This thesis presents the development of a hydrologic model in the vector environment. Establishing spatial relationship between flow elements is the key for flow routing techniques. Such a relationship is called hydrologic topology, making each flow element know which other elements are upstream and which are downstream. Based on the hydrologic topology established for the flow elements, tools were developed for flow network navigation, drainage area estimation, flow length calculation and drainage divide determination. To apply the tools, data required might be obtained from different sources, which may lead to certain problems that have to do with wrong flow direction of stream lines and, mismatches in location of stream lines with respect to the corresponding drainage area polygons. Procedures to detect such inconsistencies and to correct them have been developed and are presented here. Data inconsistencies correction and parameter computation methods form the basis for the development of a routing model, which would be referred as hydrologic model. The hydrologic model consists of an overland flow routing module, two options for channel routing and a reservoir routing module. Two case studies have been presented to show the application of the tools developed.

This thesis presents a method for calibrating regional scale hydrologic models using the upper South Saskatchewan River watershed as a case study. Regional scale hydrologic models can be very difficult to calibrate due to the spatial diversity of their land types. To deal with this diversity, both a manual calibration method and a multi-basin automated calibration method were applied to a WATFLOOD hydrologic model of the watershed. Manual calibration was used to determine the effect of each model parameter on modeling results. A parameter set that heavily influenced modeling results was selected. Each influential parameter was also assigned an initial value and a parameter range to be used during automated calibration. This manual calibration approach was found to be very effective for improving modeling results over the entire watershed. Automated calibration was performed using a weighted multi-basin objective function based on the average streamflow from six sub-basins. The initial parameter set and ranges found during manual calibration were subjected to the optimization search algorithm DDS to automatically calibrate the model. Sub-basin results not involved in the objective function were considered for validation purposes. Automatic calibration was deemed successful in providing watershed-wide modeling improvements. The calibrated model was then used as a basis for determining the effect of altering rain gauge density on model outputs for both a local (sub-basin) and global (watershed) scale. Four de-clustered precipitation data sets were used as input to the model and automated calibration was performed using the multi-basin objective function. It was found that more accurate results were obtained from models with higher rain gauge density. Adding a rain gauge did not necessarily improve modeled results over the entire watershed, but typically improved predictions in the sub-basin in which the gauge was located.

This thesis presents a method for calibrating regional scale hydrologic models using the upper South Saskatchewan River watershed as a case study. Regional scale hydrologic models can be very difficult to calibrate due to the spatial diversity of their land types. To deal with this diversity, both a manual calibration method and a multi-basin automated calibration method were applied to a WATFLOOD hydrologic model of the watershed. Manual calibration was used to determine the effect of each model parameter on modeling results. A parameter set that heavily influenced modeling results was selected. Each influential parameter was also assigned an initial value and a parameter range to be used during automated calibration. This manual calibration approach was found to be very effective for improving modeling results over the entire watershed. Automated calibration was performed using a weighted multi-basin objective function based on the average streamflow from six sub-basins. The initial parameter set and ranges found during manual calibration were subjected to the optimization search algorithm DDS to automatically calibrate the model. Sub-basin results not involved in the objective function were considered for validation purposes. Automatic calibration was deemed successful in providing watershed-wide modeling improvements. The calibrated model was then used as a basis for determining the effect of altering rain gauge density on model outputs for both a local (sub-basin) and global (watershed) scale. Four de-clustered precipitation data sets were used as input to the model and automated calibration was performed using the multi-basin objective function. It was found that more accurate results were obtained from models with higher rain gauge density. Adding a rain gauge did not necessarily improve modeled results over the entire watershed, but typically improved predictions in the sub-basin in which the gauge was located.

Thesis (M. Phil.)--University of Hong Kong, 2010. / Includes bibliographical references (p. 101-118). Also available online.

Thesis (M. Phil.)--University of Hong Kong, 2010. / Includes bibliographical references (p. 101-118). Also available in print.

Thesis (Ph.D)--Earth and Atmospheric Sciences, Georgia Institute of Technology, 2009. / Committee Chair: Athanasios Nenes; Committee Member: Andrew G. Stack; Committee Member: Irina N. Sokolik; Committee Member: Judith A. Curry; Committee Member: Mike Bergin; Committee Member: Rodney J. Weber. Part of the SMARTech Electronic Thesis and Dissertation Collection.

A perennial streamflow hydrograph, when measured at the outlet of a basin, continuously and without interruption, can be considered as an integral measure of hydrologic responses. Some of the theoretical and practical aspects of treating streamflow hydrographs as integral indicators of basin properties are addressed in this dissertation. This dissertation is divided into two parts. In the first part, a framework to identify and evaluate whether a streamflow variable is consistent and distinguishable in a given time scale and therefore can be considered as a streamflow index, is developed. The suggested framework is evaluated using as an example two streamflow variables that describe some aspects of the hydrograph shape. In the second part of the dissertation, the utilization of these streamflow indices in hydrologic model parameter estimation is demonstrated. It is assumed that streamflow indices that are evaluated on long streamflow records include large variability of climatic scenarios. Therefore, regardless of climate variability, the consistency and distinguishability are maintained the indices are more related to physical properties of a basin. Consequently, the problem of estimating model parameters that are related to basin properties can be approached by a comparison of indices between the observed and simulated streamflow. Three case studies are presented: the first demonstrates that using the streamflow index which describes the shape of the hydrograph in the parameter estimation processes improves consistency of prediction skill of the 5-parameter HYMOD model in the Leaf River, Mississippi. The second case study explores an important property of the shape descriptors as being relatively insensitive to errors in the data. Such property can be potentially used to identify key sources of uncertainty and to select model parameters that are less affected by data errors. In the final case study, the shape descriptors were used to derive the parameters of the gamma function as a model for the basin's Instantaneous Unit Hydrograph (IUH).

<p> California Department of Water Resources (DWR) Snow Surveys Section has recently explored the potential use of recently developed hydrologic models to estimate snow water equivalent (SWE) for the Sierra Nevada mountain range. DWR Snow Surveys Section&rsquo;s initial step is to determine how well these hydrologic models compare to the trusted regression equations, currently used by DWR Snow Surveys Section. A comparison scheme was ultimately developed between estimation measures for SWE by interpreting model results for the Feather River Basin from: a) National Aeronautics and Space Administration (NASA) Jet Propulsion Laboratory (JPL) gridded SWE reconstruction product, b) United States Geological Survey (USGS) Precipitation-Runoff Modeling System (PRMS), and c) DWR Snow Surveys Section regression equations. Daily SWE estimates were extracted from gridded results by computing an average SWE based on 1,000 ft elevation band increments from 3,000 to 10,000 ft (i.e. an elevation band would be from 3,000 to 4,000 ft). The dates used for processing average SWE estimates were cloud-free satellite image dates during snow ablation months, March to August, for years 2000&ndash;2012. The average SWE for each elevation band was linearly interpolated for each snow sensor elevation. The model SWE estimates were then compared to the snow sensor readings used to produce the snow index in DWR&rsquo;s regression equations. In addition to comparing JPL&rsquo;s SWE estimate to snow sensor readings, PRMS SWE variable for select hydrologic response units (HRU) were also compared to snow sensor readings. Research concluded with the application of statistical methods to determine the reliability in the JPL products and PRMS simulated SWE variable, with results varying depending on time duration being analyzed and elevation range.</p>

<p> Since 1865 California has practiced underground water storage through artificial recharge; however, in many parts of the state these efforts have been insufficient to meet its growing water demands, particularly for irrigated agriculture. During dry periods, vast agricultural areas depend upon groundwater for irrigation. In these areas, groundwater banking (GB) should be an essential strategy of their water management operations. GB is the practice of using surface water for percolation or injection into aquifers for later recovery. One variation of GB currently being studied in California is the use of agricultural lands for this practice (Ag-GB). Economic implications of Ag-GB need to be analyzed to inform water agencies and farmers interested in implementing this practice. This study proposes a conceptual model for determining the economic feasibility of Ag-GB at the irrigation district level. The Orland-Artois Water District (OAWD) in Glenn County is considered as the case study, and alfalfa as the test crop due to its tolerance to flooding and low use of pesticides and fertilizers which could leach into the aquifer. The proposed model consists of four components. The first component, the agricultural water demand calculator, calculates agricultural water demands based on historic land use, monthly reference evapotranspiration (ETo), monthly average precipitation, and average crop coefficient (Kc) values for the region. The second component, the aquifer mass balance model, is a one-bucket mass balance model that quantifies inflows and outflows to the simplified aquifer. The third component, the agronomic model, estimates costs and benefits of Ag-GB in terms of energy savings from pumping and crop production. The fourth component, the economic feasibility output, evaluates costs and benefits are evaluated to determine economic feasibility. The period of analysis is from 1993 through 2013. </p><p> Two policies (A and B) for implementation of Ag-GB are proposed and tested. Policy A proposes that all growers in OAWD pay for the implementation of the Ag-GB program. Policy B proposes that alfalfa growers using their lands for Ag-GB (Ag-GB alfalfa growers) are exempted from paying for Ag-GB implementation and the rest of the growers (non Ag-GB growers) pay for it. The economic analysis suggests that Policy A brings more costs than benefits to the Ag-GB alfalfa growers and hence is rejected as feasible. Policy B seems to bring more benefits than costs to all growers in OAWD and therefore it has potential to be economically feasible under the assumptions and limitations of the model. </p>

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