It is suggested that simulation of individual storm events be included in MOHS to improve the estimates of streamflow. The synthesis of the hydrologic cycle to obtain optimal use of water resources is extremely difficult due to the complex interrelationships between meteorological and hydrological variables. Past research has concentrated on the statistical analysis of surface runoff records used as stochastic input into models which simulate streamflow records for periods of days, months, and years. Streamflow is a variable and erratic parameter. A forecast of runoff will include a certain amount of error or imply some uncertainty as to the accuracy of the forecast.
Surface runoff is the result of precipitation and antecedent hydrologic conditions in a river basin.
Accurate forecasts of precipitation and temperature, from which evaporation, evapotranspiration, soil-moisture conditions, and surface runoff can be determined, could give better results than using statistical properties of the streamflow records. Any error, of course, in the meteorological forecasts will produce error in the resulting streamflow amounts. Stochastic meteorological forecasts were considered to improve the application of simulation methods for periods of 15 days to one month. Instead of generating completely random sequences of precipitation and temperature values by Monte Carlo techniques, the range of the variables was constrained by the 30-day meteorological forecasts. For long-term information on the variability of the weather, climatology must be used.