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Understanding the process of precipitation partitioning into evapotranspiration and streamflow is fundamental for water resource planning. The Budyko framework has been widely used to evaluate the factors influencing this process. Still, its application has primarily focused on studying watersheds with minimal human influence and on a relatively small number of factors. Furthermore, there are discrepancies in the literature regarding the effects of climatic factors and land use changes on this process. To address these gaps, this study aims to quantify the influence of climate and anthropogenic activities on streamflow generation in the contiguous United States. To accomplish this, we calibrated an analytical form of the Budyko curve from 1990 to 2020 for 383 watersheds. We developed regional models of , a free parameter introduced to account for controls of precipitation partitioning not captured in the original Budyko equation, within different climate zones. We computed 49 climatic and landscape factors that were related to using correlation analysis and stepwise multiple linear regression. The findings of this study show that human activities explained a low variance of the spatial heterogeneity of compared with the watershed slope and the synchronization between precipitation and potential evapotranspiration, nevertheless, urban development emerged as a factor in temperate climates, whereas irrigated agriculture emerged in cold climates. In arid climates, mean annual precipitation explains less than 20% of the spatial variability in mean annual streamflow; furthermore, this climate is the most responsive to changes in . These results provide valuable insights into how land use and climate interact to impact streamflow generation differently in the contiguous United States contingent on the regional climate, explaining discrepancies in the literature. 

This study synthesizes the current understanding of the hydrological, impact, and adaptation processes underlying drought‐to‐flood events (i.e., consecutive drought and flood events), and how they interact. Based on an analysis of literature and a global assessment of historic cases, we show how drought can affect flood risk and assess under which circumstances drought‐to‐flood interactions can lead to increased or decreased risk. We make a distinction between hydrological, socio‐economic and adaptation processes. Hydrological processes include storage and runoff processes, which both seem to mostly play a role when the drought is a multiyear event and when the flood occurs during the drought. However, which process is dominant when and where, and how this is influenced by human intervention needs further research. Processes related to socio‐economic impacts have been studied less than hydrological processes, but in general, changes in vulnerability seem to play an important role in increasing or decreasing drought‐to‐flood impacts. Additionally, there is evidence of increased water quality problems due to drought‐to‐flood events, when compared to drought or flood events by themselves. Adaptation affects both hydrological (e.g., through groundwater extraction) or socio‐economic (e.g., influencing vulnerability) processes. There are many examples of adaptation, but there is limited evidence of when and where certain processes occur and why. Overall, research on drought‐to‐flood events is scarce. To increase our understanding of drought‐to‐flood events we need more comprehensive studies on the underlying hydrological, socio‐economic, and adaptation processes and their interactions, as well as the circumstances that lead to the dominance of certain processes.

This article is categorized under:

Science of Water > Hydrological Processes

Science of Water > Water Extremes

 

Abstract. The Columbia River Treaty (CRT) signed between the United States and Canada in 1961 is known as one of the most successful transboundary watertreaties. Under continued cooperation, both countries equitably share collective responsibilities of reservoir operations and flood control andhydropower benefits from treaty dams. As the balance of benefits is the key factor of cooperation, future cooperation could be challenged byexternal social and environmental factors which were not originally anticipated or change in the social preferences of the two actors. To understandthe robustness of cooperation dynamics, we address two research questions. (i) How does social and environmental change influence cooperationdynamics? (ii) How do social preferences influence the probability of cooperation for both actors? We analyzed infrastructural, hydrological,economic, social, and environmental data to inform the development of a socio-hydrological system dynamics model. The model simulates the dynamicsof flood control and hydropower benefit sharing as a function of the probability to cooperate, which in turn is affected by the share ofbenefits. The model is used to evaluate scenarios that represent environmental and institutional change and changes in political characteristicsbased on social preferences. Our findings show that stronger institutional capacity ensures equitable sharing of benefits over the long term. Under the current CRT, the utility of cooperation is always higher for Canada than non-cooperation, which is in contrast to the United States. The probability tocooperate for each country is lowest when they are self-interested but fluctuates in other social preference scenarios. 

Pluvial flooding in urban regions is a natural hazard that has been rarely investigated. Here, we evaluate the utility of three radar (Stage IV, MRMS, and GCMRMS) quantitative precipitation estimates (QPEs) and the SWMM hydrologic-hydraulic model to simulate pluvial flooding during the North American Monsoon in Phoenix. We focus on an urban catchment of 2.38 km2 and, for four storms, we simulate a set of flooding metrics using the original QPEs and an ensemble of 100 QPEs characterizing radar uncertainty through a statistical error model. We find that Stage IV QPEs are the most accurate, while MRMS QPEs are positively biased and their utility to simulate flooding increases with the gage correction done for GCMRMS. For all radar products, simulated flood metrics have lower uncertainty than QPEs as a result of rainfall-runoff transformation. By relying on extensive precipitation and basin datasets, this work provides useful insights for urban flood predictions.