Location: Watershed Physical Processes ResearchTitle: Spatial optimization of conservation practices for sediment load reduction in ungauged agricultural watersheds
|ELKADIRI, RACHA - Middle Tennessee State University|
|MOMM, HENRIQUE - Middle Tennessee State University|
|Bingner, Ronald - Ron|
|MOORE, KATY - Middle Tennessee State University|
Submitted to: Soil Systems
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/30/2022
Publication Date: 1/13/2023
Citation: Elkadiri, R., Momm, H.G., Bingner, R.L., Moore, K. 2023. Spatial optimization of conservation practices for sediment load reduction in ungauged agricultural watersheds. Soil Systems. 7(1),4. https://doi.org/10.3390/soilsystems7010004.
Interpretive Summary: Conservation plans are designed to improve water quality in agricultural watersheds and downstream waterways. This can be a challenge for conservationists while managing limited resources, minimizing agricultural production loss, and reducing sediment loads. Watershed modeling technology has been developed to support the implementation of conservation practices on ungauged watersheds. Utilizing an integration of GIS-based analyses with hydrological modeling at watershed scales provides additional capabilities to quantify the effect of conservation practices to sediment loads by spatially characterizing different types of conservation practices and scenarios and their relative impact on sediment reduction. The proposed methodology was applied to a west Tennessee watershed that has been identified as impaired due to high loads of suspended sediments from agricultural sources and served as a pilot study toward the improvement of non-point source pollution from agricultural activities in ungauged watersheds across the nation and in the Mississippi River basin. This investigation demonstrated the need for inclusion of more variables in the decision-making process, such as costs of implementation, costs of maintenance, and potential loss of income from a reduced production area. The inclusion of machine learning algorithms could also aid in the task of selecting and simulating a combination of different types of practices by controlling their associated model parameters, and their location in the watershed. This technology could lead to the development of hybrid customized solutions for impaired watersheds utilized by conservationist to target the most effective practices at the optimal locations for sediment load reductions throughout the landscape.
Technical Abstract: Conservation practices (CP)s are used in agricultural watersheds to reduce soil erosion and improve water quality, leading to a sustainable management of natural resources. This is especially important as more pressure is applied on agricultural systems by a growing population and a changing climate. A challenge persists, however, in optimizing the implementation of these practices given their complex, non-linear, and location-dependent response. This study proposes the integration of watershed modeling using the Annualized Agricultural Non-Point-Source model and a GIS-based field scale localization and characterization of CPs. The investigated practices are riparian buffer, sediment basin, crop rotation, and conservation reserve program. A total of 33 conservation scenarios were developed to quantify their impact on sediment erosion reduction. This approach was applied in an ungauged watershed as part of the Mississippi River Basin initiative aiming at reducing one of the largest aquatic dead zones in the globe. Simulation results indicate that the targeted approach has a significant impact on the overall watershed-scale sediment load reduction. Among the different evaluated practices, riparian buffers were the most efficient in sediment reduction. Moreover, the study provides a blueprint for similar investigations aiming at building decision-support systems and optimizing the placement of CPs in agricultural watersheds.