Evaluation of lag time and time of concentration estimation methods in small tropical watersheds in Ethiopia

Analyzing the influence of changes in land use and management practices on the lag time of peak flows for tropical watersheds of Ethiopia

“…In other words, a low CN value means that the surface has a high potential to retain water, whereas high values indicate that rainfall can only be stored to a limited extent. CN values obtained from this research were much lower than CN values (87-98) derived from a plot-scale study in the highland region of the Kasiry watershed (399 ha), which is also in the Upper Blue Nile basin(Sultan et al, 2017). In that study, high CN values were attributed to the steep slopes, high rainfall intensity, and soil moisture conditions of the highland region.4.3 | Effect of LULC change and SWC practice on T L The main question of this research study is: Does LULC change and SWC practice affect river peak flow response time?…”

“…The sensitivities of the NRCS lag method for each parameter were checked using correlation analysis of variables with measured lag time value, watershed hydraulic length, SWC density, and weighted curve number of the watersheds showed positive correlations with T L ( r 2 = 0.96, 0.81, and 0.50, respectively). Similarly, Sultan et al (2022) had shown roles of these variables are dominant in the lag time equations, which in turn suggests that mixed (channel and overland) flow is the dominant flow regime in the watersheds.…”

“…Elucidating changes in the peak flow response time of a watershed resulting from changes in land use/land cover (LULC) and management practice is a key component of determining hydrological processes and is valuable information for any hydrologic design (Abdulkareem et al, 2017; Gericke & Smithers, 2014, 2016; Marhaento et al, 2018; McCuen, 2009; Sultan et al, 2022). The lag time ( T L ) of peak flow is a key parameter of how rapidly a watercourse responds in terms of runoff discharge to the precipitation over its catchment (Allnutt et al, 2020; McEnroe et al, 2016).…”

“…The timing of peak discharge reflects the pathway of water and is indicative of the biophysical features and flow routing of a basin. The timing varies noticeably with alterations in land surface characteristics, and it is directly related to and altered by catchment biophysical features (e.g., gradient, surface cover, soils, canal density, and storage capacity), metrological and hydrological factors (e.g., precipitation and discharge), and stream channel geomorphology (Sultan et al, 2022). Lag time of peak flow alterations governed by rainfall input and physical configurations of watersheds have been the main concern of several previous studies (Beven, 1978; Hood et al, 2010; Loukas & Quick, 1996; Sultan et al, 2022) but it can also be significantly affected by other factors.…”

“…The timing varies noticeably with alterations in land surface characteristics, and it is directly related to and altered by catchment biophysical features (e.g., gradient, surface cover, soils, canal density, and storage capacity), metrological and hydrological factors (e.g., precipitation and discharge), and stream channel geomorphology (Sultan et al, 2022). Lag time of peak flow alterations governed by rainfall input and physical configurations of watersheds have been the main concern of several previous studies (Beven, 1978; Hood et al, 2010; Loukas & Quick, 1996; Sultan et al, 2022) but it can also be significantly affected by other factors. A few studies have suggested that vegetation cover and land management practice (Gericke & Smithers, 2018; Ragan & Duru, 1972) are the most influential factor in the computation of lag time of peak flow for small to medium catchments.…”