Effect of radar rainfall time resolution on the predictive capability of a distributed hydrologic model

The performance of a hydrologic model depends on the rainfall input data, both spatially and temporally. As the spatial distribution of rainfall exerts a great influence on both runoff volumes and peak flows, the use of a distributed hydrologic model can improve the results in the case of convective rainfall in a basin where the storm area is smaller than the basin area. The aim of this study was to perform a sensitivity analysis of the rainfall time resolution on the results of a distributed hydrologic model in a flash-flood prone basin. Within such a catchment, floods are produced by heavy rainfall events with a large convective component. A second objective of the current paper is the proposal of a methodology that improves the radar rainfall estimation at a higher spatial and temporal resolution. Composite radar data from a network of three C-band radars with 6-min temporal and 2 × 2 km2 spatial resolution were used to feed the RIBS distributed hydrological model. A modification of the Window Probability Matching Method (gauge-adjustment method) was applied to four cases of heavy rainfall to improve the observed rainfall sub-estimation by computing new Z/R relationships for both convective and stratiform reflectivities. An advection correction technique based on the cross-correlation between two consecutive images was introduced to obtain several time resolutions from 1 min to 30 min. The RIBS hydrologic model was calibrated using a probabilistic approach based on a multiobjective methodology for each time resolution. A sensitivity analysis of rainfall time resolution was conducted to find the resolution that best represents the hydrological basin behaviour.

Validation of and comparison between a semidistributed rainfall-runoff hydrological model (PREVAH) and a spatially distributed snow-evolution model (SnowModel) for snow cover prediction in mountain ecosystems

Snow cover is an important control in mountain environments and a shift of the snow-free period triggered by climate warming can strongly impact ecosystem dynamics. Changing snow patterns can have severe effects on alpine plant distribution and diversity. It thus becomes urgent to provide spatially explicit assessments of snow cover changes that can be incorporated into correlative or empirical species distribution models (SDMs). Here, we provide for the first time a with a lower overestimation comparison of two physically based snow distribution models (PREVAH and SnowModel) to produce snow cover maps (SCMs) at a fine spatial resolution in a mountain landscape in Austria. SCMs have been evaluated with SPOT-HRVIR images and predictions of snow water equivalent from the two models with ground measurements. Finally, SCMs of the two models have been compared under a climate warming scenario for the end of the century. The predictive performances of PREVAH and SnowModel were similar when validated with the SPOT images. However, the tendency to overestimate snow cover was slightly lower with SnowModel during the accumulation period, whereas it was lower with PREVAH during the melting period. The rate of true positives during the melting period was two times higher on average with SnowModel with a lower overestimation of snow water equivalent. Our results allow for recommending the use of SnowModel in SDMs because it better captures persisting snow patches at the end of the snow season, which is important when modelling the response of species to long-lasting snow cover and evaluating whether they might survive under climate change.

Torrential rainfall in northeast of the Iberian Peninsula: synoptic patterns and WeMO influence

This study presents a catalogue of synoptic patterns of torrential rainfall in northeast of the Iberian Peninsula (IP). These circulation patterns were obtained by applying a T-mode Principal Component Analysis (PCA) to a daily data grid (NCEP/NCAR reanalysis) at sea level pressure (SLP). The analysis made use of 304 days which recorded >100 mm in one or more stations in provinces of Barcelona, Girona and Tarragona (coastland area of Catalonia) throughout the 1950-2005 period. The catalogue comprises 7 circulation patterns showing a great variety of atmospheric conditions and seasonal or monthly distribution. Likewise, we computed the mean index value of the Western Mediterranean Oscillation index (WeMOi) for the synoptic patterns obtained by averaging all days grouped in each pattern. The results showed a clear association between the negative values of this teleconnection index and torrential rainfall in northeast of the IP. We therefore put forward the WeMO as an essential tool for forecasting heavy rainfall in northeast of Spain

Effect of temperature, leaf wetness, and rainfall on the production of Guignardia citricarpa ascospores and on back spot severity on sweet orange

The black spot of citrus (Citrus sp.) is caused by Guignardia citricarpa with ascospore production depending on temperature, leaf wetness, and rainfall. The number of ascospores produced was monitored using a spore trap and climatic factors were recorded using an automated meteorological station of 'Natal' and 'Valencia' sweet orange (Citrus sinensis) orchards in Mogi Guaçu in the state of São Paulo, Brazil, from November 2000 to March 2001. The fruits were bagged to prevent infection and the bags removed from different sets of fruit for one week during each of the 18 weeks of the season in both orchards. Ascospores were produced during the entire experimental period, from spring through summer, primarily after rain events. In both orchards, ascospore production reached a peak in January and February. Ascospore production was related to leaf wetness only in the Natal orange orchard but was not related to total rainfall or temperature in either orchard. Disease was most severe on fruit exposed the 7th, 8th, and 13th weeks after beginning the experiment in both cultivars as well as after the 16th week for 'Natal'. There was a strong relationship between disease severity and total rainfall for both orchards and a weak correlation between temperature and severity in the 'Natal' block only. There was no relationship between severity and leaf wetness or ascospore numbers.

Spatial variability of the rainfall erosive potential in the State of Mato Grosso do Sul, Brazil

Information about rainfall erosivity is important during soil and water conservation planning. Thus, the spatial variability of rainfall erosivity of the state Mato Grosso do Sul was analyzed using ordinary kriging interpolation. For this, three pluviograph stations were used to obtain the regression equations between the erosivity index and the rainfall coefficient EI30. The equations obtained were applied to 109 pluviometric stations, resulting in EI30 values. These values were analyzed from geostatistical technique, which can be divided into: descriptive statistics, adjust to semivariogram, cross-validation process and implementation of ordinary kriging to generate the erosivity map.Highest erosivity values were found in central and northeast regions of the State, while the lowest values were observed in the southern region. In addition, high annual precipitation values not necessarily produce higher erosivity values.

Rainfall erosivity for the State of Rio de Janeiro estimated by artificial neural network

The Artificial Neural Networks (ANNs) are mathematical models method capable of estimating non-linear response plans. The advantage of these models is to present different responses of the statistical models. Thus, the objective of this study was to develop and to test ANNs for estimating rainfall erosivity index (EI30) as a function of the geographical location for the state of Rio de Janeiro, Brazil and generating a thematic visualization map. The characteristics of latitude, longitude e altitude using ANNs were acceptable to estimating EI30 and allowing visualization of the space variability of EI30. Thus, ANN is a potential option for the estimate of climatic variables in substitution to the traditional methods of interpolation.

Probabilistic structure of an annual extreme rainfall series of a coastal area of the State of São Paulo, Brazil

This study aimed to describe the probabilistic structure of the annual series of extreme daily rainfall (Preabs), available from the weather station of Ubatuba, State of São Paulo, Brazil (1935-2009), by using the general distribution of extreme value (GEV). The autocorrelation function, the Mann-Kendall test, and the wavelet analysis were used in order to evaluate the presence of serial correlations, trends, and periodical components. Considering the results obtained using these three statistical methods, it was possible to assume the hypothesis that this temporal series is free from persistence, trends, and periodicals components. Based on quantitative and qualitative adhesion tests, it was found that the GEV may be used in order to quantify the probabilities of the Preabs data. The best results of GEV were obtained when the parameters of this function were estimated using the method of maximum likelihood. The method of L-moments has also shown satisfactory results.

Determination of total accumulated rainfall, global radiation, evapotranspiration and degree-days originated from the ECMWF model to sugar cane crop

The climate variability between the growth and harvesting of sugar cane is very important because it directly affects yield. The MODIS sensor has characteristics like spatial and temporal resolution that can be applied to monitoring of vegetative vigor variability in the land surface and then, temporal profiles generation. Agro meteorological data from ECMWF model are free and easy to access and have a good representation of reality. In this study, we used the period between sugar cane growth and harvest in the state of Sao Paulo, Brazil, from temporal profiles selecting of NDVI behavior. For each period the precipitation, evapotranspiration, global radiation, length (days) and degree-days were accumulated. The periods were presented in a map format on MODIS spatial resolution of 250 meters. The results showed the spatial variability of climate variables and the relationship to the reality presented by official data.

Methodology for spatialization of intense rainfall equation parameters

The aim of this study was to generate maps of intense rainfall equation parameters using interpolated maximum intense rainfall data. The study area comprised Espírito Santo State, Brazil. A total of 59 intense rainfall equations were used to interpolate maximum intense rainfall, with a 1 x 1 km spatial resolution. Maximum intense rainfall was interpolated considering recurrence of 2; 5; 10; 20; 50 and 100 years, and duration of 10; 20; 30; 40; 50; 60; 120; 240; 360; 420; 660; 720; 900; 1,140; 1,380 and 1,440 minutes, resulting in 96 maps of maximum intense rainfall. The used interpolators were inverse distance weighting and ordinary kriging, for which significance level (p-value) and coefficient of determination (R²) were evaluated for the cross-validation data, choosing the method that presented better R² to generate maps. Finally, maps of maximum intense precipitation were used to estimate, cell by cell, the intense rainfall equation parameters. In comparison with literature data, the mean percentage error of estimated intense rainfall equations was 13.8%. Maps of spatialized parameters, obtained in this study, are of simple use; once they are georeferenced, they may be imported into any geographic information system to be used for a specific area of interest.

Analysis of the relationship intensity, duration, frequency of disaggregated daily rainfall in southern Rio Grande do Sul, Brazil

The intensity, duration, and frequency relationship (IDF) of rainfall occurrence may be done through continuous records of pluviographs or daily pluviometer values . The objective of this study was to estimate the intensity-duration-frequency relationships of precipitation, using the method of daily rainfall disaggregation, at weather stations located to the southern half of the state of Rio Grande do Sul; comparing them with those obtained by rain gauge records, in places considered homogeneous from the meteorological point of view. The IDF equation parameters were estimated from daily rainfall disaggregation data, using the method of nonlinear optimization. To validate the equations confidence indices and efficiency and the "t" Student test, among maximum intensity values obtained from the disaggregated daily rainfall durations of 10; 30; 60 min and 6; 12 and 24 h and those extracted from existing IDF equations. For all studied stations and return periods, the trust index values were regarded as "optimal", i.e., greater than 0.85. The maximal intensity of rainfall obtained by daily rainfall disaggregation have similarity with those obtained by relations IDF standards. Thus, the method constitutes a feasible alternative in obtaining the IDF relationships.

Method adjustment and equation set of maximum rainfall intensity, duration and frequency in the Mato Grosso do Sul State

Due to the lack of information concerning maximum rainfall equations for most locations in Mato Grosso do Sul State, the alternative for carrying out hydraulic work projects has been information from meteorological stations closest to the location in which the project is carried out. Alternative methods, such as 24 hours rain disaggregation method from rainfall data due to greater availability of stations and longer observations can work. Based on this approach, the objective of this study was to estimate maximum rainfall equations for Mato Grosso do Sul State by adjusting the 24 hours rain disaggregation method, depending on data obtained from rain gauge stations from Dourado and Campo Grande. For this purpose, data consisting of 105 rainfall stations were used, which are available in the ANA (Water Resources Management National Agency) database. Based on the results we concluded: the intense rainfall equations obtained by pluviogram analysis showed determination coefficient above 99%; and the performance of 24 hours rain disaggregation method was classified as excellent, based on relative average error WILMOTT concordance index (1982).

Distribution pattern, surface tension and contact angle of herbicides associated to adjuvants on spraying and control of Ipomoea hederifolia under rainfall incidence

ABSTRACTScarlet Morning Glory is considered to be an infesting weed that affects several crops and causes serious damage. The application of chemical herbicides, which is the primary control method, requires a broad knowledge of the various characteristics of the solution and application technology for a more efficient phytosanitary treatment. Therefore this study aimed to characterize the effect of rainfall incidence on the control of Ipomoea hederifolia, considering droplet size, surface tension, contact angle of droplets formed by herbicides liquid on vegetal and artificial surfaces, associated to adjuvants and the volumetric distribution profile of the spray jet. The addition of the adjuvants to the herbicide spraying liquid improved the application quality, as it influenced the angle formed by the spray by broadening the deposition band of the spray nozzle and thus the possible distance between the nozzles on spray boom and due the changes at droplet size, which contribute to a safety application. The rainfall occurrence affected negatively the weed control with the different spraying liquids and also the dry matter weight, suggesting that the phytosanitary product applied was washed off.

Rainfall effect on dissipation and movement of diuron and simazine in a vineyard soil

From 2003 to 2007, a field study was performed in a vineyard in Chile to investigate diuron and simazine soil behavior and the effect of additional rainfall. Both herbicides were applied once a year at a rate of 2.0 kg ha-1 a.i. Herbicide concentrations in soil were measured at 0, 10, 20, 40, 90 and 340 days after application, under two pluviometric conditions, natural rainfall and natural rainfall plus irrigation with 180 mm of simulated rainfall during the first 90 days after application. Soil partition coefficient (Kd) varied in the soil profile (0 to 90 cm deep) from 6.75 to 2.04 mL g-1 and from 1.4 to 0.66 mL g-1 and the maximum soil adsorption capacity was approximately 18.3 mg g-1 and 8.3 mg g-1 for diuron and simazine, respectively. Diuron and simazine reached up to 90 and 120 cm of soil depth, with an average of 8.3% and 62.4% of herbicide moved below 15 cm in the soil, respectively. Simazine soil half-life (DT50) was 38.1 days and 7.5 days, whereas the half life for diuron varied from 68.0 and 24.6 for natural rainfall and irrigated, respectively. The average of residual simazine remaining in the whole soil profile after 90 DAA was 25.4% and 39.9% for diuron, with no effect of additional rainfall amount. At 340 DAA the amount of simazine in the whole soil profile corresponded to 13.2% of the initial amount applied, being diuron more persistent with 21.5% of the initial herbicide applied. The high movement in soil of both herbicides could be due to a non-equilibrium sorption process explained by preferential flow, low Kd and high desorption.