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ARS Home » Plains Area » Fort Collins, Colorado » Center for Agricultural Resources Research » Water Management and Systems Research » Research » Research Project #435568

Research Project: Remote Sensing and Spatial Simulation of Agricultural Watersheds

Location: Water Management and Systems Research

Project Number: 3012-13660-010-001-N
Project Type: Non-Funded Cooperative Agreement

Start Date: Sep 1, 2019
End Date: Aug 31, 2024

Objective:
The overall goal of this project is to identify and assess key ecosystem services that are affected by changes in water availability, land use, agricultural management practices, and climate. Interactions between processes will be simulated in agricultural watersheds where water, plant, soil, and terrain variables are measured across multiple scales in space and time in both cropland and grassland ecosystems. More specific objectives are: 1. Quantify fluxes of water and associated nutrients (N and P) and sediment, from field to watershed scales in response to water availability, land use, management practices, and climate. Watersheds in China will include the Hetao Irrigation District (Yellow River) and rangeland watersheds flowing into Hulun Lake. 2. Develop methods to quantify evapotranspiration (ET) using remote sensing technology in cropland and glassland in the Hetao Irrigation District.

Approach:
Spatially distributed agroecosystem simulation modeling tools are needed to address complex system interactions in space and time for changing land use, management, and climate. Furthermore, spatially focused conservation practices within and adjacent to fields need better evaluation with respect to water quantity and quality impacts. The previously developed and evaluated Agricultural Ecosystem Services (AgES) model will be enhanced and used to achieve these goals. Proposed enhancements include new science components focused on quantifying conservation practice effects and plant responses based on interactions between genetics, environment, and management. Expected outcomes will provide better analysis and decision making relative to spatial implementation of management practices at field to watershed scales for current and future climates, and spatial scaling of soil-water processes within agricultural watersheds. Advances in remote sensing technology have enabled the estimation of surface energy fluxes from satellite imagery and led to the development of a relatively direct satellite-based approach to estimate crop ET using an energy balance technique. However, The availability of satellite imagery at clear-sky days and its relatively low spatial resolution are the largest limitation of using satellite-based ET models. These difficulties can be overcome by using low cost and flexible unmanned platforms such as unmanned aerial systems (UAS). With the rapid advance of low-cost UAS available in the market, producers have increasing interest in UAS-based remote sensing as a simple and promising tool to acquire spatial information within fields and assist with decision-making. We are going to develop and evaluate a UAS-based remote sensing for estimating crop water use; and fill the gap between satellite and UAS for irrigation scheduling in the area.