scholarly journals Orographic influences in rainfall downscaling

2005 ◽  
Vol 2 ◽  
pp. 285-292 ◽  
Author(s):  
M. G. Badas ◽  
R. Deidda ◽  
E. Piga
Keyword(s):  
Spatial Heterogeneity ◽  
Temporal Resolution ◽  
Rainfall Data ◽  
High Temporal Resolution ◽  
Mountainous Region ◽  
Rain Gage

Abstract. The problem of rainfall downscaling in a mountainous region is discussed, and a simple methodology aimed at introducing spatial heterogeneity induced by orography in downscaling models is proposed. This procedure was calibrated and applied to rainfall data retrieved by the high temporal resolution rain gage network of the Sardinian Hydrological Survey.

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 Exploring the possible role of satellite-based rainfall data to estimate inter‐ and intra‐annual global rainfall erosivity

2021 ◽  
Author(s):  
Nejc Bezak ◽  
Pasquale Borrelli ◽  
Panos Panagos
Keyword(s):  
Trend Analysis ◽  
Temporal Resolution ◽  
Rainfall Data ◽  
Winter Period ◽  
High Temporal Resolution ◽  
Rainfall Erosivity ◽  
Main Challenge ◽  
Precipitation Estimates ◽  
Recent Developments ◽  
Substantial Progress

Abstract. Despite recent developments in modelling global soil erosion by water, to date no substantial progress has been made towards more dynamic inter- and intra-annual assessments. In this regard, the main challenge is still represented by the limited availability of high temporal resolution rainfall data needed to estimate rainstorms rainfall erosivity. As this data scarcity is likely to characterize the upcoming years, the suitability of alternative approaches to estimate global rainfall erosivity using satellite-based rainfall data was explored. For this purpose, the high spatial and temporal resolution global precipitation estimates obtained with the NOAA CDR Climate Prediction Center MORPHing technique (CMORPH) were used. Alternatively, the erosivity density (ED) concept was used to estimate global rainfall erosivity as well. The obtained global estimates of rainfall erosivity were validated against the pluviograph data included in the Global Rainfall Erosivity Database (GloREDa). Overall, results indicated that the CMORPH estimates have a marked tendency to underestimate rainfall erosivity when compared to the GloREDa estimates. The most substantial underestimations were observed in areas with the highest rainfall erosivity values. At continental level, the best agreement between annual CMORPH and interpolated GloREDa rainfall erosivity map was observed in Europe. Worse agreement was detected for Africa and South America. Further analyses conducted at monthly scale for Europe revealed seasonal misalignments, with the occurrence of underestimation of the CMORPH estimates in the summer period and overestimation in the winter period compared to GloREDa. The best agreement between the two approaches to estimate rainfall erosivity was found for autumn, especially in Central and Eastern Europe. Conducted analysis suggested that satellite-based approaches for estimation of rainfall erosivity appear to be more suitable for low-erosivity regions, while in high erosivity regions and seasons (> 1,000–2,000 MJ mm ha−1 h−1 yr−1), the agreement with estimates obtained from pluviograph data such as GloREDa is lower. Concerning the ED estimates, this second approach to estimate rainfall erosivity yielded better agreement with GloREDa estimates compared to CMORPH. The application of a simple-linear function correction of the CMORPH data was applied to provide better fit to the GloREDa and correct systematic underestimation. This correction improved the performance of the CMORPH but in areas with the highest rainfall erosivity rates the underestimation was still observed. A preliminary trend analysis of the CMORPH rainfall erosivity estimates was also performed for the 1998–2019 period. According to this trend analysis, increasing and statistically significant trend was more frequently observed than decreasing trend.

scholarly journals Modulation of homogeneous space-time rainfall cascades to account for orographic influences

2006 ◽  
Vol 6 (3) ◽  
pp. 427-437 ◽  
Author(s):  
M. G. Badas ◽  
R. Deidda ◽  
E. Piga
Keyword(s):  
Spatial Heterogeneity ◽  
Probability Distributions ◽  
Synthetic Data ◽  
Space Time ◽  
High Temporal Resolution ◽  
Spatial Homogeneity ◽  
Mean Values ◽  
Small Watersheds ◽  
Rain Gage ◽  
Terrain Elevation

Abstract. The development of efficient space-time rainfall downscaling procedures is highly important for the implementation of a meteo-hydrological forecasting chain operating over small watersheds. Multifractal models based on homogeneous cascade have been successfully applied in literature to reproduce space-time rainfall events retrieved over ocean, where the hypothesis of spatial homogeneity can be reasonably accepted. The feasibility to apply this kind of models to rainfall fields occurring over a mountainous region, where spatial homogeneity may not hold, is herein investigated. This issue is examined through the analysis of rainfall data retrieved by the high temporal resolution rain gage network of the Sardinian Hydrological Survey. The proposed procedure involves the introduction of a modulating function which is superimposed to homogeneous and isotropic synthetic fields to take into account the spatial heterogeneity detected in observed precipitation events. Specifically the modulating function, which reproduces the differences in local mean values of the precipitation intensity probability distribution, has been linearly related to the terrain elevation of the analysed spatial domain. Comparisons performed between observed and synthetic data show how the proposed procedure preserves the observed rainfall fields features and how the introduction of the modulating function improves the reproduction of spatial heterogeneity in rainfall probability distributions.

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

Spatial and seasonal patterns of rainfall erosivity in the Lake Kivu region: Insights from a meteorological observatory network

2021 ◽  
pp. 030913332110017
Author(s):  
R.M. Bagalwa ◽  
C. Chartin ◽  
S. Baumgartner ◽  
S. Mercier ◽  
M. Syauswa ◽  
...  
Keyword(s):  
Temporal Resolution ◽  
Prediction Models ◽  
Temporal Dynamics ◽  
Rainfall Data ◽  
Annual Rainfall ◽  
High Temporal Resolution ◽  
Rainfall Erosivity ◽  
Lake Kivu ◽  
Meteorological Observatory ◽  
Resolution Data

In the Lake Kivu region, water erosion is the main driver for soil degradation, but observational data to quantify the extent and to assess the spatial-temporal dynamics of the controlling factors are hardly available. In particular, high spatial and temporal resolution rainfall data are essential as precipitation is the driving force of soil erosion. In this study, we evaluated to what extent high temporal resolution data from the TAHMO network (with poor spatial and long-term coverage) can be combined with low temporal resolution data (with a high spatial density covering long periods of time) to improve rainfall erosivity assessments. To this end, 5 minute rainfall data from TAHMO stations in the Lake Kivu region, representing ca. 37 observation-years, were analyzed. The analysis of the TAHMO data showed that rainfall erosivity was mainly controlled by rainfall amount and elevation and that this relation was different for the dry and wet season. By combining high and low temporal resolution databases and a set of spatial covariates, an environmental regression approach (GAM) was used to assess the spatiotemporal patterns of rainfall erosivity for the whole region. A validation procedure showed relatively good predictions for most months (R2 between 0.50 and 0.80), while the model was less performant for the wettest (April) and two driest months (July and August) (R2 between 0.24 and 0.38). The predicted annual erosivity was highly variable with a range between 2000 and 9000 MJ mm ha−1 h−1 yr−1 and showed a pronounced east–west gradient which is strongly influenced by local topography. This study showed that the combination of high and low temporal resolution rainfall data and spatial prediction models can be used to improve the assessments of monthly and annual rainfall erosivity patterns that are grounded in locally calibrated and validated data.

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