model
{
	Tau.noninformative <- 1.0E-3
	Hyper.gamma <- 1.0E-2

	# ion concentration
	ion[N.sample + 1] <- 0 # river head
	for (i in 1:N.sample) {
		ion[i] <- exp(log.ion[i])
	}
	for (i in 1:N.sample) {
		IonC[i] ~ dnorm(ionc[i], tau[1]) # observation
		ionc[i] <- exp(log.ion[i] - log(Wf[i]))
		log.ion[i] ~ dnorm(mean.log.ion[i], tau[2])
		mean.log.ion[i] <- log(ion[Upper[i]] + d.ion[i])
		d.ion[i] <- D.wf[i] * exp(
			alpha
			+ beta1 * LuLc[St[i]]
			+ beta2[Date[i]]
		)
	}

	alpha ~ dnorm(0.0, Tau.noninformative)
	beta1 ~ dnorm(0.0, Tau.noninformative)
	for (k in 1:N.date) {
		beta2[k] ~ dnorm(0.0, tau[3])
	}

	# tau = 1 / variance
	for (k in 1:N.tau) {
		tau[k] ~ dgamma(Hyper.gamma, Hyper.gamma)
	}
}