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The Colombian Andes (CA) are located over the northwestern corner of tropical South America (NW‐TropSA), where land and atmosphere interchange moisture and energy in a complex way owing to the orographic influence on the recycling of moisture over land. We aim to understand where and when water vapor evaporated from land turns into rainfall through moisture recycling, using the Water Accounting Model‐2layers (WAM‐2), an offline model to track atmospheric moisture forced with data from ERA‐5 at its native 0.25° resolution during 1980–2020. We define the spatiotemporal distribution of sources (high evaporation recycle ratios, ϵC) and receptors (high precipitation recycle ratios, ρC) of continental moisture at diverse timescales, including monthly, seasonal, annual and interannual (ENSO). Referring to the regional runs of WAM‐2 over NW‐TropSA (4°S–12°N/80°W–66°W), at elevations above 1,000 m.a.s.l., the CA has a mean annual ρC of 11% (ranging 6%–16%) and a mean annual ϵC of 35% (ranging 27%–40%). Moisture recycling in the CA exhibits a strong annual cycle over the region. The seasonal dynamic of moisture recycling shows two clear‐cut sources of moisture: the eastern foothills of the Eastern and Central ranges of the CA. Both foothills are also regions of high rainfall, although moisture recycling mechanisms differ. Sources of continental moisture grow spatially during September‐October‐November and March‐April‐May. The seasonal availability of moisture recycled coincides with regions where orography interacts with low level jets sourcing humidity. At interannual timescales, sources and receptors of continental moisture in the CA are modulated by the extreme phases of ENSO. Key Points: The orography of the Colombian Andes emerged as a critical factor shaping the interaction between land and atmospheric moisture fluxesFoothills and valleys of the Colombian Andes play a pivotal role in continental moisture recycling, in terms of convergence and divergenceENSO modulates both sources and receptors of continental moisture at interannual timescales [ABSTRACT FROM AUTHOR]

High Mountain Asia (HMA) is the headwater area for major Asian rivers, providing a vast amount of freshwater to billions of people in Asia. These rivers also make their surrounding areas highly vulnerable to destructive water‐related disasters. However, the complex spatiotemporal variability of runoff over HMA and its underlying mechanisms are poorly understood. This study investigates into the spatial heterogeneity of HMA's runoff variability at three timescales (interannual, interdecadal, and multidecadal) and the roles played by climate conditions and catchment properties. We find significant interannual and multidecadal variability of runoff in west and central HMA, and significant interdecadal variability in central and east HMA. At interannual and multidecadal timescales, the runoff variability tends to be more significant in dryer basins. The variability of runoff at the three timescales is largely controlled by climate variations, especially precipitation. The catchment properties, including groundwater storage and glacier‐snow meltwater, also play important roles in regulating the effect of precipitation. In particular, the high contributions of glacier‐snow meltwater in east HMA can weaken the response of runoff variability to precipitation at interannual and multidecadal timescales. The space‐time patterns of runoff variability over HMA are driven by atmospheric drivers including El Niño‐Southern Oscillation, Interdecadal Pacific Oscillation, and Atlantic Multidecadal Oscillation across timescales. The results of this study provide a better understanding of HMA's runoff variability and its physical mechanisms, which have critical implications for sustainable freshwater management and effective risk mitigation in this densely populated and ecologically vulnerable region. Key Points: Significant runoff variability at interannual and multidecadal timescales is detected in west and central High Mountain Asia (HMA)HMA's runoff variability is primarily controlled by precipitation, while catchment properties regulate precipitation effect in diverse waysSpatiotemporal variability in HMA's runoff is modulated by large‐scale atmospheric drivers including El Niño‐Southern Oscillation, Interdecadal Pacific Oscillation, and Atlantic Multidecadal Oscillation [ABSTRACT FROM AUTHOR]

Accurate flood risk assessment requires a comprehensive understanding of flood sensitivity to regional drivers and climate factors. This paper presents the scaling of floods (duration, peak, volume) with geomorphologic characteristics of the basin (i.e., drainage area, slope, elevation) and precipitation patterns (rainfall accumulation, variability). Long‐term daily streamflow observations over the 20th and early 21st centuries from Hydro‐Climatic Data Network streamgages across the conterminous United States are used to create a flood event database based on their flood stage information. Antecedent daily rainfall accumulation and variability corresponding to these floods are computed using Global Historical Climatology Network daily data set. Two Bayesian scaling models are developed, and the spatial organization of scaling exponents is investigated. The baseline model quantifies the scaling of floods to geomorphologic characteristics. The dynamic model quantifies the scaling of floods to antecedent precipitation distribution which is further conditioned on geomorphologic characteristics. Results show that small and low‐elevation basins have a stronger response to antecedent rainfall distribution in amplifying flood peaks, while high‐elevation steeper basins have a lower response for flood duration and volume. The dynamic models demonstrate that there are significant variations in the flood scaling rates, with the largest rates up to 40% and 4.5% for flood duration, 64% and 44% for peak, and 98% and 40% for volume found across the Northeast, Coastal Southeast, and Northwest with intensifying rainfall accumulation and variability, respectively. This study advances flood predictions by better informing the flood attributes in the context of dynamical land‐atmosphere perturbations. Plain Language Summary: The relationships between floods, physical properties of river basins, and the spatio‐temporal distribution of precipitation define the regional flood scaling laws. Improved regional flood scaling models are required for updating flood risk scoring tools to help insurers and decision‐makers in the light of anthropogenic climate changes and natural variability of Earth systems. Two scaling models are developed here to examine how the physical properties of basins and precipitation patterns can inform flood attributes across the conterminous United States (US). Using long records of streamflow and precipitation observations, we identified different scaling relationships between the catchment factors, preceding precipitation, and the duration, peaks, and volume of floods. Larger basins located at higher elevations are found to have lower scaling rates with flood peaks when interacting with the preceding precipitation patterns. Overall, low‐elevation flat basins across the Eastern, Southern, and Northwestern US have a larger positive response to precipitation in amplifying flood attributes. These new scaling laws can help advance our understanding of controlling mechanisms for flash floods and mega‐floods, which is required for a dynamic flood risk assessment in a changing environment. Key Points: Two Bayesian scaling models are developed to understand the sensitivity of floods to geomorphologic characteristics and catchment rainfallLow‐elevation and flat basins with different sizes have greater scaling to rainfall in amplifying flood duration and volumesLow‐elevation and small basins with different steepness show larger sensitivity to rainfall distribution that enhances flood peaks [ABSTRACT FROM AUTHOR]

The long‐term water balance of catchments is given by precipitation partitioned into either runoff or evaporation. Understanding precipitation partitioning controls is a critical focus of hydrology and water resources management. A useful theoretical framework that serves their understanding is the Budyko Framework. Our purpose is to understand how Budyko's n parameter is related to different controls and what is its relevance to precipitation partitioning. We investigated the relative importance of the dryness index and the Budyko parameter for precipitation partitioning, then applied partial correlation analysis and multivariate regressions to find out which were the principal partitioning controls. We focused our research in the central Appalachian mountains located in the eastern United States, considered as water towers to metropolitan areas in the eastern and mid‐western US (e.g., Pittsburgh, Washington DC), and selected a set of catchments characterized by minimal human disturbance and with large proportions of temperate forests. We found that climate controls such as mean annual temperature and fraction of precipitation falling in the form of snow exert a higher influence on partitioning than landscape controls (e.g., forest cover, Normalized Difference Vegetation Index, and slope). Thus, the importance of vegetation as a primary driver of partitioning could not be confirmed based on regional or basin‐wide characteristics. On the other hand, the influence of topography, and elevation in particular, was highly ranked as important. Our study highlights that partitioning controls could differ between basins in the same climate region, especially in a complex, mountainous topography setting. Key Points: Precipitation partitioning controls vary across the region due to complexity created by the eastern continental divideClimate controls, in particular temperature and fraction of precipitation falling as snow, were more important than landscape controlsAmong the landscape controls, elevation was the most influential to precipitation partitioning [ABSTRACT FROM AUTHOR]