Application of Various Hydrological Modeling Techniques and Methods in River Basin Management

Dear Colleagues,

Freshwater scarcity and freshwater mismanagement are increasingly common challenges that poses a serious threat to the socio-economic development of today’s world. Rising demand for water in different parts of the world necessitates better management of freshwater resources for agricultural purposes, irrigation, water resources management, and climate-feedback mechanisms. With advancements in modeling and computing techniques, hydrological models act as a boon for predicting extreme events like floods and droughts. Hydrological models (conceptual, semi-distributed, fully distributed) are valuable and informative tools in determining and finding different ways to combat environment-related problems and stabilize the water balance of the watershed. In addition, machine learning algorithms (MLAs) have great potential and have been promising in simulating hydrologic processes. For instance, streamflow estimation is crucial for efficient water management and decision-making in any given catchment, especially for drought and flood hydrology, crop modeling, flood forecasting, crop water requirement, major reservoir operations, freshwater allocation, as well as freshwater utilization and management. The complex nature of hydrological processes such as evapotranspiration, soil moisture, and baseflow among the land–water–plant ecosystems hinders the accurate streamflow estimation at the watershed scale. The present Special Issue of Water focuses on the developments in new techniques and perspectives in catchment modeling, the adaptation of remotely sensed data for hydrological modeling and the application of MLAs in predicting water balance components.

Dr. Ankur Srivastava
Dr. Venkat Sridhar
Dr. Nikul Kumari
Guest Editors

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