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Riverine and Flood Modeling Software
Published in Saeid Eslamian, Faezeh Eslamian, Flood Handbook, 2022
Mustafa Goodarzi, Saeid Eslamian
In Figure 16.8, inputs and outputs of the SWAT model are schematically presented. This model simulates very large watersheds or varies the management strategy and enables users to simulate long-term modeling without spending extra cost or time. The SWAT software is a physically based distributed hydrological model that uses the Soil Conservation Service (SCS) Runoff Curve Number (CN) method to calculate surface runoff, and the degree-day factor method to calculate snowmelt runoff (Duan et al., 2018). In general, this software is a comprehensive model for assessing flow discharge, long-term effects of management operations on water, sediment, and agricultural chemicals in large watersheds. In order to use this model properly, parameters which the output of the model is more sensitive to their accuracy must be specified, and the model is calibrated based on the observation data of a given period (e.g., measured discharge flow data from the river in the watershed) (Goodarzi, 2016).
Simulation of Crop Growth: CROPGRO Model
Published in Robert M. Peart, R. Bruce Curry, Agricultural Systems Modeling and Simulation, 2018
Kenneth J. Boote, James W. Jones, Gerrit Hoogenboom
The soil water balance in CROPGRO is the same as that in the CERES growth models and is described in detail by Ritchie (1985). The soil is divided into a number of layers, up to 10 or more. Water content in each layer varies between a lower limit [LL(J)] and a saturated upper limit [SAT(J)]. If water content of a given layer is above a drained upper limit [DUL(J)], then water is drained to the next layer with the “tipping bucket” approach, using a drainage coefficient specified in the soil file. Infiltration and runoff of rainfall and applied irrigation water depend on the Soil Conservation Service (SCS) runoff curve number. Vertical drainage may be limited by the saturated hydraulic conductivity (Ksat) for each layer. This feature allows the soil to retain water above layers that have been compacted or have natural impedance to water flow. In such cases, soil layers may become saturated for a period of time, causing root death, reduced root water uptake, and decreased N2 fixation.
Hydrological Modeling to Assess Runoff in a Semi-arid Andean Headwater Catchment for Water Management in Central Chile
Published in Diego A. Rivera, Alex Godoy-Faundez, Mario Lillo-Saavedra, Andean Hydrology, 2018
S. Penedo-Julien, A. Nauditt, A. Künne, M. Souvignet, P. Krause
A sensitivity analysis was conducted for both models to reduce the number of parameters to be calibrated. The most sensitive parameters (p value < 0.05) were adjusted to fit the simulated to the observed streamflow. For SWAT, the sensitive parameters included baseflow alfa factor, initial SCS runoff curve number, melt factors of snow, slope length for lateral subflow, soil evaporation compensation factor, surface runoff lag coefficient, groundwater delay and snowmelt base temperature. As it can be observed, these parameters cover a broad scope of processes such as snowmelt, surface runoff and groundwater movement as well as evapotranspiration. Furthermore, the most sensitive parameters for J2000 included base temperature, temperature, rain and soil heat factors for snowmelt calculation as well as reduction coefficient for evapotranspiration calculation and RG1 and RG2 outflow adaptation factors. These parameters also cover a wide scope of hydrological processes such as snowmelt, evapotranspiration (important for the water balance) and groundwater flows.
Performance of rainwater tanks for runoff reduction under climate change scenarios: a case study in Brazil
Published in Urban Water Journal, 2020
Taís Maria Nunes Carvalho, Francisco De Assis de Souza Filho, Marcos Abílio Medeiros de Sabóia
The Storm Water Management Model (SWMM) 5.1.013 was used for rainfall-runoff simulation. Flow routing was modelled with the dynamic wave method and the infiltration was modelled with the Soil Conservation Service curve number method. This is an empirical method for predicting runoff or infiltration based on the relationship between rainfall and ground conditions (Mishra and Singh 2003). The runoff curve number (CN) can be estimated from tables containing combinations of soil hydrology, land cover, and land management conditions. However, for urban hydrologic soils with percent impervious not specified by the Technical Release 55, the CN value can be estimated as follows (USDA Soil Conservation Service 1986):
Application of NRCS-CN method for estimation of watershed runoff and disaster risk
Published in Geomatics, Natural Hazards and Risk, 2019
The NRCS-CN model was developed in 1972 by the US Soil Conservation Service (SCS), which was the predecessor of the Natural Resources Conservation Service (NRCS). The model makes extensive use of runoff curve number, which is also referred to as curve number (CN), to estimate surface runoff in a watershed. In this model, empirical data are used to simulate the relationship between stormwater and local hydraulic changes, and this approach enables the prediction of storm runoff from rainfall depth. Lately, the CN has been increasingly applied in fields pertaining to engineering, hydrology, and water resource management and has returned favorable results (Huang et al. 2006; Jung et al. 2012; Ozdemir and Elbaşı 2015).