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Abstract. The impact of spatial and temporal variability of rainfall on hydrological response remains poorly understood, in particular in urban catchments due to their strong variability in land use, a high degree of imperviousness and the presence of stormwater infrastructure. In this study, we analyze the effect of storm scale, position and movement in relation to basin scale and flow-path network structure on urban hydrological response. A catalog of 279 peak events was extracted from a high-quality observational dataset covering 15 years of flow observations and radar rainfall data for five (semi)urbanized basins ranging from 7.0 to 111.1 km2 in size. Results showed that the largest peak flows in the event catalog were associated with storm core scales exceeding basin scale, for all except the largest basin. Spatial scale of flood-producing storm events in the smaller basins fell into two groups: storms of large spatial scales exceeding basin size or small, concentrated events, with storm core much smaller than basin size. For the majority of events, spatial rainfall variability was strongly smoothed by the flow-path network, increasingly so for larger basin size. Correlation analysis showed that position of the storm in relation to the flow-path network was significantly correlated with peak flow in the smallest and in the two more urbanized basins. Analysis of storm movement relative to the flow-path network showed that direction of storm movement, upstream or downstream relative to the flow-path network, had little influence on hydrological response. Slow-moving storms tend to be associated with higher peak flows and longer lag times. Unexpectedly, position of the storm relative to impervious cover within the basins had little effect on flow peaks. These findings show the importance of observation-based analysis in validating and improving our understanding of interactions between the spatial distribution of rainfall and catchment variability. 

Abstract. Evaporation (E) and transpiration (T) respond differentlyto ongoing changes in climate, atmospheric composition, and land use. It isdifficult to partition ecosystem-scale evapotranspiration (ET) measurementsinto E and T, which makes it difficult to validate satellite data and landsurface models. Here, we review current progress in partitioning E and T andprovide a prospectus for how to improve theory and observations goingforward. Recent advancements in analytical techniques create newopportunities for partitioning E and T at the ecosystem scale, but theirassumptions have yet to be fully tested. For example, many approaches topartition E and T rely on the notion that plant canopy conductance andecosystem water use efficiency exhibit optimal responses to atmosphericvapor pressure deficit (D). We use observations from 240 eddy covariance fluxtowers to demonstrate that optimal ecosystem response to D is a reasonableassumption, in agreement with recent studies, but more analysis is necessaryto determine the conditions for which this assumption holds. Anothercritical assumption for many partitioning approaches is that ET can beapproximated as T during ideal transpiring conditions, which has beenchallenged by observational studies. We demonstrate that T can exceed 95 %of ET from certain ecosystems, but other ecosystems do not appear to reachthis value, which suggests that this assumption is ecosystem-dependent withimplications for partitioning. It is important to further improve approachesfor partitioning E and T, yet few multi-method comparisons have beenundertaken to date. Advances in our understanding of carbon–water couplingat the stomatal, leaf, and canopy level open new perspectives on how toquantify T via its strong coupling with photosynthesis. Photosynthesis can beconstrained at the ecosystem and global scales with emerging data sourcesincluding solar-induced fluorescence, carbonyl sulfide flux measurements,thermography, and more. Such comparisons would improve our mechanisticunderstanding of ecosystem water fluxes and provide the observationsnecessary to validate remote sensing algorithms and land surface models tounderstand the changing global water cycle. 

Urban development, topographic relief, and coastal boundaries can all exert influences on storm hydroclimatology, making rainfall and flood frequency analysis a major challenge. This study explores heterogeneity in extreme rainfall in the Baltimore Metropolitan region at small spatial scales using hydrometeorological analyses of major storm events in combination with hydroclimatological analyses based onstorm catalogsdeveloped using a 16‐year record of high‐resolution bias‐corrected radar rainfall fields. Our analyses demonstrate the potential for rainfall frequency methods using storm catalogs combined with stochastic storm transposition (SST); procedures are implemented for Dead Run, a small (14.3 km²) urban watershed located within the Baltimore Metropolitan area. The results point to the pronounced impact of complex terrain (including the Chesapeake Bay to the east, mountainous terrain to the west and urbanization in the region) on the regional rainfall climatology. Warm‐season thunderstorm systems are shown to be the dominant mechanism for generating extreme, short‐duration rainfall that leads to flash flooding. The SST approach is extended through the implementation of amultiplier fieldthat accounts for spatial heterogeneities in extreme rainfall magnitude. SST‐based analyses demonstrate the need to consider rainfall heterogeneity at multiple scales when estimating the rainfall intensity‐duration‐frequency relationships.

 

Constraints of temperature on spring plant phenology are closely related to plant growth, vegetation dynamics, and ecosystem carbon cycle. However, the effects of temperature on leaf onset, especially for winter chilling, are still not well understood. Using long‐term, widespread in situ phenology observations collected over China for multiple plant species, this study analyzes the quantitative response of leaf onset to temperature, and compares empirical findings with existing theories and modeling approaches, as implemented in 18 phenology algorithms. Results show that the growing degree days (GDD) required for leaf onset vary distinctly among plant species and geographical locations as well as at organizational levels (species and community), pointing to diverse adaptation strategies. Chilling durations (CHD) needed for releasing bud dormancy decline monotonously from cold to warm areas with very limited interspecies variations. Results also reveal that winter chilling is a crucial component of phenology models, and its effect is better captured with an index that accounts for the inhomogeneous effectiveness of low temperature to chilling rate than with the conventional CHD index. The impact of spring warming on leaf onset is nonlinear, better represented by a logistical function of temperature than by the linear function currently implemented in biosphere models. The optimized base temperatures for thermal accumulation and the optimal chilling temperatures are species‐dependent and average at 6.9 and 0.2°C, respectively. Overall, plants’ chilling requirement is not a constant, and more chilling generally results in less requirement of thermal accumulation for leaf onset. Our results clearly demonstrate multiple deficiencies of the parameters (e.g., base temperature) and algorithms (e.g., method for calculating GDD) in conventional phenology models to represent leaf onset. Therefore, this study not only advances our mechanistic and quantitative understanding of temperature controls on leaf onset but also provides critical information for improving existing phenology models.