Soil Moisture Data Assimilation to Estimate Irrigation Water Use.

ABSTRACT: Knowledge of irrigation is essential to support food security, manage depleting water resources, and comprehensively understand the global water and energy cycles. Despite the importance of understanding irrigation, little consistent information exists on the amount of water that is applied for irrigation. In this study, we develop and evaluate a new method to predict daily to seasonal irrigation magnitude using a particle batch smoother data assimilation approach, where land surface model soil moisture is applied in different configurations to understand how characteristics of remotely sensed soil moisture may impact the performance of the method. The study employs a suite of synthetic data assimilation experiments, allowing for systematic diagnosis of known error sources. Assimilation of

SUBMITTER: Abolafia-Rosenzweig R 

PROVIDER: S-EPMC6988458 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature