hydroeval_release_scenarios <- local({
  baseline_observed <- c(10, 20, 30, 40)
  positive_reference_simulated <- c(12, 18, 33, 39)

  list(
    positive_reference = list(
      observed = baseline_observed,
      simulated = positive_reference_simulated
    ),
    perfect_fit = list(
      observed = baseline_observed,
      simulated = baseline_observed
    ),
    near_perfect = list(
      observed = baseline_observed,
      simulated = c(10, 19, 31, 40)
    ),
    additive_overestimation = list(
      observed = baseline_observed,
      simulated = baseline_observed + 5
    ),
    additive_underestimation = list(
      observed = baseline_observed,
      simulated = baseline_observed - 5
    ),
    multiplicative_scaling_bias = list(
      observed = baseline_observed,
      simulated = baseline_observed * 1.25
    ),
    variance_distortion_same_mean = list(
      observed = baseline_observed,
      simulated = c(5, 25, 25, 45)
    ),
    high_correlation_imperfect_fit = list(
      observed = c(10, 20, 30, 40, 50),
      simulated = c(13, 21, 29, 42, 54)
    ),
    ranking_degradation = list(
      observed = c(10, 20, 30, 40, 50),
      simulated = c(11, 19, 31, 45, 42)
    ),
    outlier_contamination = list(
      observed = baseline_observed,
      simulated = c(10, 20, 30, 70)
    ),
    low_flow_zero_heavy = list(
      observed = c(0, 0.5, 1, 2),
      simulated = c(0, 0.25, 1.5, 1.5)
    ),
    negative_values = list(
      observed = c(-3, -1, 2, 4),
      simulated = c(-2, -2, 1, 5)
    ),
    missing_omit = list(
      observed = c(10, NA, 30, 40),
      simulated = c(12, 99, 33, 39),
      kept_observed = c(10, 30, 40),
      kept_simulated = c(12, 33, 39)
    ),
    insufficient_after_omit = list(
      observed = c(10, NA, NA),
      simulated = c(12, NA, 11)
    ),
    constant_observed = list(
      observed = c(5, 5, 5, 5),
      simulated = c(4, 5, 6, 7)
    ),
    constant_simulated = list(
      observed = baseline_observed,
      simulated = c(25, 25, 25, 25)
    ),
    zero_observed_sum = list(
      observed = c(-4, -1, 1, 4),
      simulated = c(-3, -2, 2, 3)
    ),
    zero_absolute_observed_sum = list(
      observed = c(0, 0, 0, 0),
      simulated = c(0, 1, -1, 0)
    ),
    zero_observed_mean = list(
      observed = c(-2, -1, 1, 2),
      simulated = c(-1, 0, 2, 3)
    ),
    zero_simulated_mean = list(
      observed = c(1, 2, 3, 4),
      simulated = c(-2, -1, 1, 2)
    ),
    zero_simulated_mean_kge_2009_valid = list(
      observed = c(1, 2, 3),
      simulated = c(-1, 0, 1)
    ),
    single_point = list(
      observed = 10,
      simulated = 12
    ),
    large_magnitude = list(
      observed = baseline_observed * 1e7,
      simulated = positive_reference_simulated * 1e7
    ),
    very_small_magnitude = list(
      observed = baseline_observed * 1e-9,
      simulated = positive_reference_simulated * 1e-9
    ),
    calibration_validation_test = list(
      calibration = list(
        obs = baseline_observed,
        sim = c(10, 19, 31, 40)
      ),
      validation = list(
        obs = baseline_observed,
        sim = c(12, 18, 33, 39)
      ),
      test = list(
        obs = baseline_observed,
        sim = c(15, 15, 35, 45)
      )
    ),
    baseline_calibrated_stressed = list(
      baseline = list(
        obs = baseline_observed,
        sim = c(14, 18, 31, 37)
      ),
      calibrated = list(
        obs = baseline_observed,
        sim = c(10, 19, 31, 40)
      ),
      stressed = list(
        obs = baseline_observed,
        sim = c(18, 15, 38, 48)
      )
    )
  )
})

hydroeval_release_scenario <- function(name) {
  scenario <- hydroeval_release_scenarios[[name]]

  if (is.null(scenario)) {
    stop(sprintf("Unknown release-hardening scenario `%s`.", name), call. = FALSE)
  }

  scenario
}

hydroeval_release_dataset_collection <- function(name) {
  hydroeval_release_scenario(name)
}