This study investigates the presence of trends in annual maximum daily precipitation time series obtained from a global dataset of 8326 high-quality land-based observing stations with more than 30 years of record over the period from 1900 to 2009. Two complementary statistical techniques were adopted to evaluate the possible nonstationary behavior of these precipitation data. The first was a Mann‐Kendall nonparametric trend test, and it was used to evaluate the existence of monotonic trends. The second was a nonstationary generalized extreme value analysis, and it was used to determine the strength of association between the precipitation extremes and globally averaged near-surface temperature. The outcomes are that statistically significant increasing trends can be detected at the global scale, with close to two-thirds of stations showing increases. Furthermore, there is a statistically significant association with globally averaged near-surface temperature,withthemedianintensityofextremeprecipitationchanginginproportionwithchangesinglobal mean temperature at a rate of between 5.9% and 7.7%K 21 , depending on the method of analysis. This ratio was robust irrespective of record length or time period considered and was not strongly biased by the uneven global coverage of precipitation data. Finally, there is a distinct meridional variation, with the greatest sensitivity occurring in the tropics and higher latitudes and the minima around 138S and 118N. The greatest uncertainty was near the equator because of the limited number of sufficiently long precipitation records, and there remains an urgent need to improve data collection in this region to better constrain future changes in tropical precipitation.

Global increasing trends in annual maximum daily precipitation

Urban pluvial flooding and stormwater management: A contemporary review of China’s challenges and “sponge cities” strategy

Problem Given the number of times in which an unknown event has happened and failed: Required the chance that the probability of its happening in a single trial lies somewhere between any two degrees of probability that can be named. SECTION 1 Definition 1. Several events are inconsistent, when if one of them happens, none of the rest can. 2. Two events are contrary when one, or other of them must; and both together cannot happen. 3. An event is said to fail, when it cannot happen; or, which comes to the same thing, when its contrary has happened. 4. An event is said to be determined when it has either happened or failed. 5. The probability of any event is the ratio between the value at which an expectation depending on the happening of the event ought to be computed, and the value of the thing expected upon it’s 2 happening.

An essay towards solving a problem in the doctrine of chances. [Facsimil]

This paper surveys the current state of knowledge regarding large-scale meteorological patterns (LSMPs) associated with short-duration (less than 1 week) extreme precipitation events over North America. In contrast to teleconnections, which are typically defined based on the characteristic spatial variations of a meteorological field or on the remote circulation response to a known forcing, LSMPs are defined relative to the occurrence of a specific phenomenon—here, extreme precipitation—and with an emphasis on the synoptic scales that have a primary influence in individual events, have medium-range weather predictability, and are well-resolved in both weather and climate models. For the LSMP relationship with extreme precipitation, we consider the previous literature with respect to definitions and data, dynamical mechanisms, model representation, and climate change trends. There is considerable uncertainty in identifying extremes based on existing observational precipitation data and some limitations in analyzing the associated LSMPs in reanalysis data. Many different definitions of “extreme” are in use, making it difficult to directly compare different studies. Dynamically, several types of meteorological systems—extratropical cyclones, tropical cyclones, mesoscale convective systems, and mesohighs—and several mechanisms—fronts, atmospheric rivers, and orographic ascent—have been shown to be important aspects of extreme precipitation LSMPs. The extreme precipitation is often realized through mesoscale processes organized, enhanced, or triggered by the LSMP. Understanding of model representation, trends, and projections for LSMPs is at an early stage, although some promising analysis techniques have been identified and the LSMP perspective is useful for evaluating the model dynamics associated with extremes.

/pdf/north-american-extreme-temperature-events-and-related-large-1mzz6ojjpv.pdf

North American extreme temperature events and related large scale meteorological patterns: a review of statistical methods, dynamics, modeling, and trends

Enhancing future resilience in urban drainage system: Green versus grey infrastructure

Rainwater harvesting (RWH) systems have many benefits being an effective alternative water supply solution, not only in arid and semi-arid regions. Also, these systems can be useful in the reduction of flood risk in urban areas. Nevertheless, most of the studies in literature focused on the potential of RWH in reducing water consumption, whereas few examples examined their efficiency in the retention of stormwater in flood-susceptible residential areas. The aim of this work was to investigate the reliability of RWH systems in terms of stormwater retention. Specifically, the performance of RWH tanks to supply water for toilet flushing, in more than 400 single-family houses in a residential area of Sicily (Southern Italy) was analyzed. The area of study was chosen due to its high susceptibility to flooding. A flushing water demand pattern was defined using water consumption data collected during a measurement campaign. The yield-after-spillage algorithm was used to simulate the daily water balance of the RWH tanks. The effect of the RWH implementation on flood volumes in the area of study was quantified using FLO-2D. Results point out that the potential of neighborhood RWH installation in the mitigation of flood risk is highly related to rainfall amount.

Effectiveness of Rainwater Harvesting Systems for Flood Reduction in Residential Urban Areas

Flooding is one of the main natural hazards in Northern Europe and several areas of the Northern Boreal Hemisphere, where during intense rainfall events, several river basins are affected by a fast water level rise that may cause severe damage to human lives and properties. For these reasons, the development of flood models to identify susceptible areas is essential for decision-makers. Geographic Information Systems (GIS) are currently accurate and valuable support tools for defining flood susceptibility maps at different spatial scales. In this study, the prediction accuracy of different GIS-based procedures in the identification of flooding susceptibility is tested and compared. These procedures include the frequency ratio, a combination of the frequency ratio and logistic regression, a combination of the frequency ratio and Shannon’s entropy index, and the statistical index. Ten conditioning parameters of flooding susceptibility are considered: elevation, slope, curvature, land use, Topographic Wetness Index, Stream Power Index, hydrogeology, stream distance, flow direction and average annual rainfall. The comparison analysis is carried out by applying these methods to the study area of Devon County in Southwest England. A total of 225 flood events are used to define the models. For model validation, 1000 randomly selected training and testing sub-datasets have been used in the definition of the receiver operating characteristic (ROC) curves. The results show that the procedure based on the statistical index provides the highest accuracy and reliability in flood susceptibility predictions.

Comparison between Different Distributed Methods for Flood Susceptibility Mapping

Rainwater harvesting (RWH) may be an effective alternative water supply solution in regions affected by water scarcity. It has recently become a particularly important option in arid and semi-arid areas (like Mediterranean basins), mostly because of its many benefits and affordable costs. This study provides an analysis of the reliability of using a rainwater harvesting system to supply water for toilet flushing and garden irrigation purposes, with reference to a single-family home in a residential area of Sicily (Southern Italy). A flushing water demand pattern was evaluated using water consumption data collected from a sample of residential customers during an extended measurement campaign. A daily water balance simulation of the rainwater storage tank was performed, and the yield-after-spillage algorithm was used to define the tank release rule. The model’s performance was evaluated using rainfall data from more than 100 different sites located throughout the Sicilian territory. This regional analysis provided annual reliability curves for the system as a function of mean annual precipitation, which have practical applications in this area of study. The uncertainty related to the regional model predictions was also assessed. A cost-benefit analysis highlighted that the implementation of a rainwater harvesting system in Sicily can provide environmental and economic advantages over traditional water supply methods. In particular, the regional analysis identified areas where the application of this system would be most effective.

/pdf/a-reliability-analysis-of-a-rainfall-harvesting-system-in-4rz11m84yu.pdf

A Reliability Analysis of a Rainfall Harvesting System in Southern Italy

Climate change resulting from the enhanced greenhouse effect is expected to have great impacts on hydrological cycle and consequently on ecosystems. The effects of climate variability have direct implications on water management, as water availability is related to changes in temperature and precipitation regimes. At the same time, this kind of alterations drives ecological impacts on flora and fauna. For these reasons, many studies have been carried out to investigate the existence of some tendency in temperature and/or precipitation series in different geographic domains. In order to verify the hypothesis of temperature increase in Sicily (Italy), temperature data from about 80 spatially distributed weather stations have been deeply analysed. In this study, trend of annual, seasonal and monthly temperature time series have been examined for the period 1924–2006 to investigate possible evidences of climate changes in this region. In addition, also a long series (more than 200 years) has been analysed in order to individuate possible anomalies in the 20th century and to verify the presence, in the last decades, of a temperature increase larger than in the past. The Mann–Kendall non-parametric statistical test has been used to identify trends in temperature time series data. The test has been applied at local and regional scale for three different confidence level, considering the influence of serial correlation as well. The field significance of the regional results has been evaluated using a bootstrap technique of resampling that allows to eliminate the influence of data spatial correlation on Mann–Kendall test. The application of Mann–Kendall test on temperature data provides the evidence of a general warming in Sicily during the analysed period. The analysis of the long series demonstrates that the temperature trend is mainly due to the strong rising observed in the last years of the past century. In order to determine the spatial patterns of temperature trends and identify areas with a similar temperature evolution, the detected trends have been first subjected to the spatial auto correlation analysis and then interpolated using spatial analysis techniques in a GIS framework. Temperature trend maps have allowed to argue on the risk of aridity increase, in particular in the central and western part of the island. Copyright © 2013 Royal Meteorological Society

Spatial distribution of temperature trends in Sicily

Climate change resulting from the enhanced greenhouse effect is expected to have significant implications for the hydrological cycle. Several studies have pointed out the importance of basin-scale investigations for determining regional impacts on water resources, including the effects of floods and droughts. In this study, a fully distributed hydrologic model is used to assess the potential impacts of climate change on water availability in a basin in Oklahoma (United States). With this aim, the hydrologic model was applied for current conditions as well as under the hypotheses of climate variations represented by scenarios consistent with a climatic trend analysis generated using a stochastic weather model. Hydrologic simulations indicate that streamflow and evapotranspiration reflect variations in precipitation differently. Positive trends in precipitation result in an increase in surface and groundwater resources, while evapotranspiration is only affected slightly due to the higher soil moisture in th...

Basin-Scale Water Resources Assessment in Oklahoma under Synthetic Climate Change Scenarios Using a Fully Distributed Hydrologic Model

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