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<br />- <br />I <br /> <br />I <br /> <br />I <br /> <br />I <br /> <br />I <br /> <br />I <br /> <br />I <br /> <br />I <br /> <br />I <br /> <br />I <br /> <br />I <br /> <br />I <br /> <br />I <br /> <br />I <br />I <br />I <br /> <br /> <br />I <br /> <br />I <br /> <br />I <br /> <br />The general equation for error propagation of a continuous ~ystem <br /> <br />between measurements is <br /> <br />l' l' <br />Prt} = FP(t} + NtJ, + CQc- <br /> <br />(18) <br /> <br />where P(tJ is an n x n matrL~ of error covariances, and Q is a vector of <br /> <br />spectral densities of the random forcing functions, ~(tJ. The discharge- <br /> <br />computation problem has a single forcing function; therefore Q is a scalar, <br /> <br />denoted q. The elements of the matrLx, P(tJ, are as follows: Pll(tJ is <br /> <br />the error variance of xl(tJ, PZZ(tJ is the error variance of xZ(tJ, and <br /> <br />PlZ(t) = P21(tJ is the covariance between errors in xl(tJ and x2(tJ. <br /> <br />As discussed earlier, discharge measurements are considered <br /> <br />to be instantaneous and are obtained at discrete times only. Therefore, <br /> <br />the amount of information about xl(tJ and'x2(tJ changes abruptly upon <br /> <br />completion of a discharge measurement. This abrupt change is measured by a <br /> <br />change in the covariance matrix, P(t}. Denote the value of P(t} just ,prior <br /> <br />to a measurement at time t by PCt-) and the value of P(t) just after the <br />+ + <br />measurement as P(t). Gelb (1974, p. 109-110) expresses pet ) as <br /> <br />P(t+) = (I - X(t)H] 2(t-) <br /> <br />(19) <br /> <br />where I is an identity matrix and K(t) is known as the Kalman gain matrix and <br /> <br />is defined <br /> <br />_ _ 1'. _ l' -1 <br />K(t) = dt )lr (HP(t )Ir + iI] <br /> <br />(ZO) <br /> <br />where iI is the covariance matrix of measurement errors, the superscript T <br /> <br />indicates a matrL~ transpose, and the superscript -1 indicates a matru{ <br /> <br />inversion. In the discharge computation problem, the measurements pertain <br /> <br />only to x2(t), not xl (t), and R is thus a scalar, denoted!', that specifies <br /> <br />the variance of the measurement error. The combination of equations 15, 19, <br /> <br />and ZO results in <br /> <br />24 <br /> <br /> <br />- <br />