Duration-frequency relationships of heavy rainfall in Santa Catarina, Brazil

The purpose of this study was to adjust equations that establish relationships between rainfall events with different duration and data from weather stations in the state of Santa Catarina, Brazil. In this study, the relationships between different duration heavy rainfalls from 13 weather stations of Santa Catarina were analyzed. From series of maximum annual rainfalls, and using the Gumbel-Chow distribution, the maximum rainfall for durations between 5 min and 24 h were estimated considering return periods from 2 to 100 years. The data fit to the Gumbel-Chow model was verified by the Kolmogorov-Smirnov test at 5 % significance. The coefficients of Bell's equation were adjusted to estimate the relationship between rainfall duration t (min) and the return period T (y) in relation to the maximum rainfall with a duration of 1 hour and a 10 year return period. Likewise, the coefficients of Bell's equation were adjusted based on the maximum rainfall with a duration of 1 day and a 10 year return period. The results showed that these relationships are viable to estimate short-duration rainfall events at locations where there are no rainfall records.

Data analysis and hydrological modelling of rainfall and discharge extremes along the Tione River: implications for the design of water structures

There are many natural events that can negatively affect the urban ecosystem, but weather-climate variations are certainly among the most significant. The history of settlements has been characterized by extreme events like earthquakes and floods, which repeat themselves at different times, causing extensive damage to the built heritage on a structural and urban scale. Changes in climate also alter various climatic subsystems, changing rainfall regimes and hydrological cycles, increasing the frequency and intensity of extreme precipitation events (heavy rainfall).  From an hydrological risk perspective, it is crucial to understand future events that could occur and their magnitude in order to design safer infrastructures. Unfortunately, it is not easy to understand future scenarios as the complexity of climate is enormous.  For this thesis, precipitation and discharge extremes were primarily used as data sources. It is important to underline that the two data sets are not separated: changes in rainfall regime, due to climate change, could significantly affect overflows into receiving water bodies. It is imperative that we understand and model climate change effects on water structures to support the development of adaptation strategies.   The main purpose of this thesis is to search for suitable water structures for a road located along the Tione River. Therefore, through the analysis of the area from a hydrological point of view, we aim to guarantee the safety of the infrastructure over time.   The observations made have the purpose to underline how models such as a stochastic one can improve the quality of an analysis for design purposes, and influence choices.

A Computerized Method for the Hydrologic Design of Culverts, February 1974

Nationwide, about five cents of each highway construction dollar is spent on culverts. In Iowa, average annual construction costs on the interstate, primary, and federal-aid secondary systems are about $120,000,000. Assuming the national figure applies to Iowa, about $6,000,000 are spent on culvert construction annually. For each one percent reduction in overall culvert costs, annual construction costs would be reduced by $60,000. One area of potential cost reduction lies in the sizing of the culvert. Determining the flow area and hydraulic capacity is accomplished in the initial design of the culvert. The normal design sequence is accomplished in two parts. The hydrologic portion consists of the determination of a design discharge in cubic feet per second using one of several available methods. This discharge is then used directly in the hydraulic portion of the design to determine the proper type, size, and shape of culvert to be used, based on various site and design restrictions. More refined hydrologic analyses, including rainfall-runoff analysis, flood hydrograph development, and streamflow routing techniques, are not pursued in the existing design procedure used by most county and state highway engineers.

Addendum to the Design Manual for Low Water Stream Crossings, HR-247, 1984

The purpose of this manual is to provide guidelines for low water stream crossings (LWSC). Rigid criteria for determining the applicability of a LWSC to a given site are not established nor is a 'cookbook" procedure for designing a LWSC presented. Because conditions vary from county to county and from site to site within the county, judgment must be applied to the suggestions contained in this manual. A LWSC is a stream crossing that will be flooded periodically and closed to traffic. Carstens (1981) has defined a LWSC as "a ford, vented ford (one having some number of culvert pipes), low water bridge, or other structure that is designed so that its hydraulic capacity will be insufficient one or more times during a year of normal rainfall." In this manual, LWSC are subdivided into these same three main types: unvented fords, vented fords and low water bridges. Within the channel banks, an unvented ford can have its road profile coincident with the stream bed or can have its profile raised some height above the stream bed.

Leaching of Picloram in ultisol under different rainfall volumes

The present study aimed to evaluate the leaching potential of Picloram in Ultisol columns under different rainfall amounts. For such, 30 treatments were evaluated (one soil associated with three levels of rainfall and ten depths).The experiments were arranged in a split-plot design, in a completely randomized design, with four replications. PVC columns of 10 cm in diameter and 50 cm in length were filled with these soils, moistened, and placed upright for 48 hours to drain the excess water. The herbicide was applied and rainfall simulations were carried out at specified intensities, according to the treatments, to force Picloram leaching. After 72 hours, all the columns were arranged in a horizontal position and opened lengthwise. Then, soil sampling was carried out every 5 cm of depth for subsequent herbicide extraction and quantification and analysis by high performance liquid chromatography. The remaining soil samples were placed in plastic pots, and, at the respective depths, the indicator species Cucumis sativus was sown. Twenty-one days after the emergence (DAE) of the indicator plants, evaluations were conducted to verify the symptoms of toxicity caused by Picloram in the plants. It was concluded that Picloram leaching is directly dependent on the volume of rain applied. The herbicide reached the deepest regions in the soil with the highest intensity of rain. The results obtained by bioassay were in agreement with those found by liquid chromatography.

Design and optimisation of a large-area process-based model for annual crops

The formulation of a new process-based crop model, the general large-area model (GLAM) for annual crops is presented. The model has been designed to operate on spatial scales commensurate with those of global and regional climate models. It aims to simulate the impact of climate on crop yield. Procedures for model parameter determination and optimisation are described, and demonstrated for the prediction of groundnut (i.e. peanut; Arachis hypogaea L.) yields across India for the period 1966-1989. Optimal parameters (e.g. extinction coefficient, transpiration efficiency, rate of change of harvest index) were stable over space and time, provided the estimate of the yield technology trend was based on the full 24-year period. The model has two location-specific parameters, the planting date, and the yield gap parameter. The latter varies spatially and is determined by calibration. The optimal value varies slightly when different input data are used. The model was tested using a historical data set on a 2.5degrees x 2.5degrees grid to simulate yields. Three sites are examined in detail-grid cells from Gujarat in the west, Andhra Pradesh towards the south, and Uttar Pradesh in the north. Agreement between observed and modelled yield was variable, with correlation coefficients of 0.74, 0.42 and 0, respectively. Skill was highest where the climate signal was greatest, and correlations were comparable to or greater than correlations with seasonal mean rainfall. Yields from all 35 cells were aggregated to simulate all-India yield. The correlation coefficient between observed and simulated yields was 0.76, and the root mean square error was 8.4% of the mean yield. The model can be easily extended to any annual crop for the investigation of the impacts of climate variability (or change) on crop yield over large areas. (C) 2004 Elsevier B.V. All rights reserved.

The 30-year TAMSAT African rainfall climatology and time-series (TARCAT) dataset

African societies are dependent on rainfall for agricultural and other water-dependent activities, yet rainfall is extremely variable in both space and time and reoccurring water shocks, such as drought, can have considerable social and economic impacts. To help improve our knowledge of the rainfall climate, we have constructed a 30-year (1983–2012), temporally consistent rainfall dataset for Africa known as TARCAT (TAMSAT African Rainfall Climatology And Time-series) using archived Meteosat thermal infra-red (TIR) imagery, calibrated against rain gauge records collated from numerous African agencies. TARCAT has been produced at 10-day (dekad) scale at a spatial resolution of 0.0375°. An intercomparison of TARCAT from 1983 to 2010 with six long-term precipitation datasets indicates that TARCAT replicates the spatial and seasonal rainfall patterns and interannual variability well, with correlation coefficients of 0.85 and 0.70 with the Climate Research Unit (CRU) and Global Precipitation Climatology Centre (GPCC) gridded-gauge analyses respectively in the interannual variability of the Africa-wide mean monthly rainfall. The design of the algorithm for drought monitoring leads to TARCAT underestimating the Africa-wide mean annual rainfall on average by −0.37 mm day−1 (21%) compared to other datasets. As the TARCAT rainfall estimates are historically calibrated across large climatically homogeneous regions, the data can provide users with robust estimates of climate related risk, even in regions where gauge records are inconsistent in time.

Climate change impacts in the design of drainage systems: case study of Portugal

This paper aims to assess the necessity of updating the intensity-duration-frequency (IDF) curves used in Portugal to design building storm-water drainage systems. A comparative analysis of the design was performed for the three predefined rainfall regions in Portugal using the IDF curves currently in use and estimated for future decades. Data for recent and future climate conditions simulated by a global and regional climate model chain are used to estimate possible changes of rainfall extremes and its implications for the drainage systems. The methodology includes the disaggregation of precipitation up to subhourly scales, the robust development of IDF curves, and the correction of model bias. Obtained results indicate that projected changes are largest for the plains in southern Portugal (5–33%) than for mountainous regions (3–9%) and that these trends are consistent with projected changes in the long-term 95th percentile of the daily precipitation throughout the 21st century. The authors conclude there is a need to review the current precipitation regime classification and change the new drainage systems towards larger dimensions to mitigate the projected changes in extreme precipitation.

The use of remotely sensed rainfall for managing drought risk: a case study of weather index insurance in Zambia

Remotely sensed rainfall is increasingly being used to manage climate-related risk in gauge sparse regions. Applications based on such data must make maximal use of the skill of the methodology in order to avoid doing harm by providing misleading information. This is especially challenging in regions, such as Africa, which lack gauge data for validation. In this study, we show how calibrated ensembles of equally likely rainfall can be used to infer uncertainty in remotely sensed rainfall estimates, and subsequently in assessment of drought. We illustrate the methodology through a case study of weather index insurance (WII) in Zambia. Unlike traditional insurance, which compensates proven agricultural losses, WII pays out in the event that a weather index is breached. As remotely sensed rainfall is used to extend WII schemes to large numbers of farmers, it is crucial to ensure that the indices being insured are skillful representations of local environmental conditions. In our study we drive a land surface model with rainfall ensembles, in order to demonstrate how aggregation of rainfall estimates in space and time results in a clearer link with soil moisture, and hence a truer representation of agricultural drought. Although our study focuses on agricultural insurance, the methodological principles for application design are widely applicable in Africa and elsewhere.

Distribution Of Hydrological Losses For Varying Rainfall And Antecedent Wetness Conditions

Hydrological loss is a vital component in many hydrological models, which are usedin forecasting floods and evaluating water resources for both surface and subsurface flows. Due to the complex and random nature of the rainfall runoff process, hydrological losses are not yet fully understood. Consequently, practitioners often use representative values of the losses for design applications such as rainfall-runoff modelling which has led to inaccurate quantification of water quantities in the resulting applications. The existing hydrological loss models must be revisited and modellers should be encouraged to utilise other available data sets. This study is based on three unregulated catchments situated in Mt. Lofty Ranges of South Australia (SA). The paper focuses on conceptual models for: initial loss (IL), continuing loss (CL) and proportional loss (PL) with rainfall characteristics (total rainfall (TR) and storm duration (D)), and antecedent wetness (AW) conditions. The paper introduces two methods that can be implemented to estimate IL as a function of TR, D and AW. The IL distribution patterns and parameters for the study catchments are determined using multivariate analysis and descriptive statistics. The possibility of generalising the methods and the limitations of this are also discussed. This study will yield improvements to existing loss models and will encourage practitioners to utilise multiple data sets to estimate losses, instead of using hypothetical or representative values to generalise real situations.

Uncertainties In Future Projections Of Extreme Rainfall: The Role Of Climate Model, Emission Scenario And Randomness

Climate change has resulted in substantial variations in annual extreme rainfall quantiles in different durations and return periods. Predicting the future changes in extreme rainfall quantiles is essential for various water resources design, assessment, and decision making purposes. Current Predictions of future rainfall extremes, however, exhibit large uncertainties. According to extreme value theory, rainfall extremes are rather random variables, with changing distributions around different return periods; therefore there are uncertainties even under current climate conditions. Regarding future condition, our large-scale knowledge is obtained using global climate models, forced with certain emission scenarios. There are widely known deficiencies with climate models, particularly with respect to precipitation projections. There is also recognition of the limitations of emission scenarios in representing the future global change. Apart from these large-scale uncertainties, the downscaling methods also add uncertainty into estimates of future extreme rainfall when they convert the larger-scale projections into local scale. The aim of this research is to address these uncertainties in future projections of extreme rainfall of different durations and return periods. We plugged 3 emission scenarios with 2 global climate models and used LARS-WG, a well-known weather generator, to stochastically downscale daily climate models’ projections for the city of Saskatoon, Canada, by 2100. The downscaled projections were further disaggregated into hourly resolution using our new stochastic and non-parametric rainfall disaggregator. The extreme rainfall quantiles can be consequently identified for different durations (1-hour, 2-hour, 4-hour, 6-hour, 12-hour, 18-hour and 24-hour) and return periods (2-year, 10-year, 25-year, 50-year, 100-year) using Generalized Extreme Value (GEV) distribution. By providing multiple realizations of future rainfall, we attempt to measure the extent of total predictive uncertainty, which is contributed by climate models, emission scenarios, and downscaling/disaggregation procedures. The results show different proportions of these contributors in different durations and return periods.

Rainfall intensity and Mepiquat Chloride persistence in cotton

Em parte das regiões onde se encontram as maiores áreas de algodão no Brasil atualmente, o índice pluviométrico está ao redor de 2.000 mm anuais, existindo risco de ocorrer lavagem do Cloreto de Mepiquat (CM) das folhas do algodoeiro antes de ser absorvido pelas plantas. O objetivo deste trabalho foi avaliar a lavagem do CM aplicado no algodoeiro por diferentes laminas de chuva simulada. Os tratamentos constaram de três doses do regulador à base de cloreto de mepiquat: 0, 15.0 e 30.0 g ha-1 e quatro lâminas de chuva simulada: 5, 10, 20 e 40 mm, mais um tratamento sem chuva. Foram utilizados vasos de 12 litros de capacidade e a cultivar Delta Opal. Os parâmetros avaliados foram: altura de plantas, número de ramos reprodutivos, massa de matéria seca, retenção de estruturas reprodutivas e área foliar. Quanto maior a intensidade de chuva ocorrida após a aplicação do regulador maior foi o comprometimento da ação do produto, que repercutiu em interferência no crescimento das plantas. Chuvas de 5.0 mm, ocorridas 90 minutos após a aplicação do cloreto de mepiquat, já causaram prejuízo na ação do produto no crescimento do algodoeiro, sendo o efeito maior com o aumento da quantidade de chuva simulada.

COMPARING RAINFALL INTENSITY DURATION RELATIONSHIPS FOR SITES OF THE STATE OF SAO PAULO

Rainfall intensity durations relationships are extremely important in the design of systems for mitigating runoff losses. The objective of this work was to compare rainfall depths generated by the PLUVIO 2.1 software, with depths from the standard intensity duration curves developed by MARTINEZ & MAGNI (1999). It was compared rainfall intensities of 10, 20, 30, 60, 120 and 1440 minute durations for 2, 5, 10, 50 and 100 year return periods for 30 sites in the state of Sao Paulo. The results showed that PLUVIO was effective, except in predicting the 24 hours rainfall from 100 year return period events in four locations in the central and eastern regions of the state.

Probabilistic Envelope Curves for Extreme Rainfall Events - Curve Inviluppo Probabilistiche per Precipitazioni Estreme

A regional envelope curve (REC) of flood flows summarises the current bound on our experience of extreme floods in a region. RECs are available for most regions of the world. Recent scientific papers introduced a probabilistic interpretation of these curves and formulated an empirical estimator of the recurrence interval T associated with a REC, which, in principle, enables us to use RECs for design purposes in ungauged basins. The main aim of this work is twofold. First, it extends the REC concept to extreme rainstorm events by introducing the Depth-Duration Envelope Curves (DDEC), which are defined as the regional upper bound on all the record rainfall depths at present for various rainfall duration. Second, it adapts the probabilistic interpretation proposed for RECs to DDECs and it assesses the suitability of these curves for estimating the T-year rainfall event associated with a given duration and large T values. Probabilistic DDECs are complementary to regional frequency analysis of rainstorms and their utilization in combination with a suitable rainfall-runoff model can provide useful indications on the magnitude of extreme floods for gauged and ungauged basins. The study focuses on two different national datasets, the peak over threshold (POT) series of rainfall depths with duration 30 min., 1, 3, 9 and 24 hrs. obtained for 700 Austrian raingauges and the Annual Maximum Series (AMS) of rainfall depths with duration spanning from 5 min. to 24 hrs. collected at 220 raingauges located in northern-central Italy. The estimation of the recurrence interval of DDEC requires the quantification of the equivalent number of independent data which, in turn, is a function of the cross-correlation among sequences. While the quantification and modelling of intersite dependence is a straightforward task for AMS series, it may be cumbersome for POT series. This paper proposes a possible approach to address this problem.