Improvement of SCS-CN Initial Abstraction Coefficient in the Czech Republic: A Study of Five Catchments

Caletka, Martin; Michalková, Monika Šulc; Karásek, Petr; Fučík, Petr

doi:10.3390/w12071964

Cited by 48 publications

(21 citation statements)

References 56 publications

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“…Surface runoff is the process in which precipitated water flows through a channel in the catchment area after the surface and underground losses (CALETKA et al, 2020). The surface runoff potential charts were developed according to Pejon's proposal (1992), using the attributes: slope, lithology, soil texture/origin and thickness, drainage density, and features favorable to surface storage.…”

Section: Surface Runoff Potential Chartmentioning

confidence: 99%

Hydrological response of hydrographic sub-basins in the Piracicaba River Basin - Southeast Region of Brazil

Carvalho

Lorandi

Lollo

et al. 2022

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Use of water for several human needs, associated with climate change, indicates the need understand the response of watersheds, in order to provide adequate water resources planning and management. This study was carried out in two pairs of hydrographic watersheds, in the Piracicaba River Basin, southeast of Brazil, analyzing water response, integrating in-situ collected precipitation and flow data, natural environment attributes, and anthropic environmental data. To support the analysis, Surface Runoff Potential Charts (SRPC). The evaluation of the physical characteristics of the sub watersheds (SW(A) and SW(B)) shows that these areas present very low to low potential, indicating greater infiltration capacity. The use and coverage of the soil partially justifies the flow changes in pair 1, since SW(A) has a larger extent of agricultural areas that can use irrigation. SW(B), even with a greater variety of crops, has a smaller cultivated area and tends to demand less water. At pair 2, the low runoff potential is mainly due to the predominance of flat relief in the sub-basins. The soils that compose them present a higher fraction of silt and clay, with thicknesses > 5m in SW(C) and varying from 0.5m, reaching depths above 5m in SW(D), however, the physical properties of these soils do not provide a low flow rate, but associated with the low slope of the land, the geological characteristics and low drainage density are configured in regions where the flow flows more slowly, contributing to the evaporation and infiltration process. The use and coverage of the soil also partially justifies the flow oscillations, due to anthropic activities in SW(C) and SW(D), such as irrigation and spraying of citrus, fertirrigation of sugarcane, irrigation of seedling nurseries, directly interfering with the availability of surface water.

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Section: Surface Runoff Potential Chartmentioning

confidence: 99%

Hydrological response of hydrographic sub-basins in the Piracicaba River Basin - Southeast Region of Brazil

Carvalho

Lorandi

Lollo

et al. 2022

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“…where α (−) is a constant, which in original formulation was set equal to 0.2, but recent works demonstrate that its value can range from 0.05 to 0.2 [42,[44][45][46] as a function of the physiographic characteristics of the watershed, type of vegetation cover and severity of potential alterations suffered by the watershed such deforestation and fire [47,48].…”

Section: Rainfall-runoff Simulation Strategymentioning

confidence: 99%

Integrating Remote and In-Situ Data to Assess the Hydrological Response of a Post-Fire Watershed

et al. 2021

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Forest fire is a common concern in Mediterranean watersheds. Fire-induced canopy mortality may cause the degradation of chemical–physical properties in the soil and influence hydrological processes within and across watersheds. However, the prediction of the pedological and hydrological effect of forest fires with heterogenous severities across entire watersheds remains a difficult task. A large forest fire occurred in 2017 in northern Italy providing the opportunity to test an integrated approach that exploits remote and in-situ data for assessing the impact of forest fires on the hydrological response of semi-natural watersheds. The approach is based on a combination of remotely-sensed information on burned areas and in-situ measurements of soil infiltration in burned areas. Such collected data were used to adapt a rainfall–runoff model over an experimental watershed to produce a comparative evaluation of flood peak and volume of runoff in pre- and post-fire conditions. The model is based on a semi-distributed approach that exploits the Soil Conservation Service Curve Number (SCS-CN) and lag-time methods for the estimation of hydrological losses and runoff propagation, respectively, across the watershed. The effects of fire on hydrological losses were modeled by adjusting the CN values for different fire severities. Direct infiltration measurements were carried out to better understand the effect of fire on soil infiltration capacity. We simulated the hydrological response of the burned watershed following one of the most severe storm events that had hit the area in the last few years. Fire had serious repercussions in regard to the hydrological response, increasing the flood peak and the runoff volume up to 125% and 75%, respectively. Soil infiltration capacity was seriously compromised by fire as well, reducing unsaturated hydraulic conductivity up to 75% compared with pre-fire conditions. These findings can provide insights into the impact of forest fires on the hydrological response of a whole watershed and improve the assessment of surface runoff alterations suffered by a watershed in post-fire conditions.

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“…SCS-CN method is one of the most globally recognized empirical hydrological method for runoff depth estimation in applied hydrological sciences at low cost [1][2][3][4]. This is not only because of its simplicity and reliability, supported by empirical data and over 20 years long experience [5][6], but also because of the availability of a range of modified SCS-CN models in literature, applicability to various scientific areas and validated in many case studies across the globe. Originally, the method was developed by USDA in 1954 for runoff estimation in small and medium agricultural watersheds of the USA.…”

Section: Introductionmentioning

confidence: 99%

“…Originally, the method was developed by USDA in 1954 for runoff estimation in small and medium agricultural watersheds of the USA. Later, it has also been applied in various environments including mine area [7][8][9], urbanized river basin [10][11][12], forested watersheds [13][14], steep slope watersheds [15][16], mountainous watersheds [17], experimental watersheds [5,18], large watersheds having multiple land uses, geographical regions and climatic conditions (e.g. arid and semi-arid).…”

Section: Introductionmentioning

confidence: 99%

Improved SCS-CN Model Incorporating Storm Duration and Rainfall-based Initial Abstraction for Runoff Estimation

Rk¹,

Verma²,

Sharma³

et al. 2021

Preprint

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The need of incorporating storm intensity or duration in Soil Conservation Service Curve Number (SCS-CN) methodology for improved direct surface runoff estimation for a watershed has been highlighted by many engineers and hydrologists since long and despite this fact, it is still poorly explored. Therefore, this study aims to present storm duration-based improved SCS-CN models for estimating more accurate direct surface runoff from rainfall events. The accuracy and consistency of improved models are tested on a large rainfall-runoff dataset (18,660 rainfall events) derived from 39 watersheds in the USDA-ARS. Furthermore, the quantitative model’s performance is also evaluated employing six widely accepted statistical measures viz. root mean square error (RMSE), mean absolute error (MAE), normalized root mean square error (NRMSE), Nash-Sutcliffe efficiency (NSE), percent bias (PBIAS), observations standard deviation ratio (RSR), and several grading criteria. These models are compared with the original SCS-CN model (M1) and its simple form (M2) with traditionally fixed initial abstraction ratio (λ) as 0.2. The resulting lowest values of RMSE, NRMSE, MAE, NSE, PBIAS and highest values of RSR and ranking grading system (RGS) for the proposed models (M3-M5) reveal that their performance is better than M1 and M2 models. The proposed M5 model incorporating both storm duration and varying initial abstraction (Ia) as a certain percentage of rainfall, performed the best followed by M3 incorporating only storm duration. According to RGS, M5 also ranked first with the highest marks (195) followed by M3 (140). Due to high accuracy in predicted runoff, M5 can be recommended for both small and large watersheds as it overcomes the following issues: fixed λ (=0.2), assumption of constant rainfall intensity (time-independent), fixation of Ia at 2% of rainfall and applicability to only small watersheds, restricting the application of original SCS-CN and its modified versions.

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Improvement of SCS-CN Initial Abstraction Coefficient in the Czech Republic: A Study of Five Catchments

Cited by 48 publications

References 56 publications

Hydrological response of hydrographic sub-basins in the Piracicaba River Basin - Southeast Region of Brazil

Hydrological response of hydrographic sub-basins in the Piracicaba River Basin - Southeast Region of Brazil

Integrating Remote and In-Situ Data to Assess the Hydrological Response of a Post-Fire Watershed

Improved SCS-CN Model Incorporating Storm Duration and Rainfall-based Initial Abstraction for Runoff Estimation

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