Create _streamflow_flow_indices.py

.gitignore

@@ -122,3 +122,6 @@ docs/variables.json
 
 # dask
 dask-worker-space
+
+# Apple
+.DS_Store

AUTHORS.rst

@@ -46,4 +46,5 @@ Contributors
 * Javier Diez-Sierra <[email protected]> `@JavierDiezSierra <https:/JavierDiezSierra>`_
 * Hui-Min Wang `@Hem-W <https:/Hem-W>`_
 * Adrien Lamarche `@LamAdr <https:/LamAdr>`_
+* Faisal Mahmood <[email protected]> <[email protected]> `@faimahsho <https:/faimahsho>`_
 * Sebastian Lehner <[email protected]> `@seblehner <https:/seblehner>`_

docs/references.bib

@@ -2153,7 +2153,39 @@ @article{droogers2002
  type = {Article}
 }
 
-@Article{robin_2019,
+@article{addor2018,
+ author = {Addor, Nans and Nearing, Grey and Prieto, Cristina and Newman, A. and Le Vine, Nataliya and Clark, Martyn},
+ year = {2018},
+ month = {11},
+ pages = {},
+ title = {A Ranking of Hydrological Signatures Based on Their Predictability in Space},
+ journal = {Water Resources Research},
+ doi = {10.1029/2018WR022606}
+}
+
+@article{Clausen2000,
+ author = {Clausen, B and Biggs, Barry},
+ year = {2000},
+ month = {11},
+ pages = {184-197},
+ title = {Flow variables for ecological studies in temperate streams: Groupings based on covariance},
+ volume = {237},
+ journal = {Journal of Hydrology},
+ doi = {10.1016/S0022-1694(00)00306-1}
+}
+
+@article{Olden2003,
+ author = {Olden, Julian and Poff, N.},
+ year = {2003},
+ month = {03},
+ pages = {101 - 121},
+ title = {Redundancy and the Choice of Hydrologic Indices for Characterizing Stream Flow Regimes},
+ volume = {19},
+ journal = {River Research and Applications},
+ doi = {10.1002/rra.700}
+}
+
+@article{robin_2019,
  author = {Robin, Y. and Vrac, M. and Naveau, P. and Yiou, P.},
  title = {Multivariate stochastic bias corrections with optimal transport},
  journal = {Hydrology and Earth System Sciences},

tests/test_hydrology.py

@@ -70,3 +70,33 @@ def test_simple(self, snw_series, pr_series):
  out = xci.melt_and_precip_max(snw, pr)
  np.testing.assert_array_equal(out, 2)
  assert out.units == "kg m-2"
+
+
+class TestFlowindex:
+ def test_simple(self, q_series):
+ a = np.ones(365 * 2) * 10
+ a[10:50] = 50
+ q = q_series(a)
+ out = xci.flow_index(q, 0.95)
+ np.testing.assert_array_equal(out, 5)
+
+
+class TestHighflowfrequency:
+ def test_simple(self, q_series):
+ a = np.zeros(365 * 2)
+ a[50:60] = 10
+ a[200:210] = 20
+ q = q_series(a)
+ out = xci.high_flow_frequency(q, 9, freq="YS")
+ np.testing.assert_array_equal(out, [20, 0])
+
+
+class TestLowflowfrequency:
+ def test_simple(self, q_series):
+ a = np.ones(365 * 2) * 10
+ a[50:60] = 1
+ a[200:210] = 1
+ q = q_series(a)
+ out = xci.low_flow_frequency(q, 0.2, freq="YS")
+
+ np.testing.assert_array_equal(out, [20, 0])

tests/test_land.py

@@ -66,3 +66,34 @@ def test_snw_storm_days(snw_series):
  snw = snw_series(a)
  out = land.snw_storm_days(snw, thresh="0.5 kg m-2")
  np.testing.assert_array_equal(out, [9, np.nan])
+
+
+def test_flow_index(q_series):
+ a = np.ones(365 * 2) * 10
+ a[10:50] = 50
+ q = q_series(a)
+
+ out = land.flow_index(q, p=0.95)
+ np.testing.assert_array_equal(out, 5)
+
+
+def test_high_flow_frequency(q_series):
+ a = np.zeros(366 * 2) * 10
+ a[50:60] = 10
+ a[200:210] = 20
+ q = q_series(a)
+ out = land.high_flow_frequency(
+ q,
+ threshold_factor=9,
+ freq="YS",
+ )
+ np.testing.assert_array_equal(out, [20, 0, np.nan])
+
+
+def test_low_flow_frequency(q_series):
+ a = np.ones(366 * 2) * 10
+ a[50:60] = 1
+ a[200:210] = 1
+ q = q_series(a)
+ out = land.low_flow_frequency(q, threshold_factor=0.2, freq="YS")
+ np.testing.assert_array_equal(out, [20, 0, np.nan])

xclim/data/fr.json

@@ -1392,6 +1392,24 @@
  "title": "Rayonnement de grandes longueurs d'onde ascendant",
  "abstract": "Calcul du rayonnement de grandes longueurs d'onde ascendant à partir du rayonnement de grandes longueurs d'onde net et descendant."
  },
+ "FLOW_INDEX": {
+ "long_name": "Indice de débit",
+ "description": "Le {p}e percentile du débit normalisé par le débit médian.",
+ "title": "Indice de débit",
+ "abstract": "Indice de débit, calculé comme le rapport entre un percentile donné du débit et la médiane."
+ },
+ "HIGH_FLOW_FREQUENCY": {
+ "long_name": "Fréquence des débits élevés",
+ "description": "Nombre de jours où le débit est {threshold_factor} fois supérieur à la médiane.",
+ "title": "Fréquence des débits élevés",
+ "abstract": "Fréquence des débits élevés, calculée comme le nombre de jours où le débit est supérieur à un multiple de la médiane."
+ },
+ "LOW_FLOW_FREQUENCY": {
+ "long_name": "Fréquence des débits faibles",
+ "description": "Nombre de jours où le débit est inférieur à une fraction ({threshold_factor}) de la moyenne.",
+ "title": "Fréquence des débits faibles",
+ "abstract": "Fréquence des débits faibles, calculée comme le nombre de jours où le débit est inférieur à une fraction de la moyenne."
+ },
  "CP": {
  "title": "Portions de froid (Chill Portions) selon le modèle Dynamique.",
  "abstract": "Les portions de froid (chill portions) sont une mesure du potentiel de débourrement de différentes récoltes basée sur le modèle Dynamique.",

xclim/indicators/land/_streamflow.py

@@ -3,14 +3,27 @@
 from __future__ import annotations
 
 from xclim.core.cfchecks import check_valid
-from xclim.core.indicator import ResamplingIndicator
+from xclim.core.indicator import (
+ ReducingIndicator,
+ ResamplingIndicator,
+)
 from xclim.core.units import declare_units
-from xclim.indices import base_flow_index, generic, rb_flashiness_index
+from xclim.indices import (
+ base_flow_index,
+ flow_index,
+ generic,
+ high_flow_frequency,
+ low_flow_frequency,
+ rb_flashiness_index,
+)
 
 __all__ = [
  "base_flow_index",
  "doy_qmax",
  "doy_qmin",
+ "flow_index",
+ "high_flow_frequency",
+ "low_flow_frequency",
  "rb_flashiness_index",
 ]
 
@@ -74,3 +87,37 @@ def cfcheck(q):
  compute=declare_units(da="[discharge]")(generic.select_resample_op),
  parameters={"op": generic.doymin, "out_units": None},
 )
+
+flow_index = ReducingIndicator(
+ realm="land",
+ context="hydro",
+ title="Flow index",
+ identifier="flow_index",
+ var_name="q_flow_index",
+ long_name="Flow index",
+ description="{p}th percentile normalized by the median flow.",
+ units="1",
+ compute=flow_index,
+)
+
+
+high_flow_frequency = Streamflow(
+ title="High flow frequency",
+ identifier="high_flow_frequency",
+ var_name="q_high_flow_frequency",
+ long_name="High flow frequency",
+ description="{freq} frequency of flows greater than {threshold_factor} times the median flow.",
+ units="days",
+ compute=high_flow_frequency,
+)
+
+
+low_flow_frequency = Streamflow(
+ title="Low flow frequency",
+ identifier="low_flow_frequency",
+ var_name="q_low_flow_frequency",
+ long_name="Low flow frequency",
+ description="{freq} frequency of flows smaller than a fraction ({threshold_factor}) of the mean flow.",
+ units="days",
+ compute=low_flow_frequency,
+)