both evaporation and soil moisture dynamics. The correlation between NDVI and evaporation is strong particularly in wet seasons. However, the correlation between NDVI and the seasonal model parameters is only strong in dry seasons.

The Kissimmee River Basin (Florida, USA) underwent river channelization in the 1960s and subsequent restoration in the 1990s, revealing a shift in management emphasis from flood protection to wetland health. In this paper, this shift is hypothesized to result from changing human values and preferences, and a power differential between the more numerous and affluent upstream urban residents (who prioritize wetland restoration) and downstream rural residents (who prioritize flood protection). We develop a conceptual sociohydrologic model to simulate the interactions between community interests and hydrology. The modeling results show that flood intensity decreased after channelization, which reduced concern about flooding. However, channelization also led to a decrease in wetland storage, which caused an increase of wetland concern, especially among the urban residents. Eventually, the community sensitivity switched from favoring flood protection to favoring wetlands, and subsequent management strategies switched from channelization to restoration. Using the model, we project that the wetlands will be recovering for the next 20 years and community sensitivity will slowly go back to a neutral state. However, possible rainfall intensification in the future could return the community sensitivity to favoring flood protection again. The preferential increase of upstream population growth will raise the community's concern about wetlands and the preferential increase of downstream population growth will magnify concern about flooding. This study provides insight into the driving forces behind human‐water interactions in the Kissimmee River Basin while simultaneously demonstrating the potential of sociohydrologic modeling to describe complex human‐water coupled systems with simple concepts and equations.