Radar–rain-gauge rainfall estimation for hydrological applications in small catchments

Abstract

Abstract. The accurate evaluation of the precipitation's time-spatial structure is a critical step for rainfall-runoff modelling. Particularly for small catchments, the variability of rainfall can lead to mismatched results. Large errors in flow evaluation may occur during convective storms, responsible for most of the flash floods in small catchments in the Mediterranean area. During such events, we may expect large spatial and temporal variability. Therefore, using rain-gauge measurements only can be insufficient in order to adequately depict extreme rainfall events. In this work, a double-level information approach, based on rain gauges and weather radar measurements, is used to improve areal rainfall estimations for hydrological applications. In order to highlight the effect that precipitation fields with different level of spatial details have on hydrological modelling, two kinds of spatial rainfall fields were computed for precipitation data collected during 2015, considering both rain gauges only and their merging with radar information. The differences produced by these two precipitation fields in the computation of the areal mean rainfall accumulation were evaluated considering 999 basins of the region Calabria, southern Italy. Moreover, both of the two precipitation fields were used to carry out rainfall-runoff simulations at catchment scale for main precipitation events that occurred during 2015 and the differences between the scenarios obtained in the two cases were analysed. A representative case study is presented in detail.

Rainfall Intensity Temporal Patterns Affect Shallow Landslide Triggering and Hazard Evolution

“…Rainfall intensity temporal patterns affect shallow landslide triggering and hazard evolution. Geophysical Research Letters, 47. e2019GL085994 https://doi.org/ 10.1029/2019GL085994 flash floods, urban hydrology, and rainfall extremes; Gabriele et al, 2017;Villarini et al, 2010;Smith et al, 2007;Yang et al, 2004;Ntelekos et al, 2008). Motivated by studies on the role of the temporal patterns of rainfall intensity (hyetograph) on the hydrology of landscapes (e.g., Parsons & Stone, 2006;Robinson & Sivapalan, 1997;Singh, 1997;Woolhiser & Goodrich, 1988), we seek to examine the role of different temporal patterns of rainfall intensities on landslide initiation for the same rainfall amount.…”

Prediction of river temperature surges is dependent on precipitation method

“…Differences in precipitation between datasets (weather station, citizen science, and radar) were more pronounced than the differences between point‐based and catchment‐average calculation methods, which reflect precipitation variability over short distances during the events. Single precipitation gauge data are, therefore, often unrepresentative of multiple water temperature sample sites unless strict consideration is given to catchment size and strategic siting (Gabriele et al, ; Thorndahl et al, ; Villarini et al, ).…”

“…However, precipitation typically exhibits high spatial variability within catchments at different scales (Dixon & Mote, 2003;Salvadore, Bronders, & Batelaan, 2015). This is particularly evident in urban catchments where the combination of the urban heat island effect and changes in urban wind field alter precipitation patterns (Dixon & Mote, 2003;Salvadore et al, 2015) leads to variations in rainfall intensity and duration (Gabriele, Chiaravalloti, & Procopio, 2017;Pedersen et al, 2010;Thorndahl et al, 2017;Villarini, Mandapaka, Krajewski, & Moore, 2008). Consequently, the precipitation processes that drive water temperature fluxes during individual events can be difficult to quantify, particularly when using data from a single rainfall gauge.…”

“…Radar and citizen science precipitation datasets may provide a useful alternative to single rainfall gauges (Buytaert et al, 2014;Gabriele et al, 2017;Koch & Stisen, 2017;Starkey et al, 2017;Thorndahl et al, 2017), particularly in urban catchments where highspatial resolution precipitation data are required or where catchments are poorly gauged (Berne et al, 2004). Citizen science precipitation databases are increasingly common and can potentially increase the number of precipitation gauges available for catchment studies (Koch & Stisen, 2017;Starkey et al, 2017).…”

“…However, to-date concerns over data quality have inhibited their uptake for research purposes (Barthel, Seidl, Nickel, & Büttner, 2016;Buytaert et al, 2014;Starkey et al, 2017). Radar precipitation data can also yield high temporal and spatial resolution precipitation estimates (Biggs & Atkinson, 2011;Gabriele et al, 2017;Thorndahl et al, 2017;Villarini et al, 2008). For example, in the United Kingdom, the NIMROD system generates radar-derived precipitation estimates at 5-min temporal and 1-km 2 spatial resolution (Villarini et al, 2008).…”