Streamflow and precipitation data and characteristics of selected storms for four stream basins in West Virginia, 2017-2020

In cooperation with the West Virginia Division of Transportation, Department of Highways (WVDOH), precipitation and streamflow were measured at four streamgages in West Virginia to compute time of concentration (Tc) and compare it to Tc estimates made using accepted methods. Precipitation and streamflow data were collected during 2017-2020. Storms were identified and classified through an iterative process relying heavily on inspection of graphs. Three hydrograph time metrics that represent Tc were computed for this study: time to rise, time to recede from a high point on the hydrograph to an inflection on the recession, and the time between an inflection on the hyetograph and an inflection on the recession of the hydrograph (PI-to-RI). Seven-minute running averages were used to compute time metrics for the sites with flow data collected at 1-minute intervals. Storms were designated as beginning when precipitation began. A new storm was designated if six or more hours had passed since the previous rain. Periods of intermittent rain were classified as part of the same storm if breaks were less than six hours. Inspection of graphs confirmed that for all sites and storms, a six-hour break in precipitation was enough time for stormflows to end. Subsequent periods were included in the previous storm until another storm began or until flows reached zero. Cumulative total precipitation was computed for each storm. Storms that did not result in measurable flow were identified and excluded from further analysis. This process through this step resulted in the identification of 529 storms. Storms were then ranked by peak flow. The storms with the smallest peaks and therefore the least relevance for design were discarded. The 50 biggest storms from each site were retained for analysis. Three types of hydrograph time metrics were delineated: time to rise, time to recede, and PI-to-RI. To be counted, the rise needed to be (1) at a steady rate, (2) clearly the result of a specific spate of rain, (3) visually distinct, and (4) representative of a meaningful change in flow magnitude. Time to recede was assessed similarly, with the additional constraint that when repeated or sustained rain fell during the recession and caused flow to rise, the event was excluded. The time between PI-to-RI was determined as the difference between a (1) final inflection on the hyetograph before a visually distinct storm peak and (2) the inflection on the receding limb of the hydrograph from a steep decrease in stormflow to a part of the hydrograph with a flatter slope. Hydrograph events were included in analyses if (1) their maximum values were above the flow threshold for the site, (2) the event was not affected by snow, (3) the slope of the rise or recession was consistent and steady during a relevant part of an event, (4) the flow record during the hydrograph event was complete without estimated values, (5) the event in question represented a meaningful change in flow, (6) for recessions, rain that continued while flow receded was minimal and did not appear to interrupt the recession with secondary rises in flow, and (7) whether changes between successive unit flow measurements during the hydrograph event were primarily either increases or decreases, indicating it was primarily stormflow, or largely stable, which characterized minor rises and recessions that exceeded flow thresholds only because they began when baseflow was already high. Quality-assurance metrics were developed and computed to show how well the hydrograph time metrics met these criteria; these metrics are included in this data release.

本研究与西弗吉尼亚州交通运输部公路局（West Virginia Division of Transportation, Department of Highways, WVDOH）合作，在西弗吉尼亚州的4处河道测流站（streamgage）开展降水与径流观测，以计算汇流时间（time of concentration, Tc），并将实测结果与采用公认方法得到的Tc估算值进行对比。研究时段为2017-2020年，期间收集降水与径流数据。

研究通过高度依赖图形检视的迭代流程识别并分类降雨事件：以降水开始作为一场降雨的起始标志；若两场降雨间隔≥6小时，则判定为新的降雨事件；若间隔＜6小时，则将间歇降雨时段归为同一场降雨。经图形检视确认，所有测站与降雨事件中，6小时的降水间歇足以使径流完全消退，因此后续降雨时段若未超过6小时间隔阈值，则仍归入前一场降雨，直至新的降雨开始或径流归零。

每场降雨的累计总降水量均被计算。未产生可测径流的降雨事件被识别并剔除出后续分析。经此步骤共识别出529场降雨事件。随后按洪峰流量对降雨事件进行排序，剔除洪峰最小、对工程设计相关性最低的事件，最终保留每个测站的前50场大洪峰降雨事件用于分析。

本研究共定义三类表征汇流时间（Tc）的水文过程线（hydrograph）时间指标：涨水历时、从水文过程线峰值点退水至退水段拐点的历时，以及降雨过程线（hyetograph）拐点与水文过程线退水段拐点之间的历时（PI-to-RI）。对于以1分钟间隔采集径流数据的测站，采用7分钟滑动平均法计算其时间指标。退水历时的评估标准与涨水历时类似，但额外要求：若退水期间出现重复或持续降水导致流量回升，则该事件需被排除。

PI-to-RI的时长被定义为：（1）降雨过程线中视觉上可识别的降雨峰值前的最后一个拐点，与（2）水文过程线退水段中，从径流陡降阶段过渡至平缓阶段的拐点，二者之间的时间差。涨水历时需满足四项判定标准：（1）以稳定速率增长；（2）明确对应某一特定降雨时段；（3）视觉特征清晰可辨；（4）能够反映流量量级的实质性变化。

纳入分析的水文过程线事件需满足以下7项条件：
1. 最大流量高于该测站的流量阈值；
2. 事件未受降雪影响；
3. 涨水或退水阶段的坡度保持一致且稳定；
4. 水文过程线事件期间的流量记录完整，无估算值；
5. 该事件代表流量发生了有意义的变化；
6. 退水时段内的持续降水极少，未因流量二次回升干扰退水过程；
7. 水文过程线事件期间的连续单位流量测量值变化主要为单向递增、递减，或整体保持稳定——后者指那些仅因基流（baseflow）水平较高才超过流量阈值的小幅涨退水事件。

研究开发并计算了质量保证指标，用以表征水文过程线时间指标满足上述标准的程度，相关指标已包含在本数据集发布内容中。