<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>

Advancements in computation and development of physically based hydrologic models to simulate complex vadose zone scenarios helped the research community to evaluate different scenarios easily compared to long-term field experiments. However, some field data collection is necessary to obtain input data such as soil properties, water usage and land management practices to validate the model performance specific to the site. Data obtained from field experiments conducted in 2011 at Hespler farms, Winkler, MB was used in this research for model calibration and validation. The hydrologic model, HYDRUS (2D/3D) was evaluated using parameters such as visual and statistical analysis. Model evaluation during the calibration and validation stage gave RMSE values of 0.019 and 0.015 cm3 cm-3; PBIAS values of -1.01 and -0.14, respectively, suggesting that the model was efficient in simulating soil water content similar to the field observed data. The validated models were then used to simulate outcomes for different scenarios such as 30-year rainfall data (1986 – 2015), different soil physical properties, and drainage system design parameters. Models simulating free drainage predicted lower soil water content compared to controlled drainage leading to 6 – 60 more trafficable days for 8 m spacing and 0.9 drain base depth. Free drainage predicted 8 – 110 additional trafficable days compared to controlled drainage for 15 m spacing and 1.1 drain depth. Heavier than normal rainfall events caused high water contents leading to a few years with a very low to no trafficable days under controlled drainage conditions. The comparisons are presented based on models using free drain conditions. Models with 8-m drain spacing predicted a 1 to 10-day increase in the number of trafficable days compared to the 15-m drain spacing. Drains placed at a base depth of 1.1 m below the soil surface predicted 4 - 40 more trafficable days compared to those installed at a base depth of 0.9 m. / October 2017

Floods are a significant threat to communities around the world and require substantial resources and infrastructure to predict. Limited local resources in developing nations make it difficult to build and maintain dense sensor networks like those present in the United States, creating a large disparity in flood prediction across borders. To address this disparity, I operated the Iowa Flood Center Top Layer model to predict floods in Puerto Rico without relying on in-situ data measurements. Instead, all model forcing was provided by satellite remote sensing datasets that offer near-global coverage. I used three datasets gathered via satellite remote sensing to build and operate watershed streamflow models: elevation data obtained by the Space Shuttle Endeavour through the Shuttle Radar Topography Mission (SRTM), rainfall estimates gathered by a constellation of satellites through the Global Precipitation Measurement Mission (GPM), and evapotranspiration rate estimates collected by Moderate Resolution Imaging Spectroradiometer (MODIS) sensors aboard the Aqua and Terra satellites. While these satellite remote sensing datasets make observations of nearly the entire world, their spatiotemporal resolution is coarse compared to conventional on-the-ground measurements. Hydrologic models were assembled for 75 basins upstream of streamflow gages monitored by the United States Geologic Survey (USGS). Model simulations were compared to real-time measurements at these gages. Continuous simulations spanning 58 months achieve poor Nash Sutcliffe Efficiency and Klinge Gupta Efficiency of -112.0 and -0.5, respectively. The sources of error that influence model performance were investigated, underlining some limitations of relying solely on satellite data for operational flood prediction efforts.

Appropriately constructed pollutant export models can help set management priorities for catchments, identify critical pollutant source areas, and are important tools for developing and evaluating economically viable ways of minimising surface water pollution.¶ This thesis presents a comparison, an evaluation and an integration of models for predicting the export of environmental pollutants, in particular sediment, through river systems. A review of the capabilities and limitations of current water quality modelling approaches is made. Several water quality and quantity modelling approaches are applied and evaluated in the catchment of the upper Murrumbidgee River.¶ The IHACRES rainfall-runoff model and a simple hydrologic routing model are applied with the aim of developing a capacity to predict streamflow at various catchment scales and to enable integration with other pollutant load estimation techniques. Methods for calculating pollutant loads from observed pollutant concentration and modelled streamflow data are also investigated. Sediment export is estimated using these methods over a 10-year period for two case study subcatchments. Approaches for water quality sampling are discussed and a novel monitoring program using rising stage siphon samplers is presented. Results from a refinement of the Sediment River Network model in the upper Murrumbidgee catchment (SedNet-UM) are presented. The model provides a capacity to quantify sediment source, transport and to simulate the effects of management change in the catchment. The investigation of the model includes rigorous examination of the behaviour of the model through sensitivity assessment and comparison with other sediment modelling studies. The major conclusion reached through sensitivity assessment was that the outputs of the model are most sensitive to perturbation of the hydrologic parameters of the model.¶ The SedNet-UM application demonstrates that it is possible to construct stream pollutant models that assist in prioritising management across catchment scales. It can be concluded that SedNet and similar variants have much potential to address common resource management issues requiring the identification of the source, propagation and fate of environmental pollutants. In addition, incorporating the strengths of a conceptual rainfall-runoff model and the semi-distributed SedNet model has been identified as very useful for the future prediction of environmental pollutant export.

A challenge in hydrological studies in the Canadian Prairie region is to find good-quality meteorological data because many basins are located in remote regions where few stations are available, and existing stations typically have short records and often contain a high number of missing data. The recently released North American Regional Reanalysis (NARR) data set appears to have potential for hydrological studies in data-scarce central Canada. The main objectives of this study are: (1) to evaluate and utilize NARR data for hydrologic modelling and statistical downscaling, (2) to develop methods for estimating missing precipitation data using NARR data, and (3) to investigate and correct NARR precipitation bias in the Canadian Prairie region. Prior to applying NARR for hydrological modelling, the NARR surface data were evaluated by comparison with observed meteorological data over the Canadian Prairie region. The comparison results indicated that NARR is a suitable alternative to observed surface meteorological data and thus useful for hydrological modelling. After evaluation of NARR surface climate data, the SLURP model was set up with input data from NARR and calibrated for several watersheds. The results indicated that the hydrological model can be reasonably calibrated using NARR data as input. The relatively good agreement between precipitation from NARR and observed station data suggests that NARR information may be used in the estimation of missing precipitation records at weather stations. Several traditional methods for estimating missing data were compared with three NARR-based estimation methods. The results show that NARR-based methods significantly improved the estimation of precipitation compared to the traditional methods. The existence of NARR bias is a critical issue that must be addressed prior to the use of the data. Using observed weather station data, a statistical interpolation technique (also known as Optimum Interpolation) was employed to correct gridded NARR precipitation for bias. The results suggest that the method significantly reduces NARR bias over the selected study area.

A challenge in hydrological studies in the Canadian Prairie region is to find good-quality meteorological data because many basins are located in remote regions where few stations are available, and existing stations typically have short records and often contain a high number of missing data. The recently released North American Regional Reanalysis (NARR) data set appears to have potential for hydrological studies in data-scarce central Canada. The main objectives of this study are: (1) to evaluate and utilize NARR data for hydrologic modelling and statistical downscaling, (2) to develop methods for estimating missing precipitation data using NARR data, and (3) to investigate and correct NARR precipitation bias in the Canadian Prairie region. Prior to applying NARR for hydrological modelling, the NARR surface data were evaluated by comparison with observed meteorological data over the Canadian Prairie region. The comparison results indicated that NARR is a suitable alternative to observed surface meteorological data and thus useful for hydrological modelling. After evaluation of NARR surface climate data, the SLURP model was set up with input data from NARR and calibrated for several watersheds. The results indicated that the hydrological model can be reasonably calibrated using NARR data as input. The relatively good agreement between precipitation from NARR and observed station data suggests that NARR information may be used in the estimation of missing precipitation records at weather stations. Several traditional methods for estimating missing data were compared with three NARR-based estimation methods. The results show that NARR-based methods significantly improved the estimation of precipitation compared to the traditional methods. The existence of NARR bias is a critical issue that must be addressed prior to the use of the data. Using observed weather station data, a statistical interpolation technique (also known as Optimum Interpolation) was employed to correct gridded NARR precipitation for bias. The results suggest that the method significantly reduces NARR bias over the selected study area.

abstract: The increasingly recurrent extraordinary flood events in the metropolitan area of Monterrey, Mexico have led to significant stakeholder interest in understanding the hydrologic response of the Santa Catarina watershed to extreme events. This study analyzes a flood mitigation strategy proposed by stakeholders through a participatory workshop and are assessed using two hydrological models: The Hydrological Modeling System (HEC-HMS) and the Triangulated Irregular Network (TIN)-based Real-time Integrated Basin Simulator (tRIBS). The stakeholder-derived flood mitigation strategy consists of placing new hydraulic infrastructure in addition to the current flood controls in the basin. This is done by simulating three scenarios: (1) evaluate the impact of the current structure, (2) implementing a large dam similar to the Rompepicos dam and (3) the inclusion of three small detention dams. These mitigation strategies are assessed in the context of a major flood event caused by the landfall of Hurricane Alex in July 2010 through a consistent application of the two modeling tools. To do so, spatial information on topography, soil, land cover and meteorological forcing were assembled, quality-controlled and input into each model. Calibration was performed for each model based on streamflow observations and maximum observed reservoir levels from the National Water Commission in Mexico. Simulation analyses focuses on the differential capability of the two models in capturing the spatial variability in rainfall, topographic conditions, soil hydraulic properties and its effect on the flood response in the presence of the different flood mitigation structures. The implementation of new hydraulic infrastructure is shown to have a positive impact on mitigating the flood peak with a more favorable reduction in the peak at the outlet from the larger dam (16.5% in tRIBS and 23% in HEC-HMS) than the collective effect from the small structures (12% in tRIBS and 10% in HEC-HMS). Furthermore, flood peak mitigation depends strongly on the number and locations of the new dam sites in relation to the spatial distribution of rainfall and flood generation. Comparison of the two modeling approaches complements the analysis of available observations for the flood event and provides a framework within which to derive a multi-model approach for stakeholder-driven solutions. / Dissertation/Thesis / Masters Thesis Civil and Environmental Engineering 2016

Orientador: Jose Teixeira Filho / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Agricola / Made available in DSpace on 2018-08-03T23:55:35Z (GMT). No. of bitstreams: 1 Ferreira_Lucia_D.pdf: 1500242 bytes, checksum: f168afe0384add0cf44eeb8198bdd9c6 (MD5) Previous issue date: 2004 / Doutorado / Agua e Solo / Doutor em Engenharia Agrícola

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. 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. 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 &amp; 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. / 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. 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. 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 &amp; 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.

Predicted future precipitation is downscaled and used to drive a hydrologic model to assess future erosion potential in a semi-alluvial clay-bed watercourse, Watts Creek. The 21 km2 watershed is predominantly urban, with overall impervious cover of 22%, and the remaining land use split between agricultural and forested areas. Continuous simulations for the open water year, excluding spring freshet (April 1st to October 31st) were performed using the SWMHYMO (Stormwater Management Hydrologic Model) lumped hydrologic modelling platform. A shear stress exceedance and stream power erosion routine was added to the platform to calculate erosion potential. To account for uncertainty in the collected data, nine different observed discharge data sets were used to calibrate the model, each leading to a distinct set of calibrated parameter values. The difference between the observed data sets lies in the choice of rating curves and the collection period. The 2041-2080 precipitation outputs of the fourth version of the Canadian Regional Climate Model (CanRCM4) ran under Representative Concentration Pathways (RCPs) 4.5 and 8.5 at the MacDonald Cartier International Airport were downscaled using quantile matching and then used as input to the hydrologic model. For each set of calibrated parameters, a cumulative effective work index (CWI) based on the reach-averaged shear stress was calculated for Watts Creek during the open water year using both the historic (1968 2007) and projected future (2041-2080) flows, using a bed material critical shear stress for entrainment of 3.7 Pa. Results suggest an increase of 75% (resp. 139%) under RCP4.5 (resp. RCP8.5) in CWI compared to historic conditions for the average measured bed strength. The work index increase is driven by an increased occurrence of above-threshold events, and more importantly by the increased frequency of large events. The predicted flow regime under climate change would significantly alter the erosion potential and stability of Watts Creek. A channel adjustment sensitivity analysis, which balances future erosion potential with historic potential, was implemented and indicated that the channel could widen in the future from the current bankfull width of 6.1 m to 8.2 m for RCP4.5 and 10.2 m for RCP8.5. Specific morphological behaviour should be investigated in more detail, particularly to assess if the governing erosion mechanism is seasonally dependent, perhaps incising during spring freshet and widening when the bed is vegetated in the summer.