Estimation of Peak Discharges under Different Rainfall Depth–Duration–Frequency Formulations

One of the main signatures of short duration storms is given by Depth–Duration–Frequency (DDF) curves. In order to provide reliable estimates for small river basins or urban catchments, generally characterized by short concentration times, in this study the performances of different DDF curves proposed in literature are described and compared, in order to provide insights on the selection of the best approach in design practice, with particular reference to short durations. With this aim, 28 monitoring stations with time series of annual maximum rainfall depth characterized by sample size greater than 20 were selected in the Northern part of the Puglia region (South-Eastern Italy). In order to test the effect of the investigated DDF curves in reproducing the design peak discharge corresponding to an observed expected rainfall event, the Soil Conservation (SCS) curve number (CN) approach is exploited, generating peak discharges according to different selected combinations of the main parameters that control the critical rainfall duration. Results confirm the good reliability of the DDF curves with three parameters to adapt on short events both in terms of rainfall depth and in terms of peak discharge and, in particular, for durations up to 30 min, the three-parameter DDF curves always perform better than the two-parameter DDF.

Analysis of Annual Maximum Rainfall for Frequency Distribution to Determine the Best-fitted Probability Distribution for Different Sites in Pakistan.

In the project of irrigation and addition structure of hydraulic, it is important to assess the specific probability of extreme rainfall. The novelty of this study is the use of KS, Chi-square, root mean square error (RMSE), and peak weight root means square error (PWRMSE) to evaluate the fit theoretical and Empirical distributions. Thirty-seven years of meteorological data from 1980 to 2017, the frequency analysis of the annual maximum rainfall in 10 regions of Pakistan was conducted. Used eight formulas to predict the annual return period of the maximum hourly precipitation every year. Five different probability distribution functions (PDF) are used to predict the probability distribution of the annual maximum hourly rainfall. Use the chi-square test and Kolmogorov- Smirnov to assess the goodness of fit. It shows that the log-logistics distribution is the overall best-fitting PDF of the annual maximum hourly rainfall in most areas of Pakistan. Besides, the peak weight relative mean square error and root mean square error goodness of fit test indicators both indicate that most suitable distribution of the probability function of all stations analysis is similar. The value of root means square error (RMSE) is almost always smaller than peak weight root means square error (PWRMSE). This is due to the higher weighting of value above the average value in the PWRMSE goodness of fit index, while for the RMSE goodness of fit index individual value has an equal weight.

Spatial and temporal behavior of annual maximum sub-hourly rainfall intensities from 15-minute to 24-hour durations in central Chile

Maximum rainfall intensity is an interesting factor to analyze when determining whether temporal and spatial changes have occurred. Data gathered from 11 rain gauges were used to determine annual maximum rainfall intensities for the Maule Region (central Chile), for durations from 15-minute to 24-hour durations, between 1974 and 2009. Statistical tests of position and dispersion were applied to this dataset, along with the non-parametric Mann-Kendall test to identify tendencies. Results showed that the highest intensities occurred at gauging stations with greater orographic influence and in areas near bodies of water. Additionally, the statistical analysis revealed that maximum rainfall intensities did not seem to show spatial or temporal tendencies through time. Instead, results suggest that intensities have remained stable within historic ranges and have not manifested important changes.

Analysis of extreme rainfall in Oti River Basin (West Africa)

Understanding how extreme rainfall is changing locally is a useful step in the implementation of efficient adaptation strategies to negative impacts of climate change. This study aims to analyze extreme rainfall over the middle Oti River Basin. Ten moderate extreme precipitation indices as well as heavy rainfall of higher return periods (25, 50, 75, and 100 years) were calculated using observed daily data from 1921 to 2018. In addition, Mann–Kendall and Sen's slope tests were used for trend analysis. The results showed decreasing trends in most of the heavy rainfall indices while the dry spell index exhibited a rising trend in a large portion of the study area. The occurrence of heavy rainfall of higher return periods has slightly decreased in a large part of the study area. Also, analysis of the annual maximum rainfall revealed that the generalized extreme value is the most appropriate three-parameter frequency distribution for predicting extreme rainfall in the Oti River Basin. The novelty of this study lies in the combination of both descriptive indices and extreme value theory in the analysis of extreme rainfall in a data-scarce river basin. The results are useful for water resources management in this area.

Defining rainfall intensity clusters in Turkey by using the fuzzy c-means algorithm

Turkey has seven traditionally accepted climatic zones that are defined primarily by maritime and topographic influences. Across these zones, the annual amount of rainfall, including its intensity and its seasonal distribution, vary considerably. These variations, which impact on both urban and rural communities, including the occurrence of water shortages and flash flooding events, are increasing in both frequency and magnitude due to global warming and climate change. Several types of climate occur in Turkey where climate zones have been defined with various methodologies. To better understand rainfall intensity patterns across Turkey, this study used the Fuzzy C-Means (FCM) algorithm to define their spatial distribution. In the first stage, the annual maximum rainfall intensity records for periods ranging from 30 to 78 years were obtained from 95 stations operated by the Turkish State Meteorological Service, and the longitude, latitude and altitude data for the stations were compiled for cluster analysis. Secondly, all rainfall intensities and geographical values were normalized, and in the third stage, the FCM algorithm was applied. The comparison of annual maximum rainfall intensities revealed five clusters. Four clusters were identified as discrete zones and one was identified as a transitional zone. Weather stations located in different geographical regions sometimes fell into the same clusters. In other words, rainfall events of similar intensity can occur in different climatic zones. This study, which brought a different perspective to clustering studies, showed that rainfall intensity values can be successfully analyzed at a national scale with the FCM technique.

Rainfall Analysis for Hyderabad and Nawabshah, Sindh, Pakistan

The climatic change has a visible impact in recent abnormal weather events, such as Pakistan’s intensification of the hydrological cycle with changing precipitation pattern, water availability periods, and weather-induced natural disasters. The rainfall flush flood of 2010 alone displaced millionσ of people and damaged properties in just one stroke. The next year, the shocking rainfall flood of 2011 in Sindh, only underscored the enormity of the challenge posed by climate change. The current paper presents the analysis carried out for one-day annual maximum rainfall for Hyderabad and Nawabshah cities, Sindh, Pakistan for the period from 1961 to 2011 using STATISTICA Software for interpolating and forecasting the rainfall time series. The maximum values of observed rainfall were 250.70mm and 256.30mm, while the minimum values were 3.0mm and 0.0mm for Hyderabad and Nawabshah respectively, while the mean of fifty-one (51) years of rainfall data is 51.96mm and 45.3 mm and the computed standard deviations were 42.693mm and 43.896mm respectively. The difference between the mean and standard deviation of one-day maximum rainfall is small, which showed the consistency of the data. The polynomial trend curved lines exhibited fluctuations in the rainfall data, which indicates a continual change in rainfall behavior. Hence, the rainfall data are subjected to a moving mean smoothing with a duration shorter than 3 years. Through these trends, the future one-day annual maximum rainfall can be predicted. The correlation of one-day annual maximum rainfall between Hyderabad and Nawabshah cities had R2 of 0.973. The computed results of return periods of 3, 5, and 10 years for one-day annual maximum rainfall for both cities revealed that the rainfall values for Hyderabad are higher.

ANALYSIS AND DESIGN OF DRAINAGE SYSTEM PLANNING STUDY (CASE STUDY GRAHA WISATA SIDOARJO RESIDENTIAL)

Graha Wisata Sidoarjo Housing has a land area of 470,000 m2 located in Lebo Village, Sidoarjo District, Sidoarjo Regency. The housing is passed by the Anak Afvoer Sidokare channel. With the change in land function, it is necessary to analyze the capacity of the Anak Afvoer Sidokare watershed. The rainfall data used is the annual maximum rainfall from the rain station Durungbedug, Ketintang, Sidoarjo, Sumput .. The method of rainfall analysis uses the Log Pearson type III method. Planned flood discharge in the Anak Afvoer Sidokare watershed at 25 years using the Nakayasu method is 450.55 m3 / sec while the existing Afvoer capacity with dimensions of 10 m x 4.172 m is 537.39 m3 / sec, the cross section of the Son Afvoer Sidokare channel is not overflow.