An Evaluation of Image Velocimetry Techniques under Low Flow Conditions and High Seeding Densities Using Unmanned Aerial Systems
9 January 2020
Training Course “Monitoring Natural and Agricultural Ecosystems with Unmanned Aerial Systems (UAS)”
20 February 2020

Quantifying Long-term Land Surface and Root Zone Soil Moisture over Tibetan Plateau

It is crucial to monitor the dynamics of soil moisture over the Tibetan Plateau, while considering its important role in understanding the land-atmosphere interactions and their influences on climate systems (e.g., Eastern Asian Summer Monsoon). However, it is very challenging to have both the surface and root zone soil moisture (SSM and RZSM) over this area, especially the study of feedbacks between soil moisture and climate systems requires long-term (e.g., decadal) datasets. In this study, the SSM data from different sources (satellites, land data assimilation, and in-situ measurements) were blended while using triple collocation and least squares method with the constraint of in-situ data climatology. A depth scaling was performed based on the blended SSM product, using Cumulative Distribution Function (CDF) matching approach and simulation with Soil Moisture Analytical Relationship (SMAR) model, to estimate the RZSM. The final product is a set of long-term (~10yr) consistent SSM and RZSM product. The inter-comparison with other existing SSM and RZSM products demonstrates the credibility of the data blending procedure used in this study and the reliability of the CDF matching method and SMAR model in deriving the RZSM.

How to cite: Zhuang, R.; Zeng, Y.; Manfreda, S.; Su, Z. Quantifying Long-term Land Surface and Root Zone Soil Moisture over Tibetan Plateau. Remote Sens. 202012, 509. [pdf]

Salvatore Manfreda
Author: Salvatore Manfreda

Salvatore Manfreda is Full Professor of Water Management, Hydrology and Hydraulic Constructions at the University of Naples Federico II. He is currently the Chair of the COST Action HARMONIOUS and the Scientific Coordinator of the Research Grant aimed at the Development of the Flood Forecasting System of the Basilicata Region Civil Protection. He has broad interest on distributed modeling, flood risk, stochastic processes in hydrology and UAS-based monitoring.

Attachments

# File Description Date added Added by File size Downloads
1 pdf 2020_Zhuang_et_al_remotesensing 5 February 2020 18:13 Salvatore Manfreda 7 MB 96