California relies extensively on two pieces of natural infrastructure for water storage and conveyance: the Sierra Nevada mountains and the Sacramento-San Joaquin Delta. The mountains act as a natural reservoir, storing winter precipitation throughout the year and slowly releasing it during the summer when demand is high. Snowmelt is then routed through the Sacramento-San Joaquin Delta to the state water project, which distributes water throughout California. Despite the importance of these natural environments for the state's water resources, the in-situ infrastructure for water monitoring is limited. The existing distribution of real-time snow-sensors is present only in flat, low-elevation regions, which does not adequately capture the spatial variability of snow depth in complex terrain. To address this, the state relies on monthly synoptic snow surveys, which require trained surveyors to manually measure the snow depth at locations across the Sierra Nevada. This process provides dense in-situ data but is labor intensive and temporally sparse. It also does not capture other important variables, such as soil moisture and radiative forcing, which are necessary for next-generation hydrologic modeling. In the Delta, in-situ measurements are limited to Eulerian sensors, which measure the rate of flow going past a point on shore, but are unable to resolve finer resolution flow fields, or measure properties of the water, such as temperature, turbidity, and salinity. This dissertation explores problems related to the design and optimization of wireless in-situ sensor networks for monitoring the water balance in the Sierra Nevada and flow fields in the Sacramento-San Joaquin Delta. Topics include: optimizing wireless snow-sensor placements using LIDAR data and machine learning, constructing reliable wireless mesh networks in complex terrain, estimating the spatial variability of soil moisture in montane regions from in-situ sensors, and the design and controller optimization of wireless in-situ sensors in the Sacramento-San Joaquin Delta.