In recent decades, flash floods have become one of the most severe natural hazards in the context of global climate change [1
]. Flash floods threaten human lives and properties worldwide with potentially devastating consequences, giving rise to one third of all losses due to natural disasters [2
]. Unfortunately, with increasing intense precipitation over highly saturated soils in mountainous terrain, flash flooding events are likely to be more frequent over the globe [6
]. However, the forecasting and warning of flash floods of small-scale catchments in mountainous areas faces various challenges, which urgently calls for the development of effective models and calibration methods for predicting flash floods [7
Over past decades, numerous hydrological models with simple to complex structures were developed as a useful tool to deal with flood simulation [8
]. Hydrological models are classified as lumped models and distributed models [9
]. Distributed models consider the spatial distribution of land surface features, e.g., the Digital Elevation Model (DEM) and land cover type, however, it has a complex structure and requires intensive computation. Lumped models have a simple structure and require low computation, which proves that they effectively simulate flood events in small catchments (<2000 km2
]. Complex models do not always perform better than simple ones [8
]. Boithias et al. [12
] reported that the lumped SWAT model and distributed MARINE model equally satisfactorily simulated flood events, and Li et al. [13
] found that the distributed SWAT model and lumped XAJ (Xin’anjiang) model performed sub-daily simulation fairly in small catchments. Similarly, Huang et al. [14
] reported that the distributed HBV model does not outperform the lumped HBV model. These authors stated that increasing spatiality in the model structure is not the main reason to improve model performances but the rainfall quality and quantity are the most important factors influencing the simulation result [11
To date, only a few models have been designed to simulate flash flood events, because it is difficult to accurately describe runoff processes of flash events due to their short duration, fast recession and the peak of discharge being sustained only for a few hours or a few minutes [15
]. A couple of studies have extended daily models to simulate floods at sub-daily and hourly time steps using existing rainfall–runoff models, e.g., SWAT [12
]. In contrast, the MISDc-2L model was designed to simulate flood events at hourly time steps. It combines a soil water balance (SWB) model and a semi-distributed event-based rainfall–runoff model (MISD) with a two-layer scheme for better representation of the soil moisture state [20
]. The MISDc-2L model is advantageous due to its simple structure and low data requirements, and has been proven to effectively simulate flash floods at small catchments in Italy, America and other European countries [20
]. Nonetheless, the performance of flood simulation varies with different environmental conditions, especially for mountainous areas [5
]. Thus, it is necessary to examine the MISDc-2L capacity in different regions like China.
Although the MISDc-2L model has been applied in several study areas in the world, its parametric uncertainties and its performances over other regions have not been analyzed. Previous works on the calibration of MISDc-2L often operated with the full parameter set, which could have led to the uncertainties in simulation. The uncertainty occurs where the values of the calibrated parameters do not realistically reflect watershed characteristics or the equifinality of parameter sets endures due to the value assignments of model parameters with multiple combinations [27
]. The reduction in the calibration parameter amount along with sensitivity analysis is known as a useful method to lessen the computational consumption and uncertainties [29
]. Gan et al. [31
] reported that reducing the number of parameters of the CREST (Coupled Routing and Excess Storage) model from 12 to 7 based on sensitivity analysis improves the streamflow simulation. Moreover, several studies raised concerns about sensitive characteristic of parameters, whereby sensitive parameters should be calibrated while the insensitive parameter can be empirically set as a fixed value [32
]. As one of the most sensitive parameters, W_max dominates the infiltration process for small to medium catchments, which controls the runoff generation in flood models [34
]. However, W_max was set as a constant in previous studies using the MISDc-2L model, according to the spatial distribution of the Curve Number values computed from soil/land use characteristics and scaling factor based on the assumption about its variety in space [21
]. This value is empirically determined from flood events for the catchments in limited study areas, but it may be inappropriate in other areas or catchments [35
]. Hence, it is needed to assess the impact of W_max calibration on flood simulation.
This study aims to investigate the influence of calibration parameter selection on flash flood simulation for small to medium catchments with the MISDc-2L model in the Huai River basin of China. We focus on three main research questions: (1) How effective is the MISDc-2L model for flash flood simulations at hourly time-steps in the Huai River basin of China? (2) Is the reducing of the amount of calibration parameters favorable for streamflow simulation? (3) Does the inclusion of parameter maximum water capacity on calibration lead to the improvement in flood simulations with the MISDc-2L model? To address these questions, the paper is organized as follows: Section 2
and Section 3
describe the study area, data and methodology including model structure and model constraining strategies, Section 4
presents the results about model applicability with different calibration schemes, and Section 5
includes the discussion and Section 6
2. Study Area
The study area, namely the Huangnizhuang catchment (31°06′–31°42′ N, 115°21′–115°43′ E, 805 km2
) is located in the upstream section of Shiguan River, which is the first tributary of the Huai River Basin, Anhui Province, China (Figure 1
The upstream Shiguan River is a deep mountain area with deep valleys and steep slopes. The surrounding underlying surface is well covered by vegetation and is rich with granite and gneiss. The Huangnizhuang catchment has a loose sand bed structure and strong water permeability. It contains a complex topographical setting, including highly mountainous, hilly areas with a maximum elevation of 1495 m where the streamflow is very rapid, and a low alluvial plain where the drainage network is well developed. It has different land cover properties; woodland accounts for 81.01% of the total catchment, wooded grassland covers 9.21%, temperate deciduous forest (3.92%), mixed-forest (2.83%), and cropland and evergreen forest (3.01%). It has a monsoonal climate, which is affected by the climate of the Huai River and 60–70% of the annual precipitation is concentrated in summer. The mean annual air temperature is 11–16 °C and the mean annual precipitation is around 1077 mm. The precipitation in the rainy season from June to September accounts for almost 50–80% of annual total and greatly varies from year to year. This area is a center of rainstorm. Favorable geographical and climate characteristics, combined with heavy rain, commonly occur during drought seasons, causing flash floods in the study area.
In this study, we investigated the influence of calibration parameter selection on flash flood simulation for small to medium catchments with the MISDc-2L model in the Huai River basin of China over the 2010–2015 period. We explored the necessity of reducing calibration parameters and the role of W_max parameter calibration for flood simulations. The role of the W_max parameter for single events, split-sample tests and combined-events, and for different magnitude levels of flood, were investigated.
Although it is quite challenging to simulate floods in small to medium catchments in semi-humid areas, in our study the MISDc-2L model has satisfactory performance after reducing calibration parameters and including the W_max parameter for calibration. The results confirmed the finding that lumped models with suitable calibration strategies can effectively simulate flash floods in small to medium catchments (SMC). The reduction in calibration parameters’ amount is confirmed to remarkably improve streamflow simulation. In addition, we found that the inclusion of calibration of the parameter W_max in the infiltration process is crucial for streamflow simulation, especially for base flow, and it needs to be treated carefully for calibration. Model performances varied with flood magnitude levels and the simulations are generally better for high-magnitude floods than medium and low ones, but clear improvements can be achieved for low and medium magnitude flood events with careful calibration parameter selection. Therefore, improving the understanding of physical meanings of parameters as well as their roles in model simulation is highly necessary to build better calibration schemes, which are beneficial in terms of enhancing the accuracy of flood prediction and thus better serve early warning systems.
It is important to note that MISDc-2L performance in this study was limited by the length of the available data records (only 6 years of flood-events) and uncertainty from hourly rainfall input data associated with low rain-gauge density in small mountainous catchments, which could lead to the errors on the runoff generation. Thus, the methods for improving the quality and quantity of rainfall data should be given more attention in future.