Water is the key of development and stability of any region. Under climate change condition, water systems are less reliable and more vulnerable. In this study, performance of Saline reservoir in Odisha, India has been evaluated under the climate change condition. The study mainly focused on the trend analysis for identified the temporal changes in precipitation and inflow time series using Mann-Kendall test, quantification of inflows to reservoir using ARNO model and performance evaluation of reservoir using WEAP model under climate change condition. In the results, it has been observed that there is no significant trend for annual, seasonal and for any monthly rainfall. Variation in precipitation shows that rainy days are decreasing whereas number of intense rainy days ([100 mm) are increasing. A significant rising trend with test statistic value of ?3.18 is observed for daily inflow series at 95 % confidence level. Evaluation of inflow to reservoir, ARNO model shows that the change in simulated flow is directly proportional to the change in rainfall. In order to 25 % Change, decrease or increase in rainfall amount resulted in equal amount of decrease or increase in the inflow. Performance evaluation of reservoir using WEAP model shows that if inflows reduced by 20 % there would be a decrease in supply reliability and it would not be possible to increase supplies. Reducing live storage by 10 % influence supply delivered in May and June, but again has little impact on the rest of the year.
In the present study, an attempt has been made to analyse the variability and trends in annual and seasonal rainfall over the Eastern Ganga Canal command area, India. To determine the trend in annual/seasonal rainfall and rainy days, the non‐parametric Mann−Kendall test and Sen's slope method were used over daily gridded rainfall for the time period 1901–2012. The results of the trend analysis revealed a decreasing trend in annual and monsoon rainfall in the range 18.5−61.7 and 19.4−56.7 mm/decade, respectively. For annual and monsoon rainy days, the results demonstrated a decreasing trend which varied from 1.8 to 2.9 and 1.4 to 2.2 days/decade, respectively, and an increasing trend in the range 0.2−1.4 and 1.0 days/decade, respectively. A variability analysis was performed to highlight the need for selecting an appropriate confidence level in trend analysis. It was observed that the grids showing a statistically non‐significant trend at the 95% confidence level exhibit a statistically significant trend at lower confidence levels. An analysis of dry and wet years on an annual scale revealed that the chances of occurrence of a wet year are more in comparison with the chances of occurrence of a dry year in the command area by a ratio of 14:13. However, data from the last one and a half decades has a contradictory trend with higher chances of occurrence of a dry year to very minimal chances of occurrence of a wet year. Dependable rainfall at various probability levels was estimated using a gamma distribution function. It was observed that the 75% dependable weighted annual and seasonal rainfall over the command area (985.48 and 727.54 mm) was significantly different with respect to the climatic mean weighted annual and seasonal rainfall against the weighted mean annual and seasonal rainfall (1,165.93 and 901.95 mm).
1. I n t r o d u c t i o n : The BAIRSTOW Process The basic idea for finding the roots of real polynomials by finding a quadratic factor makes use of the following identity.@ + a, f l -1 + a, @-2 + . . . + an (9 + p 5 + q) ( f l -2 + b, ~n -3 + + 4 f l -4 + . . . + bn-2) + R@, 4 ) z + S(p7 q ) . B~~RSTOW method [2] consists in solving the systemStarting with the initial approximation (p, q), the correctioy A p and d q are found so that Expanding in T A Y~R series and truncating after the first order terms, we get R (P + LIP, P + Aq) = 0 9 (P + AP, q + Aq) = 0 * (2) R(P, q) -S(P, q ) -I JTp All + Sq Aq = 0 9 11, AP + 1 1 9 4 = 0 3(3)where R,, S, and R,, S, designate partial order derivates with respect to p and q. This is regarded as a linear system of equations for A p and Aq and when this system has been solved the procedure is repeated with the corrected values @, , q,) wherepIFp+ A p and q, = q + Aq. Similarly the subsequent approxlmatiom (pi, 4.1) are found out. Coefficients b,, 4,. . . , bn-2; R and S are computed from ( 1 ) by comparison.where n represents the degree of the polynomial with b, , = 1 and b-, = 0 .We get and bn = anp bn-1q bn-2 = Sp bn-1 Thus beginning with arbitrary values p and q, (3), (4) and ( 5 ) can be used to define an iterative process for getting a quadratic factor. This is usually known m LIN's method [3] which was extended and studied by FRIEDMAN [4] and LUKE and UPFORD [B]. The convergence properties have not been fully established, but the method is often slowly convergent. The theorem of KANTOKOVICII [l] gives conditions on R and S and on the starting values p , q which ensure convergence. The verification of these conditions is not computationally feasible, but the method is usually quadratically convergent. bk = akp bk-1 -4 bk-2 (k = 1,2, . . . , n) , (4) bn-1 = an-1 -p bn-2 -q bn-3 = R R = bn-1, S = bn + p bn-1.( 5 ) Higher Order B A~R S T O WProcess We introduce the following notations bk = CO, k where n is the degree of the polynomial. (4) and (5) are transformed to (k = 1,2,. . . , n), CO,k = akp CO,k-1 -qC0,k-2 c0,o = 1, Go, -1 = 0 R = C o , n -l , S = C o , n + p C o , n -~. (6)(k = 1,2, . . . , n) I n general when the process considers the effect of all the terms (say upto m-th order) in the expansion of (2) by means of TAYLOR series, we get the following recurrence relation ( k = 1 , 2 ,..., m -T ; T = l , 2 ,...)The partial derivatives upto m-th order are computed from the following recurrence relations R,(9) AP = pi -P = A,@, q) + A~( P , q) + . . * + 4) A q = 41 -4 = B~( P , 4) + B~P , q) + . . . + Btnb 4) where At and Bt (i = 1,2, . . . , m) are increment functions of the first, 2-nd and m-th order respectively. The equations (2), (7), (8) and (9) yield to the following system of equations which will determine the increment functions At and Bi. RpAt+Rg&+Ri=O, S p A( + Sq & + 8 1 = 0 9 where and R , = R ,
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