The Community Water Model (CWatM; https://cwatm.iiasa.ac.at/) is an advanced, open-source hydrology model that is designed to simulate and analyze the terrestrial water cycle on both regional and global scales (https://github.com/iiasa/CWatM). It is especially well-suited for addressing hydrological and climate-related research questions, with an emphasis on understanding the interplay between water systems and human activities. One of the standout features of CWatM is its ability to incorporate human water use, including water demands from households, industries, and agriculture. Unlike many traditional hydrological models, CWatM explicitly models irrigation, domestic, and industrial water use, making it a highly valuable tool for studying the impacts of human activities on hydrological systems.
CWatM’s comprehensive modeling capabilities include groundwater, surface water, streamflow, and even fossil groundwater, providing a holistic view of the hydrological cycle. It integrates multiple processes such as precipitation, evaporation, infiltration, runoff, and the movement of water through both surface and subsurface pathways. By incorporating human interventions—such as groundwater extraction, water withdrawals, and irrigation—it offers a more realistic representation of modern hydrology where anthropogenic impacts are a dominant force. This approach is particularly critical in the current context of climate change, which is coupled with growing demands for freshwater resources. The model’s ability to represent the full range of hydrological components and human interactions makes it a powerful tool for assessing water availability, predicting water scarcity, and understanding the dynamics of water stress.
One of the key benefits of CWatM over other hydrological models is its seamless integration of human and natural components of the water cycle. While many hydrology models focus primarily on natural processes, CWatM explicitly includes human activities that impact water availability, allowing for a more realistic and detailed representation of the system. This results in improved accuracy, particularly in scenarios involving anthropogenic influences such as agricultural expansion, urbanization, and industrial water use. The model also allows for simulations that assess the effectiveness of water management interventions, which is valuable for decision-makers working on sustainable water resource planning and policy development.
CWatM is written in Python, which enhances its usability and adaptability for researchers. Python’s versatility and its extensive libraries for data handling, analysis, and visualization make CWatM accessible for a wide range of applications. The model’s open-source nature promotes collaboration within the scientific community, fostering the development of new features and improvements that further benefit research into hydrology and climate. By providing an open and flexible platform, CWatM empowers researchers to customize the model to fit specific study areas, incorporate new data sources, and address unique water-related challenges.
In ALICE-LAB, we utilize CWatM to differentiate between the impacts of climate variability and human activities on water resources, which proves to be particularly useful for developing country-level strategic plans. By using CWatM, we can assess both natural hydrological changes and the influence of human activities such as irrigation and industrial water use. This distinction is essential in understanding the underlying causes of changes in water availability, helping policymakers create informed, targeted strategies for water resource management.
Our research has highlighted that without accounting for human impacts, planned water allocations tend to be underestimated, potentially leading to unrealistic or insufficient water supply strategies. This finding emphasizes the importance of models like CWatM, which integrate anthropogenic factors to produce more accurate assessments. In addition to differentiating impacts, we also investigate water resource availability under different climate scenarios. These insights are critical for informing authorities about potential risks and challenges under future climate conditions, enabling proactive and adaptive planning to ensure sustainable water management in the face of changing environmental conditions.
ALICE-LAB: Asian Land Information for Climate and Environmental Research Laboratory
The Noah-MP LSM, developed by NCAR, simulates complex land surface processes like soil moisture, snowpack, and evapotranspiration, vital for hydrology and climate studies. With customizable modules, it supports diverse scales and applications, enabling ALICE-LAB to conduct high-resolution simulations on global water dynamics and long-term climate impacts.
PCR-GLOBWB, developed by Utrecht University, models global water cycles and includes human water use, making it invaluable for studying water scarcity and sustainability. ALICE-LAB leverages this model with GRACE satellite data to assess global water resources and inform climate resilience strategies.