Rainfall Intensity-Duration-Frequency Relationships for Risk Analysis in the Region of Matopiba, Brazil

Silva, Luciele Vaz da; Casaroli, Derblai; Evangelista, Adão Wagner Pêgo; Júnior, José Alves; Battisti, Rafael

doi:10.1590/0102-77863340239

Cited by 5 publications

(4 citation statements)

References 18 publications

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“…The CO 2 increase has been reported as a positive effect over C 3 crops, but yield increases only occur under well-watered conditions (Ainsworth and Long 2021) and not limiting conditions for temperature (Baker et al, 1989). Future climate scenarios are expected to increase the rainfall intensity (Almagro et al, 2017), water losses by runoff (Burt et al, 2016) and the erodibility risk, which was classified as moderate for Ferralsols and Leptosols in the MATOPIBA for baseline conditions (da Silva et al, 2019). In these scenarios, the water can be used for irrigation, a potential management tool to improve crop yield and reduce climate change impacts (Battisti et al, 2018a).…”

Section: Discussionmentioning

confidence: 99%

Climate change impacts on rainfed and irrigated soybean yield in Brazil’s new agricultural frontier

Fernandes

Melo

Elli

et al. 2021

Theor Appl Climatol

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Climate is one of the main limiting factors for agricultural productivity, where climate change may increase the risk for food production. Based on that, the aim of this study was to evaluate the impacts of climate change on rainfed and irrigated soybean yield in the MATOPIBA region, the new agricultural frontier in Brazil. The DSSAT CSM-CROPGRO-Soybean was used to simulate rainfed and irrigated yield using local soils, sowing dates, and maturity groups. The simulations included the baseline , and two future scenarios (2011-2040 and 2041-2070) for two representative concentration pathways (RCP 2.6 and 8.5). The future climate scenarios were obtained from global climate models (HadGEM2-ES and CSIRO mk3-6-0). The baseline showed a median yield of 3907 kg ha −1 across the region, a value that increased to 4006 kg ha −1 in the RCP 8.5 in 2011-2040. For the 2041-2070 period, RCPs 2.6 and 8.5 had a yield reduction to 3686 and 2388 kg ha −1 , respectively. The average yield reduction was higher than 23% under RCP 8.5 , reaching more than 53% in some areas. The yield impact in future climate scenarios was related to rainfall reduction by 300-400 mm cycle −1 , and temperature increased above 3 °C. The irrigation showed potential to offset negative climate change impacts, where yield gain was 2400 kg ha −1 under RCP 8.5. The future climate impact can be reduced by moving soybean crops preferentially to areas of higher altitude, with lower air temperature associated with irrigation. Further studies could explore potential adaptations related with physiological traits and crop management.

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Section: Discussionmentioning

confidence: 99%

Climate change impacts on rainfed and irrigated soybean yield in Brazil’s new agricultural frontier

Fernandes

Melo

Elli

et al. 2021

Theor Appl Climatol

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“…The mean areal rainfall was then presented in a group according to its duration [DA SILVA et al 2019]. The maximum duration of 5 h was chosen considering that most flood events were commonly caused by rainfall with a 5-hour duration in the study area [ADI 2013].…”

Section: Methodology and Data Usedmentioning

confidence: 99%

Journal of Water and Land Development

2022

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Rainfall is one of the main components of the hydrologic cycle; thus, the availability of accurate rainfall data is fundamental for designing and operating water resources systems and infrastructure. This study aims to develop an empirical model of rainfall intensity (I t,p ) as a function of its probability (p) and duration (t). In 1999-2020, data on the hourly duration of rainfall were collected from automatic rainfall recorder (ARR) gauges. The empirical model has been developed using a statistical approach based on duration (t) and probability (p), and subsequently they have been validated with those obtained from ARR data. The resulting model demonstrates good performance compared with other empirical formulas (Sherman and Ishiguro) as indicated by the percent bias (PBIAS) values (2.35-3.17), ratio of the RMSE (root mean square error) between simulated and observed values to the standard deviation of the observations (RSR, 0.028-0.031), Nash-Sutcliffe efficiency (NSE, 0.905-0.996), and index of agreement (d, 0.96-0.98) which classified in the rating of "very good" in model performance. The reliability of the estimated intensity based on the empirical model shows a tendency to decrease as duration (t) increases, and a good accuracy mainly for the rainfall intensity for shorter periods (1-, 2-, and 3-hours), whereas low accuracy for long rainfall periods. The study found that the empirical model exhibits a reliable estimate for rainfall intensity with small recurrence intervals (Tr) 2-, 5-, 10-, and a 20-year interval and for a shorter duration (t). Validation results confirm that the rainfall intensity model shows good performance; thus, it could be used as a reliable instrument to estimate rainfall intensity in the study area.

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“…Each set of annual maximum rainfall intensities was assumed to follow the distribution of the extreme value type I (EV I) or Gumbel distribution which is the popular one for extrapolating to higher return levels (Koutsoyiannis et al 1998;da Silva et al 2019). To model the EV I distribution, we need two parameters namely location parameter, u, and scale parameter, β, which can be evaluated using the method of moment as follows (Chow et al 1988):…”

Section: Methodsmentioning

confidence: 99%

Temporal change of extreme precipitation intensity–duration–frequency relationships in Thailand

Yamoat

Hanchoowong

Sriboonlue

et al. 2021

Journal of Water and Climate Change

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Due to climate change, many research studies have derived the updated extreme precipitation intensity–duration–frequency relationship (IDF curve) from forecasted sub-hourly rainfall intensity time series, which is one of the most important tools for the planning and designing of hydraulic infrastructures. In this study, the IDF curves (1990–2016) of the six regions and procedures are used in accordance with those of the Royal Irrigation Department (RID)’s study (1950–1988). Each set of IDF relationships consists of 81 intensity values which are the combination of nine durations and nine return periods. The intensity ratios of this study and RID are compared. A greater-than-1 ratio indicates extreme intensity increment from the past to the present. Considering 81 ratios for each region, the number of greater-than-1 ratios for the North, Northeast, Central, East, West, and South regions are 8, 2, 31, 34, 6, and 7, respectively. These ratio numbers are far below 81 which means that the majority of extreme rainfall intensities do not increase from the past to the present. The study found that using accurate historical sub-hourly rainfall time series to create a set of IDF curves would be more reliable than using forecasted rainfall modeling.

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Rainfall Intensity-Duration-Frequency Relationships for Risk Analysis in the Region of Matopiba, Brazil

Cited by 5 publications

References 18 publications

Climate change impacts on rainfed and irrigated soybean yield in Brazil’s new agricultural frontier

Climate change impacts on rainfed and irrigated soybean yield in Brazil’s new agricultural frontier

Journal of Water and Land Development

Temporal change of extreme precipitation intensity–duration–frequency relationships in Thailand

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