scholarly journals Rainfall intensity bursts and the erosion of soils: an analysis highlighting the need for high temporal resolution rainfall data for research under current and future climates

2019 ◽  
Author(s):  
David L. Dunkerley
Keyword(s):  
Climate Change ◽  
Temporal Resolution ◽  
Rainfall Intensity ◽  
Explanatory Power ◽  
Tropical Climate ◽  
Rainfall Data ◽  
High Temporal Resolution ◽  
Hourly Data ◽  
Rainfall Extremes ◽  
Period Data

Abstract. Many landsurface processes, including splash dislodgment and downslope transport of soil materials, are influenced strongly by short-lived peaks in rainfall intensity but are less well accounted for by longer-term average rates. Specifically, rainfall intensities reached over periods of 10–30 minutes appear to have more explanatory power than hourly or longer-period data. However, most analyses of rainfall, and particularly scenarios of possible future rainfall extremes under climate change, rely on hourly data. Using two Australian pluviograph records with 1 second resolution, one from an arid and one from a wet tropical climate, the nature of short-lived intensity bursts is analysed from the raw inter-tip times of the tipping bucket gauges. Hourly apparent rainfall intensities average just 1.43 mm h−1 at the wet tropical site, and 2.12 mm h−1 at the arid site. At the wet tropical site, intensity bursts of extreme intensity occur frequently, those exceeding 30 mm h−1 occurring on average at intervals of  60 mm h−1 occurring on average at intervals of

scholarly journals Rainfall intensity bursts and the erosion of soils: an analysis highlighting the need for high temporal resolution rainfall data for research under current and future climates

2019 ◽  
Vol 7 (2) ◽  
pp. 345-360 ◽  
Author(s):  
David L. Dunkerley
Keyword(s):  
Climate Change ◽  
Land Surface ◽  
Rainfall Intensity ◽  
Overland Flow ◽  
Explanatory Power ◽  
Short Review ◽  
Rainfall Data ◽  
High Temporal Resolution ◽  
Hourly Data ◽  
Rainfall Extremes

Abstract. Many land surface processes, including splash dislodgment and downslope transport of soil materials, are influenced strongly by short-lived peaks in rainfall intensity but are less well accounted for by longer-term average rates. Specifically, rainfall intensities reached over periods of 10–30 min appear to have more explanatory power than hourly or longer-period data. However, most analyses of rainfall, and particularly scenarios of possible future rainfall extremes under climate change, rely on hourly data. Using two Australian pluviograph records with 1 s resolution, one from an arid and one from a wet tropical climate, the nature of short-lived “intensity bursts” is analysed from the raw inter-tip times of the tipping bucket gauges. Hourly apparent rainfall intensities average just 1.43 mm h−1 at the wet tropical site and 2.12 mm h−1 at the arid site. At the wet tropical site, intensity bursts of extreme intensity occur frequently, those exceeding 30 mm h−1 occurring on average at intervals of <1 d and those of >60 mm h−1 occurring on average at intervals of <2 d. These bursts include falls of 13.2 mm in 4.4 min, the equivalent of 180 mm h−1, and 29 mm in 12.6 min, equivalent to 138 mm h−1. Intensity bursts at the arid site are much less frequent, those of 50–60 mm h−1 occurring at intervals of ∼1 month; moreover, the bursts have a much shorter duration. The aggregation of rainfall data to hourly level conceals the occurrence of many of these short-intensity bursts, which are potentially highly erosive. A short review examines some of the mechanisms through which intensity bursts affect infiltration, overland flow, and soil dislodgment. It is proposed that more attention to resolving these short-lived but important aspects of rainfall climatology is warranted, especially in light of possible changes in rainfall extremes under climate change.

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.

Climate change during the past 1000 years: a high-temporal-resolution multiproxy record from a mire in northern Finland

2012 ◽  
Vol 28 (2) ◽  
pp. 152-164 ◽  
Author(s):  
Walter Finsinger ◽  
Kristian Schoning ◽  
Sheila Hicks ◽  
Andreas Lücke ◽  
Tomasz Goslar ◽  
...  
Keyword(s):  
Climate Change ◽  
Temporal Resolution ◽  
High Temporal Resolution ◽  
The Past ◽  
Past 1000 Years

scholarly journals Comparing CLIGEN-Generated Storm Patterns with 1-Minute and Hourly Precipitation Data from China

2018 ◽  
Vol 57 (9) ◽  
pp. 2005-2017 ◽  
Author(s):  
Wenting Wang ◽  
Shuiqing Yin ◽  
Dennis C. Flanagan ◽  
Bofu Yu
Keyword(s):  
Rainfall Intensity ◽  
Rainfall Data ◽  
Central China ◽  
Cumulative Distribution ◽  
Precipitation Data ◽  
Adjustment Factor ◽  
Stochastic Weather Generator ◽  
Hourly Precipitation ◽  
Hourly Data ◽  
Two Parameters

AbstractClimate Generator (CLIGEN) is a stochastic weather generator that has been widely used to generate daily precipitation and storm patterns for hydrological and erosion prediction models. Rainfall data with measurement intervals ≤ 30 min are required to compute two parameters for generating storm patterns, namely, the cumulative distribution of the time to peak rainfall intensity (TimePk) and the mean daily maximum 30-min rainfall intensity (MX.5P). High-resolution rainfall data, however, are not widely available around the world. One-minute precipitation data for 18 stations in eastern and central China were aggregated into hourly intervals to evaluate methods to optimally prepare TimePk and MX.5P for CLIGEN. Four sets of the two parameters were used to run CLIGEN for comparison: C0, using the original 1-min data; C1, replacing TimePk with those computed with hourly data; C2, replacing MX.5P with those computed with hourly data with an adjustment factor; and C3, replacing both parameters with those computed with hourly data, and the MX.5P was adjusted as for C2. Results showed that 1) MX.5P computed with hourly data was systematically lower than that computed with the 1-min data, and the bias could be corrected by multiplying by an adjustment factor of 1.40; 2) the difference in generated storm patterns between C0 and C1 was insignificant; and 3) results from C2 and C3 agreed well with those generated from C0. Hourly precipitation data can be used to prepare CLIGEN input parameter values for generating storm patterns for sites where only hourly data are available.

scholarly journals Different definitions of species presence to refine estimates of local species richness

2017 ◽  
Author(s):  
Alejandro Ruete ◽  
Tomas Pärt ◽  
Åke Berg ◽  
Jonas Knape ◽  
Debora Arlt
Keyword(s):  
Species Richness ◽  
Breeding Season ◽  
Temporal Resolution ◽  
Explanatory Power ◽  
Bird Species ◽  
High Temporal Resolution ◽  
Occupancy Models ◽  
Local Species Richness ◽  
Site Use ◽  
Local Species

Abstract Aim To improve predictions of spatial and temporal patterns of species richness it is important to consider how species presence at a site is defined. This is because this definition affects our estimate of species richness, which should be aligned with the aims of the study, e.g. estimating richness of the breeding community. Here we explore the sensitivity of species richness estimates to criteria for defining presence of species (e.g. in relation to number of days present during the breeding season) at 107 wetlands. Innovation We use opportunistic citizen science data of high density (a total of 151,817 observations of 77 wetland bird species; i.e. about 16 observations per day) to build site-occupancy models calculating occupancy probabilities at a high temporal resolution (e.g. daily occupancies) to derive probabilistic estimates of seasonal site use of each species. We introduce a new way for defining species presence by using different criteria related to the number of days the species are required to be present at local sites. We compared patterns of species richness when using these different criteria of species inclusions. Main conclusion While estimates of local species richness derived from high temporal resolution occupancy models are robust to observational bias, these estimates are sensitive to restrictions concerning the number of days of presence required during the breeding season. Unlike complete local species lists, summaries of seasonal site use and different presence criteria allow identifying differences between sites and amplifying the variability in species richness among sites. Thus, this approach allows filtering out species according to their phenology and migration behaviour (e.g. passer-by species) and could improve the explanatory power of environmental variables on predictive models.

scholarly journals Disaggregation of Future Regional Climate Model Data to Generate Future Rainfall Intensity-Duration-Frequency Curves to Assess Climate Change Impacts

2021 ◽  
Author(s):  
Hüsamettin Tayşi ◽  
Mehmet Ozger
Keyword(s):  
Climate Change ◽  
Urban Areas ◽  
Climate Model ◽  
Regional Climate ◽  
Rainfall Data ◽  
Rainfall Events ◽  
Rainfall Characteristics ◽  
Hourly Data ◽  
Idf Curves ◽  
Intensity Duration Frequency

Heavy increase in urbanization, industrialization and population is causing an increase in emissions of greenhouse gases (GHG) and this causes variations in atmosphere. Climate change causes extreme rainfall events and these events are expected to be enhanced in the future. Since flooding is influencing urban areas, controlling and management of flooding is a major necessity. Intensity-Duration-Frequency (IDF) curves play a huge role in representing rainfall characteristics by linking intensity, duration, and frequency of rainfall. Analysing short-duration rainfall is crucial for urban areas due to fast responses of drainage systems against heavy rainfall events. IDF curves were generated via the Gumbel method for rainfalls from 5-min to 24-h in this study. However, providing short-duration rainfall data is challenging due to the low capacity, costs and geographic conditions. Therefore, the HYETOS disaggregation model was applied to obtain sub-hourly data. IDF curves are stationary since they only consider historical events. However, IDF curves must be non-stationary and time varying based on preparation for upcoming extreme events. This study aims to generate IDF curves under climate change scenarios. The Regional Climate Model (RCM) HadGEM2-ES generated under Representative Concentration Pathways (RCP) 4.5 and 8.5 scenarios and was used in the study to represent future rainfalls. Future daily rainfalls were disaggregated into sub-hourly using disaggregation parameters of corresponding station’s historical rainfall data since it is impossible to estimate parameters when hourly data is not available. With this new approach, future daily rainfall data is disaggregated into 5-min data by complying with historical rainfall patterns rather than complying with randomly selected rainfall characteristics. The study concluded that future rainfall intensities increases compared to historical IDF curves. RCP8.5 scenarios have higher rainfall intensities for all return periods compared to RCP4.5 scenarios for all stations except a station. In addition, the accuracy of the selected disaggregation model was verified.

scholarly journals Data-based mechanistic model of catchment phosphorus load improves predictions of storm transfers and annual loads in surface waters

2017 ◽  
Author(s):  
Mary C. Ockenden ◽  
Wlodek Tych ◽  
Keith J. Beven ◽  
Adrian L. Collins ◽  
Robert Evans ◽  
...  
Keyword(s):  
Temporal Resolution ◽  
Surface Waters ◽  
Dynamic Models ◽  
Mechanistic Model ◽  
Second Order ◽  
Dynamic Responses ◽  
Mitigation Measures ◽  
High Temporal Resolution ◽  
Hourly Data ◽  
The Uk

Abstract. Excess nutrients in surface waters, such as phosphorus (P) from agriculture, result in poor water quality, with adverse effects on ecological health and costs for remediation. However, understanding and prediction of P transfers in catchments have been limited by inadequate data and over-parameterised models with high uncertainty. We show that, with high temporal resolution data, we are able to identify simple dynamic models that capture the P load dynamics in three contrasting agricultural catchments in the UK. For a flashy catchment, a linear, second-order (two pathways) model for discharge gave high simulation efficiencies for short-term storm sequences and was useful in highlighting uncertainties in out-of-bank flows. A model with non-linear rainfall input was appropriate for predicting seasonal or annual cumulative P loads where antecedent conditions affected the catchment response. For second-order models, the time constant for the fast pathway varied between 2 and 15 hours for all three catchments and for both discharge and P, confirming that high temporal resolution (hourly) data are necessary to capture the dynamic responses in small catchments (10–50 km2). The models led to a better understanding of the dominant nutrient transfer modes, which will, in-turn, help in planning appropriate pollution mitigation measures.

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