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Mirela Tulbure

Assoc Professor

Jordan Hall NA

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Date: 09/01/21 - 8/31/23
Amount: $45,000.00
Funding Agencies: National Aeronautics & Space Administration (NASA)

Fresh water stored by on-farm reservoirs (OFRs) is a fundamental component of surface hydrology and is critical for meeting global irrigation needs. Farmers use OFRs to store water during the wet season for crop irrigation during the dry season. There are more than 2.6 million OFRs in the US alone, and many of these OFRs were constructed during the last 40 years. Despite their importance for irrigating crops, OFRs can contribute to downstream water stress by decreasing stream discharge and peak flow in the watersheds where they are built, thereby exacerbating water stress intensified by climate change and population growth. However, modeling the impact of OFRs on surface hydrology remains a challenge because they are so abundant and have frequent fluctuations in surface area and water volume. Prior to the recent availability of satellite data, widespread monitoring of OFRs’ surface area and water volume across space and time was impossible due to temporal latency of satellite observations. The goal of this project, therefore, is to harness a multi-sensor satellite imagery approach to reduce observation latency and improve surface hydrology modeling, with the aim of supporting more efficient management of OFRs and mitigation of their downstream impacts. Our objectives are: 1) Develop a multi-sensor imagery approach to reduce latency and obtain sub-weekly OFRs surface area and volume change; and 2) Input sub-weekly OFRs volume change into the Soil Water and Assessment Tool (SWAT) model to estimate OFRs’ impact on surface hydrology. Specifically for Objective 1, a novel method based on the Kalman filter will be used to harmonize data from multiple optical sensors and to provide sub-weekly OFRs surface area change, which will be converted to volume change using area-elevation equations. Then for Objective 2, we will carry out hydrological simulations in SWAT to quantify OFRs’ impact on simulated daily and monthly stream discharge, simulating stream discharge with and without the OFRs. We will perform yearly simulations, based on satellite imagery availability, to measure OFRs’ impact during low and peak flows in each watershed of our study region, which will account for both intra- as well as inter-annual variability in flows. This project will monitor OFRs’ surface area and volume change to enable better assessment and management of water quantity, and further the use of Earth system science to inform decisions and provide benefits to society regarding preservation of surface water resources, both of which are overarching science goals that guide NASA’s Earth Science Division program.

Date: 09/01/21 - 8/31/23
Amount: $0.00
Funding Agencies: National Aeronautics & Space Administration (NASA)

On-farm water reservoirs – artificial water impoundment to retain water from rainfall and run-off – are essential to global food production, as they enable growers to store water during the rainfall season to support water use during the dry season, particularly for crop irrigation. Understanding their volume spatial temporal variability is essential to describe their impact to terrestrial hydrological system. However, the wide monitoring of inter- and intra-annual volume variability of these waterbodies remains a challenging task – since they have a changing nature, a high occurrence number and difficult accessibility in private properties. Therefore, I propose a remote sensing multi-sensor (optical + radar), multi-temporal approach to deliver an assessment of the spatial distribution, volume change, seasonality and hydrological impact of on-farm reservoirs in Eastern Arkansas, United States. I chose Eastern Arkansas due to its importance for irrigated food production; it ranks as the third most irrigated region in the United States and has seen a rapid increase of on-farm reservoirs occurrence since the 1980s. In this study, I will harness the power of openly available satellite imagery (i.e. Landsat-8, Sentinel-1 and Sentinel-2) and the high-resolution Planet CubeSats combined with digital elevation models, and long-term surface water area datasets (e.g. Dynamic Surface Water Extent) to derive volume-area and volume-elevation relationships. I will apply the widely used Soil and Water Assessment Tool (SWAT) to model the hydrological impact of on-farm reservoirs at the watershed scale. This study will provide methods and algorithms to guide water authorities and policy makers when implementing water preservation policies in Eastern Arkansas. The findings will advance understanding of the on-farms reservoirs spatial temporal variability in volume, which is pivotal for irrigation planning purposes. The developed methods will be openly available to be applied to other important agricultural regions of the world.


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