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A first order Markov chain model has been fitted to daily  rainfall data of tbe monsoon months in the Delhi region. Conditional probabilities, length of dry spells for different cumulative probabilities with particular reference to  developmental stages of bajra crop in the kharif season have been computed and illustrated by means of   nomograms.

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A profile moisture model has been developed to evaluate the seasonal soil moisture fluctuation with respect to soil characteristics and land use pattern under irrigated and rainfed conditions in an area of agricultural fields. Daily rainfall and irrigation were used as model inputs. Instantaneous uniform redistribution of soil moisture in the effective root zone and negligible contribution of soil water through upward flux were assumed. An empirical model was used to determine the root depth. Runoff was estimated from rainfall data using the curve number technique of the Soil Conservation Service adapted for conditions in India and combined with a soil moisture–accounting procedure. The modified Penman method was used to calculate the reference evapotranspiration. To calculate the crop coefficient (Kc), regression equations were developed taking Kc as the dependent variable on normalized difference vegetation index. This model was very easy to parameterize and required a minimum soil data set of field capacity and permanent wilting point. To evaluate model performance, observed values of soil water were taken for wheat (Triticum aestivum L.) in the Mehrauli (sandy loam to loam texture) and Daryapur (loamy texture) soil series under irrigated conditions and for gram (Cicer arietinum L.) in the Jagat (clay loam texture) and Holambi (loam texture) soil series under rainfed conditions in Delhi. The r2 and D index between observed and predicted soil water values varied between 0.67 and 0.77 and 0.83 and 0.93, respectively.

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