Regionally scaled assessments of hydrologic alteration for small streams and its effects on freshwater taxa are often inhibited by a low number of stream gages. To overcome this limitation, we paired modeled estimates of hydrologic alteration to a benthic macroinvertebrate index of biotic integrity data for 4522 stream reaches across the Chesapeake Bay watershed. Using separate random-forest models, we predicted flow status (inflated, diminished, or indeterminant) for 12 published hydrologic metrics (HMs) that characterize the main components of flow regimes. We used these models to predict each HM status for each stream reach in the watershed, and linked predictions to macroinvertebrate condition samples collected from streams with drainage areas less than 200 km². Flow alteration was calculated as the number of HMs with inflated or diminished status and ranged from 0 (no HM inflated or diminished) to 12 (all 12 HMs inflated or diminished). When focused solely on the stream condition and flow-alteration relationship, degraded macroinvertebrate condition was, depending on the number of HMs used, 3.8–4.7 times more likely in a flow-altered site; this likelihood was over twofold higher in the urban-focused dataset (8.7–10.8), and was never significant in the agriculture-focused dataset. Logistic regression analysis using the entire dataset showed for every unit increase in flow-alteration intensity, the odds of a degraded condition increased 3.7%. Our results provide an indication of whether altered streamflow is a possible driver of degraded biological conditions, information that could help managers prioritize management actions and lead to more effective restoration efforts.

小型河流水位计通常会抑制对小河水量的水文变化及其对淡水分类群的影响的区域性评估。为了克服这一局限性，我们将切萨皮克湾流域的4522条溪流的水文蚀变模型估计值与生物完整性数据的底栖大无脊椎动物指数配对。使用单独的随机森林模型，我们预测了表征流态主要组成部分的12种已发布水文度量标准（HM）的流量状态（膨胀，减少或不确定）。我们使用这些模型来预测流域中每条河流到达的每个HM状态，并将预测与从流域面积小于200 km ^2的河流收集的大型无脊椎动物条件样本相关联。流量变化以状态为已膨胀或减少的HM的数量计算，范围为0（无HM膨胀或减小的HM）到12（所有12个HM膨胀或减小的HM）。当仅关注河流状况和流量变化关系时，根据所用重金属的数量，退化的大型无脊椎动物状况在流量发生变化的地点的可能性高3.8-4.7倍。在以城市为中心的数据集中，这种可能性要高出两倍多（8.7-10.8），而在以农业为中心的数据集中则没有显着性。使用整个数据集进行的Logistic回归分析表明，流量改变强度每增加一个单位，退化情况的几率就会增加3.7％。我们的研究结果表明，流量变化是否可能是导致生物学条件下降的原因，