Data management plan (DMP) is a formal document that outlines how data are to be handled with respect to the FAIR (Findable, Accessible, Interoperable and Re‐usable) data principles and in […]
Deliverable 6.2: Data management plan Read More »
This deliverable describes the ethical management plan of the project. It outlines the guidelines and procedures to ensure ethical standards and integrity throughout the project. It includes a comprehensive ethical
Deliverable 7.2: Ethics management plan Read More »
Project power point template: https://transcendresearchproject.com/wp-content/uploads/2026/01/TRANSCEND-PPT.pptx
Abstract Groundwater pumping for irrigation has led to declining groundwater levels in agricultural areas around the world, including the U.S. High Plains Aquifer. Here, we used a process-based crop model,
Abstract This paper studies the environmental and socioeconomic performance and sustainability of wetland creation/restoration in agricultural watersheds under nonstationary climatic conditions. To this end, we develop a dynamic hydroeconomic modeling
Abstract Abatement costs (ACs) and transaction costs (TCs) are involved in motivating and implementing changes in public and private policies and programs. For example, Coase is best known for his
AC-TC Back in Black: Restoring Environmental Water in the Douro Basin, Spain Read More »
In the realm of climate change and water scarcity, accuracy of hydrological modeling becomes more important as it helps to understand how precipitation over a watershed turns into runoff in
Here you can find the recordings of the TRANSCEND webinar of September 5th 2025 TRANSCEND webinar The webinar featured a keynote presentation by Magdalena Rzeczkowska, Vice President for European Affairs
TRANSCEND Webinar “Advancing investment in water resilience” materials Read More »
Uncertainty assessment is crucial for rainfall-runoff simulations in a typical watershed. Generally, three major sources of uncertainty are input forcing, model structure, and model parameterization. The uncertainty of hydrological modelling
In the realm of climate predictions and extremes, machine learning (ML) techniques serve as versatile tools not only for capturing climate patterns but also for climate change impact assessments. Generally,
