Browsing by Subject "Hydrologic Modeling"
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Item Advanced Technology for Railway Hydraulic Hazard Forecasting(2012-12-05) Huff, William Edward 1988-Railroad bridges and culverts in the United States are often subject to extreme floods, which have been known to washout sections of track and ultimately lead to derailments. The potential for these events is particularly high in the western U.S. due to the lack of data, inadequate radar coverage, and the high spatial and temporal variability of storm events and terrain. In this work, a hydrologic model is developed that is capable of effectively describing the rainfall-runoff relationship of extreme thunderstorms in arid and semi-arid regions. The model was calibrated and validated using data from ten storms at the semi-arid Walnut Gulch Experimental Watershed. A methodology is also proposed for reducing the amount of raingages required to provide acceptable inputs to the hydrologic model, and also determining the most appropriate placement location for these gages. Results show that the model is capable of reproducing peak discharges, peak timings, and total volumes to within 22.1%, 12 min, and 32.8%, respectively. Results of the gage reduction procedure show that a decrease in the amount of raingages used to drive the model results in a disproportionally smaller decrease in model accuracy. Results also indicate that choosing gages using the minimization of correlation approach that is described herein will lead to an increase in model accuracy as opposed to selecting gages on a random basis.Item Development of indices for agricultural drought monitoring using a spatially distributed hydrologic model(Texas A&M University, 2005-11-01) Narasimhan, BalajiFarming communities in the United States and around the world lose billions of dollars every year due to drought. Drought Indices such as the Palmer Drought Severity Index (PDSI) and Standardized Precipitation Index (SPI) are widely used by the government agencies to assess and respond to drought. These drought indices are currently monitored at a large spatial resolution (several thousand km2). Further, these drought indices are primarily based on precipitation deficits and are thus good indicators for monitoring large scale meteorological drought. However, agricultural drought depends on soil moisture and evapotranspiration deficits. Hence, two drought indices, the Evapotranspiration Deficit Index (ETDI) and Soil Moisture Deficit Index (SMDI), were developed in this study based on evapotranspiration and soil moisture deficits, respectively. A Geographical Information System (GIS) based approach was used to simulate the hydrology using soil and land use properties at a much finer spatial resolution (16km2) than the existing drought indices. The Soil and Water Assessment Tool (SWAT) was used to simulate the long-term hydrology of six watersheds located in various climatic zones of Texas. The simulated soil water was well-correlated with the Normalized Difference Vegetation Index NDVI (r ~ 0.6) for agriculture and pasture land use types, indicating that the model performed well in simulating the soil water. Using historical weather data from 1901-2002, long-term weekly normal soil moisture and evapotranspiration were estimated. This long-term weekly normal soil moisture and evapotranspiration data was used to calculate ETDI and SMDI at a spatial resolution of 4km ?? 4km. Analysis of the data showed that ETDI and SMDI compared well with wheat and sorghum yields (r > 0.75) suggesting that they are good indicators of agricultural drought. Rainfall is a highly variable input both spatially and temporally. Hence, the use of NEXRAD rainfall data was studied for simulating soil moisture and drought. Analysis of the data showed that raingages often miss small rainfall events that introduce considerable spatial variability among soil moisture simulated using raingage and NEXRAD rainfall data, especially during drought conditions. The study showed that the use of NEXRAD data could improve drought monitoring at a much better spatial resolution.