Nonpoint source (NPS) pollution is possibly the greatest form of contamination to our nation's waters. Nutrient pollutants, such as nitrate and ammonium, often enter aquatic ecosystems through surface and subsurface hydrological transport that drain agricultural watersheds. The over-abundance of nitrogen within these watersheds is easily transported to receiving stream and rivers, and result in aquatic ecosystem degradation. In response to the problem of nutrient loading to aquatic ecosystems, ecosystems scientists and federal and state governments have recommended the use of streamside management zones (SMZ) to reduce the amount of NPS pollutants. A small agricultural watershed in southwestern North Carolina was utilized to quantify subsurface transport of nitrate and ammonium to a naturally developing riparian area along Cartoogechaye Creek. Vertical and lateral transport of nitrate and ammonium were measured along three transect perpendicular to the stream. Transects were instrumented with time domain reflectometry (TDR) and porous cup tension lysimeters to monitor soil water and nutrient flux through the pasture and riparian area located at the base of the watershed. The HYDRUS 2-D flow and transport model was used to predict and simulate subsurface flow. Predicted flow was coupled with observed field nutrient data to quantify nutrient flux as a function of slope location. HYDRUS 2-D was capable of simulating subsurface flow (saturated and unsaturated) as a function of observed soil physical properties (bulk density, saturated hydraulic conductivity, particle size distribution, water retention characteristics) and climatic data (precipitation, air temperature, wind speed, etc.). The riparian area was effective in reducing the amount of nonpoint source pollution to a naturally developing riparian area from an agricultural watershed. Dramatic decreases in both NO3- -N and NH4+ -N in upland pasture water were observed within the riparian area. Seasonal percent reductions of NO3- from the pasture to riparian area in subsurface water within the study watershed are as follows: summer (2002) = 456%; fall (2002) = 116%; winter (2003) = 29%; spring = 9%, pasture and riparian, respectively. / Master of Science

Master of Arts / Department of Geography / John A. Harrington Jr / Environmental degradation is a major concern in agricultural landscapes. Innovative tools and methods will be necessary to identify and deal with the ongoing environmental impacts of past and present agricultural practices. The use of scenarios in environmental modeling is one way to address these concerns. Recently a group of researchers devised a framework for creating future land cover scenarios for two physiographic regions in Iowa. Based on that work, a suite of scenarios were created for Antelope Creek watershed in the Northern Flint Hills of Kansas. The Antelope Creek scenarios represent conditions pre Euro-American settlement, present day, increased intensification of agricultural production, enhancement of water quality, and enhancement of biodiversity. These scenarios were then modeled using the Soil and Water Assessment Tool (SWAT). Additional model runs were completed to compare SSURGO and STATSGO soil datasets. Results indicated that reductions in discharge, total suspended sediment and various nitrogen and phosphorus loads could be achieved by implementing modest changes to agricultural management practices. Results also indicated that a higher detail soil dataset such as SSURGO lead to slightly higher loads than with STATSGO data.

Doctor of Philosophy / Department of Biological & Agricultural Engineering / Stacy L. Hutchinson / The Soil Conservation Service-Curve Number (SCS-CN) method is widely used to estimate direct runoff from rainfall events; however, the method does not account for the dynamic rainfall-runoff relationship. This study used back-calculated curve numbers (CNs) and Normalized Difference Vegetation Index (NDVI) to develop NDVI-based CNs (CN[subscript]NDV) using four small northeastern Kansas grassland watersheds with average areas of 1 km² and twelve years (2001–2012) of daily precipitation and runoff data. Analysis indicated that the CN[subscript]NDVI model improved runoff predictions compared to the SCS-CN method. The CN[subscript]NDVI also showed greater variability in CNs, especially during growing season, thereby increasing the model’s ability to estimate relatively accurate runoff from rainfall events since most rainfall occurs during the growing season. The CN[subscript]NDVI model was applied to small, disturbed grassland watersheds to assess the model’s ability to detect land cover change impact for military maneuver damage and large, diverse land use/cover watersheds to assess the impact of scaling up the model. CN[subscript]NDVI application was assessed using a paired watershed study at Fort Riley, Kansas. Paired watersheds were identified through k-means and hierarchical-agglomerative clustering techniques. At the large watershed scale, Daymet precipitation was used to estimate runoff, which was compared to direct runoff extracted from stream flow at gauging points for Chapman (grassland dominated) and Upper Delaware (agriculture dominated) watersheds. In large, diverse watersheds, CN[subscript]NDVI performed better in moderate and overall flow years. Overall, CN[subscript]NDVI more accurately simulated runoff compared to SCS-CN results: The calibrated model increased by 0.91 for every unit increase in observed flow (r = 0.83), while standard CN-based flow increased by 0.506 for every unit increase in observed flow (r = 0.404). Therefore, CN[subscript]NDVI could help identify land use/cover changes and disturbances and spatiotemporal changes in runoff at various scales. CN[subscript]NDVI could also be used to accurately estimate runoff from precipitation events in order to instigate more timely land management decisions.

The Canadian Precipitation Analysis (CaPA) system has been developed by Environment and Climate Change Canada (ECCC) to optimally combine different sources of information to estimate precipitation accumulation across Canada. The system combines observations from different networks of weather stations and radar measurements with the background information generated by ECCC's Regional Deterministic Prediction System (RDPS), derived from the Global Environmental Multiscale (GEM) model. The main scope of this study is to assess the importance of weather stations when combined with the background information for hydrological modeling. A new approach to meteorological network design, considered to be a stochastic hydro-geostatistical scheme, is proposed and investigated which is particularly useful for augmenting data-sparse networks. The approach stands out from similar approaches of its kind in that it is comprised of a data assimilation component included based on the paradigm of an Observing System Simulation Experiment (OSSE), a technique used to simulate data assimilation systems in order to evaluate the sensitivity of the analysis to new observation network. The proposed OSSE-based algorithm develops gridded stochastic precipitation and temperature models to generate synthetic time-series assumed to represent the 'reference' atmosphere over the basin. The precipitation realizations are used to simulate synthetic observations, associated with hypothetical station networks of various densities, and synthetic background data, which in turn are assimilated in CaPA to realize various pseudo-analyses. The reference atmosphere and the pseudo-analyses are then compared through hydrological modeling in WATFLOOD. By comparing the flow rates, the relative performance of each pseudo-analysis associated with a specific network density is assessed. The simulations show that as the network density increases, the accuracy of the hydrological signature of the CaPA precipitation products improves hyperbolically to a certain limit beyond which adding more stations to the network does not result in further accuracy. This study identifies an observation network density that can satisfy the hydrological criteria as well as the threshold at which assimilated products outperforms numerical weather prediction outputs. It also underlines the importance of augmenting observation networks in small river basins to better resolve mesoscale weather patterns and thus improve the predictive accuracy of streamflow simulation. / May 2017

Mudanças climáticas podem afetar a distribuição espacial e temporal das variáveis hidrológicas, tendo como consequências alterações nos regimes de precipitação e vazão dos rios. Aumentos ou reduções no volume de escoamento de uma bacia hidrográfica podem, por exemplo, produzir danos aos ecossistemas, afetar a produção de alimentos, abastecimento de água, navegação e geração de energia. Atualmente buscam-se relações que permitam entender os processos de mudanças climáticas a fim avaliar os impactos e mitigá-los, assim como avaliar as incertezas inerentes ao processo de modelagem hidrológica de tais mudanças. Neste contexto este trabalho apresenta uma metodologia de quantificação e análise de incertezas para estudos de mudanças climáticas, tomando como estudo de caso a bacia hidrográfica do Rio Uruguai (BHRU) com área aproximada de 110,000 Km². Para tanto três fontes de incerteza foram analisadas e comparadas: o modelo hidrológico, técnicas de remoção de viés e modelos climáticos. O modelo hidrológico MGB-IPH foi avaliado quanto ao processo de parametrização, utilizando diferentes períodos de simulação para calibração: (i) Período de calibração 1 – MGB/P1: representando a série completa de observações de 1960-1990 com verificação no período de 1992-1999; (ii) Período de calibração 2 - MGB/P2: calibração em período seco e verificação de período de cheias (iii) Período de calibração 3 – MGB/P3: calibração em período característico de cheias e verificação de período de estiagem. Três diferentes técnicas de remoção de viés foram aplicadas para analisar o grau de incerteza que a escolha de um determinado método de correção pode agregar ao resultado final: (i) RV1 - Técnica de Mapeamento Quantil-Quantil; (ii) RV2 - Técnica de Escalonamento Linear e (iii) RV3 - Técnica Delta change. Os modelos climáticos globais (GMC’s) foram analisados quanto a sua estrutura, comparando projeções de cinco diferentes modelos: MPEH5 (ECHAM5/MPIOM), GFCM21 (GFDL-CM2.1), MRCGCM (MRI-CGCM2.3.2), HADCM3 (UKMO-HadCM3) e NCCCSM (CCSM3). Adicionalmente, também foram analisadas as projeções climáticas de cinco diferentes versões do modelo climático regional (RCM) ETA/CPTEC: CT20, CT40, LOW, MID e HIGH. Inicialmente os resultados das simulações provenientes de cada uma destas fontes foram comparados de maneira isolada e em seguida de maneira combinada. Portanto, a metodologia foi dividida em Etapa (1) e Etapa (2). A Etapa (1) teve por objetivo responder a seguinte pergunta: Qual dentre as fontes de incerteza selecionadas agrega maior variação ao resultado final? Ou seja, qual destas fontes propaga maior incerteza em termos de impactos de mudanças climáticas na BHRU? Os resultados obtidos por cada uma das fontes de incerteza foram comparados em termos de anomalias de vazões médias de longo período (QMLP), máximas e mínimas anuais. Na Etapa (2) foi realizada a análise total de incerteza, ou seja, a análise combinada dos resultados obtidos na Etapa (1). As anomalias de vazões foram apresentadas utilizando as curvas de distribuição acumulada (CDF’s) e a incerteza total expressa pela diferença entre os percentis 5% e 95%. Considerando os resultados obtidos para as vazões médias de longo período (QMLP), as fontes podem ser ordenadas de forma decrescente, em relção ao grau de incerteza que propagam: modelos climáticos globais > modelos climáticos regionais > técnicas de remoção de viés > modelo hidrológico. Para as vazões extremas os RCM’s apresentam as maiores variações de anomalias se comparadas às dos modelos hidrológicos e técnicas de remoção de viés, inclusive para ambos os extremos, máximos e mínimos. Esta variação se dá principalmente, pelos resultados de LOW e MID. Estas informações podem ajudar os gestores e tomadores de decisão no adequado gerenciamento e planejamento dos recursos hídricos sob condições de mudanças climáticas, assim como o entendimento da incerteza associada. / Climate change can affect the spatial and temporal distribution of hydrological variables, with the consequences of changes in precipitation regimes and river flows. Increase or decrease the flow of rivers, for example, can cause damage to ecosystems, affecting food production, water supply, navigation and power generation. Currently seeking to relationships that allow understand climate change processes in order to assess the impacts and mitigate them, and assess the uncertainties inherent in hydrologic modeling process of such climate change. This thesis aimed at the development of a methodology for quantification and analysis of uncertainties for climate change studies in hydrology , taking as a case study the basin of the Uruguay River (BHRU) with a drainage area near 110,000 km². For that three sources of uncertainty were analyzed and compared: the hydrologic model, bias removal techniques and climate models. The hydrological model MGB-IPH was evaluated for parameterization, using different simulation periods for calibration: (i) MGB /P1: full range with calibration period (1960-1990) and validate (1992-1999); (ii) MGB / P2: calibrated in the period of dry and validated in the flood season (iii) MGB/P3: calibrated in the period of floods and validated in the dry season. Three different bias correction methods were applied to analyze the degree of uncertainty that the choice of a particular method of correction can add to the final result: (i) RV1 - Quantil-Quantil Mapping; (ii) RV2 - Linear Scaling, and (iii) RV3 - Delta Change Technique. Global climate models (GMC's) were analyzed for their structure, comparing projections of five different models: MPEH5 (ECHAM5/MPI-OM), GFCM21 (GFDLCM2.1), MRCGCM (MRI-CGCM2.3.2), HADCM3 (UKMO-HadCM3) e NCCCSM (CCSM3). Additionaly, climate projections from five different versions of the regional climate model (RCM) ETA / CPTEC were also analyzed: CT20, CT40, LOW, MID e HIGH. Initially the simulation results from each of the sources of uncertainty were compared individually (single propagation) and then in a combined way (multi propagation). Therefore, the methodology was divided in Step (1) and Step (2). Step (1) aimed to answer: Which of the selected sources of uncertainty adds more variation to the final result? Which of these sources propagates greater uncertainty in terms of impacts of climate change on BHRU? The results for each of the sources of uncertainty were compared in terms of long-term mean flow (QMLP), maximum and minimum annual flow. In Step (2) total uncertainty analysis was performed, therefore the combined analysis of the results obtained in Step (1). The anomalies in discharge were presented using the cumulative distribution function (CDF's) and the total uncertainty expressed by the difference between the percentiles 5% and 95%. Throughout the application of the proposed methodology it was concluded that: (i) for the extremes (maximum and minimum) annual discharges the largest source of uncertainty are the projections of the RCM's, followed by the the bias removal technique and finally the hydrological model; (ii) for the QMLP the largest source of uncertainty are followed global climate models, then the regional climate models. This information can help managers and decision makers in the proper management and planning of water resources under climate change conditions, as well as the understanding of the associated uncertainty.

In 2016 the Iowa Watershed Approach (IWA) was created to increase community resiliency against flooding, to develop hydrologic assessments that would identify strategies to reduce flooding, and to implement those strategies within nine identified watersheds that experienced flooding between 2011 and 2013. One of the nine watersheds was the Upper Iowa watershed located in northeast Iowa. This thesis focuses on the work that has been done to create a hydrologic assessment of the Upper Iowa watershed. The hydrologic assessment identifies potential conservation practices, creates a hydrologic model to assess the hydrologic cycle over the past ten years, and identifies strategies to reduce flooding within the watershed. Many potential agricultural conservation practices within the Upper Iowa watershed were identified and trends relating to the soil, land use, and topography were determined. In addition, a methodology to compare potential conservation practices with existing conservation practices actually in place was developed including a tool to estimate the size of grassed waterways to NRCS design guidelines. The comparison validated the methodologies used to identify potential practice placements, identified locations where potential practices could be implemented, and showed how stakeholder preferences influence conservation implementation. Additionally, a hydrologic model of the Upper Iowa watershed was developed, using the new Generic Hydrologic Overland-Subsurface Toolset model and calibrated to simulate the time period of 2007 through 2016. The model was evaluated against water balance ratios and performance statistics calculated from measured data. The model achieved Nash Sutcliffe Efficiency scores for streamflow above 0.7 and percent bias scores between ±12% for the three wettest years of 2008, 2013, and 2016. With the calibrated model, the benefits of continuous cover crop implementation were investigated under current conditions and under increased extreme precipitation intensity expected from climate change over the next half century. The results of this investigation determined that continuous cover crops increased evapotranspiration within the early half of the year creating more storage within the soil. Thus the flood risk from convective storms during the summer was lowered. In addition, the benefits from cover crops in terms of peak flow and volume reductions were cumulative increasing each consecutive year and were proportional to the percentage of cover cropped area. Lastly, a scenario using cover crops in a future extreme precipitation environment resulted in a reduction of peak discharge to current conditions. The results of this thesis will guide both future work within the Upper Iowa watershed and contribute to the knowledge of hydrologic planning and modeling within agricultural watersheds.

For the process of social and economic development, hydropower energy has an important role such as being renewable, clean, and having less impact on the environment. In decision of the hydropower potential of a study area, the preliminary condition is the availability of the gages in the area. However, in Turkey, the gages in working order are limited and getting decreased in recent years. Therefore, the satellite based precipitation estimates has been gaining importance to predict runoff for ungauged basins. In this study, &Ccedil / oruh basin, which is located in the north-eastern part of Turkey, is selected to perform hydrologic modeling. The input precipitation data for the model are provided from the observations at meteorological stations and the Tropical Rainfall Measuring Mission (TRMM) satellite products (3B42 and 3B43). TRMM satellite is used to monitor and study the rainfall distribution. The precipitation radar on the TRMM is the first radar to make precipitation estimation from the space. Using both precipitation data, HEC-HMS, being well known hydrological model, is applied to the &Ccedil / oruh Basin for 2005 and 2003 water years. To distinguish the differences in the runoff simulations and water budget, comparisons are done with respect to flow monitoring stations. Statistical criteria show that model simulation results obtained from TRMM 3B42 products are promising in estimating the water potential in ungauged basins.

Title from PDF of title page. / Document formatted into pages; contains 123 pages. / Thesis (M.S.)--University of South Florida, 2001. / Includes bibliographical references. / Text (Electronic thesis) in PDF format. / ABSTRACT: Simulating the processes of rainfall and runoff are at the core of hydrologic modeling. Geomorphologic features, rainfall variability, soil types, and water table depths strongly influence hydrological process in Florida ecosystems. Topographic characteristics of the terrain define the stream paths and landscape. Alteration of these characteristics as a result of urban and/or agricultural developments, for example, can highly influence wetlands and river basin response. There are two predominant landforms in Florida: wetlands, where Variable Saturated Areas form near streams causing saturation excess runoff, and uplands where runoff is mainly generated by infiltration excess. The objective of this work is to analyze the impacts of geomorphologic and hydrologic characteristics on runoff mechanisms in humid environments such as Florida. In general, most research at the hillslope scale use hypothetical values of rainfall, sometimes non-realistic values, and single slope forms to explain the geomorphic and hydrologic process on Variable Saturated Areas. In this thesis, the complexity of hillslope processes on actual Florida topography is assessed by coupling a Digital Elevation Model with a two-dimensional variable saturated-unsaturated flow model called HYDRUS-2D. Actual rainfall records and soil parameters from the Characterization Data for Selected Florida Soils, Soil Survey were used to evaluate hydrologic impacts. A commerical software package, River Tools was used to display and extract topographic information from the Digital Elevation Models.Results show that when inflitration excess runoff is dominant, infiltration and runoff are very sensitive to time resolution, especially for convective storms. When saturation excess occurs, runoff is not affected by rainfall intensity. However, saturated hydraulic conductivity, depth to the water table, slope and curvature highly influence the extent of Variable Saturated Areas. Results indicate runoff in shallow water table environments is produced mainly by subsurface storm runoff, running below the surface, except in hillslopes with concave curvature and mild slopes. Additionally, concave hillslopes generate more saturation excess runoff than straight and convex hillslopes. / System requirements: World Wide Web browser and PDF reader. / Mode of access: World Wide Web.

The segment of the Pecos River that extends from Red Bluff Reservoir until it discharges to the Rio Grande/Bravo near Langtry was studied in this project. Hydrologic behavior of the basin was analyzed between 1981 and 2000, the first ten year period for calibration and the second ten year period for validation by using Water Evaluation and Planning Software (WEAP, SEI, 2006). Simulated streamflows were compared with naturalized streamflows (RJBCO, 2003) at two control points, one in the middle of the basin near Girvin and the other one is at the end of the basin near Langtry. The purpose of the project is to create a valid model for water availability simulations in the Pecos River Basin to be used for future water availability simulations considering climate change effects. The basin was divided into two parts in order to evaluate the results, the upper basin and the entire basin (below Red Bluff reservoir) according to the location of control gages. Simulated streamflows closely match the naturalized flows at the Girvin station in the upper basin. Although the results at the Langtry station for the entire basin are not as good as Girvin, the model still reproduces streamflows well enough to represent the hydrologic behavior of the basin, especially for the base flow. Considering the complex geological structure of the Pecos River Basin below Red Bluff Reservoir, the results can be considered satisfactory. The model can be used for future water availability predictions in the basin considering climate change effects. / text

Water resources availability could be affected by alterations of hydrologic processes as a result of climate change. Global projections of climate change indicate negative impacts on water systems with increasing flooding and drought events. This investigation presents the modeling of climate change effects on the hydrology and water resources availability in the Rio Conchos basin, the main tributary of the lower portion of the bi-national Rio Grande/Bravo basin, and its impact on the water treaty signed between the United States of America and Mexico in 1944. One of the problems most relevant to the study basin is the frequent occurrence of long drought periods. Coupled with increased water demands and low irrigation efficiencies, the competition for water resources is high on both sides of the border. Three main parts are addressed in this research. First, a hydrologic model has been developed using the one-dimensional, 2 layer soil moisture accounting scheme embedded in a water evaluation and planning model. Second, downscaled precipitation and temperature data, from five general circulation models for two emission scenarios, A1B and A2, were used as inputs to the Rio Conchos hydrologic model to determine the effect on basin hydrology. A multi-model ensemble is developed and several techniques, such as probability density functions, wavelet analysis, and trend analysis, are used to assess the impacts. Third, a water resources planning model for the basin has been developed, which integrates the hydrologic model and water management modeling, to evaluate the impacts on the entire water system and simulate adaptive strategies to mitigate climate change in the study basin. Skill-weighted multi-model ensemble results show that annual average runoff may be reduced by 12% ± 53% and 20% ± 45% in 2080-2099 relative to 1980-1999 for the A1B and A2 scenarios, respectively. Likewise, results show that reliability and resiliency of the water system will tend to decrease; consequently, the vulnerability of the system increases over time. Proposed adaptation measures could make the system more reliable and less vulnerable in meeting water demands for irrigation and municipal uses. / text