Preprints
https://doi.org/10.5194/hess-2024-148
https://doi.org/10.5194/hess-2024-148
17 Jun 2024
 | 17 Jun 2024
Status: a revised version of this preprint was accepted for the journal HESS and is expected to appear here in due course.

Assessing the cumulative impact of on-farm reservoirs on modeled surface hydrology

Vinicius Perin, Mirela G. Tulbure, Shiqi Fang, Sankarasubramanian Arumugam, Michele L. Reba, and Mary Yaeger

Abstract. On-farm reservoirs (OFRs) are essential water bodies to meet global irrigation needs. Farmers use OFRs to store water from precipitation and runoff during the rainy season to irrigate their crops during the dry season. Despite their importance to crop irrigation, OFRs can have a cumulative impact on surface hydrology by decreasing flow and peak flow. Nonetheless, there is limited knowledge on the spatial and temporal variability of the OFRs' impacts. Therefore, to gain novel understanding on the cumulative impact of OFRs on surface hydrology, here we propose a novel framework that integrates a top-down data driven remote sensing-based algorithm with physically-based models by leveraging the latest developments in the Soil Water Assessment Tool+ (SWAT+). We assessed the impact of OFRs in a watershed located in eastern Arkansas, the third most irrigated state in the USA. Our results show that the presence of OFRs in the watershed decreased annual flow on average between 14 and 24 %, and the mean reduction in peak flow varied between 43 and 60 %. In addition, the cumulative impact of the OFRs was not equally distributed across the watershed, and it varied according to the OFR spatial distribution, and their storage capacity. The results of this study and the proposed framework can support water agencies with information on the cumulative impact of OFRs, aiming to support surface water resources management. This is relevant as the number of OFRs is expected to increase globally as an adaptation to climate change under severe drought conditions.

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Vinicius Perin, Mirela G. Tulbure, Shiqi Fang, Sankarasubramanian Arumugam, Michele L. Reba, and Mary Yaeger

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on hess-2024-148', Anonymous Referee #1, 24 Jul 2024
    • AC2: 'Reply on RC1', Vinicius Perin, 31 Oct 2024
  • RC2: 'Comment on hess-2024-148', Anonymous Referee #2, 30 Sep 2024
    • AC1: 'Reply on RC2', Vinicius Perin, 31 Oct 2024

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on hess-2024-148', Anonymous Referee #1, 24 Jul 2024
    • AC2: 'Reply on RC1', Vinicius Perin, 31 Oct 2024
  • RC2: 'Comment on hess-2024-148', Anonymous Referee #2, 30 Sep 2024
    • AC1: 'Reply on RC2', Vinicius Perin, 31 Oct 2024
Vinicius Perin, Mirela G. Tulbure, Shiqi Fang, Sankarasubramanian Arumugam, Michele L. Reba, and Mary Yaeger
Vinicius Perin, Mirela G. Tulbure, Shiqi Fang, Sankarasubramanian Arumugam, Michele L. Reba, and Mary Yaeger

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Short summary
This study assesses how on-farm reservoirs (OFRs) can impact surface hydrology in Eastern Arkansas, US, using a new framework combining remote sensing and hydrological modeling. Findings show that reservoirs can reduce annual flow by 14–24 % and peak flow by 43–60 %, with effects varying by location and reservoirs's capacity. This is relevant as the number of OFRs is expected to increase globally as an adaptation to climate change under severe drought conditions.
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