In a groundbreaking development for hydrological studies, researchers have introduced CAMELS-IND, a comprehensive dataset that promises to revolutionize our understanding of water management and hydrological extremes in Peninsular India. The dataset, a collaborative effort led by N. K. Mangukiya from the Department of Hydrology at the Indian Institute of Technology Roorkee, offers an unprecedented level of detail and accessibility for hydrometeorological data. This initiative could significantly impact the energy sector, particularly in regions where water resources are crucial for power generation.
CAMELS-IND, which stands for Catchment Attributes and MEteorology for Large-sample Studies – India, covers 472 catchments across 15 interstate river basins defined by the Central Water Commission (CWC). The dataset includes hydrometeorological time series and catchment attributes for a 41-year period from 1980 to 2020. Notably, 228 of these catchments have observed streamflow data available for over 30% of this period. This extensive dataset is poised to fill critical gaps in our knowledge of hydrological processes in India, an area that has historically lacked reliable and accessible data.
The dataset includes a wide array of meteorological forcings, such as precipitation, temperature, radiation flux, wind components, relative humidity, evaporation rates, and soil moisture, among others. Additionally, CAMELS-IND incorporates catchment attributes representing human influences, including the number of dams, their utilization, population density, and changes in land cover. This holistic approach allows researchers to study the interplay between natural and human-induced factors on catchment hydrology.
One of the most exciting aspects of CAMELS-IND is its potential to support the development and testing of new hydrological models. The dataset includes predicted streamflow time series from a regionally trained long short-term memory (LSTM)-based hydrological model, which can fill gaps in observed streamflow data and serve as a benchmark for future models. According to Mangukiya, “This dataset will provide a strong foundation for a community-led effort toward gaining new hydrological insights from hydrologically distinct Indian catchments and solving pertinent issues related to water management, quantification and risk assessment of hydrologic extremes, and climate change impact assessment of catchments across India.”
The implications for the energy sector are profound. Water is a critical resource for power generation, particularly in hydroelectric plants, which rely on consistent water flow. Accurate hydrological data can help energy companies optimize their operations, predict water availability, and plan for future infrastructure needs. Moreover, understanding the impacts of climate change on water resources can inform long-term energy strategies, ensuring that power generation remains reliable and sustainable.
CAMELS-IND follows the standards of previously developed CAMELS datasets for countries like the USA, Chile, Brazil, Great Britain, Australia, Switzerland, and Germany. This consistency allows for comparative studies and the inclusion of Indian catchments in global hydrological research. The dataset is available at https://doi.org/10.5281/zenodo.14005378, published in Earth System Science Data, an open-access journal that translates to “Earth System Science Data” in English.
As we look to the future, CAMELS-IND has the potential to shape significant developments in hydrological science and water management. By providing a comprehensive and accessible dataset, researchers and policymakers can make more informed decisions, leading to better water resource management and more resilient infrastructure. This initiative marks a pivotal moment in the field, paving the way for innovative solutions to some of the most pressing challenges in hydrology and energy.