2 results — Climate Insights Directory

Search syntax

intitle:: The document title intitle:"climate education"
ispublisher:: The publishing organization ispublisher:CAPE
insummary:: Summary and key findings insummary:"conflict of interest"
hasconcept:: Climate tags, frame/perspective and analysis type hasconcept:"Climate Justice"
geography:: Regions the document covers or discusses geography:Canada
doctype:: Document type doctype:report
lang:: Document language, as an ISO code lang:fr
cidid:: One record, by its directory id cidid:cape-ca-b76f0c

2 results

DateDocumentOrganization and typeRegions

27 September 2023
Predicting agricultural drought indicators
This research paper evaluates the effectiveness of various machine learning and deep learning models in predicting agricultural drought indicators, specifically soil moisture and the Palmer drought severity index (PDSI), across Sweden.
AI-generated
This summary is written by a language model reading the source document. It is not the publisher's words and is not a substitute for the original.
Themes: agricultural drought soil moisture palmer drought severity index (pdsi)machine learning deep learning
Stockholm Environment Institute
Document type: Research paper
Regions: Sweden
Using a Deep Learning Framework to Forecast Reservoir Water Availability in India
This research paper presents a deep learning framework developed by the World Resources Institute (WRI) to forecast reservoir water volumes in India over a 90-day period to mitigate risks of water-driven power outages.
AI-generated
This summary is written by a language model reading the source document. It is not the publisher's words and is not a substitute for the original.
Themes: climate change water stress energy transition power outages deep learning
World Resources Institute
Document type: Research paper
Regions: India

Showing 1–2 of 2 documents