scholarly journals A pioneer and preliminary study on sub-daily rainfall data in Brazil: what can we learn from this new high temporal resolution database?

2020 ◽  
Author(s):  
Cristiano Almeida ◽  
Emerson Freitas ◽  
Victor Coelho ◽  
Davi Melo
Keyword(s):  
Temporal Resolution ◽  
Daily Rainfall ◽  
Rainfall Data ◽  
High Temporal Resolution ◽  
Daily Rainfall Data ◽  
Preliminary Study

The effect of weather, drainage efficiency and duration of spring cultivations on barley yields in England

1972 ◽  
Vol 7 (2) ◽  
pp. 79-83 ◽  
Author(s):  
L P Smith
Keyword(s):  
Yield Loss ◽  
Daily Rainfall ◽  
Rainfall Data ◽  
Work Schedule ◽  
Average Yield ◽  
Daily Rainfall Data ◽  
Arable Farming ◽  
Work Distribution

Daily rainfall data for twenty years in arable farming areas are analysed with respect to four standards of drainage and for three lengths of schedule of spring work. Distribution and frequency in time of available work days are interpreted in terms of lateness of sowing and of barley yield. Formulae are established to calculate average yield loss in terms of drainage standard and work schedule, enabling estimates to be made of the effect of planned improvements.

scholarly journals Bayesian Time Series Modelling of the Italian Daily Rainfall Data using Mixed Distribution

2019 ◽  
Vol 8 (4) ◽  
pp. 2279-2288
Keyword(s):  
Time Series ◽  
Daily Rainfall ◽  
Rainfall Data ◽  
Seasonal Effects ◽  
Model Parameters ◽  
Daily Rainfall Data ◽  
Mixed Distribution ◽  
Time Series Modelling ◽  
Bayesian Time Series ◽  
The Ideal

A combination of continuous and discrete elements is referred to as a mixed distribution. For example, daily rainfall data consist of zero and positive values. We aim to develop a Bayesian time series model that captures the evolution of the daily rainfall data in Italy, focussing on directly linking the amount and occurrence of rainfall. Two gamma (G1 and G2) distributions with different parameterisations and lognormal distribution were investigated to identify the ideal distribution representing the amount process. Truncated Fourier series was used to incorporate the seasonal effects which captures the variability in daily rainfall amounts throughout the year. A first-order Markov chain was used to model rainfall occurrence conditional on the presence or absence of rainfall on the previous day. We also built a hierarchical prior structure to represent our subjective beliefs and capture the initial uncertainties of the unknown model parameters for both amount and occurrence processes. The daily rainfall data from Urbino rain gauge station in Italy were then used to demonstrate the applicability of our proposed methods. Residual analysis and posterior predictive checking method were utilised to assess the adequacy of model fit. In conclusion, we clearly found that our proposed method satisfactorily and accurately fits the Italian daily rainfall data. The gamma distribution was found to be the ideal probability density function to represent the amount of daily rainfall.

scholarly journals Comparison of Different Rainfall Erosion Estimation Methods for the Island of Crete

Proceedings ◽  
2020 ◽  
Vol 30 (1) ◽  
pp. 67 ◽  
Author(s):  
Dimitrios D. Alexakis ◽  
Manolis Grillakis
Keyword(s):  
Temporal Resolution ◽  
Total Duration ◽  
Power Estimation ◽  
Monthly Rainfall ◽  
Rainfall Data ◽  
Estimation Methods ◽  
Accurate Estimation ◽  
High Temporal Resolution ◽  
Rainfall Erosivity ◽  
Daily Data

Interactions between soil and rainfall plays a vital role in ecological, hydrological and biogeochemical cycles of land. Among those interactions, the phenomenon of rainfall induced soil erosion is crucial to the soil functions, as it affects the soil structure and organic matter content that subsequently affects soil ability to hold moisture and nutrients. The erosive power of a specific rainfall event is regulated by its intensity and total duration. Various methodologies have been developed and tested to estimate the rainfall erosivity in different hydroclimatic regions and using different rainfall measuring timescales. Studies have shown that high temporal resolution measurements provide a more robust erosivity estimation. Nonetheless the sparsity and scarcity of such high temporal resolution data make the accurate estimation of rainfall erosivity difficult. Here, we compare different erosion power estimation methods based on different rainfall timescales for the island of Crete. Sub-daily (30-min) rainfall data based estimation is used as the basis for the assessment of a daily data based estimation methodology and two different methods that use monthly rainfall data. Modified Fournier Index (MFI) is incorporated in the study through different literature approaches and a regression equation is developed between rainfall erosivity power and MFI index for Crete. Results indicate that the use of daily data in the rainfall erosive power estimation is a good approximation of the sub-daily estimation, while formulas based on monthly rainfall data tend to exhibit larger deviations.

scholarly journals Sensitivity of hydrological models to temporal and spatial resolutions of rainfall data

2019 ◽  
Vol 23 (6) ◽  
pp. 2647-2663 ◽  
Author(s):  
Yingchun Huang ◽  
András Bárdossy ◽  
Ke Zhang
Keyword(s):  
Spatial Resolution ◽  
Temporal Resolution ◽  
Model Performance ◽  
Daily Rainfall ◽  
High Temporal Resolution ◽  
Dense Network ◽  
Spatially Distributed ◽  
Important Input ◽  
Temporal And Spatial ◽  
Improved Model

Abstract. Rainfall is the most important input for rainfall–runoff models. It is usually measured at specific sites on a daily or sub-daily timescale and requires interpolation for further application. This study aims to evaluate whether a higher temporal and spatial resolution of rainfall can lead to improved model performance. Four different gridded hourly and daily rainfall datasets with a spatial resolution of 1 km × 1 km for the state of Baden-Württemberg in Germany were constructed using a combination of data from a dense network of daily rainfall stations and a less dense network of sub-daily stations. Lumped and spatially distributed HBV models were used to investigate the sensitivity of model performance to the spatial resolution of rainfall. The four different rainfall datasets were used to drive both lumped and distributed HBV models to simulate daily discharges in four catchments. The main findings include that (1) a higher temporal resolution of rainfall improves the model performance if the station density is high; (2) a combination of observed high temporal resolution observations with disaggregated daily rainfall leads to further improvement in the tested models; and (3) for the present research, the increase in spatial resolution improves the performance of the model insubstantially or only marginally in most of the study catchments.

scholarly journals Structural break or long memory: an empirical survey on daily rainfall data sets across Malaysia

2013 ◽  
Vol 17 (4) ◽  
pp. 1311-1318 ◽  
Author(s):  
F. Yusof ◽  
I. L. Kane ◽  
Z. Yusop
Keyword(s):  
Long Memory ◽  
Structural Breaks ◽  
Structural Break ◽  
Daily Rainfall ◽  
Least Square ◽  
Rainfall Data ◽  
Data Sets ◽  
Original Series ◽  
Empirical Survey ◽  
Daily Rainfall Data

Abstract. A short memory process that encounters occasional structural breaks in mean can show a slower rate of decay in the autocorrelation function and other properties of fractional integrated I (d) processes. In this paper we employed a procedure for estimating the fractional differencing parameter in semiparametric contexts proposed by Geweke and Porter-Hudak (1983) to analyse nine daily rainfall data sets across Malaysia. The results indicate that all the data sets exhibit long memory. Furthermore, an empirical fluctuation process using the ordinary least square (OLS)-based cumulative sum (CUSUM) test for the break date was applied. Break dates were detected in all data sets. The data sets were partitioned according to their respective break date, and a further test for long memory was applied for all subseries. Results show that all subseries follows the same pattern as the original series. The estimate of the fractional parameters d1 and d2 on the subseries obtained by splitting the original series at the break date confirms that there is a long memory in the data generating process (DGP). Therefore this evidence shows a true long memory not due to structural break.

scholarly journals The Fitting of a Truncated Log?Normal Curve to Daily Rainfall Data

1956 ◽  
Vol 9 (1) ◽  
pp. 151 ◽  
Author(s):  
SC Das
Keyword(s):  
Curve Fitting ◽  
Daily Rainfall ◽  
Rainfall Data ◽  
Normal Curve ◽  
Daily Rainfall Data ◽  
Log Normal

In a previous paper (Das 1955) the author discussed a problem of curve fitting which arose in testing the hypothesis proposed by Bowen (1953) concerning daily rainfall data.

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