Using a high-resolution regional climate model large ensemble to simulate the impact of extreme precipitation on flooding over small to medium-size catchments

2021 ◽  
Author(s):  
Mina Faghih ◽  
François Brissette ◽  
Parham Sabeti ◽  
Mostafa Tarek
Keyword(s):  
Return Period ◽  
Extreme Precipitation ◽  
Climate Model ◽  
Large Ensemble ◽  
Catchment Scale ◽  
Time Step ◽  
Daily Time Step ◽  
The Impact ◽  
Small Catchments ◽  
Daily Time

<p>Recent studies show that the frequency and intensity of extreme precipitation will increase under a warmer climate. It is expected that extreme convective precipitation will scale at a larger than Clausius–Clapeyron rate and especially so for short-duration rainfall. This has implication on flooding risk, and especially so on small catchments (<500 km<sup>2</sup>) which have a quick response time and are therefore particularly vulnerable to short duration rainfall. The impact of the amplification of extreme precipitation as a function of catchment scale has not been widely studied because most of the climate change impact studies have been conducted at the daily time step or higher. This is because until recently the vast majority of climate model outputs have only been available at the daily time step.</p><p>This study has looked at the amplification of sub-daily, daily, and multiday extreme precipitation and flooding and its dependency on catchment scale. This work uses outputs from the Climex large-ensemble to study the amplification of extreme streamflow with return period from 2 to 300 years and durations from 1 to 24 hours over 133 North-American catchments. Using a large ensemble allows for the accurate empirical computation of extreme events with very large return periods.  Results indicate that future extreme streamflow relative increases are largest for smaller catchments, longer return period, and shorter rainfall durations. Small catchments are therefore more vulnerable to future extreme rainfall than their larger counterparts.</p>

scholarly journals The Impact of Gridded Weather Database on Soil Water Availability in Rice Crop Modeling

2021 ◽  
Author(s):  
Caio Teodoro Menezes ◽  
Derblai Casaroli ◽  
Alexandre Bryan Heinemann ◽  
Vinicius Cintra Moschetti ◽  
Rafael Battisti
Keyword(s):  
Sandy Soil ◽  
Upland Rice ◽  
Crop Modeling ◽  
Time Step ◽  
R And D ◽  
Daily Time Step ◽  
D Values ◽  
Attainable Yield ◽  
The Impact ◽  
Daily Time

Abstract In recent years, there has been an increase in studies suggesting that gridded weather database (GWD) is a suitable source for simulating crop yield. Brazil has low geospatial coverage by measured weather database (MWD). Based on that, this study aimed to compare two different GWD sources, Daily Gridded (DG) and NASA/POWER (NP), on the simulated yield of upland rice (UR) against the MWD input. The GWD and MWD were obtained for seven locations across UR Brazilian region, considering a period ranging from 1984 to 2016. GWD and MWD were used to estimate rice potential (Yp) and attainable yield (Ya), in clay soil and sandy soil, using ORYZA (v3) model. DG had the best performance for all variables. GWD-based yields had a reasonable performance. However, DG had a slightly better performance than NP in all conditions, DG-based yields showed RMSE values of 0.57, 0.71 and 0.52 for Yp and Ya in clay and sandy soil, whereas NP showed RMSE values of 0.86, 0.91 and 0.64. DG also showed higher R² and d values for yields assessed. Both GWD overestimated Ya, these overestimations in DG-based yield were 3.54, 9.61, and 21.35% for Yp and Ya in clay and sandy soil respectively, in NP-based yield were 13.67, 18.45, 29.11%, showing that for both GWD-based yield increased as the soil type texture as well as water storage decreased. As a consequence, we do not recommend the use of precipitation data in daily time-step crop modeling.

scholarly journals Simulations of future changes in thermal structure of Lake Erken: Proof of concept for ISIMIP2b lake sector local simulation strategy

2019 ◽  
Author(s):  
Ana I. Ayala ◽  
Simone Moras ◽  
Don C. Pierson
Keyword(s):  
Water Temperature ◽  
Climate Model ◽  
Thermal Structure ◽  
Meteorological Data ◽  
Time Step ◽  
Data Set ◽  
Lake Model ◽  
Hourly Data ◽  
Daily Time Step ◽  
Daily Time

Abstract. This paper, as a part of Inter-Sectoral Impact Model Intercomparison Project (ISIMIP2b), assesses the impacts of different levels of global warming on the thermal structure of Lake Erken (Sweden). The GOTM one-dimensional hydrodynamic model was used to simulate water temperature when using ISIMIP2b bias-corrected climate model projections as input. These projections have a daily time step, while lake model simulations are often forced at hourly or shorter time steps. Therefore, it was necessary to first test the ability of GOTM to simulate Lake Erken water temperature using daily vs hourly meteorological forcing data. In order to do this three data sets were used to force the model: (1) hourly measured data; (2) daily average data derived from the first data set and; (3) synthetic hourly data created from the daily data set using Generalized Regression Artificial Neural Network methods. This last data set is developed using a method that could also be applied to the daily time step ISIMIP scenarios to obtain hourly model input if needed. The lake model was shown to accurately simulate Lake Erken water temperature when forced with either daily or synthetic hourly data. Long-term simulations forced with daily or synthetic hourly meteorological data suggest that by 2099 the lake will undergo clear changes in thermal structure, for RCP 2.6 surface water temperature was projected to increase from 0.87 to 1.48 °C and from 0.69 to 1.20 °C when the lake model was forced at daily and hourly resolutions respectively, and for RCP 6.0 these increases were projected to range from 1.58 to 3.58 °C and from 1.19 to 2.65 °C when the lake model was also forced at daily and hourly resolutions. Changes in lake stability were projected to increase significantly and the stratification duration was projected to be longer by 9 to 16 days and from 7 to 13 days under RCP 2.6 scenario and from 20 to 33 days and from 17 to 27 under RCP 6.0 scenario for daily and hourly resolutions. Model trends were very similar when using either the daily or synthetic hourly forcing, suggesting that the original climate model projections at a daily time step can be sufficient for the purpose of simulating water temperature in the lake sector in ISIMIP.

scholarly journals Impact of correcting sub-daily climate model biases for hydrological studies

2021 ◽  
Author(s):  
Mina Faghih ◽  
François Brissette ◽  
Parham Sabeti
Keyword(s):  
Diurnal Cycle ◽  
Bias Correction ◽  
Time Scale ◽  
Climate Model ◽  
Temperature And Precipitation ◽  
Diurnal Cycle Of Precipitation ◽  
The Impact ◽  
Small Catchments ◽  
Precipitation And Temperature ◽  
Daily Time

Abstract. The study of climate change impact on water resources has accelerated worldwide over the past two decades. An important component of such studies is the bias correction step, which accounts for spatiotemporal biases present in climate model outputs over a reference period, and which allows realistic streamflow simulations using future climate scenarios. Most of the literature on bias correction focuses on daily scale climate model temporal resolution. However, a large amount of regional and global climate simulations are becoming increasingly available at the sub-daily time step, and even extend to the hourly scale, with convection-permitting models exploring sub-hourly time resolution. Recent studies have shown that the diurnal cycle of variables simulated by climate models is also biased, which raises issues respecting the necessity (or not) of correcting such biases prior to generating streamflows at the sub-daily time scale. This paper investigates the impact of bias-correcting the diurnal cycle of climate model outputs on the computation of streamflow over 133 small to large North American catchments. A standard hydrological modeling chain was set up using the temperature and precipitation outputs from a high spatial (12-km) and temporal (1-hour) regional climate model large ensemble (ClimEx-LE). Two bias-corrected time series were generated using a multivariate quantile mapping method, with and without correction of the diurnal cycles of temperature and precipitation. The impact of this correction was evaluated on three small (< 500 km2), medium and large (> 1000 km2) surface area catchment size classes. Results show small but systematic improvements of streamflow simulations when bias-correcting the diurnal cycle of precipitation and temperature. The greatest improvements were seen on the small catchments, and least noticeable on the largest. The diurnal cycle correction allowed for hydrological simulations to accurately represent the diurnal cycle of summer streamflow on small catchments. Bias-correcting the diurnal cycle of precipitation and temperature is therefore recommended when conducting impact studies at the sub-daily time scale on small catchments.

scholarly journals Simulations of future changes in thermal structure of Lake Erken: proof of concept for ISIMIP2b lake sector local simulation strategy

2020 ◽  
Vol 24 (6) ◽  
pp. 3311-3330 ◽  
Author(s):  
Ana I. Ayala ◽  
Simone Moras ◽  
Donald C. Pierson
Keyword(s):  
Water Temperature ◽  
Climate Model ◽  
Thermal Structure ◽  
Meteorological Data ◽  
Time Step ◽  
Data Set ◽  
Lake Model ◽  
Hourly Data ◽  
Daily Time Step ◽  
Daily Time

Abstract. This paper, as a part of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP2b), assesses the impacts of different levels of global warming on the thermal structure of Lake Erken (Sweden). The General Ocean Turbulence Model (GOTM) one-dimensional hydrodynamic model was used to simulate water temperature when using ISIMIP2b bias-corrected climate model projections as input. These projections have a daily time step, while lake model simulations are often forced at hourly or shorter time steps. Therefore, it was necessary to first test the ability of GOTM to simulate Lake Erken water temperature using daily vs hourly meteorological forcing data. In order to do this, three data sets were used to force the model as follows: (1) hourly measured data, (2) daily average data derived from the first data set, and (3) synthetic hourly data created from the daily data set using generalised regression artificial neural network methods. This last data set is developed using a method that could also be applied to the daily time step ISIMIP scenarios to obtain hourly model input if needed. The lake model was shown to accurately simulate Lake Erken water temperature when forced with either daily or synthetic hourly data. Long-term simulations forced with daily or synthetic hourly meteorological data suggest that by the late 21st century the lake will undergo clear changes in thermal structure. For the representative concentration pathway (RCP) scenario, namely RCP2.6, surface water temperature was projected to increase by 1.79 and 1.36 ∘C when the lake model was forced at daily and hourly resolutions respectively, and for RCP6.0 these increases were projected to be 3.08 and 2.31 ∘C. Changes in lake stability were projected to increase, and the stratification duration was projected to be longer by 13 and 11 d under RCP2.6 scenario and 22 and 18 d under RCP6.0 scenario for daily and hourly resolutions. Model changes in thermal indices were very similar when using either the daily or synthetic hourly forcing, suggesting that the original ISIMIP climate model projections at a daily time step can be sufficient for the purpose of simulating lake water temperature.

Alternative climate data sources for distributed hydrological modelling on a daily time step

2010 ◽  
Vol 25 (10) ◽  
pp. 1542-1557 ◽  
Author(s):  
Ashraf El-Sadek ◽  
Max Bleiweiss ◽  
Manoj Shukla ◽  
Steve Guldan ◽  
Alexander Fernald
Keyword(s):  
Hydrological Modelling ◽  
Data Sources ◽  
Climate Data ◽  
Time Step ◽  
Daily Time Step ◽  
Distributed Hydrological Modelling ◽  
Daily Time

scholarly journals Climate Change Impact on the Frequency of Hydrometeorological Extremes in the Island of Crete

Water ◽  
2019 ◽  
Vol 11 (3) ◽  
pp. 587 ◽  
Author(s):  
Evdokia Tapoglou ◽  
Anthi Vozinaki ◽  
Ioannis Tsanis
Keyword(s):  
Climate Change ◽  
Frequency Analysis ◽  
Extreme Precipitation ◽  
Climate Model ◽  
Regional Climate ◽  
Standardized Precipitation Index ◽  
Hydrological Drought ◽  
Drought Indices ◽  
Rcp Scenarios ◽  
The Impact

Frequency analysis on extreme hydrological and meteorological events under the effect of climate change is performed in the island of Crete. Data from Regional Climate Model simulations (RCMs) that follow three Representative Concentration Pathways (RCP2.6, RCP4.5, RCP8.5) are used in the analysis. The analysis was performed for the 1985–2100 time period, divided into three equal-duration time slices (1985–2010, 2025–2050, and 2075–2100). Comparison between the results from the three time slices for the different RCMs under different RCP scenarios indicate that drought events are expected to increase in the future. The meteorological and hydrological drought indices, relative Standardized Precipitation Index (SPI) and Standardized Runoff index (SRI), are used to identify the number of drought events for each RCM. Results from extreme precipitation, extreme flow, meteorological and hydrological drought frequency analysis over Crete show that the impact of climate change on the magnitude of 100 years return period extreme events will also increase, along with the magnitude of extreme precipitation and flow events.

A model of expansion and senescence of individual leaves of field-grown maize (Zea mays L.)

1994 ◽  
Vol 74 (1) ◽  
pp. 37-42 ◽  
Author(s):  
D. W. Stewart ◽  
L M. Dwyer
Keyword(s):  
Leaf Area ◽  
Zea Mays L ◽  
Growth Models ◽  
Time Step ◽  
Leaf Area Expansion ◽  
Daily Time Step ◽  
Area Expansion ◽  
Area Development ◽  
Leaf Area Development ◽  
Daily Time

Estimation of leaf area is a major component of plant growth models. In this study, a model was developed to calculate field-grown maize leaf area expansion and senescence on an individual leaf basis. The model began with an equation, based on cumulative growing degree-days from emergence, to initiate leaf area development. The model required daily values of maximum and minimum air temperature, solar radiation and precipitation, had essentially a daily time step with day and night modes, and could be run on commonly accessible computers (micros to mainframes). The objective of the development of the model was to assist plant breeders in optimizing leaf number and shape for adaptation to specific environments. Key words: Leaf area and number, temperature, phenological development

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