OWCAP

Historical Climate District Data

An interactive tool to visualize historical climate data by district, including temperature, precipitation and crop growing degree days: Historical Climate District Data

Ogallala Water Data Portal

Climate datasets created for OWCAP, publicly available during summer 2021: Ogallala Water Data Portal

OWCAP Summary

The climate team at Kansas State University led by Dr. Xiaomao Lin participated in the Ogallala Water Coordinated Agricultural Project (OWCAP), a USDA-NIFA funded project that has been leading the interdisciplinary effort to conserve groundwater from the Ogallala Aquifer, which is widely used for irrigated agriculture in the semiarid High Plains, USA. It has brought together producers, scientists, and policymakers across state-lines to address the challenging issues surrounding agricultural water management. Our group focused on historical and projected climate data acquisition and analysis for integrated modeling efforts in addition to the creation of climate-based tools that help producers make management decisions. Multiple peer-reviewed publications from our group resulted from this work, including studies that quantified the spatial and temporal variability of frost, drought, and estimates of satellite-derived groundwater. Visitors are referred to the official Ogallala Water website for more information about the project scope and objectives.

                In the climate tool Historical Climate District Data, producers can select one of nine agricultural districts in Kansas to visualize and download recent and historical temperature, precipitation, and growing degree days for corn or winter wheat for a selected range of dates. This tool streamlines relevant information for producers using the Applied Climate Information Web Services developed by the NOAA Regional Climate Centers. The weather station data retrieved for each district is described in Table 1. The latest 5-minute data from the Kansas Mesonet is also provided in its own tab. In addition, producers can select the Climate change button to examine changes in climate since 1950 to get an overview of trends that may guide long-term decisions in crop management. The trend line displayed is based on ordinary least squares. The climate datasets created by our team for the OWCAP integrated modeling efforts will become publicly available during summer 2021 at the Ogallala Water Data Portal.

Table 1.  Corresponding Global Historical Climatology Network (GHCN) station data retrieved and displayed when selecting one of the nine agricultural districts.

District

Name

GHCN ID

NW

Colby

USC00141699

NC

Concordia

USW00013984

NE

Manhattan

USC00144972

WC

Tribune

USC00148235

C

Hays

USC00143527

EC

Ottawa

USC00146128

SW

Garden City

USW00023064

SC

Pratt

USC00146549

SE

Parsons

USC00146242

Figure 1: The study domain used for the 2018 publication “Identification of hydroclimate subregions for seasonal drought monitoring in the U.S. Great Plains”, which identified subregions of homogeneous drought variability within the Great Plains. The blue shaded region is the extent of Ogallala Aquifer (Source).

Figure 2: Subregions of homogenous drought variability during the winter in the Great Plains, USA. Data used to create the figure was from source.

Figure 3: Dissertation figure showing the domain for a regional climate simulation study that examined the atmospheric response to irrigation. Colors in blue show areas that increased in irrigated cropland fraction between 1984 and 2017.

Publications

Araya, A., Kisekka, I., Lin, X., Vara Prasad, P. V., Gowda, P. H., Rice, C., & Andales, A. (2017). Evaluating the impact of future climate change on irrigated maize production in Kansas. Climate Risk Management, 17, 139-154. doi:https://doi.org/10.1016/j.crm.2017.08.001

Dhungel, R., Aiken, R., Colaizzi, P. D., Lin, X., Baumhardt, R. L., Evett, S. R., . . . O’Brien, D. (2019). Increased Bias in Evapotranspiration Modeling Due to Weather and Vegetation Indices Data Sources. Agronomy Journal, 111(3), 1407-1424. doi:https://doi.org/10.2134/agronj2018.10.0636

Dhungel, R., Aiken, R., Evett, S. R., Colaizzi, P. D., Marek, G., Moorhead, J. E., . . . Lin, X. (2021). Energy Imbalance and Evapotranspiration Hysteresis Under an Advective Environment: Evidence From Lysimeter, Eddy Covariance, and Energy Balance Modeling. Geophysical Research Letters, 48(1), e2020GL091203. doi:https://doi.org/10.1029/2020GL091203

Dhungel, R., Aiken, R., Lin, X., Kenyon, S., Colaizzi, P. D., Luhman, R., . . . Brauer, D. K. (2020). Restricted water allocations: Landscape-scale energy balance simulations and adjustments in agricultural water applications. Agricultural water management, 227, 105854. doi:https://doi.org/10.1016/j.agwat.2019.105854

Evett, S. R., Colaizzi, P. D., Lamm, F. R., O’Shaughnessy, S. A., Heeren, D. M., Trout, T. J., . . . Lin, X. (2020). Past, Present, and Future of Irrigation on the U.S. Great Plains. Transactions of the ASABE, 63(3), 703-729. doi:https://doi.org/10.13031/trans.13620

Gowda, P., Bailey, R., Kisekka, I., Lin, X., & Uddameri, V. (2019). Featured Series Introduction: Optimizing Ogallala Aquifer Water Use to Sustain Food Systems. JAWRA Journal of the American Water Resources Association, 55(1), 3-5. doi:https://doi.org/10.1111/1752-1688.12719

Haacker, E. M. K., Sharda, V., Cano, A. M., Hrozencik, R. A., Núñez, A., Zambreski, Z., . . . Waskom, R. (2019). Transition Pathways to Sustainable Agricultural Water Management: A Review of Integrated Modeling Approaches. JAWRA Journal of the American Water Resources Association, 55(1), 6-23. doi:10.1111/1752-1688.12722

Kutikoff, S., Lin, X., Evett, S., Gowda, P., Moorhead, J., Marek, G., . . . Brauer, D. (2019). Heat storage and its effect on the surface energy balance closure under advective conditions. Agricultural and Forest Meteorology, 265, 56-69. doi:https://doi.org/10.1016/j.agrformet.2018.10.018

Kutikoff, S., Lin, X., Evett, S. R., Gowda, P., Brauer, D., Moorhead, J., . . . Owensby, C. (2021). Water vapor density and turbulent fluxes from three generations of infrared gas analyzers. Atmos. Meas. Tech., 14(2), 1253-1266. doi:10.5194/amt-14-1253-2021

Lin, X., Harrington, J., Ciampitti, I., Gowda, P., Brown, D., & Kisekka, I. (2017). Kansas Trends and Changes in Temperature, Precipitation, Drought, and Frost-Free Days from the 1890s to 2015. Journal of Contemporary Water Research & Education, 162(1), 18-30. doi:https://doi.org/10.1111/j.1936-704X.2017.03257.x

Moberly, J. T., Aiken, R. M., Lin, X., Schlegel, A. J., Baumhardt, R. L., & Schwartz, R. C. (2017). Crop Water Production Functions of Grain Sorghum and Winter Wheat in Kansas and Texas. Journal of Contemporary Water Research & Education, 162(1), 42-60. doi:https://doi.org/10.1111/j.1936-704X.2017.03259.x

Rouhi Rad, M., Araya, A., & Zambreski, Z. T. (2020). Downside risk of aquifer depletion. Irrigation Science, 38(5), 577-591. doi:10.1007/s00271-020-00688-x

Zambreski, Z. T., Lin, X., Aiken, R. M., Kluitenberg, G. J., & Pielke Sr, R. A. (2018). Identification of hydroclimate subregions for seasonal drought monitoring in the U.S. Great Plains. Journal of Hydrology, 567, 370-381. doi:https://doi.org/10.1016/j.jhydrol.2018.10.013

Zhang, T., Mahmood, R., Lin, X., & Pielke, R. A. (2019). Irrigation impacts on minimum and maximum surface moist enthalpy in the Central Great Plains of the USA. Weather and Climate Extremes, 100197. doi:https://doi.org/10.1016/j.wace.2019.100197

Zhang, Y., Gowda, P., Brown, D., Rice, C., Zambreski, Z., Kutikoff, S., & Lin, X. (2020). Time-varying trends in frost indicators in the U.S. Southern Great Plains. International Journal of Climatology, n/a(n/a). doi:https://doi.org/10.1002/joc.6803

Zhang, Y., Lin, X., Gowda, P., Brown, D., Zambreski, Z., & Kutikoff, S. (2019). Recent Ogallala Aquifer Region Drought Conditions as Observed by Terrestrial Water Storage Anomalies from GRACE. JAWRA Journal of the American Water Resources Association, 55(6), 1370-1381. doi:https://doi.org/10.1111/1752-1688.12798