Poster Presentation at the 5ᵗʰ Congress of Geographical Information Systems and Spatial Analysis in Agriculture and Environment
Spatially Explicit Digital Twin of the Greek Agro-Hydro-System DT-Agro This paper presents the DT-Agro project which aims to develop a spatially defined Digital Twin of the Greek agricultural and hydrological system that will function as an effective tool that will merge at various scales the main components of the water-soil-food-environment energy nexus system.
Presentation at the EGU 2024
SCS-CN parameter determination from observed rainfall runoff data. A critical review. Konstantinos Soulis, Stergia Palli Gravani, and Dionissios Kalivas Agricultural University of Athens, Natural Resources Management and Agricultural Engineering, Athens, Greece (soco@aua.gr) One the most difficult challenges in applied hydrology is predicting runoff in ungauged or poorly gauged watersheds. Thus, simple approaches for runoff estimation are especially useful in hydrologic applications. A simple, well established, and widely used technique for predicting the direct runoff depths of rainfall events is the Soil Conservation Service – Curve Number (SCS-CN) method. Due to its straightforward but well-proven approach, readily available and well documented environmental inputs, and incorporation of numerous variables influencing runoff generation into a single CN parameter, it quickly rose to prominence among engineers and practitioners. Tables can be used to identify the CN parameter values corresponding to prevailing soil, land cover and land management conditions. However, it is always better to estimate the CN value using observed rainfall-runoff (P-Q) data when available. Estimating appropriate CN values for additional soil – land cover conditions and additional regions is also critical for extending and updating the method’s documentation given that the SCS-CN approach is extremely sensitive to variations in the CN values.
