Merge pull request #325 from OCHA-DAP/tcd-quick-update

TCD biomass update
OCHA-DAP · Oct 12, 2023 · d17031d · d17031d
2 parents 341cf5c + 6aab748
commit d17031d
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diff --git a/analyses/ner/README.md b/analyses/ner/README.md
@@ -2,9 +2,11 @@
 
 [![Generic badge](https://img.shields.io/badge/STATUS-ENDORSED-%231EBFB3)](https://shields.io/)
 
-Endorsed in 2021. Did not activate in 2021.
-Last updated: Sep 2021
+Endorsed in Dec 2021 and July 2022. The observational trigger was met and the framework was activated in August 2022.
+Last updated: Sep 2022
 
 ## Background information
 
-Anticipatory action in Niger aims to preemptively respond to drought. The trigger was defined to reflect a 1 in 3 year event. It is evaluated once monthly between January and June, inclusively. It is monitored by IRI/WFP (through their tool Maproom) and uses analysis developed specifically for this purpose. CHD provided guidance but did not perform data analysis for this project. Forecasts, groundtruth dataset, impact data: presented by the IRI/WFP collaboration.
+Anticipatory action in Niger aims to preemptively respond to drought. The triggers are precipitation-focused and were defined to reflect a 1 in 3 year event. A forecast-based trigger (forecasting July-August-September) is evaluated once monthly between January and June, inclusively. An observational trigger is evaluated once in early August based on the SPI for June - July.
+
+It is monitored by IRI (through their tool Maproom) with data shared by the Direction de la météorologie nationale du Niger. and uses forecasts developed specifically for this purpose. CHD provided guidance but did not perform data analysis for this project. Forecasts, groundtruth dataset, impact data: provided by a collaboration between Direction de la météorologie nationale, AGRHYMET, IRI, WFP.
diff --git a/analyses/tcd/notebooks/observations/tcd_biomasse.md b/analyses/tcd/notebooks/observations/tcd_biomasse.md
@@ -7,7 +7,8 @@
 from pathlib import Path
 import sys
 import os
-
+# quick fix for changing env variables from AA to OAP
+os.environ["AA_DATA_DIR"] = os.environ["OAP_DATA_DIR"]
 import geopandas as gpd
 
 path_mod = f"{Path(os.path.dirname(os.path.abspath(''))).parents[2]}/"
@@ -30,12 +31,20 @@ import src.indicators.drought.biomasse as bm
 This is just the code for downloading and procesing the Biomasse data, then aggregating to a specific set of admin codes (our region of interest in Chad. Additional analysis and exploration is done within `biomasse_exploration.R`.
 
 ```python
-# bm.download_dmp()
-# dmp = bm.calculate_biomasse(admin_level="ADM2")
+bm.download_dmp()
+dmp = bm.calculate_biomasse(admin_level="ADM2")
 gdf_adm2 = gpd.read_file(adm2_bound_path)
 gdf_reg = gdf_adm2[gdf_adm2.area_of_interest == True]
 bm_df = bm.aggregate_biomasse(
     admin_pcodes = gdf_reg.admin2Pcod,
     iso3 = "tcd"
 )
 ```
+
+We are activating if the `biomasse_anomaly` is below 80 in the 24th dekad of 2023. We can quickly check that below.
+
+```python
+bm_df
+```
+
+
diff --git a/src/indicators/drought/biomasse.py b/src/indicators/drought/biomasse.py
@@ -35,11 +35,11 @@
 from src.utils_general.utils import download_ftp
 
 _BASE_URL = (
-    "http://80.69.76.253:8080/geoserver"
+    "http://213.206.230.89:8080/geoserver"
     "/Biomass/wfs?&REQUEST="
     "GetFeature&SERVICE=wfs&VERSION=1.1.0"
-    "&TYPENAME=WA_DMP_{admin_level}_ef_v0&"
-    "outputformat=CSV&srsName=EPSG:4326"
+    "&TYPENAME=WA_DMP_{admin_level}_ef_v1&"
+    "outputformat=csv&srsName=EPSG:4326"
 )
 
 _RAW_FILENAME = "WA_DMP_{admin_level}_ef_v0.csv"
@@ -78,7 +78,7 @@ def download_dmp(admin_level: AdminArgument = "ADM2") -> None:
     None
     """
     _check_admin(admin_level)
-    url = _BASE_URL.format(admin=admin_level)
+    url = _BASE_URL.format(admin_level=admin_level)
     raw_path = _get_raw_path(admin_level)
     download_ftp(url=url, save_path=raw_path)