SPRING DISCHARGE MONITORING IN LOW-RESOURCE SETTINGS: A CASE STUDY OF CONCEPCIÓN CHIQUIRICHAPA, GUATEMALA

Water springs are the principal source of water for many localities in Central America, including the municipality of Concepción Chiquirichapa in the Western Highlands of Guatemala. Long-term monitoring records are critical for informed water management as well as resource forecasting, though data are scarce and monitoring in low-resource settings presents special challenges. Spring discharge was monitored monthly in six municipal springs during the author’s Peace Corps assignment, from May 2011 to March 2012, and water level height was monitored in two spring boxes over the same time period using automated water-level loggers. The intention of this approach was to circumvent the need for frequent and time-intensive manual measurement by identifying a fixed relationship between discharge and water level. No such relationship was identified, but the water level record reveals that spring yield increased for four months following Tropical Depression 12E in October 2011. This suggests that the relationship between extreme precipitation events and long-term water spring yields in Concepción should be examined further. These limited discharge data also indicate that aquifer baseflow recession and catchment water balance could be successfully characterized if a long-term discharge record were established. This study also presents technical and social considerations for selecting a methodology for spring discharge measurement and highlights the importance of local interest in conducting successful community-based research in intercultural low-resource settings.

Algorithms for spacecraft formation flying navigation based on wireless positioning system measurements

Spacecraft formation flying navigation continues to receive a great deal of interest. The research presented in this dissertation focuses on developing methods for estimating spacecraft absolute and relative positions, assuming measurements of only relative positions using wireless sensors. The implementation of the extended Kalman filter to the spacecraft formation navigation problem results in high estimation errors and instabilities in state estimation at times. This is due tp the high nonlinearities in the system dynamic model. Several approaches are attempted in this dissertation aiming at increasing the estimation stability and improving the estimation accuracy. A differential geometric filter is implemented for spacecraft positions estimation. The differential geometric filter avoids the linearization step (which is always carried out in the extended Kalman filter) through a mathematical transformation that converts the nonlinear system into a linear system. A linear estimator is designed in the linear domain, and then transformed back to the physical domain. This approach demonstrated better estimation stability for spacecraft formation positions estimation, as detailed in this dissertation. The constrained Kalman filter is also implemented for spacecraft formation flying absolute positions estimation. The orbital motion of a spacecraft is characterized by two range extrema (perigee and apogee). At the extremum, the rate of change of a spacecraft’s range vanishes. This motion constraint can be used to improve the position estimation accuracy. The application of the constrained Kalman filter at only two points in the orbit causes filter instability. Two variables are introduced into the constrained Kalman filter to maintain the stability and improve the estimation accuracy. An extended Kalman filter is implemented as a benchmark for comparison with the constrained Kalman filter. Simulation results show that the constrained Kalman filter provides better estimation accuracy as compared with the extended Kalman filter. A Weighted Measurement Fusion Kalman Filter (WMFKF) is proposed in this dissertation. In wireless localizing sensors, a measurement error is proportional to the distance of the signal travels and sensor noise. In this proposed Weighted Measurement Fusion Kalman Filter, the signal traveling time delay is not modeled; however, each measurement is weighted based on the measured signal travel distance. The obtained estimation performance is compared to the standard Kalman filter in two scenarios. The first scenario assumes using a wireless local positioning system in a GPS denied environment. The second scenario assumes the availability of both the wireless local positioning system and GPS measurements. The simulation results show that the WMFKF has similar accuracy performance as the standard Kalman Filter (KF) in the GPS denied environment. However, the WMFKF maintains the position estimation error within its expected error boundary when the WLPS detection range limit is above 30km. In addition, the WMFKF has a better accuracy and stability performance when GPS is available. Also, the computational cost analysis shows that the WMFKF has less computational cost than the standard KF, and the WMFKF has higher ellipsoid error probable percentage than the standard Measurement Fusion method. A method to determine the relative attitudes between three spacecraft is developed. The method requires four direction measurements between the three spacecraft. The simulation results and covariance analysis show that the method’s error falls within a three sigma boundary without exhibiting any singularity issues. A study of the accuracy of the proposed method with respect to the shape of the spacecraft formation is also presented.