Many karst aquifers are rapidly filled and depleted and therefore are likely to be susceptible to changes in short-term climate variability. Here we explore methods that could be applied to model site-specific hydraulic responses, with the intent of simulating these responses to different climate scenarios from high-resolution climate models. We compare hydraulic responses (spring flow, groundwater level, stream base flow, and cave drip) at several sites in two karst aquifers: the Edwards aquifer (Texas, USA) and the Madison aquifer (South Dakota, USA). A lumped-parameter model simulates nonlinear soil moisture changes for estimation of recharge, and a time-variant convolution model simulates the aquifer response to this recharge. Model fit to data is 2.4% better for calibration periods than for validation periods according to the Nash–Sutcliffe coefficient of efficiency, which ranges from 0.53 to 0.94 for validation periods. We use metrics that describe the shapes of the impulse-response functions (IRFs) obtained from convolution modeling to make comparisons in the distribution of response times among sites and between aquifers. Time-variant IRFs were applied to 62% of the sites. Principal component analysis (PCA) of metrics describing the shapes of the IRFs indicates three principal components that together account for 84% of the variability in IRF shape: the first is related to IRF skewness and temporal spread and accounts for 51% of the variability; the second and third largely are related to time-variant properties and together account for 33% of the variability. Sites with IRFs that dominantly comprise exponential curves are separated geographically from those dominantly comprising lognormal curves in both aquifers as a result of spatial heterogeneity. The use of multiple IRF metrics in PCA is a novel method to characterize, compare, and classify the way in which different sites and aquifers respond to recharge. As convolution models are developed for additional aquifers, they could contribute to an IRF database and a general classification system for karst aquifers

Abstract. The Rainfall-Response Aquifer and Watershed Flow Model (RRAWFLOW) is a lumped-parameter model that simulates streamflow, spring flow, groundwater level, or solute transport for a measurement point in response to a system input of precipitation, recharge, or solute injection. I introduce the first version of RRAWFLOW available for download and public use and describe additional options. The open-source code is written in the R language and is available at http://sd.water.usgs.gov/projects/RRAWFLOW/ RRAWFLOW.html along with an example model of streamflow. RRAWFLOW includes a time-series process to estimate recharge from precipitation and simulates the response to recharge by convolution, i.e., the unit-hydrograph approach. Gamma functions are used for estimation of parametric impulse-response functions (IRFs); a combination of two gamma functions results in a double-peaked IRF. A spline fit to a set of control points is introduced as a new method for estimation of nonparametric IRFs. Several options are included to simulate time-variant systems. For many applications, lumped models simulate the system response with equal accuracy to that of distributed models, but moreover, the ease of model construction and calibration of lumped models makes them a good choice for many applications (e.g., estimating missing periods in a hydrologic record). RRAWFLOW provides professional hydrologists and students with an accessible and versatile tool for lumped-parameter modeling.

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