U.S. flagAn official website of the United States government
                    Here's how you know **Official websites use .gov**
                            
                            A **.gov** website belongs to an official government organization in the United States.
 **Secure .gov websites use HTTPS**
                            
                            A **lock** (                            
                              A locked padlock                                                      
                            
                            ) or **https://** means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.


Menu Agricultural Research Service
						
                    U.S. DEPARTMENT OF AGRICULTURE
 Southwest Watershed Research Center: Tucson, AZ
 close



    Research

                    Research Projects
                                    Publications
                                    Collaborations
                                    News
                                    Software
                People

                    Staff Listing
                                    Careers


        


                    About SWRCSearch small
                    Search
            
            ARS Home
                                About ARS
                                Contact Us




ARS Home Pacific West Area Tucson, Arizona SWRC Research





- Scott, Russell - Russ
- Goodrich, David - Dave
- Nichols, Mary
- Williams, Christopher - Jason
- Biederman, Joel
- Heilman, Philip - Phil
- 2023
- 2022
- Publications
- Water Availability and Watershed Management (211)
- Soil and Air (212)
- Grass, Forage, and Rangeland Agroecosystems (215)

Research Project: Understanding Ecological, Hydrological, and Erosion Processes in the Semiarid Southwest to Improve Watershed Management **Location:
                            Southwest Watershed Research Center** 2023 Annual Report **Objectives**
                                

Objective 1. Quantify the magnitude and variability of the water balance components in semiarid landscapes and identify their controlling processes. 1.A: As an LTAR observatory, continue to collect and curate WGEW datasets including precipitation, runoff, sediment, pond runoff and sediment, meteorology, soil moisture, fluxes, vegetation, spatial datasets, and make datasets available under FAIR principles. 1.B: Quantify intra-storm variation in stable isotope values of precipitation over WGEW and identify relative influence of moisture source, season, local weather and sub-cloud processes.  1.C: Track daily watershed water balance components for rangeland ecosystems in the WGEW and SRER for improved assessment of water status and associated productivity. 1.D: Incorporate a variety of enhancements into watershed and erosion models maintained by the SWRC to add additional sub-processes, reduce predictive uncertainty, make them easier to use, enhance integration with land management agency workflows, and expand their use geographically. 

Objective 2: As part of the Long-Term Agroecosystem Research (LTAR) network, characterize and quantify impacts of water and agriculture/water management on semiarid watershed and agroecosystem processes. 2.A: Assess how novel remote sensing tools and low-cost, automated optical imagery can be used to quantify evapotranspiration and vegetation carbon uptake in water-limited regions. 2.B: Improve large-scale mapping of rangeland vegetation cover, lifeform, and biomass to classify rangeland ecological sites and states. 2.C: Quantify the long-term variability of riparian woodland evapotranspiration and CO2 exchange and their controls. 2.D: Assess impacts of altered temporal rainfall regime on semiarid grassland water and carbon cycling processes.

Objective 3: Quantify and predict effects of climatic change, plant community transitions, and conservation practices on ecological, hydrological, and erosion processes. 3.A: Develop new conceptual and quantitative frameworks to assess the impacts of brush management on ecosystem structure and function and enhanced delivery of ecosystem services. 3.B: Assess impacts of climate change, wildfire, and vegetation management on hydrology and erosion processes across spatial scales within the rangeland-dry forest continuum. Two Goals are included for this Sub-objective. 3.C:  Conduct field-based experiments on southwestern U.S. rangelands to assess the impact of woodland encroachment/infilling and tree removal conservation practices on vegetation, surface soils, and hydrology and erosion processes. 3.D: Evaluate the hydrologic, geomorphic, and ecologic impacts of failed soil and water conservation structures in Southwest rangelands. 3.E: Quantify how weather variability and potential changes in climate impact ecosystem net and gross carbon uptake in the water-limited Southwest. 3.F: Quantify how snowmelt amount and timing are impacted by vegetation structure under changing climate, wildfire, and vegetation management in the semiarid interior western U.S. 3.G: Estimate runoff and erosion risks over western U.S. rangelands. **Approach**
                                

Objective 1. A. Collect and make available Walnut Gulch Experimental Watershed (WGEW) datasets including precipitation, runoff, sediment, pond runoff and sediment, meteorology, soil moisture, fluxes, vegetation, spatial datasets. B. Quality-control and collate precipitation samples during summer rainfall events using a custom autosampler. C. Make measurements of precipitation, soil water content, runoff and evapotranspiration in the headwater watersheds of the WGEW and Santa Rita Experimental Range from the SECA network to track daily water balance components. D. Add functionality to existing runoff and erosion models to improve the applicability and ease of use for watershed management and assessments. 

Objective 2. A. Evaluate novel remote sensing spectral tools across the gradients of spatial and temporal dryland measurements. B. Use field measurements of cover, biomass and lifeform along with remotely sensed data to classify states on ecological sites. Structure from Motion will be used to estimate the distribution of cover and biomass by lifeform using machine learning (ML) and estimate erosion and runoff model parameters within the common site/state combinations. C. Use eddy covariance flux data from a riparian woodland site to better understand what controls annual ET and productivity. D. Utilize the Rainfall Manipulation facility in the SRER to fully control precipitation (using rainout shelters and irrigations) over hydrologically isolated plots with equal mixtures of multiple semiarid grassland plants and initiate hydroclimate disturbance treatments.

Objective 3. A. Test for impacts on measured runoff after brush management treatments and demonstrate Rangeland Hydrology and Erosion Model (RHEM) capability to accurately simulate runoff and erosion processes for tree canopy and intercanopy areas on untreated and treated sites. B. Conduct a series of field studies quantifying impacts of fire on vegetation, ground cover, soil water repellency, infiltration, and runoff and erosion processes, and evaluate climatic and vegetation controls on surface water supplies using daily streamflow records in watersheds of the Colorado River Basin.  C. Use artificial rainfall simulation and overland flow experiments to quantify infiltration, runoff, rainsplash, and erosion on tree-encroached sagebrush with tree-removal practices. D. Quantify the impacts of failed conservation structures using LiDAR data, aerial photographs, and satellite imagery. E. Use water and carbon flux data to better understand ecosystem responses to short and long term climate variability and improve models. F. Combine various datasets to quantify how snowmelt amount and timing are impacted by vegetation structure.  G. Employ ML methods complemented by auxiliary data to develop relationships to field-collected variables from monitoring locations across the West and determine if ML techniques can predict RHEM parameters and runoff and erosion predictions directly. **Progress Report**
                                

This report documents fiscal year (FY) 2023 progress for project 2022-13610-013-000D, titled, “Understanding Ecological, Hydrological, and Erosion Processes in the Semiarid Southwest to Improve Watershed Management”. 

In support of Objective 1, research continued under four sub-objectives. Under Sub-objective 1A, soil moisture data from four sites, two on the Walnut Gulch Experimental Watershed and two on the Santa Rita Experimental Range was made available through AmeriFlux. The meteorological data from three sites on Walnut Gulch were also updated and available via the Unit’s website, and the fourth meteorological site on the Audubon Research Ranch still needs additional processing and quality control. Under Sub-objective 1B, twenty summer convective rainstorms and six frontal winter rainstorms were analyzed to assess the dominant factors controlling water isotopic variability among and within storms. Moisture sources were mapped using publicly available NOAA atmospheric pathway models.  Local meteorological measurements were evaluated for their predictive capacity with respect to intra-storm isotopic variability. Under Sub-objective 1C, computer scripts to calculate and plot eddy covariance site water balances variables were refined and figures on the webpages are automatically updated. Estimates of evapotranspiration using annual watershed water balance measurements at the Semiarid Ecohydrological Array (SECA) savanna and shrubland sites were compared with evapotranspiration measurements from eddy covariance. The new webpages for the Santa Rita Experimental Range hosted by the University of Arizona were published and include surveys to ask for viewer/user feedback.  Under Sub-objective 1D, a robust snow model capable of running on Cligen daily weather input was developed and coupled with Kineros2 runoff model. Also, significant success was realized in estimating climate generation parameters over most of the globe and publishing them in peer-reviewed data papers. For the evaluation of using radar precipitation data for runoff prediction, model runs for a large number of storms using National Weather Service radar-rainfall data and data from the Long-term Agroecosystem Research (LTAR) Walnut Gulch Experimental Watershed rain gauge network have been completed. Processing of radar-rainfall data from the high-resolution mobile radar has been completed.

In support of Objective 2, research continued under four sub-objectives. In support of Sub-objective 2A, ARS researchers evaluated two years of RainMan data to assess the sensitivity of proximal remote sensing methods as proxies for directly measured photosynthesis by desert plants under variable-duration drought events. Also, spectrometers at grassland and forest sites were maintained to continue solar-induced florescence measurements to compare with flux tower photosynthesis measurements. Thermal camera measurements also continued, and ARS researchers are now comparing how these novel remote sensing measurements can capture various ecosystem processes like photosynthetic activity, photosynthetic capacity, and evapotranspiration. Under Sub-objective 2B, additional testing of cover estimates based on Landsat (30m spatial resolution), Sentinel2 (10m) and PlanetScope (3.5m) imagery was performed using very high resolution data from UAVs on the Santa Rita Experimental Range. Under Sub-objective 2C, the AmeriFlux-funded post-doctoral scientist has been analyzing the 20-year Charleston Mesquite Woodland eddy covariance data to understand what controls the interannual variability of land-atmosphere carbon dioxide and water fluxes. Under Sub-Objective 2D, comparison between spring and summer precipitation pulse response was delayed due to temporary staffing shortages.

In support of Objective 3, research continued under seven sub-objectives. Under Sub-objective 3A, the ecosystem service impact from partially successful mesquite treatment was assessed. Also, allometric models to estimate biomass were compared for multiple grass species from two locations in different years on the Santa Rita Experimental Range, and it was determined that site specific data would be needed to better improve the models. Further, data from research plots across the Sagebrush Steppe Treatment Evaluation Project network were compiled in preparation for modeling studies on effects of woodland encroachment and tree removal on hydrologic vulnerability and erosion using the Rangeland Hydrology and Erosion Model (RHEM). The dataset was screened for data quality and preparation for subsequent RHEM runs. Data include foliar cover, ground cover, soils, and topography data necessary for simulating runoff and erosion with the RHEM web tool.  Under Sub-objective 3B, vegetation, ground cover, soil properties, soil water repellency, and infiltration data collected on twenty 10 m x 10 m plots (121 sample points per plot) across unburned and burned dry forest sites in the Santa Catalina Mountains, southern Arizona, were compiled into a database for subsequent analyses on the effects of wildfire on vegetation, ground surface conditions, surface hydrology and erosion. Also, watersheds in the upper Colorado River Basin were identified for comparison with existing study watersheds in the Lower Basin.  Three snowtography and soil moisture stations were installed and operated over the winter of 2022-23 in the Dolores/San Juan watershed, comprising ponderosa pine forests thinned by harvest or managed fire and a spruce-fir forest with mechanical thinning. Two new sites were identified in the Little Snake Watershed, Wyoming, and stations will be installed there in summer of 2023. In support of Sub-objective 3C, research sites were established on Grand Staircase Escalante National Monument in Utah. ARS researchers conducted rainfall simulation and overland flow experiments at an untreated woodland site and at a site where trees were removed by mastication. Sampling included vegetation, ground cover, soil crusts cover, soil physical attributes, infiltration, runoff, and erosion. Data were compiled and summarized for untreated sagebrush and for woodland sites in preparation for a peer-review journal article. The data were presented in a technical report prepared and delivered to the Kanab Field Office (Kanab, UT) of the Bureau of Land Management, managing agency for the Grand Staircase Escalante National Monument. Under Sub-objective 3D, computer scripts to implement landform classification and train a machine learning model were developed and tested for identifying earthen water control berms at four sites in Arizona and Colorado rangelands. A second method for identifying berms based on homology was developed and tested. A geodatabase of earthen berm information was expanded to include berms in six HUC8 watersheds. Under Sub-Objective 3E, micrometeorological data collection for the SECA sites continued. Site data was quality-checked twice yearly and submitted to the AmeriFlux network database where the dataset was published and made publicly available. Data from the savanna site collected over 19 years was used to quantify the variability and controls on the spring and summer growing carbon fluxes and identify trends. The data was also used to determine how well evapotranspiration and photosynthesis estimates derived from satellite and land surface models capture the interannual variability observed in the measurements. Under Sub-objective 3F, a self-published a practitioner’s handbook of snowtography was developed. The Snowtography network operated by ARS stakeholders under ARS support and coordination reached 11 stations comprising daily snow measurement at about 350 points arrayed across gradients of elevation, forest type, and vegetation management in Arizona and Colorado. Under Sub-objective 3G, field survey data from over 60,000 rangeland locations collected by the NRCS as part of the National Resource Inventory (NRI) program, and the Assessment, Inventory, and Monitoring Program collected by the Bureau of Land Management (BLM), the National Park Service and Fish and Wildlife Service have been collected, error checked, and organized. This data was input into the RHEM to provide risk-based erosion estimates across the western United States. **Accomplishments**
                                

1. Increasing rainfall intensities amplify erosion risk of earthen cultural resources. Projected increases in high intensity rainfall in the southwestern United States pose major threats to culturally important historical adobe structures managed by the National Park Service (NPS). In collaboration with the NPS Vanishing Treasures Program, ARS scientists from Tucson, Arizona, utilized ARS rainfall simulation technologies to evaluate effects of preservation practices to mitigate erosion of adobe constructed cultural resources under high intensity rainfall. The study results indicate that standard patching techniques alone provide minimal protection against substantial erosion of adobe walls and that restructuring and patching of adobe wall caps (tops of walls) to shed water offers enhanced protection against wall losses under high intensity rainfall. Study results enable local heritage resource managers to better target preservation methods for return on investment of material and labor costs, resulting in better preservation overall and retention of culturally valuable resources. Further, the results demonstrate the potential impact of climate-driven increasing rainfall intensity on raindrop energy, erosivity, and erosion processes in general. 2. Unraveling the effects of management and climate on carbon fluxes of US croplands using the USDA Long-Term Agroecosystem (LTAR) network. Understanding the carbon flux dynamics from a broad range of agricultural systems has the potential to improve our ability to increase carbon sequestration while maintaining crop yields. ARS scientists in Tucson, Arizona, and scientists at the University of Arizona, examined measured crop-atmosphere carbon dioxide exchanges across the Long-Term Agroecosystem Research (LTAR) locations. Average seasonal patterns of carbon dioxide exchange from plant photosynthesis and respiration were determined. At rainfed sites, carbon fluxes were better correlated with precipitation than temperature. The greatest net carbon uptake occurred in sugarcane fields and the least in soybean fields. Across cropping systems, grain crops often had higher photosynthesis and gross carbon uptake and were more likely to have net uptake of carbon across the growing season. This multi-site analysis highlights the potential of the LTAR network to further carbon flux research. 3. Snowtography quantifies effects of forest cover on net water input to soil at ephemeral and seasonal snowpack sites in Arizona. Snow water resources are under combined threats from warmer winters, increased prevalence of winter rain instead of snow, and rapid changes to forested watersheds through fire and other disturbances. ARS scientists in Tucson, Arizona, and collaborators from universities and nonprofit organizations used three years of snow and soil moisture measurements at contrasting elevations in Arizona to quantify the fate of snowfall. At higher elevation watersheds with cold, stable snowpack, forest canopy reduced the amount of spring snowmelt but prolonged melt duration, creating a shorter drought period for trees to survive before onset of summer rains. At lower elevation watersheds with ephemeral snowpack, canopy had less effects on snowmelt amount or timing. These results imply that vegetation management impacts on water resources should be concentrated at higher, colder watersheds. 4. Using high frequency digital repeat photography to quantify the sensitivity of a semi-arid grassland ecosystem to the temporal repackaging of precipitation. Historical data and climate models agree that summer rainstorms are becoming larger but less frequent in many parts of the western United States, with unknown impacts on plant communities. ARS researchers in Tucson, Arizona, collaborated with university scientists at the University of Arizona, to operate a long-term rainfall manipulation experimental facility in a Sonoran desert grassland. Rainfall was repackaged into fewer, larger storms while maintaining a constant, historically normal total rainfall amount. Automated daily photographs compared favorably to labor-intensive measurements of photosynthesis, the main process driving plant productivity. Rainfall packaging into fewer/larger storms delayed plant productivity and favored deeper-rooted perennial plants, while many shallow-rooted annual plants perished. The results imply that under near-term climate change, rangeland productivity may shift later in the growing season and that deeper-rooted perennial grasses and shrubs may proliferate, while ground cover declines. 5. Gridded 20-year climate parameterization of Africa and South America for a stochastic weather generator (CLIGEN). ARS researchers in Tucson, Arizona, developed parameters for a stochastic weather dataset of CLIGEN (Command-Line Interface generator) inputs. These can be used to generate time series at any point in a 0.25 arc degree resolution grid covering South American and African continents. Estimated parameter values at each grid point are based on 20-year records taken from global climate datasets. Precipitation parameters are statistically downscaled from grid-scale to point-scale based on observations from globally distributed ground networks representing more than 10,000 weather stations. This dataset will expand the exploration of novel hydrological and soil erosional hypotheses across African and South American continents and is intended for use in climate-related research in ungauged areas where observed climate records are unavailable or are non-ideal. 6. A global rain-driven soil erosion investigation based on simulated breakpoint precipitation. Climate inputs are a necessary part of soil erosion prediction and assessment, but they are not always available, particularly in international applications. In this study, ARS researchers in Tucson, Arizona, tested a new international climate dataset, with particularly good coverage of the United States, Mexico, Europe, and Australia, for use with the ARS-Rangeland Hydrology and Erosion model (RHEM), and for determination of the climate factor in the ARS-Revised Universal Soil Loss Equation model (RUSLE). The international climate dataset represents numerous global climate types, and therefore, this study provides a generalization of global erosion rates that are useful for erosion risk assessment. This study also brings attention to the openly available international climate dataset, which may encourage soil erosion modeling in new locations. **Review Publications**
                            *Fullhart, A.T., Ponce-Campos, G., Meles, M.B., Mcgehee, R., Armendariz, G.A., Oliveira, P., Almeida, C., De Araujo, J., Nel, W., Goodrich, D.C. 2022. Gridded 20-year climate parameterization of Africa and South America for a stochastic weather generator (CLIGEN). Big Earth Data. 7(2):349-374. https://doi.org/10.1080/20964471.2022.2136610.*
                                *Fullhart, A.T., McGehee, R., Nearing, M., Hernandez, M., Weltz, M., Goodrich, D.C. 2022. A global rain-driven soil erosion investigation based on simulated breakpoint precipitation. American Society of Agricultural and Biological Engineers. 65(5):1081-1096. https://doi.org/10.13031/ja.14817.*
                                *Dannenberg, M., Barnes, M., Smith, W., Johnston, M., Meerdink, S., Wang, X., Scott, R.L., Biederman, J.A. 2023. Upscaling dryland carbon and water fluxes with artificial neural networks of optical, thermal, and microwave satellite remote sensing. Biogeosciences. 20(2):383-404. https://doi.org/10.5194/bg-20-383-2023.*
                                *Archer, S., Naito, A., Heilman, P., Vivoni, E., Scott, R.L. 2023. Prosopis velutina response to aerial herbicide application. Rangeland Ecology and Management. 88:129-134. https://doi.org/10.1016/j.rama.2023.02.014.*
                                *Knowles, J., Bjarke, N., Badger, A., Berkelhammer, M., Biederman, J.A., Blanken, P., Bretfeld, M., Burns, S., Ewers, B., Frank, J., Hicke, J., Lestak, L., Livneh, B., Reed, D., Scott, R.L., Molotch, N. 2023. Bark beetle impacts on forest evapotranspiration and its partitioning. Science of the Total Environment. 880. Article 163260. https://doi.org/10.1016/j.scitotenv.2023.163260.*
                                *Goodrich, D.C., Bosch, D.D., Bryant, R.B., Cosh, M.H., Endale, D.M., Veith, T.L., Kleinman, P.J., Langendoen, E.J., McCarty, G.W., Pierson Jr., F.B., Schomberg, H.H., Smith, D.R., Starks, P.J., Strickland, T.C., Tsegaye, T.D., Awada, T., Swain, H., Derner, J.D., Bestelmeyer, B.T., Schmer, M.R., Baker, J.M., Carlson, B.R., Huggins, D.R., Archer, D.W., Armendariz, G.A. 2022. Long term agroecosystem research experimental watershed network. Hydrological Processes. 36(3). Article e14534. https://doi.org/10.1002/hyp.14534. [Corrigendum: Hydrological Processes: 2022, 36(6), Article e14609. https://doi.org/10.1002/hyp.14609.]*
                                *Li, L., Hao, Y., Wang, W., Biederman, J.A., Wang, Y., Zheng, Z., Wen, F., Qian, R., Zhang, B., Song, X., Cui, X., Xu, Z. 2022. Joint control by soil moisture, functional genes and substrates on response of N2O flux to climate extremes in a semiarid grassland. Agricultural and Forest Meteorology. 316. Article 108854. https://doi.org/10.1016/j.agrformet.2022.108854.*
                                *Belmonte, A., Sankey, T., Biederman, J.A., Bradford, J., Kolb, T. 2022. Soil moisture response to seasonal drought conditions and post-thinning forest structure. Ecohydrology. 15(5). Article e2406. https://doi.org/10.1002/eco.2406.*
                                *Norton, C., Hartfield, K., Holifield Collins, C.D., van Leeuwen, W., Metz, L. 2022. Multi-temporal LiDAR and hyperspectral data fusion for classification of semi-arid woody cover species. Remote Sensing. 14(12). Article 2896. https://doi.org/10.3390/rs14122896.*
                                *Zhang, F., Biederman, J.A., Devine, C., Pierce, N., Yan, D., Javadian, M., Potts, D., Smith, W. 2023. Using high frequency digital repeat photography to quantify the sensitivity of a semi-arid grassland ecosystem to the temporal repackaging of precipitation. Agricultural and Forest Meteorology. 338(15). Article 109539. https://doi.org/10.1016/j.agrformet.2023.109539.*
                                *Kibler, C., Trugman, A., Roberts, D., Still, C., Scott, R.L., Caylor, K., Stella, J., Singer, M. 2023. Evapotranspiration regulates leaf temperature and respiration in dryland vegetation. Agricultural and Forest Meteorology. 339. Article 109560. https://doi.org/10.1016/j.agrformet.2023.109560.*
                                *Lapides, D., Sytsma, A., O'Neil, G., Djokic, D., Nichols, M.H., Thompson, S. 2022. Arc Hydro Hillslope and Critical Duration: New tools for hillslope-scale runoff analysis. Journal of Environmental Modeling and Software. 153. Article 105408. https://doi.org/10.1016/j.envsoft.2022.105408.*
                                *Roby, M.C., Scott, R.L., Biederman, J.A., Smith, W.K., Moore, D.J. 2022. Response of soil carbon dioxide efflux to temporal repackaging of rainfall into fewer, larger events in a semiarid grassland. Frontiers in Environmental Science. 10. Article 940943. https://doi.org/10.3389/fenvs.2022.940943.*
                                *Menefee, D.S., Scott, R.L., Abraha, M., Alfieri, J.G., Baker, J.M., Browning, D.M., Chen, J., Gonet, J.M., Johnson, J.M., Miller, G.R., Nifong, R.L., Robertson, P., Russel, E.R., Saliendra, N.Z., Schreiner-Mcgraw, A.P., Suyker, A., Wagle, P., Wente, C.D., White Jr, P.M., Smith, D.R. 2022. Unraveling the effects of management and climate on carbon fluxes of U.S. croplands using the USDA Long-Term Agroecosystem (LTAR) network. Agricultural and Forest Meteorology. 326. Article 109154. https://doi.org/10.1016/j.agrformet.2022.109154.*
                                *Feldman, A., Short Gianotti, D., Dong, J., Akbar, R., Crow, W.T., McColl, K., Konings, S., Nippert, J., Tumber-Dávila, S., Holbrook, N., Rockwell, F., Scott, R.L., Reichle, R.H., Chatterjee, A., Joiner, J., Poulter, B., Entekhabi, D. 2023. Remotely sensed soil moisture can capture dynamics relevant to plant water uptake. Water Resources Research. 59(2). Article e2022WR033814. https://doi.org/10.1029/2022WR033814.*
                                *Elias, E.H., Tsegaye, T.D., Hapeman, C.J., Mankin, K.R., Kleinman, P.J., Cosh, M.H., Peck, D.E., Coffin, A.W., Archer, D.W., Alfieri, J.G., Anderson, M.C., Baffaut, C., Baker, J.M., Bingner, R.L., Bjorneberg, D.L., Bryant, R.B., Gao, F.N., Gao, S., Heilman, P., Knipper, K.R., Kustas, W.P., Leytem, A.B., Locke, M.A., McCarty, G.W., McElrone, A.J., Moglen, G.E., Moriasi, D.N., O'Shaughnessy, S.A., Reba, M.L., Rice, P.J., Silber-Coats, N., Wang, D., White, M.J., Dobrowolski, J.P. 2023. A vision for integrated, collaborative solutions to critical water and food challenges. Journal of Soil and Water Conservation. 78(3):63A-68A. https://doi.org/10.2489/jswc.2023.1220A.*
                                *Hart, S., Raymond, K., Williams, C.J., Rutherford, W.A., DeGayner, J. 2023. Modeling earthen treatments for climate change effects. Heritage. 6(5):4214-4226. https://doi.org/10.3390/heritage6050222.*
                                *Li, L., Nearing, M.A., Heilman, P., Nichols, M.H., Guertin, D., Williams, C.J. 2022. Rangeland hillslope lengths: A case study at the Walnut Gulch Experimental Watershed, southeastern Arizona. International Soil and Water Conservation Research. 10(4):597-609. https://doi.org/10.1016/j.iswcr.2022.02.004.*
                                *Polyakov, V.O., Kadoya, W., Beal, S., Morehead, H., Hunt, E., Cubello, F., Meding, S., Dontsova, K. 2023. Transport of insensitive munitions constituents, NTO, DNAN, RDX, and HMX in runoff and sediment under simulated rainfall. Science of the Total Environment. 866. Article 161434. https://doi.org/10.1016/j.scitotenv.2023.161434.*
                                *Kumar, J., Coffin, A.W., Baffaut, C., Ponce-Campos, G., Witthaus, L., Hargrove, W. 2023. Quantitative representativeness and constituency of the long-term agroecosystem research network and analysis of complementarity with existing ecological networks. Environmental Management. 72:705-726. https://doi.org/10.1007/s00267-023-01834-9.*
                                *Hoover, D.L., Abendroth, L.J., Browning, D.M., Saha, A., Snyder, K.A., Wagle, P., Witthaus, L.M., Baffaut, C., Biederman, J.A., Bosch, D.D., Bracho, R., Busch, D., Clark, P., Ellsworth, P.Z., Fay, P.A., Flerchinger, G.N., Kearney, S.P., Levers, L.R., Saliendra, N.Z., Schmer, M.R., Schomberg, H.H., Scott, R.L. 2022. Indicators of water use efficiency across diverse agroecosystems and spatiotemporal scales. Science of the Total Environment. 864. Article e160992. https://doi.org/10.1016/j.scitotenv.2022.160992.*
                                *Dwivedi, R., Biederman, J.A., Broxton, P., Lee, K., van Leeuwen, W. 2022. Snowtography quantifies effects of forest cover on net water input to soil at sites with ephemeral or stable seasonal snowpack in Arizona, USA. Ecohydrology. 16(2). Article e2494. https://doi.org/10.1002/eco.2494.*
                                *Li, L., Hao, Y., Wang, W., Biederman, J.A., Zheng, Z., Zhang, Z., Wang, Y., Song, X., Cui, X., Xu, Z. 2023. Seasonal timing of extreme drought regulates N2O fluxes in a semiarid grassland. Geoderma. 436. Article 116530. https://doi.org/10.1016/j.geoderma.2023.116530.*
                                *Mcdowell, N., Anderson-Teixeira, K., Biederman, J.A., Breshears, D., Fang, Y., Fernandez-De-Una, L., Graham, E., Mackay, D., Mcdonnell, J., Moore, G., Nehemy, M., Stevens Rumann, C.S., Stegen, J., Tague, N., Turner, M., Chen, X. 2023. Ecohydrological decoupling under changing disturbances and climate. One Earth. 6(3):251-266. https://doi.org/10.1016/j.oneear.2023.02.007.*


Return to top


Connect with ARS Sign up


ARS Home
                            USDA.gov
                            Plain Writing
                            Policies & Links
                            Civil Rights Statements
                            FOIA
                            Accessibility Statement
                            Privacy Policy
                            Non-Discrimination Statement
                            Quality of Information
                            USA.gov
                            WhiteHouse.gov