METHODS
This study presents an approach to extract, quantify, and explain three
temporal patterns within SC time series, which are related to
streamwater responses to rain events. These patterns are found in
chemographs produced from in situ sensors across numerous New
Hampshire lotic systems (Inserillo et al. 2017). The first of these
patterns is a rapid increase in SC near the beginning of a precipitation
event, on the rising limb of a hydrograph, known as a solute flush
(Figure 1). The second is the subsequent dilution of SC, as low SC water
(i.e., precipitation) mixes with higher SC water (i.e., groundwater);
and the third is the recovery of SC as that low conductivity water
leaves the catchment and the streamwater returns to a SC resembling
groundwater. Although flushing responses do not occur in all streams,
dilutions and their subsequent recoveries after a precipitation event
are common (e.g., Inserillo et al. 2017).
We developed an algorithm to consistently and objectively locate these
temporal patterns in streamwater SC, quantify the FSCand DSC behavior, and calculate the RSCthat follows. This process was sequential: a flush following the onset
of rain, a dilution following a flush, if one was present, and a
recovery following a dilution, if one was present. We then compared
those streamwater responses to various environmental conditions
surrounding the periods in which they occurred, to understand how such
independent variables related to each chemograph pattern. The
environmental conditions examined were based upon precipitation,
antecedent moisture, and the season in which the precipitation event
occurred.
Precipitation variables included the total amount of precipitation
(PT), the intensity at which it fell
(IP), and maximum precipitation intensity per 20-minute
interval (IP,max). Precipitation that occurred after a
flush reached its peak would not influence the FSC;
likewise, with the maximum dilution and DSC. So, for
both flushing and dilution responses, each precipitation variable was
analyzed only from the beginning of the storm to the point in time at
which the response occurred. Analysis of the RSCincluded the precipitation of the entire event, as the tail end of a
storm presumably impacts the rate at which SC recovers, and as the
recovery is an expression low SC water leaving the system or becoming
chemically similar to stored water.
Antecedent moisture variables included the length of the inter-storm
period (ISP) and the cumulative vapor pressure deficit (ΣVPD) during
that period of time. The ISP was determined by the amount of time
between the first measurement of rain for a precipitation event and the
last measurement of rain for the previous event. The ΣVPD for that
period of time was indicative of the intensity of drying pressure and
was determined by summing the vapor pressure deficit (VPD) over this
ISP. VPD was calculated by subtracting vapor pressure (VP) from
saturated vapor pressure (VPS). VP was calculated by
multiplying relative humidity (RH) by VPS.
VPS was calculated using
where T was air temperature in °C, and the resulting VPSwas in kPa (Bolton 1980). These temperature and RH data were measured at
20-minute intervals, and all subsequent calculations maintained this
time step.
Variables of seasonal impact were the day of year (DoY) on which the
precipitation event began and the median air temperature
(TA) of the day on which the event began. In both
instances the day on which the event began was the calendar day that the
first rain measurement of that precipitation event occurred.