Datasets

Check out our Zenodo Community to find out different datasets developed by our team:

https://zenodo.org/communities/ehc_iitr/records 

CAMELS-INDIA

CAMELS-INDIA: hydrometeorological time series and catchment attributes for 472 catchments in Peninsular India

We introduce CAMELS-INDIA (Catchment Attributes and MEteorology for Large-sample Studies – India), which provides daily meteorological time series, available observed and LSTM-based predicted streamflow, and static catchment attributes for 472 catchments in peninsular India, to foster large-sample hydrological studies in India and promote the inclusion of Indian catchments in global hydrological research.

The data set covers 41 years of data between 1st January 1980 and 31st December 2020 for each catchments: daily time series of available streamflow observations, meteorological data such as precipitation, air temperature, solar radiation, relative humidity, wind speed, potential and actual evapotranspiration, and soil moisture. Additionally, CAMELS-INDIA includes regionally trained LSTM-model predicted streamflow for all 472 catchments. The static catchment attributes includes location and topography, climate, hydrological signatures, land-use, land cover, soil, geology, and anthropogenic influences.

Link: CAMELS-IND 

NPP-DATA

Monthly, Seasonal and Yearly Net Primary Productivity (NPP) data of India from 2003-2020 modelled using the CASA model

We estimated monthly Net Primary Productivity (NPP) at 1km spatial resolution for India using the Carnegie-Ames-Stanford Approach (CASA) Model. The CASA is a light use efficiency (LUE) based model that simulates NPP driven by remote sensing and meteorological data inputs. NPP is calculated as a product of the light use efficiency (LUE) and absorbed photosynthetically active radiation (APAR). The seasonal and annual data are prepared by aggregating the monthly data. The India Meteorological Department (IMD) recognizes four seasons in India based on climate conditions. The four seasons are defined as Winter (January-February), Pre-monsoon (March-May), Monsoon (June-September), and Post-monsoon (October-December). The seasonal data is prepared according to the above classification of the seasons.

Link to data: https://zenodo.org/records/13740397 

Link to manuscript preprint: Manuscript is currently under-review.