Farming 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.

Using ERA40 and independent observations, I assess how well Amazon surface water budget is estimated. ERA40 basin wide annual precipitation (P) agrees with observations showing an underestimation of 10%, whereas runoff (R) is underestimated by a larger margin (~25%). Observed residual of precipitation and runoff (P-R) is better estimated by ERA40 P-R than actual ET which includes soil moisture nudging. Nudging is necessary during the dry season to produce realistic ET and compensate for low soil moisture recharge during the wet season. Insufficient recharge may be caused by: underestimation of rainfall amount and intensity; a shallow root layer in the model that does not represent the deep soil water reservoir of the Amazonian forest. The physical links between changes in wet season onset and synoptic scale systems are investigated in the second part of my work. A delayed wet season onset is consistent with a decreasing number of cold air incursion (CAI) days in southern Amazon during 1979-2001. CAI variability in southern Amazon is related to SST in the tropical Pacific and Indian Oceans. The first mode of co-variability shows that during El Nio (La Nia) a strong (weak) subtropical jet stream over South America is related to decreased (increased) CAI days during SON. The second mode shows warm western Indian Ocean also related to strong subtropical jet stream. The absence a well defined subpolar jet stream, favors the northward displacement of transient waves into central South America, but shows little response in southern Amazon. CAI days reconstructed from the first and second modes do not present any significant trend in southern Amazon. CAI days reconstructed from the third mode of co-variability reproduces SON observed trend. This mode describes negative (positive) anomalies in CAI days associated with cold (warm) SST anomalies, anomalous wavetrain in the tropical Pacific and Walker Cell displacement that are unfavorable (favorable) to the incursion of CAI into southern Amazon. This mode's temporal evolution correlates with the Pacific Decadal Oscillation (PDO), suggesting that its recent gradual signal shift reflected on the interannual response of southern Pacific atmospheric patterns, hence on the behavior of transients propagation.

Thesis (M.S.)--Oregon State University, 2010. / Printout. Includes bibliographical references (leaves 66-69). Also available on the World Wide Web.

Thesis (Ph. D.)--University of Hong Kong, 2010. / Includes bibliographical references (p. 199-216). Also available in print.

Thesis (M.S.)--West Virginia University, 2003. / Title from document title page. Document formatted into pages; contains vii, 73 p. : ill. (some col.), maps (some col.). Includes abstract. Includes bibliographical references (p. 71-73).

This research estimates nitrogen removal from stormwater runoff using a denitrifying bioretention system using the USEPA Storm Water Management Model Version 5 (SWMM-5). SWMM-5 has been used to help planners make better decisions since its development in 1971. A conventional bioretention system is a type of Low Impact Development (LID) technology, which designed without a media layer specifically for achieving nitrogen removal. More recently studies have showed that high TN removal efficiencies are possible when incorporating a denitrification media layer. These systems are known as denitrifying bioretention systems, or alternative bioretention systems. LID projects are currently being designed and developed in Sarasota County, Florida. These projects include a bioretention cell retrofit project on Venice East Blvd., in Venice, FL where thirteen bioretention cells will be developed. Although implementation of LID has already begun in southwest Florida, little research exists on whether these systems are effective at reducing non-point sources of nutrients. Therefore, the overall goal of this research project was to investigate the performance of a proposed bioretention system in Venice, FL to treat non-point sources of nitrogen from stormwater runoff. An alternative bioretention cell (ABC) model was designed to conceptually address water routing through a layered bioretention cell by separating the model into treatment layers- the layers where the nitrification and denitrification reactions are expected to occur within an alternative bioretention system (i.e., nitrification is assumed to occur in the sand media layer, and denitrification in the wood chip media layer). The bioretention cell configuration was based largely on the development plans provided by Sarasota County; however, the configuration incorporated the same electron donor media for denitrification that was used in a prior study (i.e., wood chips). Site-specific input parameters needed to calibrate the ABC model were obtained from laboratory analyses, the literature, and the US Geological website (websoilsurvey.nrcs.usda.gov). Using a mass balance approach, and the hydraulic residence time (HRT) values from the results of a previous study, first-order loss rate coefficients for both nitrification and denitrification (k1 and k2, respectively) were estimated. The rate coefficients were then used to develop treatment expression for nitrification and denitrification reactions. The treatment expressions were used to estimate the annual load reductions for TKN, NO3--N, and TN at the Venice East Blvd. bioretention retrofit site. Six storm events were simulated using a range of nitrogen concentrations. The simulation results showed minimal nitrification removal rates for storm events exceeding 1 inch, due to the planned bioretention system area being only 1% of the subcatchment area. A new ABC model was created (based on EPA bioretention cell sizing guidelines), to be 6% of the subcatchment area. Both systems were used to estimate TN removal efficiencies. The larger sized ABC model results showed average TKN, NO3--N and TN reductions of 84%, 96%; and 87%, respectively; these are comparable to results from similar studies. Results indicate that adequate nitrogen attenuation is achievable in the alternative bioretention system, if it is sized according to EPA sizing guidelines (5-7%).

A surge function is a mathematical function of the form f(x)=axpe-bx. We simplify the surge function by holding p constant at 1 and investigate the simplified form as a potential model to represent the full peak of a stream discharge hydrograph. The previously studied Weibull and gamma distributions are included for comparison. We develop an analysis algorithm which produces the best-fit parameters for every peak for each model function, and we process the data with a MATLAB script that uses spectral analysis to filter year-long, 15-minute, stream-discharge data sets. The filtering is necessary to locate the concave-upward inflection points used to separate the data set into its constituent, individual peaks. The Levenberg-Marquardt algorithm is used to iteratively estimate the unknown parameters for each version of the modeled peak by minimizing the sum of squares of residuals. The results allow goodness-of-fit comparisons between the three model functions, as well as a comparison of peaks at the same gage through the year of record. Application of these methods to five rivers from three distinct hydrologic regions shows that the simple surge function is a special case of the gamma distribution, which is known to be useful as a modeling function for a full-peak hydrograph. The study also confirms that the Weibull distribution produces good fits to 15-minute hydrograph data.

World Water Online is a global system of hydrologic data. It is an integration of geospatial and temporal information across spatial scales: global, national, regional and local. This global water information system has no parallel, and its scope would be extended with the active participation of the global water community. Its consolidation depends on the accessibility of countries’ databases through the system. In this study, a test case using Mexican data within World Water Online is created, applying the CUAHSI framework, web services and standards. The resulting Mexican-HIS unifies the water information for the nation regardless of data provider, improving storage practices and allowing additional querying and retrieving functionalities: World Water Online is a source of information and also a supplier of web-based processing services. In the second part of this study, a precipitation-runoff analysis using the data in the system is performed. / text

published_or_final_version / Civil Engineering / Master / Master of Philosophy

<p>Seasonally dry ecosystems cover large areas over the world, have high potential for carbon sequestration, and harbor high levels of biodiversity. They are characterized by high rainfall variability at timescales ranging from the daily to the seasonal to the interannual, and water availability and timing play key roles in primary productivity, biogeochemical cycles, phenology of growth and reproduction, and agricultural production. In addition, a growing demand for food and other natural resources in these regions renders seasonally dry ecosystems increasingly vulnerable to human interventions. Compounded with changes in rainfall regimes due to climate change, there is a need to better understand the role of climate variabilities in these regions to pave the way for better management of existing infrastructure and investment into future adaptations. </p><p>In this dissertation, the ecohydrological responses of seasonally dry ecosystem to climate variabilities are investigated under a comprehensive framework. This is achieved by first developing diagnostic tools to quantify the degree of rainfall seasonality across different types of seasonal climates, including tropical dry, Mediterranean, and monsoon climates. This global measure of seasonality borrows from information theory and captures the essential contributions from both the magnitude and concentration of the rainy season. By decomposing the rainfall signal from seasonality hotspots, increase in the interannual variability of rainfall seasonality is found, accompanied by concurrent changes in the magnitude, timing, and durations of seasonal rainfall, suggesting that increase in the uncertainty of seasonal rainfall may well extend into the next century. Next, changes in the hydrological partitioning, and the temporal responses of vegetation resulting from these climate variabilities, are analyzed using a set of stochastic models that accounts for the unpredictability rainfall as well as its seasonal trajectories. Soil water storage is found to play a pivotal role in regulating seasonal soil water hysteresis, and the balance between seasonal soil water availability and growth duration is found to induce maximum plant growth for a given amount of annual rainfall. Finally, these methods are applied in the context of biodiversity and the interplay of irrigation and soil salinity, which are prevailing management issues in seasonally dry ecosystems.</p> / Dissertation