Design soil moisture estimation by comparing continuous and storm‐based rainfall‐runoff modeling

Abstract

[1] In recent years local, national, and international authorities have showed an increasing awareness of flood and inundation hazard, likely due to the large floods which occurred in the past years in many regions of the world. In this context, the estimation of the design flood values to be adopted for flood risk assessment or floodplain management represents a crucial factor. In the case of ungauged or scarcely gauged catchments where a sufficiently long discharge time series is missing, a relevant uncertainty is involved in the flood frequency analysis and a possible solution to reduce this uncertainty is the application of continuous simulation (CS) approaches. Because of the complex structure of this type of approaches and pursuing the parameters parsimony criteria, in the hydrological practice the approaches based on the design storm (DS) estimation are more widely known and applied, mainly for their simplicity. However, one major limit of the DS method is the choice of the ''design soil moisture'' conditions, representing a critical parameter for assessing the initial wetness of the basin. To that end, this study of investigating six subcatchments of the upper Tiber River basin (Central Italy), with drainage area ranging from 13 to 284 km 2 , proposes a procedure based on the application of the CS approach as a tool to define the design soil moisture to be afterwards incorporated into the more simple DS method. For each catchment, the procedure consists of (1) stochastic generation of long synthetic rainfall and temperature series starting from observed hourly data; (2) application of a lumped continuous rainfall-runoff model to generate synthetic discharge series and, hence, to obtain the corresponding flood frequency curves; (3) estimation of the design soil moisture, for each return period, by varying in the DS approach the initial wetness conditions of the catchment so that the peak discharge estimated by the DS method matches the one given by the synthetic flood frequency curve. Moreover, in order to apply the more simple DS approach avoiding the use of the CS one, a preliminary analysis to regionalize the design soil moisture as a function of the geomorphological characteristics and the return period is also shown.Citation: Camici, S., A. Tarpanelli, L. Brocca, F. Melone, and T. Moramarco (2011), Design soil moisture estimation by comparing continuous and storm-based rainfall-runoff modeling, Water Resour. Res., 47, W05527,

Coupling soil moisture and precipitation observations for predicting hourly runoff at small catchment scale

“…Previous studies in the Niccone and Colorso catchments (Brocca et al, 2009a;Camici et al, 2011) highlighted the strong influence of the initial soil moisture conditions in the runoff generation mechanism of the study area, as it usually occurs for Mediterranean catchments (Tramblay et al, 2012). Specifically, the basins are characterized by a quick runoff response likely dominated by shallow subsurface flow taking place near the surface layer of soil.…”

An Investigation into Sub-Basin Rainfall Losses in Different Underlying Surface Conditions Using HEC-HMS: A Case Study of a Loess Hilly Region in Gedong Basin in the Western Shanxi Province of China

“…The basin is a typical hilly and gully region of the Loess Plateau. The area of soil erosion is 524 km 2 , and the area of soil and water conservation is 621 km 2 . The climate of the basin is arid and semi-arid warm temperature, the average annual temperature is 8.7 • C, and the average annual rainfall is 517 mm.…”

“…Rainfall losses, which occur during flood events, play a crucial role in real-time flood forecasting and flood estimation [1,2]. The losses are generated through canopy interception, infiltration, depression storage, evaporation, and evapotranspiration [3].…”

Fuzzy Logic for Rainfall-Runoff Modelling Considering Soil Moisture

“…To assess the performance the fuzzy model with respect to classical continuous rainfall-runoff models, the MISDc (BModello Idrologico Semi Distribuito in continuo^), developed by Brocca et al (2011) and already applied successfully by Camici et al (2011), was employed in this study. MISDc consists of two main components: 1) a soil water balance (SWB) model to simulate the soil moisture temporal pattern and 2) a semi-distributed event-based Rainfall-Runoff (RR) model (MISD) for flood simulation.…”