Daily Rainfall - District Level
This dataset has data of Normal rainfall, Actual rainfall, Percentage deviation from Normal Rainfall and Rainfall Storage collected daily district wise data from the Indian Meteorological Department ranging from 2007 to till date. This has the data from the year 2007 to 2022.
Data Dictionary
| Column | Type | Label | Description |
|---|---|---|---|
| id | int4 | index | |
| date | date | Date | |
| state_code | text | State Code | |
| state_name | text | State Name | |
| district_code | text | District Code | |
| district_name | text | District Name | |
| actual | numeric | Actual Rainfall | |
| rfs | numeric | Rainfall Storage | |
| normal | numeric | Normal Rainfall | |
| deviation | numeric | Percentage Deviation from Normal |
Additional Information
| Field | Value |
|---|---|
| Data last updated | June 24, 2024 |
| Metadata last updated | June 25, 2024 |
| Created | June 24, 2024 |
| Format | CSV |
| License | Open Data Commons Attribution License |
| Additional info | nan |
| Data extraction page | https://indiawris.gov.in/wris/#/rainfall |
| Data insights | District-Level Rainfall Trends: Analysis of actual rainfall over the years can reveal patterns, seasonal variations, and long-term trends in rainfall for each district in Himachal Pradesh.Identification of Rainfall Anomalies: By comparing actual rainfall with normal rainfall, we can identify districts and periods with significant deviations, indicating droughts or unusually wet periods.Assessment of Rainfall Storage: Comparing rainfall storage data with actual rainfall can provide insights into the efficiency of water storage systems in each district.Impact of Climate Change: Long-term data analysis can help assess the impact of climate change on rainfall patterns at the district level in Himachal Pradesh.Agricultural Planning and Management: Insights from district-level rainfall patterns and deviations can aid in agricultural planning, helping farmers make informed decisions on crop selection and irrigation needs.Disaster Preparedness and Management: Understanding periods of excessive or deficient rainfall can help in disaster preparedness and management, such as planning for floods or droughts at the district level.Water Resource Management: The data can support effective water resource management, ensuring sustainable use of water resources in each district of Himachal Pradesh.Micro-Climate Analysis: Detailed district-wise data allows for micro-climate analysis, helping to understand local climate conditions and their variations within the state.Policy Formulation and Evaluation: Policymakers can use the data to formulate and evaluate policies related to water management, agriculture, and disaster management based on accurate and granular data.Historical Comparison: Comparing historical rainfall data with recent data can provide insights into how rainfall patterns have changed over time in each district. |
| Data last updated | 2023-05-01 00:00:00 |
| Data retreival date | 2023-05-01 00:00:00 |
| Datastore active | True |
| District no | 12 |
| Frequency | Daily |
| Granularity | District |
| Has views | True |
| Id | ccfddbe2-326d-46df-af6b-413232e9da15 |
| Idp ready | True |
| Methodology | Actual rainfall data used in this module are from different sources, i.e., IMD Grid (0.25 x 0.25-degree size), NRSC (0.05 X 0.05-degree size), APWRIMS (Station wise rainfall) & different state/ central agencies (Station wise rainfall). |
| No indicators | 4 |
| Package id | 4e75d3fb-2bec-4a0a-8144-ab73da1415cc |
| Position | 2 |
| Size | 4.9 MiB |
| Sku | wris-daily_rainfall_district-dt-dl-him |
| State | active |
| States uts no | 1 |
| Url type | upload |
| Years covered | 2009-2023 |
| Methodology | Actual rainfall data used in this module are from different sources, i.e., IMD Grid (0.25 x 0.25-degree size), NRSC (0.05 X 0.05-degree size), APWRIMS (Station wise rainfall) & different state/ central agencies (Station wise rainfall). |
| Similar Resources | |
| Granularity Level | District |
| Data Extraction Page | https://indiawris.gov.in/wris/#/rainfall |
| Data Retreival Date | 2023-05-01 00:00:00 |
| Data Last Updated | 2023-05-01 00:00:00 |
| Sku | wris-daily_rainfall_district-dt-dl-him |
| Dataset Frequency | Daily |
| Years Covered | 2009-2023 |
| No of States/UT(s) | 1 |
| No of Districts | 12 |
| No of Tehsils/blocks | |
| No of Gram Panchayats | |
| Additional Information | nan |
| Number of Indicators | 4 |
| Insights from the dataset | District-Level Rainfall Trends: Analysis of actual rainfall over the years can reveal patterns, seasonal variations, and long-term trends in rainfall for each district in Himachal Pradesh.Identification of Rainfall Anomalies: By comparing actual rainfall with normal rainfall, we can identify districts and periods with significant deviations, indicating droughts or unusually wet periods.Assessment of Rainfall Storage: Comparing rainfall storage data with actual rainfall can provide insights into the efficiency of water storage systems in each district.Impact of Climate Change: Long-term data analysis can help assess the impact of climate change on rainfall patterns at the district level in Himachal Pradesh.Agricultural Planning and Management: Insights from district-level rainfall patterns and deviations can aid in agricultural planning, helping farmers make informed decisions on crop selection and irrigation needs.Disaster Preparedness and Management: Understanding periods of excessive or deficient rainfall can help in disaster preparedness and management, such as planning for floods or droughts at the district level.Water Resource Management: The data can support effective water resource management, ensuring sustainable use of water resources in each district of Himachal Pradesh.Micro-Climate Analysis: Detailed district-wise data allows for micro-climate analysis, helping to understand local climate conditions and their variations within the state.Policy Formulation and Evaluation: Policymakers can use the data to formulate and evaluate policies related to water management, agriculture, and disaster management based on accurate and granular data.Historical Comparison: Comparing historical rainfall data with recent data can provide insights into how rainfall patterns have changed over time in each district. |
| IDP Ready | Yes |