Research Project: Response of Ecosystem Services in Agricultural Watersheds to Changes in Water Availability, Land Use, Management, and Climate

Location: Water Management and Systems Research

2022 Annual Report

Objectives
Objective 1: Quantify changes in agricultural production and fluxes of water and associated nutrients (N and P) and sediment from field to watershed scales over the next several decades at fine temporal resolutions in response to changes in water availability, land use, management practices, and climate. Sub-objective 1.1. Understand and quantify the effects of variable irrigation practices on crop production responses by assessing genotype x environment x limited-water management (GEM) interactions for different land use, management, and climate scenarios at field to watershed scales. Sub-objective 1.2. Improve estimates of water redistribution and storage by resolving spatial scale issues related to the measurement and simulation of soil moisture in cropland and grassland ecosystems at field to watershed scales. Simulate hydroecology within the SPRB and the Central Plains Experimental Range (CPER) Long-Term Agroecosystem Research (LTAR) site to extend experimental results to larger areas and different management scenarios. Sub-objective 1.3. Understand how the effectiveness of spatially distributed water conservation strategies and agricultural best management practices (BMPs) for nutrient and sediment control vary with landscape position, geographic/geologic characteristics of the field, farm, or watershed, and other factors. Objective 2: Assess key ecosystem services for projected water requirements and water quality targets in the South Platte River Basin, Colorado, at field to watershed scales in response to changes in water availability, land use, management, and climate. Objective 3: Develop and disseminate a web-based geospatial data management system as a repository of data, models, and tools for accelerating collaborative research and facilitating sustainable management of water, nutrients, and sediment.

Approach
Objectives 1 and 2 focus on enhancing scientific knowledge for incorporation into the Agricultural Ecosystems Services (AgES) distributed watershed model with subsequent testing and application of AgES. Objective 1 is divided into three sub-objectives integrated from smaller to larger scales, which focus on: (1.1) improved model components for plant modeling of GEM interactions, particularly for irrigated water management, (1.2) soil water modeling emphasizing spatial scaling of soil water and surface runoff in dryland cropping and rangeland systems, and (1.3) simulation of conservation effects over regional watersheds, primarily in Iowa where collaborators have been investigating and monitoring water quality impacts over decadal time scales. In Objective 2, the AgES model will be used to simulate a series of land use, management practice and climate scenarios for hydrologic and water quality ecosystem service indicators in eastern Colorado. Objective 3 involves development of a web-based Geospatial Portal for Scientific Research (GPSR) for technology transfer of geospatial information. GPSR will be used for dissemination of the results of the present project together with broader technology transfer by ARS and collaborators, such as experimental results generated from Long-Term Agricultural Research sites and Climate Hubs.

Progress Report
This is the final report for this project, which was replaced by 3012-13660-010-000D "Improving Resiliency of Semi-Arid Agroecosystems and Watersheds to Change and Disturbance through Data-Driven Research, AI, and Integrated Models". The Agricultural Ecosystems Services (Ages) model-as-a-service allows users to run instances of Ages on a computer server or cloud service. Specific instances of the Ages executable model can be packaged with project data; only the data that needs to be manipulated by the client, such as parameters that change during model calibration, are sent to the model-as-a-service, which makes remote computing very efficient. Instances of Ages can also be run in parallel (Objective 3). Cadel (Catchment areas delineation) is a tool that computes the watershed (catchment) boundaries based on digital topography, then delineates internal areas called hydrologic response units (HRUs) and their connectedness (topology) used to route water and constituents among HRUs and to stream reaches. HRUs are delineated based on topography, soils, land use or any mapped layer, and the users controls the minimum HRU size based upon the scales of interest and computational capacity. Cadel produces input files needed to run the Ages model for a given catchment. Cadel can be run by experts using the “backend” code, and a prototype of a webpage interface is available (https://alm.engr.colostate.edu/cb/project/cadel) (Objective 3). The Unified Plant Growth Model (UPGM) in Ages simulated crop developmental stages at the Limited Irrigation Research Farm, Colorado. Calibration of phenological parameters in UPGM provided default values for future case studies at new sites (Sub-objective 1.1). Water security indicators based on the water footprint account for the return flow from the total water withdrawn from a watershed. The Ages watershed model results for the Big Dry Creek Watershed (BDCW) near Denver indicated that the blue water (irrigation) footprint is higher than the green water (precipitation) footprint in the BDCW, and the spatial distribution of gray water footprint is highly correlated with fertilizer application (Objective 2). Food security and trade are linked to global groundwater use. Pumping of groundwater for irrigation is often unsustainable across the globe. A new international study connected global food trade to groundwater (un)sustainability (Objective 2). Landuse and Agricultural Management Practices web-Service (LAMPS) mapped the United States corn belt and how it is changing. Geographers with the USDA mapped a contiguous Midwest corn belt in 1949, but over recent decades, it had not been updated, and many publications have referred to the “Corn Belt” vaguely or only at the level of States. ARS researchers and collaborators in Fort Collins, Colorado extended the LAMPS tool developed for the USDA Natural Resources Conservation Service (NRCS) in the preceding ARS project to detect all counties in the contiguous United States with corn at specified fractional areas. LAMPS produced maps of corn intensity and showed how corn was expanding into parts of the country (primarily with ethanol incentives) from 2010 through 2016, and contracting to a lesser extent in other places. The LAMPS tool and methods for delineating the corn belt is available for extended use into the future. LAMPS is also used by the NRCS to build default crop sequences for water and wind erosion modeling using the ARS models WEPP (Watershed Erosion Prediction Project) and WEPS (Wind Erosion Prediction System). Conservation practices to reduce soil erosion were identified. Soil erosion occurs in gullies, hillslopes and stream riparian zones, causing loss of crop production and environmental water quality problems. Effects of different conservation practices were quantified in terms of their effectiveness in reducing soil losses (Objectives 2 and 3). Water pathways to streams from mixed agricultural and suburban lands were simulated. Municipalities, state and regional water management organizations, and the U.S. Environmental Protection Agency need to identify non-point sources of water contamination and the quantity of water that flows from agricultural fields and other land areas to streams. In partnership with Colorado State University, we successfully used the Ages model to determine pathways of surface runoff, irrigation return flow, shallow lateral flow through soils (interflow), and groundwater discharge from different land uses in the Big Dry Creek Watershed (BDCW), Colorado. This research showed that nitrate loads from wastewater treatment plants exceeded those from agricultural sources, which is changing environmental protection priorities in the several Colorado cities (Broomfield, Thornton, and Westminster). These results were requested by the BDCW Association and the Colorado State Department of Public Health and Environment (CDPHE), who plan to use them to inform multi-million-dollar municipal water management and environmental monitoring decisions (Objective 2). Soil moisture from global remote sensing is scaled down to high spatial resolution for precision agriculture and trafficability. Surface soil moisture is estimated at multi-kilometer scales using satellite remote sensing, but practical applications in precision agriculture and military traffic planning require understanding of soil moisture variability at the scale of meters. ARS researchers in Fort Collins, Colorado in collaboration with Colorado State University found the EMT+VS (Equilibrium Moisture from Topography, Vegetation, and Soil) model was able to map soil moisture at finer scales (down to 10 m) and to estimate confidence levels across complex landscapes. This research has proven to be extremely valuable for land managers and has attracted Department of Defense funding for application to military trafficability (capacity of soils to support vehicles) because wet soils hinder the ability to remain mobile and cross many different terrain types, costing the armed forces valuable training dollars, equipment, and human lives (Objective 2).

Accomplishments
1. Spatially explicit watershed model for agricultural and ecohydrological systems (Ages, version 1.0). Users, mostly researchers, need a model that is scalable, written in open-source code, and integrated with cloud computing services, including open access tools for building model input files, calibrating model results to match site-specific data, and analyzing results for decision support. ARS researchers in Fort Collins, Colorado, developed the Ages model to uniquely account for spatial process interactions between land areas from field management areas to hillslopes to large mixed-use watersheds. We designed Ages to meet the needs of diverse stakeholders, including non-profits (Southfork Watershed Association, Iowa; Big Dry Creek Watershed Association, Colorado), universities (Colorado State University, University of Nebraska, Prairie View A&M, Colorado School of Mines), Federal agencies (U.S. Forest Service, U.S. Geological Survey), and international organizations (Embrapa Environment, Brazil; University of São Paulo, Brazil; Inner Mongolia Agricultural University, China; University of Trento, Italy). Ages is programmed to allow new features and functions to be readily added as needed to meet emerging stakeholder needs.

Review Publications
Heeren, D., Guertault, L., Mankin, K.R. 2021. Preferential flow in riparian buffers: Current research and future needs. Transactions of the ASABE. 64(6):1907-1911. https://doi.org/10.13031/trans.14732.
Barnard, D.M., Germino, M.J., Bradford, J.B., O'Connor, R.C., Andrews, C.M., Shriver, R.K. 2021. Are climate data and drought indices good indicators of ecologically relevant soil moisture dynamics in drylands? Ecological Indicators. 133. Article e108379. https://doi.org/10.1016/j.ecolind.2021.108379.
Poessel, S.A., Barnard, D.M., Applestein, C.V., Germino, M.J., Ellsworth, E.A., Major, D., Moser, A., Katzner, T.E. 2022. Greater sage-grouse respond positively to intensive post-fire restoration treatments. Ecology and Evolution. 12(3). Article e8671. https://doi.org/10.1002/ece3.8671.
Anandhi, A., Douglas-Mankin, K.R., Srivastava, P., Aiken, R.M., Leung, L., Chaubey, I., Senay, G. 2020. DPSIR-ESA vulnerability assessment (Deva) framework: Synthesis, foundational overview, and expert case studies. Transactions of the ASABE. 63(3):741-752. https://doi.org/10.13031/trans.13516.
Taylor et al., 2022. Groundwater, aquifers and climate change. In: The United Nations World Water Development Report 2022: Groundwater: Making the invisible visible. UNESCO, Paris. pp. 101-114. https://unesdoc.unesco.org/ark:/48223/pf0000380721
Figueiredo, R.O., Simioli, M.R., Jesus, T.V., Cruz, P.P., Nogueira, S.F., Green, T.R., Camargo, P.B. 2020. Hydrobiogeochemistry of two catchments in Brazil under forest recovery in an environmental services payment program. Environmental Monitoring and Assessment. 193. Article e3. https://doi.org/10.1007/s10661-020-08773-6.
Yuan, Y., Book, R., Mankin, K.R., Koropeckyj-Cox, L., Christianson, L.E., Messer, T.L., Christianson, R.D. 2022. An overview of the effectiveness of agricultural conservation practices for water quality improvement. Journal of the ASABE. 65(2):419-426. https://doi.org/10.13031/ja.14503.
Serafin, F., David, O., Carlson, J.R., Green, T.R., Rigon, R. 2021. Bridging technology transfer boundaries: Integrated cloud services deliver results of nonlinear process models as surrogate model ensembles. Environmental Modelling & Software. 146. Article e105231. https://doi.org/10.1016/j.envsoft.2021.105231.
Mankin, K.R., Modala, N.R. 2022. Integrating streambank erosion with overland and ephemeral gully models improves stream sediment yield simulation. Journal of the ASABE. 65(4):763-778. https://doi.org/10.13031/ja.14840.
Mankin, K.R., Wells, R.M., Kipka, H., Green, T.R., Barnard, D.M. 2022. Hydrologic effects of fire in a sub-alpine watershed: AgES outperforms previous PRMS simulations. Transactions of the ASABE. 65(4):751-762. https://doi.org/10.13031/ja.14881.
Veettil, A.V., Mishra, A.K., Green, T.R. 2022. Explaining water security indicators using hydrologic and agricultural systems models. Journal of Hydrology. 607. Article e127463. https://doi.org/10.1016/j.jhydrol.2022.127463.