A New Weighting Scheme in Weighted Markov Model for Predicting the Probability of Drought Episodes

Table 4

One-month ahead probabilities under weighted Markov chain and Steady State behavior.

Stations	Statistics	ED	EW	MD	MW	NN	SD	SW
Skardu	Kappa	3.1794	0.9962	−0.5078	0.2383	−1.5348	−2.0740	Nil
	value	0.0015	0.3191	0.6116	0.8117	0.1248	0.0381	Nil
	Weights	0.3727	0.1168	0.0595	0.0279	0.1799	0.2431	Nil
	IRMWMC	Nil	0.0250	0.0702	0.1263	0.2483	0.5003	0.0299
	Steady states	Nil	0.0013	0.0034	0.2974	0.0563	0.6221	0.0195
Chilas	Kappa	1.6412	2.7045	0.5361	0.5355	−1.2023	0.1986	Nil
	value	0.1008	0.0068	0.5919	0.5923	0.2293	0.8426	Nil
	Weights	0.2407	0.3967	0.0786	0.0785	0.1763	0.0291	Nil
	IRMWMC	Nil	0.0004	0.1488	0.0445	0.4869	0.2616	0.0578
	Steady states	Nil	0.0025	0.1626	0.0560	0.4902	0.2646	0.0242
Cherat	Kappa	2.6746	−0.7443	0.0175	−0.0322	−0.6303	0.0663	0.0949
	value	0.0075	0.4567	0.9861	0.9743	0.5285	0.9471	0.9244
	Weights	0.6278	0.1747	0.0041	0.0076	0.1480	0.0156	0.0223
	IRMWMC	0.0241	0.0408	0.0162	0.1391	0.6948	0.0214	0.0637
	Steady states	0.0085	0.0938	0.0521	0.0948	0.6978	0.0128	0.0403
Peshawar	Kappa	1.6807	−1.9287	−0.0091	−1.1911	−1.9143	−0.1484	0.6617
	value	0.0928	0.0538	0.9928	0.2336	0.0556	0.8820	0.5082
	Weights	0.2231	0.2560	0.0012	0.1581	0.2541	0.0197	0.0878
	IRMWMC	0.0129	0.0641	0.0490	0.0838	0.6623	0.0594	0.0684
	Steady states	0.0189	0.0847	0.0782	0.0846	0.6649	0.0154	0.0532