Informing Volunteer Water Quality Monitoring Program Design and Watershed Planning: Case Study of StreamSmart Data Analysis in the Upper White River Basin, Arkansas

被引:1
|
作者
Grantz, Erin E. [1 ]
Haggard, Brian [1 ,2 ]
机构
[1] Univ Arkansas, Arkansas Water Resources Ctr, Div Agr, Fayetteville, AR 72704 USA
[2] Univ Arkansas, Biol & Agr Engn Dept, Fayetteville, AR USA
关键词
Volunteer monitoring; water quality; watershed management; LAND-USE; HABITAT; MACROINVERTEBRATES; BIAS;
D O I
10.1111/j.1936-704X.2022.3380.x
中图分类号
TV21 [水资源调查与水利规划];
学科分类号
081501 ;
摘要
The watershed group H(2)Ozarks founded the StreamSmart Citizen Science Program to establish baseline and long-term water quality data for the Upper White River Basin, Arkansas. StreamSmart volunteers collect water samples and conduct habitat and macroinvertebrate community assessments at >20 sites across a land use-land cover (LULC) gradient. Since 2020, H(2)Ozarks has adaptively assessed the program to ensure that the investment in water quality data meets core goals, with particular interest in planning tools and aligning expectations of volunteer effort with the level of training and support. Study objectives were to use StreamSmart data to 1) facilitate understanding of water quality response to stressors in the basin using a range of methods (Spearman rank correlation, non-parametric changepoint analysis, and categorical and regression tree analysis) and 2) explore implications for program design and watershed planning. Water chemistry-LULC relationships were in-line with prior regional studies, as well as global patterns. Detected thresholds and hierarchy provide potential targets for managing LULC change to protect water quality, but further analysis is warranted to refine these relationships. Macroinvertebrate stressor-response was most detectable for sensitive and less sensitive taxa and for habitat index components, suggesting potential to streamline these programmatic elements. Study findings for StreamSmart should also be informative for other small-scale volunteer monitoring programs with limited resources, but which actively evaluate the types of data and program activities that yield a maximum scientific return on investment.
引用
收藏
页码:46 / 62
页数:17
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