reservoir (version 1.1.5)

rrv: Reliability, resilience, and vulnerability analysis for water supply reservoirs

Description

Computes time-based, annual, and volumetric reliability, as well as resilience and dimensionless vulnerability for a single reservoir.

Usage

rrv(Q, target, capacity, double_cycle = FALSE, surface_area, max_depth, evap, plot = TRUE, S_initial = 1, policy)

Arguments

Q

vector or time series object. Net inflow totals to the reservoir. Recommended units: Mm^3 (Million cubic meters).

target

numerical. The target release constant. Recommended units: Mm^3 (Million cubic meters).

capacity

numerical. The reservoir capacity. Should be same volumetric unit as Q and R.

double_cycle

logical. If TRUE the input series will be replicated and placed end-to-end to double the simulation. (Recommended if the critical period occurs at the end of the recorded inflow time series)

surface_area

numerical. The reservoir water surface area at maximum capacity. Recommended units: km^2 (square kilometers).

max_depth

numerical. The maximum water depth of the reservoir at maximum capacity. If omitted, the depth-storage-area relationship will be estimated from surface area and capacity only. Recommended units: meters.

evap

vector or time series object of length Q, or a numerical constant. Evaporation from losses from reservoir surface. Varies with level if depth and surface_area parameters are specified. Recommended units: meters, or kg/m2 * 10 ^ -3.

plot

logical. If TRUE (the default) the storage behavior diagram and release time series are plotted.

S_initial

numeric. The initial storage as a ratio of capacity (0

policy

list. The output of the SDP function. If omitted, Standard Operating Policy is assumed.

Value

Returns reliability, resilience and vulnerability metrics based on supply deficits.

Examples

# Compare reliability, resilience and vulnerability for two operating policies (SOP and SDP).
rrv(resX$Q_Mm3, capacity = 20*resX$cap_Mm3, target = 0.95 * mean(resX$Q_Mm3))
pol_Markov <- sdp_supply(resX$Q_Mm3, capacity = 20 * resX$cap_Mm3,
target = 0.95 * mean(resX$Q_Mm3), Markov = TRUE)
rrv(resX$Q_Mm3, capacity = 20*resX$cap_Mm3, target = 0.95 * mean(resX$Q_Mm3), policy = pol_Markov)