Irrigation activities are a major control on water movement and storage in irrigated river valleys in the Intermountain West, USA. Particularly in dry years, surface water diversions can deplete streams over the summer irrigation season, leading to more variable stream temperatures and increased risk for resident aquatic species. Cooler lateral inflows derived from irrigation activities can mitigate the impacts of depletion by buffering main channel stream temperatures. Given the increasing susceptibility of depleted streams to climate and land use changes, understanding stream temperature patterns and controls in these systems is critical. We used intensive field monitoring over three summers and thermal aerial imagery to characterize stream temperature patterns and irrigation influences in a 2.5 km reach of a small agricultural stream in northern Utah. Considering variable hydrology, weather, channel morphology, diversions, and lateral inflows we found stream temperatures to be relatively insensitive to flow depletion or lateral inflows in a wet year but very sensitive in drier years. Irrigation-related lateral inflows reduced longitudinal warming and diel variability during drier years and at times prevented temperatures from reaching stressful or lethal limits. Reaches with substantial lateral inflow contributions also had a greater areal proportion of low temperatures and spatial temperature diversity. These trends were enhanced by differences in channel morphology, with greater spatial and temporal variability in multi-thread than single-thread reaches. Study results highlight critical flow and weather conditions driving increased temperature variability that will likely become more extreme with additional climate change related reductions in baseflow. Regardless of the cause, this study highlights that decreased instream flows increase the importance of identifying, quantifying, and maintaining lateral inflows to maintain instream temperatures and preservation of these inflows should be considered in future water management decisions.

The era of "big data'' promises to provide new hydrologic insights, and open web-based platforms are being developed and adopted by the hydrologic science community to harness these datasets and data services. This shift accompanies advances in hydrology education and the growth of web-based hydrology learning modules, but their capacity to utilize emerging open platforms and data services to enhance student learning through data-driven activities remains largely untapped. Given that generic equations may not easily translate into local or regional solutions, teaching students to explore how well models or equations work in particular settings or to answer specific problems using real data is essential. This paper introduces an open web-based learning module developed to advance data-driven hydrologic process learning, targeting upper level undergraduate and early graduate students in hydrology and engineering. The module was developed and deployed on the HydroLearn open educational platform, which provides a formal pedagogical structure for developing effective problem-based learning activities. We found that data-driven learning activities utilizing collaborative open web platforms like HydroShare and CUAHSI JupyterHub computational notebooks allowed students to access and work with datasets for systems of personal interest and promoted critical evaluation of results and assumptions. Initial student feedback was generally positive, but also highlights challenges including trouble-shooting and future-proofing difficulties and some resistance to open-source software and programming. Opportunities to further enhance hydrology learning include better articulating the myriad benefits of open web platforms upfront, incorporating additional user-support tools, and focusing methods and questions on implementing and adapting notebooks to explore fundamental processes rather than tools and syntax. The profound shift in the field of hydrology toward big data, open data services and reproducible research practices requires hydrology instructors to rethink traditional content delivery and focus instruction on harnessing these datasets and practices in the preparation of future hydrologists and engineers.