Runoff Modelling under Climate Change

Dear Colleagues,

Runoff modeling under climate change involves predicting changes in the amount and timing of water flows in watersheds due to the impacts of climate change. It plays a crucial role in water resource management, flood forecasting, agricultural management, and the assessment of potential impacts on ecosystems and human populations. The goal of this Special Issue is to collect papers (original research articles and review papers) which provide insights on this topic. This Special Issue will welcome manuscripts that link the following themes:

• Data collection: Gathering historical climate and hydrological data, including precipitation, temperature, evapotranspiration, and streamflow records. This information is necessary for model calibration and validation;
• Climate change scenarios: Selecting climate change scenarios based on projections from global climate models (GCMs) or regional climate models (RCMs). These scenarios provide information on future changes in temperature and precipitation patterns;
• Hydrological model selection: Choosing an appropriate hydrological model that represents watershed physical processes, including rainfall–runoff relationships, infiltration, evapotranspiration, and flow routing. In this context, applications of artificial intelligence (AI) or machine learning (ML) models are more and more frequent;
• Model calibration: Calibrating hydrological models using historical data to ensure that it accurately represents observed streamflow patterns. This step involves adjusting model parameters to minimize the differences between simulated and observed streamflows;
• Climate change impact assessment: Applying the selected climate change scenarios to the calibrated hydrological model to simulate future runoff. This involves incorporating the projected changes in temperature and precipitation into the model inputs;
• Uncertainty analysis: Assessing the uncertainty associated with climate change projections and hydrological model outputs. Uncertainties arise from various sources, including the choice in climate models, emission scenarios, and inherent uncertainties in hydrological modeling;
• Model validation: Validating hydrological models by comparing simulated runoff under climate change scenarios with observed streamflow data for a specific period. This step helps evaluate the model performance and reliability in representing future runoff conditions;
• Impact assessment: Analyzing the modeled runoff data to understand the potential impacts of climate change on water resources. This information can guide adaptation strategies and water management decisions in various fields, such as civil protection and agriculture water management;
• Communicating results: Effective communication of the findings can help raise awareness and facilitate informed decisionmaking regarding water resource management under climate change.

We look forward to receiving your original research articles and reviews.

Dr. Carmelina Costanzo
Dr. Fabiola Gangi
Dr. Majid Niazkar
Guest Editors

Manuscript Submission Information

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• climate change
• runoff modeling
• urban flood hazard
• agriculture water management
• hydrological modeling
• machine learning