Location: Hydrology and Remote Sensing Laboratory
Project Number: 8042-13610-029-027-I
Project Type: Interagency Reimbursable Agreement
Start Date: Jul 31, 2017
End Date: Sep 30, 2019
Objective:
Objective 1. Use extensive irrigated maps from the Maryland Department of Agriculture to be used in calibration and testing of the USDA-ARS Soil and Water Assessment Tool (or SWAT) model under a broad range of irrigation intensities and climatic conditions.
Objective 2. Develop methodology for determining the age of ground water contributing to stream flow based on measurement of chiral MESA composition of stream water.
Approach:
Effective conservation practice implementation requires landscape assessments of the most vulnerable areas where they are most needed. We hypothesize that simulated SWAT scenarios that ingest remotely sensed ET estimates would be a useful tool in examining the impacts of a new irrigation BMP recommendation. A rigorous assessment of irrigation BMP will require a thorough understanding of how irrigation affects crop productivity, water availability and quality. Thus, our specific objective is to develop a reliable tool for evaluating the effect of differing irrigation practices on nitrogen fate and transport. The validated and tested model/tool would ultimately be used for the development of improved nitrogen management practices. The irrigation maps will be supplemented with remote sensing-based estimates of ET (Since ET varies with crop water availability, it can be used to identify irrigated fields, particularly during dry period). This watershed also has extensive irrigation practices and is well-instrumented that allows a more precise model calibration & validation.
Work will be initiated to improve the SWAT model to simulate the effects of hydric soils and wetlands on water and nitrogen cycling to represent the catchment characteristics. Currently, SWAT does not provide reliable simulation framework to account for the varying degree of soil moisture and inundation on nutrient cycling in spatially explicit way. The improved model representation will enhance the ability of model to evaluate the impacts of irrigation at the field and catchment scales. We will calibrate and validate the SWAT model using field monitoring and geospatial data (multitemporal remote sensing of ET, vegetation (NDVI), soil moisture, and inundation).
Water quality monitoring activities will continue on the Choptank River watershed which will including maintenance and operation of real-time optical sensors calibrated for water quality as well as sub-watershed and estuary sampling to evaluate novel usage of chiral MESA signals for dating nitrate in stream water. Further study will involve use of both urban and agricultural tracers to detect nutrient sources (urban vs. agricultural) in the Choptank River estuary.
