Advancing Irrigated Agriculture Water Use and Resources Assessment in NextGen and USGS Agricultural Water Use Framework The Upper Colorado River Basin as a Testing Case

Objective:

This project aims to overcome current challenges in irrigated agriculture water use estimation and irrigation forecasting in the arid and semi-arid regions under climate change. We will advance USGS pywatershed-MODFLOW 6 model framework by developing and incorporating a BMI-compatible and AI-assisted crop module (CIROH-CROP) with the ability to precise ET and irrigation demand estimations, advanced forecasting of irrigation withdrawal and consumption under various irrigation practices, and improved USGS water use estimates. The project will deliver: (1) operational crop modules that equip the pywatershed-MODFLOW 6 with the advanced prediction capacity of irrigated agriculture and the resultant impact on water resources assessment, (2) detailed datasets for USGS water use estimate refinement in UCRB, and (3) an assessment of irrigation practices' effects on the region's water resources in the UCRB. These outcomes will yield critical findings for managing agricultural water resources under climate change and climate extremes and refine USGS agricultural water use assessment. We offer stakeholders a practical and operational tool for decision-making and developing more efficient irrigation practices and water use. These outcomes will also share insights through academic outlets, foster educational programs, and contribute benchmark data and novel methodologies to USGS and NextGen communities.

Approach:

To achieve our research objectives, we employ a methodology that combines high-resolution climate-forcing data, cutting-edge water resource modeling, AI-based emulators, and the validation and assessment of multiple objectives using multi-scale and multi-source flux data. In detail, we will develop and incorporate a BMI-compatible, AI-assisted crop module into the pywatershed-MODFLOW 6 framework, with parameterization of crop-specific growth processes, water demand, and ET estimation in response to a changing climate. We will add a BMI-compatible irrigation metrics module in the pywatershed-MODFLOW 6 to quantify irrigation water withdrawal and consumption under various irrigation practices. Using UCRB as a test basin, we will employ the advanced pywatershed-MODFLOW 6 to validate and refine the crop water use estimation in UCRB and assess the effects of different irrigation practices on both short-term and long-term water budgets in UCRB.

Impact:

Abstract:

This project aims to enhance water resource management for irrigated agriculture in arid and semi-arid regions, using the upper Colorado River Basin (UCRB) as a test case. It will implement an irrigated crop module (CIROH-CROP) within the USGS pywatershed-MODFLOW 6 framework through the Basic Model Interface (BMI). This study aims to address the current challenges in estimating water use in irrigated agriculture and forecasting irrigation in arid and semi-arid regions under climate change. Outcomes include (Outcome 1) operational crop modules that equip the pywatershed-MODFLOW 6 with the advanced prediction capacity of irrigated agriculture and the resultant impact on water resources, (Outcome 2) detailed datasets for USGS water use estimate refinement in UCRB, and (Outcome 3) an assessment of irrigation practices' effects on the region's water resources in the UCRB. To implement outcome 1 and consequent water use estimation for outcome 2, we have developed crop-specific growth and water demand and ET estimation modules for main crop types in UCRB and constructed AI-based ET emulators to leverage their computational and parameter validation efficiency. We are incorporating emulators into the pywatershed-MODFLOW, utilizing the Basic Model Interface (BMI). To improve irrigation water estimation for Outcome 2 and enable the delivery of Outcome 3, we are synthesizing reported irrigation information to quantify irrigation efficiency and withdrawals from different sources and develop an irrigation model scheme. The advanced Pywatershed-MODFLOW 6 framework, with implemented CIROH irrigated crop modules, enhanced USGS water use estimation, and outcome data products, offers stakeholders a practical and operational tool for decision-making and developing more efficient irrigation practices and water use. The study will elucidate the intricate dynamics between agricultural production, irrigation practices, and climate change within a key Western US region. Our project will also share insights through academic outlets, foster educational programs, and contribute benchmark data and novel methodologies to the USGS and NextGen communities.