ABSTRACT:

Hydroclimatic extremes such as droughts and floods pose major challenges for water management across Kansas and the broader Great Plains. Climate models have limited ability to predict these extremes, making historical analysis essential for understanding how such events may evolve in the future. Compound extremes — including recurring wet or dry conditions across consecutive years and "weather whiplash" transitions between opposite extremes — add further complexity and uncertainty.
This project aimed to better understand historical patterns and trends in seasonal to annual hydroclimatic extremes in Kansas, organized around three objectives. The first objective focused on quantifying spatiotemporal patterns in compound extremes. Historical precipitation data from meteorological stations and the gridded PRISM dataset were compiled for Kansas and surrounding areas contributing to federal reservoirs. A comparison of these sources confirmed that PRISM accurately reproduces annual and seasonal precipitation totals, with minimal bias in identifying extremes. PRISM was therefore selected for statewide analysis across a 128-year period (1895–2023). A percentile-based classification system was developed to identify six types of extremes: isolated wet and dry events, recurring wet-to-wet and dry-to-dry sequences, and whiplash transitions in both directions, producing a 4 km resolution database of precipitation extremes.
The second objective analyzed changes in compound extremes across water management areas. Annual precipitation is increasing over much of Kansas, with significant long-term wetting trends across 40.3% of the state, driven primarily by increased spring rainfall. Both isolated wet and recurring wet-to-wet extremes have become more widespread since approximately 1980. Results were summarized for 148 management-relevant areas including federal reservoir watersheds, groundwater management districts, and Regional Advisory Committee boundaries. Western reservoirs show persistent drying, while eastern reservoirs exhibit increasingly wet conditions. Whiplash events occur most frequently in summer and are more common in northern and eastern reservoirs. The frequency of wet extremes since reservoir construction is significantly correlated with loss in reservoir storage capacity.
The third objective produced an interactive web-based tool built on ESRI Experience Builder, allowing users to explore visualizations of historical precipitation and extremes for all 148 management boundaries and download the underlying data for further use.

ABSTRACT:

This manuscript shares data and code used in the manuscript:
Ndlovu W, S Zipper, T Foster (2025). Assessing the effectiveness of irrigator-driven groundwater conservation programs to drought: a case study of the northwestern Kansas Local Enhanced Management Areas. Agricultural Water Management.
Please cite the manuscript if you use this data/code.

Manuscript abstract:
Groundwater pumping for irrigation has led to declining groundwater levels in agricultural areas around the world, including the U.S. High Plains Aquifer. Here, we used a process-based crop model, AquaCrop, to assess the effectiveness of different irrigation management strategies during a synthetic multi-year drought. We focused on the Groundwater Management District 4 Local Enhanced Management Area (GMD-4 LEMA), a regional groundwater conservation program in the northwestern Kansas portion of the High Plains Aquifer. We first calibrated corn and sorghum AquaCrop models to simulate yield and irrigation using the Particle Swarm Optimization algorithm, and then applied a novel difference-based bias correction method to improve performance. We found that the corn models outperformed the sorghum models, likely due to limited observational sorghum data. However, both models performed satisfactorily during drought periods. We then evaluated the effectiveness of the groundwater conservation program in reducing water use during a synthetic five-year drought under three irrigation strategies. During the synthetic drought, corn irrigation requirements were roughly double those of sorghum. However, even simulated corn irrigation needs were generally less than current water allocations, supporting past work that suggests the current GMD-4 LEMA water allocations are ineffective for conserving water. Model simulations also indicated that water conservation strategies could reduce annual irrigation requirements without a substantial reduction in crop yield through improved water use efficiency, suggesting that lower allocations would be a feasible approach to reduce irrigation and slow groundwater decline rates.

ABSTRACT:

This resource contains the data supporting the paper "The drying regimes of non-perennial rivers" currently in preparation. The data provided with this release contains streamflow drying characteristics for over 25,000 discrete drying events at 894 non-perennial U.S. Geological Survey GAGES-II (Falcone, 2011) gaging stations for years 1979 to 2019.

The columns of the dataset associated with stream drying are described below:

gage = USGS station ID (STAID)
event_id = unique drying event identifier
dec_lat_va = Latitude in decimal degrees of streamgage location
dec_long_va = Longitude in decimal degrees of streamgage location
peak_date = Day of year that peak occurred marking the beginning of drying event
peak_value = Discharge value in cubic feet per second of peak marking the beginning of drying event
peak_quantile = Discharge quantile value of peak marking the beginning of drying event
peak2zero = Number of days from peak_date to dry_date_start
drying_rate = The streamflow recession rate defined as the slope in log-log space of −d(discharge)/d(time) plotted against discharge
p_value = P-value reported from the fit of a linear model for discharge and time in log-log space
calendar_year = The calendar year in which the first no flow of the drying event occurred
season = The season in which the first no flow of the drying event occurred (April, May, June = spring; July, August, September = summer; October, November, December = fall; January, February, March = winter)
meteorologic_year = The meteorologic year in which the first no flow of the drying event occurred. Meteorologic years begin April 1 and conclude Mach 30.
dry_date_start = Julian day of the first no flow occurrence associated with the drying event
dry_date_mean = Julian day at the center of continuous no flow associated with the drying event
dry_dur = Duration (in days) of continuous no flow associated with the drying event

For information on the additional columns of data supplied that were used to run random forest models please see the section below "Additional Metadata."

References:
- Abatzoglou, J. T. (2013), Development of gridded surface meteorological data for ecological applications and modelling. Int. J. Climatol., 33: 121–131.
- Broxton, P., X. Zeng, and N. Dawson. 2019. Daily 4 km Gridded SWE and Snow Depth from Assimilated In-Situ and Modeled Data over the Conterminous US, Version 1. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. doi: https://doi.org/10.5067/0GGPB220EX6A.
- Falcone, J. A. (2011). GAGES-II: Geospatial attributes of gages for evaluating streamflow (Digit. Spat. Data set). Reston, VA: U.S. Geological Survey.
- Gleeson, T., Moosdorf, N., Hartmann, J., & Van Beek, L. P. H. (2014). A glimpse beneath earth's surface: GLobal HYdrogeology MaPS (GLHYMPS) of permeability and porosity. Geophysical Research Letters, 41(11), 3891-3898.
- Hammond, J. C., Zimmer, M., Shanafield, M., Kaiser, K., Godsey, S. E., Mims, M. C., ... & Allen, D. C. Spatial patterns and drivers of non‐perennial flow regimes in the contiguous US. Geophysical Research Letters, 2020GL090794.
- Hengl, T., Mendes de Jesus, J., Heuvelink, G. B., Ruiperez Gonzalez, M., Kilibarda, M., Blagotić, A., ... & Kempen, B. (2017). SoilGrids250m: Global gridded soil information based on machine learning. PLoS one, 12(2), e0169748.
- Homer, C. H., Fry, J. A., & Barnes, C. A. (2012). The national land cover database. US Geological Survey Fact Sheet, 3020(4), 1-4.
- Sohl, T.L., Reker, Ryan, Bouchard, Michelle, Sayler, Kristi, Dornbierer, Jordan, Wika, Steve, Quenzer, Rob, and Friesz, Aaron, 2018a, Modeled historical land use and land cover for the conterminous United States: 1938-1992: U.S. Geological Survey data release, https://doi.org/10.5066/F7KK99RR.
- Sohl, T.L., Sayler, K.L., Bouchard, M.A., Reker, R.R., Freisz, A.M., Bennett, S.L., Sleeter, B.M., Sleeter, R.R., Wilson, T., Soulard, C., Knuppe, M., and Van Hofwegen, T., 2018b, Conterminous United States Land Cover Projections - 1992 to 2100: U.S. Geological Survey data release, https://doi.org/10.5066/P95AK9HP.