James J. Niemeier

RF communications in underwater wireless sensor networks

We investigate the propagation of radio waves underwater and between water and air to facilitate setting up hybrid wireless sensor networks with both surface and subsurface nodes. Our investigation includes signal attenuation, antenna radiation patterns, multipath due to reflections from the surface and substrate, noise, and reflection losses transmitting from one medium to another.

Real-Time Flood Forecasting and Information System for the State of Iowa

AbstractThe Iowa Flood Center (IFC), established following the 2008 record floods, has developed a real-time flood forecasting and information dissemination system for use by all Iowans. The system complements the operational forecasting issued by the National Weather Service, is based on sound scientific principles of flood genesis and spatial organization, and includes many technological advances. At its core is a continuous rainfall–runoff model based on landscape decomposition into hillslopes and channel links. Rainfall conversion to runoff is modeled through soil moisture accounting at hillslopes. Channel routing is based on a nonlinear representation of water velocity that considers the discharge amount as well as the upstream drainage area. Mathematically, the model represents a large system of ordinary differential equations organized to follow river network topology. The IFC also developed an efficient numerical solver suitable for high-performance computing architecture. The solver allows the IF...

Soil Moisture Model Calibration and Validation: An ARS Watershed on the South Fork Iowa River

AbstractSoil moisture monitoring with in situ technology is a time-consuming and costly endeavor for which a method of increasing the resolution of spatial estimates across in situ networks is necessary. Using a simple hydrologic model, the estimation capacity of an in situ watershed network can be increased beyond the station distribution by using available precipitation, soil, and topographic information. A study site was selected on the Iowa River, characterized by homogeneous soil and topographic features, reducing the variables to precipitation only. Using 10-km precipitation estimates from the North American Land Data Assimilation System (NLDAS) for 2013, high-resolution estimates of surface soil moisture were generated in coordination with an in situ network, which was deployed as part of the Iowa Flood Studies (IFloodS). A simple, bucket model for soil moisture at each in situ sensor was calibrated using four precipitation products and subsequently validated at both the sensor for which it was cal...

Deployment and Performance Analyses of High-Resolution Iowa XPOL Radar System during the NASA IFloodS Campaign

AbstractThis article presents the data collected and analyzed using the University of Iowa’s X-band polarimetric (XPOL) radars that were part of the spring 2013 hydrology-oriented Iowa Flood Studies (IFloodS) field campaign, sponsored by NASA’s Global Precipitation Measurement (GPM) Ground Validation (GV) program. The four mobile radars have full scanning capabilities that provide quantitative estimation of the rainfall at high temporal and spatial resolutions over experimental watersheds. IFloodS was the first extensive test of the XPOL radars, and the XPOL radars demonstrated their field worthiness during this campaign with 46 days of nearly uninterrupted, remotely monitored, and controlled operations. This paper presents detailed postcampaign analyses of the high-resolution, research-quality data that the XPOL radars collected. The XPOL dual-polarimetric products and rainfall are compared with data from other instruments for selected diverse meteorological events at high spatiotemporal resolutions from...

Using Cellular Network Signal Strength to Monitor Vegetation Characteristics

We demonstrate a new application for cellular communications equipment in monitoring vegetation. We analyze how the vegetation in a cornfield affects the received signal power recorded at cell modems in the field, and we show that the received signal power exhibited long-term and diurnal patterns related to the properties of the vegetation biomass. A novel aspect of this letter is that we recorded the signal strength data at the cellular modem in the field rather than at a cell phone tower and therefore does not require the cooperation of the cell tower owner.

Introducing a sensor to measure budburst and its environmental drivers

Budburst is a key adaptive trait that can help us understand how plants respond to a changing climate from the molecular to landscape scale. Despite this, acquisition of budburst data is constrained by a lack of information at the plant scale on the environmental stimuli associated with the release of bud dormancy. Additionally, to date, little effort has been devoted to phenotyping plants in natural populations due to the challenge of accounting for the effect of environmental variation. Nonetheless, natural selection operates on natural populations, and investigation of adaptive phenotypes in situ is warranted and can validate results from controlled laboratory experiments. To identify genomic effects on individual plant phenotypes in nature, environmental drivers must be concurrently measured, and characterized. Here, we designed and evaluated a sensor to meet these requirements for temperate woody plants. It was designed for use on a tree branch to measure the timing of budburst together with its key environmental drivers; temperature, and photoperiod. Specifically, we evaluated the sensor through independent corroboration with time-lapse photography and a suite of environmental sampling instruments. We also tested whether the presence of the device on a branch influenced the timing of budburst. Our results indicated the following: the temperatures measured by the budburst sensor’s digital thermometer closely approximated the temperatures measured using a thermocouple touching plant tissue; the photoperiod detector measured ambient light with the same accuracy as did time lapse photography; the budburst sensor accurately detected the timing of budburst; and the sensor itself did not influence the budburst timing of Populus clones. Among other potential applications, future use of the sensor may provide plant phenotyping at the landscape level for integration with landscape genomics.

Design considerations and signal processing for a microwave rain gauge sensor

Previous works have validated the concept of a microwave rain gauge that operates as follows. With a microwave Doppler motion sensor, the Doppler shift created by falling rain drops is measured. One can then relate the corresponding fall velocity to rain rate. However, the available Doppler motion sensors are lacking in several aspects. Here we address the important electronic design and signal processing considerations related to a microwave-based rain gauge.

Antennas for mussel-based underwater biological sensor networks in rivers

Researchers are working on using freshwater mussels as biological sensors. A sensor placed on the mussel detects the mussels rhythmic opening and closing, or gape. Changes in the gape can indicate changes in the mussels environment. We plan to attach gape sensors, microcontrollers, and radios to mussels and place them back in their natural environment. Small, inexpensive radios operating in the Industrial, Scientific and Medical (ISM) bands will provide the physical link of an underwater wireless sensor network (WSN). Despite the attenuation radio waves experience in water, the low cost of these radios should allow us to deploy enough to set up a reliable communications network. While commercially available radios can be used underwater with waterproofing, antennas designed for use in air are unsuitable for use in water, because of the different electromagnetic properties of water and air. We designed dipole, loop, and folded dipole antennas for use in water and attached these to transmitters. We measured the power transmitted by the antennas by immersing the transmitters in a tank of water and measuring the received power at different distances using a small dipole antenna attached to a spectrum analyzer. The distance between the antennas was precisely controlled with a motorized xy positioner.

Bridge-Mounted River Stage Sensors (BMRSS)

We have developed a robust sensor for mounting on bridges over rivers and streams. These bridge-mounted river stage sensors (BMRSS) make periodic measurements of the distance from the sensor to the water level below. Properly interpreted, these measurements provide river-stage information, data of great importance to society and crucial to effective flood forecasting. The traditional approach to river stage measurement is the installation of pipes in rivers, digging stilling wells, and the construction of attendant brick-and-mortar infrastructure. The cost of this approach limits the deployment to larger rivers. In most instances, river-stage data from smaller tributaries are few, even though such data can greatly enhance the quality of flood-forecasting models’ outputs. In contrast, BMRSS units are an order of magnitude less expensive and allow for widespread deployment. BMRSS units incorporate an ultrasonic distance-measuring module, a solar panel/battery/charge controller, and a GPS receiver. In recent years, the Internet access through commercial cellular networks has become ubiquitous, even in most rural areas. BMRSS units incorporate cell modems and transmit data through the Internet to servers at the Iowa Flood Center. Here, the data are ingested into relational databases and made available to flood forecasting models and information systems. We have deployed and operated more than 220 BMRSS units across Iowa, many for several years continuously.

Environmental sensor network data packaging and transmission via cellular networks

Here we present a part of our work on environmental sensing networks. Specifically, we focus on the data packaging and transmission from a field site to an ingest server. Such networks gather environmental data and periodically transmit it via the commercial cellular data networks. The ingest server processes the data, populates a relational data base, and makes data accessible through a Web interface.