Storm Depth Research Articles

Precipitation and evapotranspiration controls on daily runoff variability in the contiguous United States and Puerto Rico

AbstractDaily runoff variability is an important driver of fluvial erosion but is difficult to incorporate into landscape evolution models due to limited observations and incomplete understanding of hydroclimatic controls on runoff distributions. Prior work in the contiguous U.S. showed how limitations can be overcome when mean runoff is correlated with the shape of the right tail of runoff distributions. However, which probability distribution functions best capture geomorphically important events and whether patterns in the contiguous U.S. transfer to other settings remain important open questions. Our analysis of large hydroclimatic data sets from the contiguous U.S. and Puerto Rico reveals that stretched exponential distributions provide a common probabilistic framework to evaluate daily rainfall and runoff variability. In both settings, daily runoff variability is correlated with the evapotranspiration ratio, aridity index, and the ratio of wet to dry days. Surprisingly, mean storm depth (estimated from average daily precipitation during wet days only) and storm depth variability are uncorrelated with daily runoff variability in either data set. These findings suggest that first‐order controls on runoff variability are processes that reduce runoff during intermediate frequency flows rather than processes that enhance the magnitude of rare floods. However, by normalizing local runoff variability by storm depth variability, some correlations collapse onto a single trend for the contiguous U.S. and Puerto Rico, suggesting a secondary role for rainfall variability on runoff variability. Taken together, this analysis provides a rationale for how hydroclimatic controls on runoff variability can be better incorporated into landscape evolution models from readily available data.

Analysis of Climate Change and 24-Hour Design Storm Depths for a Range of Return Periods Across South Carolina

A warming climate leads to a moister atmosphere and more rapid hydrologic cycle. As such, many parts of the country are predicted to experience more total rainfall per year and more frequent extreme rainfall events. Most regions of the country have stormwater systems designed to a standard that matches outflow rates to pre-development values for specified return period storms. Increases in these return period storm depths, as predicted by many global climate models, will stress existing stormwater infrastructure. This paper examines how rainfall patterns will change over the remainder of the century across the state of South Carolina. Rainfall simulations from 134 realizations of 21 global climate models were analyzed across the state of South Carolina through 2099. Results show that there will be increases in both annual total rainfall (ATR) and 24-hour design storm depth for a range of return period storms. Across South Carolina, ATR is predicted to increase by approximately 2.3-4.0 inches over the forecast period while the 100 year design storm depth is predicted to increase by 0.5-1.2 inches depending on location. However there are significant regional variations with the Savannah River Basin experiencing smaller increases in ATR compared to the rest of the state.

Climate Change Impact on Design Storm and Performance of Urban Storm-Water Management System - A Case Study on West Central Mountain Drainage Area in Canada

A number of future climate projections indicate a likelihood of increased magnitude and frequency of hydrological extremes for many regions around the world. The urban storm-water management infrastructures are designed to mitigate the effect of extreme hydrological events. Changes in extreme rainfall events will have a significant implication on the design of storm-water management infrastructures. This study assessed the potential impact of changed rainfall extreme on drainage systems in the West Central Mountain drainage area located in Southern Ontario, Canada. First, the design storms for the study area were calculated from observed rainfall data and the North American Regional Climate Change Assessment Program (NARCCAP) climate simulations based on SRES A2 Scenario. Frequency analysis was performed on the annual maximum time series data by using the best fitted distribution among twenty seven distributions. The Pearson chi-square test and Kolmogorov-Smirnov were used to test the goodness of fit of each distribution. The results show that L-moment Pareto distribution was selected the most often for data from six RCM+GCM pairs. Overall increase of storm depth in the future is highest when the distributions were identified by the Kolmogorov-Smirnov test. The design storm depths calculated from the observed and climate model simulated data were used as input into an existing PCSWMM model of the study area for flow simulation and hydraulic analysis for the storm-water management system, specifically storm sewer and detention pond. The results show an increase in design storm depths under projected climatic change scenarios that suggest an update of current standard for designing both the minor system and detention pond in the study area. The assessment results of storm water management infrastructures indicate that performance of the detention pond as well as the storm sewer network will deteriorate under future climate condition.

Identification of rainfall patterns in Johor

Temporal pattern for rainfall events is required in the design and evaluation of hydrologic safety for hydraulic structures. In this paper, a method of statistical cluster analysis is applied to identify event-based representative temporal rainfall pattern in fourteen stations in Johor. The 8 hour separation time of no rain is used to divide the 5 years rainfall data into individual rainfall event according to the monsoons. The analysis is implemented from the dimensionless mass curve ordinates as the attributes in statistical cluster analysis of the cumulative storm depth over the non-dimensionalized time. As a result, three representative rainstorm patterns are identified and classified under the two basic types of advanced-type (A) and central-peak type (C) for northeast and southwest monsoon. Meanwhile, only one basic type is identified to represent rainstorm pattern during the inter-monsoon that is advanced type (A). In addition, the rainfall pattern is found to be dependent on rainfall depth and duration, season and geographical location by using the contingency table test. Therefore, the identification of only one rainfall pattern as currently used in Malaysia is not sufficient. The identification of three representative rainfall temporal patterns according to the monsoon seasons in Johor can be used as a basis to stochastically generate the plausible rainfall hyetographs of the specified pattern in Joho

Application of the UKCP09 WG Outputs to Assess Performance of Combined Sewers System in a Changing Climate

In many parts of the world old sewer systems have been designed without consideration for change in climate, so probabilities and risks of sewer surcharge and flooding are elevated due to increase in extreme rainfall events as a consequence of global warming. The current paper is aiming to assess how the climate change on interannual to multidecadal timescale (2020s, 2050s, 2080s) will affect design standards of waste water networks due to the presumed increase in rainfall intensity and frequency in the Northwest of England area (selected site). Design storms have been analysed for future rainfall obtained from the UK Climate Projection version 2009 (UKCP09) weather generator, which was applied to the existing urban drainage system to check the level of service in winter and summer seasons. Two emission scenarios (SRES) have been adopted to simulate the greenhouse gas concentration; high scenario (A1FI) and low scenario (B1). Results indicate that the impact of increase in the deign storm of the system in winter lead to a potential of increase flood volume from manholes and intern basements at risk of flooding with the worst condition associated with 24 hours storm in 2080s. Moreover, when this design storm depth increased by only 15%, the corresponding flood volume increase by 40%, this indicates that the relation between the cause of flooding and its consequences is non-linear. Summer season has an opposite picture and flood volume is projected to decrease with the increase in the storm duration causing low risk. Considering climate change in this study caused most of urban drainage models runs to be very slow with some interruption in the simulation due to the inflation in some parameters, so cautious should be taken.

Evaluation of Dual Tipping-Bucket Rain Gauges Measurement in Arid Region Western Saudi Arabia

In this study, a dual tipping-bucket (TB) rain gauge station is installed in an arid region in western Saudi Arabia. The size of the gauge collector was the only difference between the two installed rain gauges. Records of both gauges for the period 2006–2013 are collected, analyzed and compared, focusing on characteristics of rainfall events as well as rainfall temporal variability. The two gages recorded almost the same total rainfall depth but significantly different mean storm depth values. For the large storms, both gauges recorded the same mean storm depth. However, significantly variable values throughout the storm duration are observed. The TB gauge with the larger funnel size (TEMM) has the advantage of recoding more storms with depth less than 1 mm though it underestimates the depth for storms of high intensities. This study also shows the importance of using dual rain gauges in arid regions where large storms are rare and hence can be missed if only one gauge is used due to gauge failure, which is not a surprise in such harsh environment.

Hydrologic Characterization of Undrained Porous Pavements

Results of a simplified analysis of the hydrologic performance of undrained porous pavements, pavements without underdrains but that allow infiltration, are reported. The characterization of porous pavement behavior presented is appropriate for initial pavement design purposes. During any given storm, there are four distinct phases of porous pavement behavior: infiltration, accumulation, runoff, and drawdown. Analytical and graphical methods are presented for describing each of these phases from which a nonconvoluted approximate runoff hydrograph can be derived. This approach approximates peak runoff and time of that peak for a given storm depth, rainfall distribution, and pavement design. Second, a generalized method for calculating a porous pavement’s effective curve number (ECN) based on the National Resources Conservation Service (NRCS) [formerly Soil Conservation Service (SCS)] runoff curve number is presented. The analysis shows that for undrained porous pavements, the ECN is a function not only of the pavement and soil properties, but also of the storm depths and hyetographs used in the analysis. A standard calculation and presentation method is suggested that will allow local regions or municipalities to generate a local ECN design tool appropriate for their intensity-duration-frequency (IDF) data, which are only a function of the effective storage depth and the daily effective soil infiltration depth. A plot of the maximum ECN for all pavement depths and soil types is presented for each NRCS storm type as a reference for generating local ECN figures.

Runoff Curve Numbers at the Agricultural Field-Scale and Implications for Continuous Simulation Modeling

This study used monitoring in the waterways of agricultural fields to understand the use of the runoff curve number (CN) in continuous simulation models. The CN has a long history as a design tool for estimating runoff volumes for large, single storms on small watersheds, but its use in continuous simulation models to describe runoff from smaller storms and relatively small areas is more recent and controversial. We examined 788 nonwinter rainfall events on four agricultural fields over five years (2004-2008) during which runoff was generated in 87 events. The largest 20 runoff events on each field generated approximately 90% of the total runoff volume. The runoff event CNs showed an inverse correlation with storm depth that could not consistently be explained by previous precipitation. We review how small areas of higher runoff generation within larger areas will systematically increase the apparent CN of the larger area as the storm size decreases. If this variation is not incorporated into a model explicitly, continuous simulation modelers must understand that when source areas are aggregated or when runoff generation is spatially variable, the overall CN is not unique when smaller storms are included in the calibration set.

Study of cloudburst and flash floods around Leh, India, during August 4–6, 2010

Leh and surrounding region of the Ladakh mountain range in the trans-Himalaya experienced multiple cloudbursts and associated flash floods during August 4–6, 2010. However, 12.8 mm/day rainfall recorded at the nearest meteorological station at Leh did not corroborate with the flood severity. For better understanding of this event, hydrological analysis and atmospheric modeling are carried out in tandem. Two small catchments (<3 km2) were studied along the stream continuum to assess the flood characteristics to identify the cloudburst impact zones. Peak flood discharges were estimated close to the head wall region and at the catchment outlet of the Leh town and the Sabu eastern tributary catchments. Storm runoff depth is estimated by developing a triangular hydrograph by using the known time base of the flood hydrograph. This triangular hydrographs have been transformed further into storm hydrographs to gain a better understanding of the storm duration by using the dimensionless hydrograph method at selected cross sections. Storm duration is estimated by using the relationship between time to peak and time of concentration of the catchment. The peak flood estimates ranged from 122(±35 %) m3/s for Leh town catchment (2.393 km2), 545(±35 %) m3/s for Sabu eastern tributary catchment (2.831 km2) to 1,070(±35 %) m3/sec for Sabu catchment (64.95 km2). To assess the atmospheric processes associated with this event, a triple nest simulation (27, 9 and 3 km) is performed using Advanced Research Weather Research and Forecasting (WRF) modeling system. The simulation does show the evolution of the event from August 4 to 6, 2010. Observation constraints, orographic responses, etc. make such analysis complex at such scale. Independent estimate by the atmospheric process model and the hydrological method shows the storm depth of 70 mm and 91.8(±35 %) mm, respectively, in catchment scale. Hydrological evaluation further refined the spatial and temporal extents of the cloudbursts in the respective catchments with an estimated storm depth of 209(±35 %) mm in 11.9 min and 320(±35 %) in 8.8 min occurring in an area of 0.842–1.601 km2, respectively. This study shows that the insight developed on the cloudburst phenomena by the atmospheric and the hydrological modeling is hugely constrained by the spatial and temporal scales of data used for the analysis. Apart from this, study also highlighted the regular occurrence of cloudburst events over this region in the recent past. Most of such events go unreported due to lack of monitoring mechanisms in the region and weaken our ability to understand these events in complete perspective.

An Analysis of NCEP Tropical Cyclone Vitals and Potential Effects on Forecasting Models

Abstract This study analyzes the Tropical Cyclone Vitals Database (TCVitals), which contains cyclone location, intensity, and structure information, generated in real time by forecasters. These data are used to initialize cyclones in several NCEP operational forecasting models via bogusing and vortex relocation methods. In many situations, time is of the essence and the TCVitals database represents the best real-time estimate of the cyclone state possible in real time, given the limitations of available data and time constraints inherent in real-time forecasting. NCEP and other users of TCVitals have a responsibility to work around the inevitable limitations of what forecasters can do for TCVitals in real time. With ensemble systems becoming available, a way to do that will soon be available. However, the TCVitals’ limitations must first be quantitatively understood so that model developers can take them into account. That is the motivation for the present study, which compares the TCVitals storm location and intensity to postseason reanalysis values found in the best-track database and statistically compares the TCVitals storm depth to 946 Tropical Rainfall Measuring Mission (TRMM) overpasses. All storms of tropical depression strength or stronger in all basins are analyzed, with a special focus on National Hurricane Center TCVitals for the North Atlantic and eastern Pacific basins, the main areas of responsibility for NCEP. In addition, the sensitivity to TCVitals on the Hurricane Weather Research and Forecasting (HWRF) model is examined by rerunning the 2011 HWRF for the 2010 North Atlantic season twice: once with TCVitals input and once with best-track input.

Nonparametric method for estimating the effects of climatic and catchment characteristics on mean annual evapotranspiration

It is now well known that forested catchments have higher evapotranspiration than grassed catchments. Models for mean annual evapotranspiration have been developed to quantify catchment scale differences in mean annual evapotranspiration. Zhang et al. (2001) developed a simple, one parameter, model for the relationships between evapotranspiration and vegetation cover by evaluating the differences of model parameter values for different vegetation covers. However, other factors such as climate and catchment topography may also affect evapotranspiration and therefore the model parameter. Simple models acknowledging only categorical vegetation cover (forested, mixed, and grassed) may introduce some uncertainty, and more seriously, lead to inconsistent conclusions regarding relationships between vegetation cover and evapotranspiration. Zhang et al. (2004) investigated possible inclusion of climatic factors and catchment characteristics to improve the estimation of mean annual evapotranspiration by modeling the residuals of the model parameter via a stepwise linear regression. In this paper we propose the use of a multivariate adaptive regression spline (MARS) model for estimating the model parameter. In contrast to a simple stepwise regression, the MARS model provides not only insight into the interactions between explanatory factors but also a potential for prediction for ungauged basins as long as the values of explanatory factors are within the domain of calibration catchments. The MARS model is able to determine statistically significant factors and therefore is a powerful tool to identify important factors and their interactions. Using 241 Australian catchments where climate factors and catchment characteristics are available, we found the following significant terms affecting the mean annual evapotranspiration. (1) The functional relationship with the number of months that peak precipitation follows peak potential evapotranspiration (PfE) states that closer phase between precipitation and potential evapotranspiration results in less streamflow. (2) The interactions between coefficient of variation of precipitation and average storm depth shows that the value of the model parameter is smaller when the coefficient of variance of precipitation is larger than 2.24 and the average storm depth is less than 8.70 mm d−1. (3) The interaction between relief ratio and average storm depth term shows that both larger average storm depth in flat catchments and smaller average storm depth in hilly catchments result in more streamflow. (4) The interaction between relief ratio and forest coverage reveals that for flat catchments with reasonable forest cover, increasing forest cover generally results in more mean annual evapotranspiration and less mean annual streamflow. The performance of the MARS model was assessed by a calibration‐testing procedure to support its usage for prediction for ungauged basins.

Roots, storms and soil pores: Incorporating key ecohydrological processes into Budyko’s hydrological model

Summary Due to its role in intercepting and evaporating water, vegetation is a key medium through which catchment water yields can be manipulated and may prove to be an important tool available to managers for mitigating the effects of climatic changes on yields. Understanding of the effects of vegetation on long-term catchment flows is growing, yet incorporation of these effects into hydrological models has typically been empirical and qualitative, or deterministic and quantitative – but at the cost of simplicity. Here we present a new ecohydrological model (the Budyko–Choudhury–Porporato, or BCP, model) that is the combination of two pre-existing models. It is simple, quantitative and process-based. As well as accounting for the well established roles played by average precipitation (P) and potential evaporation (Ep) on long-term catchment flows (R), the BCP model also provides estimates of n – a catchment-specific model parameter that alters the partitioning of P between R and evaporation – which is estimated as a function of plant-available soil water holding capacity (κ), mean storm depth (α) and effective rooting depth (Ze). After developing this model and testing results at several spatial scales across Australia, we used the model to analyse the sensitivity of R to changes in Ze and α (as well as P and Ep) in the high yield zones of the Murray-Darling Basin. The model performed well overall at both the coarse spatial scale (i.e., the Basin) and at the finer scales of sub-basin regions and of catchments, capturing ∼90% of the observed variability in R. At the regional scale, BCP-modelled R was more or less the same as when a default (constant) value of n was used to model R (that is, n = 1.8). This is due to the general aridity of these regions (under such conditions R is insensitive to small variations in n). However, at the catchment scale, use of the BCP model in ‘wet’ catchments (i.e., R > 500 mm y−1) increased the accuracy of predictions by approximately 10% compared to the default (n = 1.8) model. Runoff was shown to be highly sensitive to changes in P in the highest yield zones of the Basin, followed by changes in Ze and then in α. In contrast, across the whole basin – which is highly arid – the sensitivity of R to changes in Ze and α, whilst small in absolute terms, are substantial relative to total basin flows. The incorporation of α, κ and – most importantly from a management perspective – Ze into the Budyko model provides a simple and transparent tool for aiding the understanding of the long-term ecohydrological behaviour of catchments and assessing the potential hydrological effects of different land management options under a variable climate.

The hydrological performance of a green roof test bed under UK climatic conditions

► New continuous 5-min hydrological performance data from a UK green roof test bed. ► 50.2% Overall retention, falling to 30% for significant events (>1 year return period). ► Regression analysis shows retention is not simply a function of ADWP. ► Performance is dependent upon substrate moisture fluxes; ET is critical. ► The roof has a finite retention capacity, in this case a maximum of 20 mm. This paper presents new rainfall and runoff data from a UK green roof test bed which has been collected almost-continuously over a 29-month period from 01/01/2007 to 31/05/2009. Overall, the monitoring period was fairly typical of the location’s long-term climatic averages, although the data set includes some extreme events in June 2007, which were associated with serious flooding locally. To focus on the system’s performance under rainfall events likely to be of interest from an urban drainage/stormwater management perspective, return period analysis has been applied to identify those storm events with a rainfall depth in excess of 5 mm and a return period greater than one year. According to these criteria, 22 significant events have been identified, of which 21 have reliable runoff records. Overall the roof provided 50.2% cumulative annual rainfall retention, with a total volumetric retention equivalent to 30% during the significant events. The annual performance figures are towards the lower end of a range of international data, probably reflecting the fact that rainfall depths may be higher and evapotranspiration rates lower than in some more continental climatic settings. The roof’s finite retention depth means that the maximum possible retention percentage declines as storm depth increases, and retention varied from between 0 and 20 mm, or 0% to 100%. Although some attenuation and delay of peak runoff is generally observed (mean peak flow reduction of 60% for the 21 significant events), the irregularity of natural rainfall patterns, combined with the variable influence of detention storage in specific events, makes the identification of peak-to-peak lag times difficult and arguably meaningless. Regression analyses have been undertaken to explore the potential to predict the roof’s hydrological performance as a function of storm characteristics. However, these are shown to have poor predictive capability, even for the system from which they were derived. Through a detailed examination of data from three contrasting events, it is argued that the inter-event processes are too complex to be captured by this type of modelling approach. Instead, an understanding of the hydrological processes affecting the flux of moisture into and out of the substrate is required to explain the observed runoff response. Locally-derived evapotranspiration rates and the roof’s observed maximum retention capacity are utilised to provide pragmatic guidance on the retention performance to be expected in response to selected design events.

A probabilistic description of rain storms incorporating peak intensities

Summary Design storms with standardized hyetograph shapes and selected combinations of storm depths and durations are widely used in engineering hydrology. The key distinguishing feature between equal-duration design storms is their distinct intensity distributions. Differences in design storm hyetographs do not affect storm frequency, since only the frequency of the combination of storm depth and duration are determined through the use of Depth–Duration–Frequency curves. Probability distributions of peak intensity within rainfall events are not determined in current practice. Some current research applies copulas to joint distributions of rainstorm variables, but most of these are limited to bivariate distributions, and those that are developed for trivariate distributions do not address key variables important to everyday practice, or are limited by complexity of analysis. An alternative approach to characterizing peak storm intensity, intensity peak factor, together with its probability distribution is developed in this paper. An Archimedean copula is applied to describe the joint probability distribution of storm duration with intensity peak factor. That joint distribution is combined with the probability distribution of storm depth, to produce a joint probability distribution for storm depth, duration, and peak intensity. The result is a simple approach to fully characterizing the storm variables of direct interest to practitioners, thereby providing a complete probabilistic description of the return period or frequency of a selected design storm.

Comparison of Synthetic Design Storms with Observed Storms in Southern Arizona

Historical storms with a 24-h rainfall depth exceeding 50.8 mm (2 in.) recorded in southern Arizona were compared with design storms developed both locally and by the USDA Soil Conservation Service (SCS). This study aims to evaluate if those design storms can be representative to southern Arizona. These storm depths represent the return-period storms that pose hazards considered in design. The temporal rainfall distributions, pattern index (PI), and intensity-duration relationships of the observed and design storms were compared. The comparison of the distributions and PIs of 3- or 24-h storms showed that the observed storms were diverse, and it was not clear which design storm fits best with the observed storms. The comparison of the intensity-duration relationships showed that most of the observed storms were less intense than any design storms, especially for short duration. This suggests that the application of any of the 3- or 24-h design storms would result in overestimating rainfall intensities for...

Spatio‐temporal characterization of Korean drought using severity–area–duration curve analysis

AbstractIn this study, the depth–area–duration (DAD) analysis for characterizing an extreme precipitation event provides a basis for analysing drought events when storm depth is replaced by an appropriate measure of drought severity. Monthly precipitation is probabilistically transformed into standardized precipitation index (SPI) and SPI time series are decomposed into a mutually independent data set by the empirical orthogonal function (EOF) analysis. All EOFs are spatially expanded to a 6 × 6 km resolution by kriging, for which a commercial package, SuRFER™, is used. Twenty main drought events from the grid‐based SPI time series are identified to construct the drought severity–effective area–drought duration (SAD) curves. The shape of SAD curves is similar to that of the rainfall DAD curves in the sense that drought severity and effective area are out of phase and that drought severity and duration are also out of phase. However, the severity reduction rate in SAD curves is much smaller than the corresponding rate in DAD analysis.

A stochastic design rainfall generator based on copulas and mass curves

Abstract. The use of design storms can be very useful in many hydrological and hydraulic practices. In this study, the concept of a copula-based secondary return period in combination with the concept of mass curves is used to generate point-scale design storms. The analysis is based on storms selected from the 105 year rainfall time series with a 10 min resolution, measured at Uccle, Belgium. In first instance, bivariate copulas and secondary return periods are explained, together with a focus on which couple of storm variables is of highest interest for the analysis and a discussion of how the results might be affected by the goodness-of-fit of the copula. Subsequently, the fitted copula is used to sample storms with a predefined secondary return period for which characteristic variables such as storm duration and total storm depth can be derived. In order to construct design storms with a realistic storm structure, mass curves of 1st, 2nd, 3rd and 4th quartile storms are developed. An analysis shows that the assumption of independence between the secondary return period and the internal storm structure could be made. Based on the mass curves, a technique is developed to randomly generate an intrastorm structure. The coupling of both techniques eventually results in a methodology for stochastic design storm generation. Finally, its practical usefulness for design studies is illustrated based on the generation of a set of statistically identical design storm and rainfall-runoff modelling.

Is Precipitation in Northern New England Becoming More Extreme? Statistical Analysis of Extreme Rainfall in Massachusetts, New Hampshire, and Maine and Updated Estimates of the 100-Year Storm

The objective of this study was to investigate the presence of trends in extreme precipitation (denoted MAXP and defined as the annual maximum daily precipitation depth) time series for coastal northern New England and to assess changes in the magnitude of the so-called 100-year storm. MAXP depths from 48 stations with long, continuous records in Maine, New Hampshire, and Massachusetts were analyzed. At those same stations, the number of daily precipitation depths ≥ 2i n: (51 mm, denoted as GT2in) was also quantified for each year. Although the seasonally averaged MAXP was found to be fairly uniform throughout the year, the frequency of MAXP is highest during August through October, the typical hurricane season in New England. The presence of trends in MAXP and GT2in was evaluated over four time frames (1954-2005, 1954-2008, 1970-2005, and 1970-2008) using two statistical methods (linear regression and the Mann-Kendall trend test) and at two scales (at-site and regional). The trend analysis over the time period 1954-2005 indicated that MAXP was amazingly stationary; however, a trend in GT2in was found at some stations. More trends in both MAXP and GT2in were present in the time period 1954-2008. The majority of stations in southern New Hampshire and eastern Massachusetts showed evidence of trends in MAXP (but not GT2in) for the time period 1970-2008. That the number of trends in MAXP increased despite the shorter record length suggests a strong increase in the magnitude of extreme precipitation in northern coastal New England in the last few decades. The stationarity of the 1954-2005 record was confirmed by the regional trend analysis, as was the presence of stronger trends in coastal stations when the record was extended through 2008. Most stations that had trends in MAXP also had trends in GT2in. The generalized extreme value (GEV) distribution was used to estimate 100-year precipitation depth quantiles for the 1954-2005 record, which were then compared with Technical Paper No. 40 (TP-40) 100-year, 24-h precipitation depths. Estimates for stations along coastal Massachusetts, New Hampshire, and Maine all exceeded 7 in. (180 mm) and exceeded TP-40 by 1 in. (25 mm) or more. Stations in northeastern Massachusetts, southeastern New Hampshire, and southern Maine exceeded 8 in. (200 mm) and also exceeded TP-40 estimates by more than 2 in. (51 mm). These findings indicate that TP-40 underrepresents coastal storm depths. This study, as well as recent record-breaking events in northern New England, strongly suggests the need for updating of design storm estimates. Furthermore, extreme precipitation events of longer than one-day duration have caused large-scale flooding in the region over the last decade. The magnitude of longer duration storms (particularly two-day storms) may also be increasing, calling for engineered infrastructure that can accommodate increases in both storm magnitude and duration. DOI: 10.1061/(ASCE)HE.1943-5584.0000303. © 2011 American Society of Civil Engineers.

A Comparison of Tropical and Midlatitude Thunderstorm Evolution in Response to Wind Shear

Abstract The influence of vertical wind shear on storm development within a tropical environment is studied with the aid of two numerical models and compared with that in simulations of midlatitude storms. The simulations show that larger wind shears are required in a tropical environment than in a midlatitude environment for a storm of given updraft velocity to split. This finding is supported by the experience of forecasters at the Australian Bureau of Meteorology Regional Forecasting Centre in Darwin that the operational storm forecasting tools developed for midlatitude storms overforecast supercells within the tropics. That tropical storms require higher shears to split can be attributed either to the larger gust front speed or to the earlier gust front occurrence compared to those in the midlatitudes. A fast gust front cuts off the storm from the warm moist inflow and the updraft has little or no time to split. In the cases where the midtropospheric relative humidity is larger in the tropics or comparable with that in the midlatitudes, the total liquid water and ice content within the deeper tropical storms is larger than in the midlatitude storms, causing a stronger downdraft. In other words, the main contribution to the negative buoyancy of the downdraft is the water loading rather than the evaporative cooling. When a tropical storm is simulated in an environment with smaller midtropospheric relative humidity than in the midlatitudes, the amount of liquid water and ice within the storm is comparable to that within the midlatitude storm. Intense evaporation within the tropical storm then leads to a stronger negative buoyancy than in the midlatitude storm, causing a stronger downdraft and thus an earlier or a faster-spreading gust front. At higher shears in the tropics, entrainment reduces the storm depth and thus water loading, resulting in a delayed gust front initiation and/or reduction of the gust front speed, which then allows storm splitting to occur.

Parking Deck’s First Flush

The goals of storm-water management have shifted from a flood control to a holistic and sustainable strategy, emphasizing the relationship between rainfall event size and pollutant loadings. The first flush concept is the first part of a rainfall event that contains the largest pollutant loading. Questions have been raised on the concept's validity for storms across different land uses and pollutant types. The existence and magnitude of the first flush impacts sizing of best management practices used to meet pollutant reduction goals, assessment sampling methodologies, and state storm-water management strategies. Current concepts support the use of distributed control measures focused on smaller storms off impervious surfaces. Runoff from a small impervious parking area was sampled incrementally during multiple storm events to measure pollutant concentration with respect to storm depth. This sampling routine established the existence of a first flush for a single use paved parking area. Total suspended solids, nitrate, chloride, dissolved copper, and dissolved cadmium exhibited a first flush up to a rainfall depth of 25.4 mm; total dissolved solids, total nitrogen, total phosphorus, nitrite, phosphate, and dissolved chromium did not exhibit a first flush.