Estimation of Net Irrigation Requirements of Crops in the Deterministic and Stochastic Regimes for Limbasi Canal Command Area

Estimation of Net Irrigation Requirement (NIR) of crops is essential for agricultural planning, irrigation scheduling, regional water balance studies and optimal allocation of land and water resources in a canal command area. In the present study, NIR estimation of different crops of Limbasi Canal command area, Gujarat, India is carried out in the deterministic and stochastic regimes for nineteen years of available data. In the deterministic regime, the estimated average NIR of 19 years for kharif crops paddy & vegetables was 229.8 & 92.9mm ; rabi crops sorghum, tobacco, wheat & vegetables was 355.5, 391, 427.2 & 407.1mm and hot weather crops paddy, pearl millet & vegetables was 863.9, 600.6 & 754.7 mm respectively. In the stochastic regime, NIR of different crops was predicted at Probability of Exceedance (PE) levels of 0.02, 0.05, 0.08, 0.10, 0.15, 0.20, 0.25, 0.35 and 0.40 using 19 years of NIR. MATLAB was used for prediction of NIR. The goodness of fit was tested by Kolmogorov – Smirnov test and normal distribution was found as the best fit.

Stochastic Phenomena in One-Dimensional Rulkov Model of Neuronal Dynamics

We study the nonlinear Rulkov map-based neuron model forced by random disturbances. For this model, an overview of the variety of stochastic regimes is given. For the parametric analysis of these regimes, the stochastic sensitivity functions technique is used. In a period-doubling zone, we analyze backward stochastic bifurcations modelling changes of modality of noisy neuron spiking. Noise-induced transitions in a zone of bistability are considered. It is shown how such random transitions can generate a new neuronal regime of the stochastic bursting and transfer the system from order to chaos. A transient zone of values of noise intensity corresponding to the onset of noise-induced bursting and chaotization is localized by the stochastic sensitivity functions technique.