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In the mathematical models, the parameters need to be optimized for the given catchment area and give the maximum efficiency in terms of goodness-of-fit statistics. The SOLVER tool is used for optimization, which uses the Generalized Reduced Gradient (GRG) non-linear method of optimization (Hirpurkar & Ghare 2015). The initial values and optimized values of all parameters are shown in Table 2.

Table 2

Optimized parameters of different mathematical models

S. No.	Method	Parameter		Initial value	Optimized value
1.	SCS-CN with λ optimization	λ	Initial abstraction ratio	0.2	0.037
2.	MS	f_c	Minimum infiltration rate	1	0.02
2.	MS	S	Amount of potential maximum retention in soil	125	41.95
3.	MVP	α	Coefficient for initial soil moisture	0.01	0.22
		β	Coefficient for threshold soil moisture	0.01	0.02
		S	Amount of potential maximum retention in soil	125	217.5
4.	ASMA-SCS-CN	α	Coefficient for initial soil moisture	0.01	0.11
		β	Coefficient for threshold soil moisture	0.01	0.01
		f_c	Minimum infiltration rate	1	0.1
		S	Amount of potential maximum retention in soil	125	109

S. No.	Method	Parameter		Initial value	Optimized value
1.	SCS-CN with λ optimization	λ	Initial abstraction ratio	0.2	0.037
2.	MS	f_c	Minimum infiltration rate	1	0.02
2.	MS	S	Amount of potential maximum retention in soil	125	41.95
3.	MVP	α	Coefficient for initial soil moisture	0.01	0.22
		β	Coefficient for threshold soil moisture	0.01	0.02
		S	Amount of potential maximum retention in soil	125	217.5
4.	ASMA-SCS-CN	α	Coefficient for initial soil moisture	0.01	0.11
		β	Coefficient for threshold soil moisture	0.01	0.01
		f_c	Minimum infiltration rate	1	0.1
		S	Amount of potential maximum retention in soil	125	109

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