abstract: The North American Monsoon (NAM) is characterized by high inter- and intra-seasonal variability, and potential climate change effects have been forecasted to increase this variability. The potential effects of climate change to the hydrology of the southwestern U.S. is of interest as they could have consequences to water resources, floods, and land management. I applied a distributed watershed model, the Triangulated Irregular Network (TIN)-based Real-time Integrated Basin Simulator (tRIBS), to the Beaver Creek basin in Arizona. This sub-basin of the Verde River is representative of the regional topography, land cover, and soils distribution. As such, it can serve to illustrate the utility of distributed models for change assessment studies. Model calibration was performed utilizing radar-based NEXRAD data, and comparisons were done to two additional sources of precipitation data: ground-based stations and the North American Land Data Assimilation System (NLDAS). Comparisons focus on the spatiotemporal distributions of precipitation and stream discharge. Utilizing the calibrated model, I applied scenarios from the HadCM3 General Circulation Model (GCM) which was dynamically downscaled by the Weather Research and Forecast (WRF) model, to refine the representation of Arizona's regional climate. Two time periods were examined, a historical 1990-2000 and a future 2031-2040, to evaluate the hydrologic consequence in the form of differences and similarities between the decadal averages for temperature, precipitation, stream discharge and evapotranspiration. Results indicate an increase in mean air temperature over the basin by 1.2 ºC. The average decadal precipitation amounts increased between the two time periods by 2.4 times that of the historical period and had an increase in variability that was 3 times the historical period. For the future period, modeled streamflow discharge in the summer increased by a factor of 3. There was no significant change in the average evapotranspiration (ET). Overall trends of increase precipitation and variability for future climate scenarios have a more significant effect on the hydrologic response than temperature increases in the system during NAM in this study basin. The results from this study suggest that water management in the Beaver Creek will need to adapt to higher summer streamflow amounts. / Dissertation/Thesis / M.S. Civil and Environmental Engineering 2012

abstract: The Phoenix Metropolitan region is subject to intense summer monsoon thunderstorms that cause highly localized flooding. Due to the challenges in predicting these meteorological phenomena and modeling rainfall-runoff transformations in urban areas, the ability of the current operational forecasting system to predict the exact occurrence in space and time of floods in the urban region is still very limited. This thesis contributes to addressing this limitation in two ways. First, the existing 4-km, 1-h Stage IV and the new 1-km, 2-min Multi-Radar Multi-Sensor (MRMS) radar products are compared using a network of 365 gages as reference. It is found that MRMS products consistently overestimate rainfall during both monsoonal and tropical storms compared to Stage IV and local rain gauge measurements, although once bias-corrected offer a reasonable estimate for true rainfall at a higher spatial and temporal resolution than rain gauges can offer. Second, a model that quantifies the uncertainty of the radar products is applied and used to assess the propagation of rainfall errors through a hydrologic-hydraulic model of a small urban catchment in Downtown Phoenix using a Monte Carlo simulation. The results of these simulations suggest that for this catchment, the magnitude of variability in the distribution of runoff values is proportional to that of the input rainfall values. / Dissertation/Thesis / Masters Thesis Civil, Environmental and Sustainable Engineering 2020

No description available.

Master of Science / Department of Computing and Information Sciences / Mitchell L. Neilsen / The United States Department of Agriculture (USDA) is currently researching the effectiveness of various earth dam designs and their ability to prevent erosion. This report utilizes experimental results from the USDA experimental hydraulic engineering research unit to develop computational fluid dynamics models using OpenFOAM. Several variations of smooth and stepped dam models are created and analyzed with OpenFOAM on multiple cores using Message Passing Interface. In this report, seven dam designs are analyzed to extract flow velocities and pressures and animations. This data and OpenFOAM models are helpful for determining potential erosion conditions.

Many planning decisions related to the land phase of the hydrologic cycle involve uncertainty due to stochasticity of rainfall inputs and uncertainty in state and knowledge of hydrologic processes. Consideration of this uncertainty in planning requires quantification in the form of probability distributions. Needed probability distributions, for many cases, must be obtained by transforming distributions of rainfall input and hydrologic state through deterministic models of hydrologic processes. Probability generating functions are used to derive a recursive technique that provides the necessary probability transformation for situations where the hydrologic output of interest is the cumulative effect of a random number of stochastic inputs. The derived recursive technique is observed to be quite accurate from a comparison of probability distributions obtained independently by the recursive technique and an exact analytic method for a simple problem that can be solved with the analytic method. The assumption of Poisson occurrence of rainfall events, which is inherent in derivation of the recursive technique, is examined and found reasonable for practical application. Application of the derived technique is demonstrated with two important hydrology- related problems. It is first demonstrated for computing probability distributions of annual direct runoff from a watershed, using the USDA Soil Conservation Service (SCS direct runoff model and stochastic models for rainfall event depth and watershed state. The technique is also demonstrated for obtaining probability distributions of annual sediment yield. For this demonstration, the-deterministic transform model consists of a parametric event -based sediment yield model and the SCS models for direct runoff volume and peak flow rate. The stochastic rainfall model consists of a marginal Weibull distribution for rainfall event duration and a conditional log -normal distribution for rainfall event depth, given duration. The stochastic state model is the same as used for the direct runoff application. Probability distributions obtained with the recursive technique for both the direct runoff and sediment yield demonstration examples appear to be reasonable when compared to available data. It is, therefore, concluded that the recursive technique, derived from probability generating functions, is a feasible transform method that can be useful for coupling stochastic models of rainfall input and state to deterministic models of hydrologic processes to obtain probability distributions of outputs where these outputs are cumulative effects of random numbers of stochastic inputs.

published_or_final_version / abstract / Civil Engineering / Doctoral / Doctor of Philosophy

published_or_final_version / Civil Engineering / Doctoral / Doctor of Philosophy

<p>A distributed hydrological rainfall-runoff model has been developed using a GIS integrated with a dynamic programming module (PCRaster). The model has been developed within the framework of the EU-project TWINBAS at IVL Swedish Environmental Research Institute, and is intended for use in WATSHMAN – a tool for watershed management developed at IVL. The model simulates runoff from a catchment based on daily mean values of temperature and precipitation. The GIS input data consist of maps with soil type, land-use, lakes, rivers and a digital elevation model. The model is a hybrid between a conceptual and a physical model. The snow routine uses the degree-day method, the evapotranspiration routine uses the Blainey-Criddle equation, the infiltration routine is based on Green-Ampt, groundwater is modelled assuming a linear reservoir and the flow routing is done with the kinematic wave equation combined with Manning’s equation.</p><p>The GIS and the hydrologic model are embedded in one another, allowing calculation of each parameter in each grid cell. The output from the model consists of raster maps for each time step for a pre-defined parameter, or a time series for a parameter at a specified grid cell. The flow network is generated from the digital elevation model and determines the water flow on the grid scale. The smallest possible grid size is thus obtained from the resolution of the digital elevation model. In this implementation the grid size was 50 m x 50 m. The raster structure of the model allows for easy use of data from climate models or remotely sensed data.</p><p>The model was evaluated using the River Kölstaån catchment, a part (110 km2) of the Lake Mälaren catchment, which has its outflow in central Stockholm, Sweden. The integration of the GIS and the hydrologic model worked well, giving significant advantages with respect to taking lakes and land-use into account. The evaluation data consisted of observed run-off for the period 1981 to 1991. The result from the calibration period shows a great variation in Reff (Nash & Sutcliffe) between the years, the three best years having Reff-values of 0.70 – 0.80. The Reff-value for the entire calibration period was 0.55 and 0.48 for the validation period, where again there was great variation between different years. The volume error was 0.1 % for the calibration period and -21 % for the validation period. The evapotranspiration was overestimated during the validation period, which is probably a result of excess rain during the calibration period. The results are promising and the model has many advantages – especially the integrated GIS-system – compared to the present WATSHMAN model. It could be further developed by introducing a second groundwater storage and refining the evapotranspiration and infiltration routine. Given the promising results, the model should be evaluated in other larger and hillier areas and preferably against more distributed data.</p> / <p>En helt distribuerad GIS-baserad hydrologisk modell för modellering i avrinningsområden på lokal/regional skala har byggts upp i PCRaster. Arbetet utfördes på IVL Svenska Miljöinstitutet AB inom ramen för EU-projektet TWINBAS, som har som mål att identifiera kunskapsluckor inför implementeringen av EU:s ramdirektiv för vatten. Modellen är tänkt att användas i WATSHMAN (Watershed Management System), IVLs verktyg för vattenplanering i avrinningsområden där bland annat källfördelningsberäkningar och åtgärdsanalyser ingår. Den uppbyggda modellen är en hybrid mellan en fysikalisk och en konceptuell hydrologisk modell och predikterar vattenföring på pixelnivå i avrinningsområden. Simuleringen drivs av dygnsmedelvärden för temperatur och nederbörd och modellen tar hänsyn till markanvändning, jordart, topografi och sjöar. De modellekvationer som används är grad-dagsmetoden för snö, Blainey-Criddle för evapotranspiration, Green-Ampt för infiltration, linjärt magasin för grundvatten och Mannings ekvation för flödesrouting.</p><p>Det geografiska informationssystemet och den hydrologiska modellen är helt integrerade, vilket gör att alla parametervärden beräknas för varje enskild pixel. Som utdata ger modellen en rasterkarta för varje tidssteg för en i förväg bestämd parameter, eller tidsserier över parametervärden i definierade punkter. Vattnet transporteras i ett utifrån höjdmodellen genererat flödesnätverk och vattnets flödesväg bestäms därmed på pixelnivå. Minsta möjliga pixelstorlek bestäms således utifrån höjdmodellens upplösning, och var vid denna tillämpning 50 m gånger 50 m. Modellens uppbyggnad med raster gör det enkelt att använda data från klimatmodeller eller fjärranalys.</p><p>Avrinningsområdet för Kölstaån, ett biflöde till Köpingsån i Mälardalen, har använts för att utvärdera modellen. Integreringen av GIS och hydrologisk modell fungerade mycket väl och gav stora fördelar t ex vad gäller att ta hänsyn till sjöar och markanvändning. Modellen kalibrerades med data från åren 1981 till 1986 och det erhållna volymfelet var då 0,1 % och Reff-värdet (Nash & Sutcliffe) 0,55. Stora variationer erhölls dock mellan åren; för de tre bästa åren låg Reff-värdet mellan 0,70 och 0,80. Ett mycket kraftigt nederbördstillfälle samt regleringar i huvudfåran av vattendraget ligger troligtvis bakom de mindre väl beskrivna åren. Även under valideringsperioden (1987 till 1991) fungerade modellen väl, så när som på att avdunstningen överskattades på vårarna (antagligen beroende av det stora regnet under kalibreringen), och Reff-värde och volymfel hamnade på 0,48 respektive -21 %, även här med stora variationer mellan åren. Resultaten är lovande och modellen har många fördelar jämfört med den nuvarande WATSHMAN-modellen. Den skulle kunna förbättras ytterligare genom att dela upp grundvattnet i två magasin samt förfina evapotranspirations- och infiltrationsrutinerna. Den höjdmodellsbaserade modellen bör utvärderas även i andra mer kuperade områden samt mot mer distibuerade data.</p>

Suppose C(x,t) is the concentration at position x in Rᵈ and time t > 0 of a solute which is diffusing in some medium. If on a local scale the dispersion of the solute is governed by a constant dispersion matrix, 1/2(δ²), and a random velocity field, V(x), then C satisfies a convection-diffusion equation with random coefficients, (DIAGRAM, TABLE OR GRAPHIC OMITTED...PLEASE SEE DAI) (1). Usually V(x) is taken to be μ + εU(x) where μ ε Rᵈ, U(x) is a given stationary random field with mean zero, and ε > 0 is a dimensionless parameter which measures the variability of V(x). Hydrological experiments suggest that on a regional scale the diffusion is classically Fickian with effective diffusion matrix D(ε) and drift velocity α(ε). Thus for large scales (DIAGRAM, TABLE OR GRAPHIC OMITTED...PLEASE SEE DAI) (2) is satisfied by the solute concentration. Here τ and χ are respectively time and space measured on large scales. It is natural to investigate the relation of the large scale coefficients D and α to the statistical properties of V(x). To relate (1) to (2)--and thus to approximate D(ε) and α(ε)--it is necessary to rescale t and x and average over the distribution of V. It can then be shown that the transition form (1) to (2) is equivalent to (DIAGRAM, TABLE OR GRAPHIC OMITTED...PLEASE SEE DAI) (3) where A = (∇•δ²∇)/2 + √nμ• ∇ and B(U) = √nU(√nx) • ∇. By expanding each side of (3) estimates of D(ε) and α(ε) can be obtained. The estimates have the form (DIAGRAM, TABLE OR GRAPHIC OMITTED...PLEASE SEE DAI) (4). Both D₂ and α₂ depend on the power spectrum of U. Analysis shows that in at least the case of incompressible fluids D₂ is positive definite. In one dimensional transport α₂ < 0, hence α(k) < μ(k) through second order.

Many planning decisions related to the land phase of the hydrologic cycle involve uncertainty due to stochasticity of rainfall inputs and uncertainty in state and knowledge of hydrologic processes. Consideration of this uncertainty in planning requires quantification in the form of probability distributions. Needed probability distributions, for many cases, must be obtained by transforming distributions of rainfall input and hydrologic state through deterministic models of hydrologic processes. Probability generating functions are used to derive a recursive technique that provides the necessary probability transformation for situations where the hydrologic output of interest is the cumulative effect of a random number of stochastic inputs. The derived recursive technique is observed to be quite accurate from a comparison of probability distributions obtained independently by the recursive technique and an exact analytic method for a simple problem that can be solved with the analytic method. The assumption of Poisson occurrence of rainfall events, which is inherent in derivation of the recursive technique, is examined and found reasonable for practical application. Application of the derived technique is demonstrated on two important hydrology-related problems. It is first demonstrated for computing probability distributions of annual direct runoff from a watershed using the USDA Soil Conservation Service (SCS) direct runoff model and stochastic models for rainfall event depth and watershed state. The technique is also demonstrated for obtaining probability distributions of annual sediment yield. For this demonstration, the deterministic transform model consists of a parametric event-based sediment yield model and the SCS models for direct runoff volume and peak flow rate. The stochastic rainfall model consists of a marginal Weibull distribution for rainfall event duration and a conditional log-normal distribution for rainfall event depth given duration. The stochastic state model is the same as employed for the direct runoff application. Probability distributions obtained with the recursive technique for both the direct runoff and sediment yield demonstration examples appear to be reasonable when compared to available data. It is therefore concluded that the recursive technique, derived from probability generating functions, is a feasible transform method that can be useful for coupling stochastic models of rainfall input and state to deterministic models of hydrologic processes to obtain probability distributions of outputs where these outputs are cumulative effects of random numbers of stochastic inputs.