Geomorphology-based unit hydrograph models for flood risk management: case study in Brazilian watersheds with contrasting physiographic characteristics

Abstract

Heavy rainfall in conjunction with an increase in population and intensification of agricultural activities have resulted in countless problems related to flooding in watersheds. Among the techniques available for direct surface runoff (DSR) modeling and flood risk management are the Unit Hydrograph (UH) and Instantaneous Unit Hydrograph (IUH). This study focuses on the evaluation of predictive capability of two conceptual IUH models (Nash and Clark), considering their original (NIUH and CIUH) and geomorphological approaches (NIUHGEO and CIUHGEO), and their advantages over two traditional synthetics UH models - Triangular (TUH) and Dimensionless (DUH), to estimate DSR hydrographs taking as reference two Brazilian watersheds with contrasting geomorphological and climatic characteristics. The main results and conclusions were: i) there was an impact of the differences in physiographical characteristics between watersheds, especially those parameters associated with soil; the dominant rainfall patterns in each watershed had an influence on flood modeling; and ii) CIUH was the most satisfactory model for both watersheds, followed by NIUH, and both models had substantial superiority over synthetic models traditionally employed; iii) although geomorphological approaches for IUH had performances slightly better than TUH and DUH, they should not be considered as standard tools for flood modeling in these watersheds.

Adequacy of methodologies for determining SCS / CN in a watershed with characteristics of the Pampa biome

“…This corresponds to the Yellow Argisol (78.7%), Red Argisol (14.7%) and Grayish Brown Argisol (6.6%) (Figure 1b), according to the Brazilian Soil Classification System -SiBCS (Santos et al, 2018). According to Beskow et al (2018), the land-use classes identified in CRW are forest (31.0%), grassland (30.0%), bare soil (25.0%), pasture (13.9%), and water body (0.1%) (Figure 1c).…”

“…It should be noted that the SCS/CN model considers rainfall events of short duration and, therefore, without significant variation in the maximum potential for water infiltration in the soil during the event. However, the events that occur in watersheds with predominance of frontal systems, such as CRW, are long-lasting and experience varying intensities over time (Beskow et al, 2018). Thus, the maximum potential for water infiltration in the soil may vary during the event, given the variability of losses by evapotranspiration and infiltration that significantly depend on the time that water remains on the soil surface (Mishra et al, 2008).…”

Hydrograph Study of Palu River Watershed

“…Another factor is the time to peak. In Nakayasu method, the time to peak is fixed and the equation is a function of time of concentration and the main river length [15]. Changes in properties of runoff environmental changes in land use cannot be replaced through peak time because Nakayasu synthetic unit hydrograph does not give the peak time coefficient, so calibration is done through the coefficient of peak discharge, Cp only.…”

Spatial discretization influence on flood modeling using unit hydrograph theory

“…time-area histograms, time of concentration and storage (AHMAD; GHUMMAN; AHMAD, 2009; SADEGHI; ASADI 2010; RIVARD; LEFEBVRE; PARADIS, 2014). Scientific studies have demonstrated the potential of Clark's IUH to estimate watershed floods around the world (SILVA; WEERAKOON;HERATH, 2014;DU et al, 2015;DARIANE;JAVADIANZADEH;JAMES, 2016;BESKOW et al, 2018).…”

“…Semi-distributed models are capable of providing a more detailed characterization of watersheds as well as better water balance estimates, especially at their outlet (SMITH et al, 2004). The use of SCS UH and Clark's IUH, based on lumped modeling, can be found in some studies at the watershed level in different regions worldwide (WAŁĘGA, 2013; SILVA; WEERAKOON; HERATH, 2014; DU et al, 2015; DARIANE; JAVADIANZADEH; JAMES, FOULI et al, 2016;IBRAHIM-BATHIS;AHMED, 2016;MASOUD, 2016;BESKOW et al, 2018). On the other hand, there are few studies intended for evaluation of such models according to a semi-distributed approach (GONZALO;ROBREDO;MINTEGUI, 2012;JOO et al, 2014).…”