Matching Items (15)
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- All Subjects: Hydrologic sciences
- Creators: Mascaro, Giuseppe
Description
Population growth within drylands is occurring faster than growth in any other ecologic zone, putting pressure on already stressed water resources. Because the availability of surface water supplies in drylands tends to be highly variable, many of these populations rely on groundwater. A critical process contributing to groundwater recharge is the interaction between ephemeral channels and groundwater aquifers. Generally, it has been found that ephemeral channels contribute to groundwater recharge when streamflow infiltrates into the sandy bottoms of channels. This process has traditionally been studied in channels that drain large areas (10s to 100s km2). In this dissertation, I study the interactions between surface water and groundwater via ephemeral channels in a first-order watershed located on an arid piedmont slope within the Jornada Experimental Range (JER) in the Chihuahuan Desert. To achieve this, I utilize a combination of high-resolution observations and computer simulations using a modified hydrologic model to quantify groundwater recharge and shed light on the geomorphic and ecologic processes that affect the rate of recharge. Observational results indicate that runoff generated within the piedmont slope contributes significantly to deep percolation. During the short-term (6 yr) study period, we estimated 385 mm of total percolation, 62 mm/year, or a ratio of percolation to rainfall of 0.25. Based on the instrument network, we identified that percolation occurs inside channel areas when these receive overland sheetflow from hillslopes. By utilizing a modified version of the hydrologic model, TIN-based Real-time Integrated Basin Simulator (tRIBS), that was calibrated and validated using the observational dataset, I quantified the effects of changing watershed properties on groundwater recharge. Distributed model simulations quantify how deep percolation is produced during the streamflow generation process, and indicate that it plays a significant role in moderating the production of streamflow. Sensitivity analyses reveal that hillslope properties control the amount of rainfall necessary to initiate percolation while channel properties control the partitioning of hillslope runoff into streamflow and deep percolation. Synthetic vegetation experiments show that woody plant encroachment leads to increases in both deep percolation and streamflow. Further woody plant encroachment may result in the unexpected enhancement of dryland aquifer sustainability.
ContributorsSchreiner-McGraw, Adam P (Author) / Vivoni, Enrique R. (Thesis advisor) / Whipple, Kelin X. (Committee member) / Mascaro, Giuseppe (Committee member) / Throop, Heather L. (Committee member) / Sala, Osvaldo E. (Committee member) / Arizona State University (Publisher)
Created2017
Description
The Colorado River Basin (CRB) is the primary source of water in the
southwestern United States. A key step to reduce the uncertainty of future streamflow
projections in the CRB is to evaluate the performance of historical simulations of General
Circulation Models (GCMs). In this study, this challenge is addressed by evaluating the
ability of nineteen GCMs from the Coupled Model Intercomparison Project Phase Five
(CMIP5) and four nested Regional Climate Models (RCMs) in reproducing the statistical
properties of the hydrologic cycle and temperature in the CRB. To capture the transition
from snow-dominated to semiarid regions, analyses are conducted by spatially averaging
the climate variables in four nested sub-basins. Most models overestimate the mean
annual precipitation (P) and underestimate the mean annual temperature (T) at all
locations. While a group of models capture the mean annual runoff at all sub-basins with
different strengths of the hydrological cycle, another set of models overestimate the mean
annual runoff, due to a weak cycle in the evaporation channel. An abrupt increase in the
mean annual T in observed and most of the simulated time series (~0.8 °C) is detected at
all locations despite the lack of any statistically significant monotonic trends for both P
and T. While all models simulate the seasonality of T quite well, the phasing of the
seasonal cycle of P is fairly reproduced in just the upper, snow-dominated sub-basin.
Model performances degrade in the larger sub-basins that include semiarid areas, because
several GCMs are not able to capture the effect of the North American monsoon. Finally,
the relative performances of the climate models in reproducing the climatologies of P and
T are quantified to support future impact studies in the basin.
southwestern United States. A key step to reduce the uncertainty of future streamflow
projections in the CRB is to evaluate the performance of historical simulations of General
Circulation Models (GCMs). In this study, this challenge is addressed by evaluating the
ability of nineteen GCMs from the Coupled Model Intercomparison Project Phase Five
(CMIP5) and four nested Regional Climate Models (RCMs) in reproducing the statistical
properties of the hydrologic cycle and temperature in the CRB. To capture the transition
from snow-dominated to semiarid regions, analyses are conducted by spatially averaging
the climate variables in four nested sub-basins. Most models overestimate the mean
annual precipitation (P) and underestimate the mean annual temperature (T) at all
locations. While a group of models capture the mean annual runoff at all sub-basins with
different strengths of the hydrological cycle, another set of models overestimate the mean
annual runoff, due to a weak cycle in the evaporation channel. An abrupt increase in the
mean annual T in observed and most of the simulated time series (~0.8 °C) is detected at
all locations despite the lack of any statistically significant monotonic trends for both P
and T. While all models simulate the seasonality of T quite well, the phasing of the
seasonal cycle of P is fairly reproduced in just the upper, snow-dominated sub-basin.
Model performances degrade in the larger sub-basins that include semiarid areas, because
several GCMs are not able to capture the effect of the North American monsoon. Finally,
the relative performances of the climate models in reproducing the climatologies of P and
T are quantified to support future impact studies in the basin.
ContributorsGautam, Jenita (Author) / Mascaro, Giuseppe (Thesis advisor) / Vivoni, Enrique (Committee member) / Wang, Zhihua (Committee member) / Arizona State University (Publisher)
Created2018
Description
Soil moisture (θ) is a fundamental variable controlling the exchange of water and energy at the land surface. As a result, the characterization of the statistical properties of θ across multiple scales is essential for many applications including flood prediction, drought monitoring, and weather forecasting. Empirical evidences have demonstrated the existence of emergent relationships and scale invariance properties in θ fields collected from the ground and airborne sensors during intensive field campaigns, mostly in natural landscapes. This dissertation advances the characterization of these relations and statistical properties of θ by (1) analyzing the role of irrigation, and (2) investigating how these properties change in time and across different landscape conditions through θ outputs of a distributed hydrologic model. First, θ observations from two field campaigns in Australia are used to explore how the presence of irrigated fields modifies the spatial distribution of θ and the associated scale invariance properties. Results reveal that the impact of irrigation is larger in drier regions or conditions, where irrigation creates a drastic contrast with the surrounding areas. Second, a physically-based distributed hydrologic model is applied in a regional basin in northern Mexico to generate hyperresolution θ fields, which are useful to conduct analyses in regions and times where θ has not been monitored. For this aim, strategies are proposed to address data, model validation, and computational challenges associated with hyperresolution hydrologic simulations. Third, analyses are carried out to investigate whether the hyperresolution simulated θ fields reproduce the statistical and scaling properties observed from the ground or remote sensors. Results confirm that (i) the relations between spatial mean and standard deviation of θ derived from the model outputs are very similar to those observed in other areas, and (ii) simulated θ fields exhibit the scale invariance properties that are consistent with those analyzed from aircraft-derived estimates. The simulated θ fields are then used to explore the influence of physical controls on the statistical properties, finding that soil properties significantly affect spatial variability and multifractality. The knowledge acquired through this dissertation provides insights on θ statistical properties in regions and landscape conditions that were never investigated before; supports the refinement of the calibration of multifractal downscaling models; and contributes to the improvement of hyperresolution hydrologic modeling.
ContributorsKo, Ara (Author) / Mascaro, Giuseppe (Thesis advisor) / Vivoni, Enrique R. (Thesis advisor) / Myint, Soe (Committee member) / Wang, Zhihua (Committee member) / Muenich, Rebecca (Committee member) / Arizona State University (Publisher)
Created2018
Description
Rapid urban expansion and the associated landscape modifications have led to significant changes of surface processes in built environments. These changes further interact with the overlying atmospheric boundary layer and strongly modulate urban microclimate. To capture the impacts of urban land surface processes on urban boundary layer dynamics, a coupled urban land-atmospheric modeling framework has been developed. The urban land surface is parameterized by an advanced single-layer urban canopy model (SLUCM) with realistic representations of urban green infrastructures such as lawn, tree, and green roof, etc. The urban atmospheric boundary layer is simulated by a single column model (SCM) with both convective and stable schemes. This coupled SLUCM-SCM framework can simulate the time evolution and vertical profile of different meteorological variables such as virtual potential temperature, specific humidity and carbon dioxide concentration. The coupled framework has been calibrated and validated in the metropolitan Phoenix area, Arizona. To quantify the model sensitivity, an advanced stochastic approach based on Markov-Chain Monte Carlo procedure has been applied. It is found that the development of urban boundary layer is highly sensitive to surface characteristics of built terrains, including urban land use, geometry, roughness of momentum, and vegetation fraction. In particular, different types of urban vegetation (mesic/xeric) affect the boundary layer dynamics through different mechanisms. Furthermore, this framework can be implanted into large-scale models such as Weather Research and Forecasting model to assess the impact of urbanization on regional climate.
ContributorsSong, Jiyun (Author) / Wang, Zhihua (Thesis advisor) / Vivoni, Enrique R (Committee member) / Mascaro, Giuseppe (Committee member) / Myint, Soe W (Committee member) / Sailor, David (Committee member) / Arizona State University (Publisher)
Created2016
Description
Land surface fluxes of energy and mass developed over heterogeneous mountain landscapes are fundamental to atmospheric processes. However, due to their high complexity and the lack of spatial observations, land surface processes and land-atmosphere interactions are not fully understood in mountain regions. This thesis investigates land surface processes and their impact on convective precipitation by conducting numerical modeling experiments at multiple scales over the North American Monsoon (NAM) region. Specifically, the following scientific questions are addressed: (1) how do land surface conditions evolve during the monsoon season, and what are their main controls?, (2) how do the diurnal cycles of surface energy fluxes vary during the monsoon season for the major ecosystems?, and (3) what are the impacts of surface soil moisture and vegetation condition on convective precipitation?
Hydrologic simulation using the TIN-based Real-time Integrated Basin Simulator (tRIBS) is firstly carried out to examine the seasonal evolution of land surface conditions. Results reveal that the spatial heterogeneity of land surface temperature and soil moisture increases dramatically with the onset of monsoon, which is related to seasonal changes in topographic and vegetation controls. Similar results are found at regional basin scale using the uncoupled WRF-Hydro model. Meanwhile, the diurnal cycles of surface energy fluxes show large variation between the major ecosystems. Differences in both the peak magnitude and peak timing of plant transpiration induce mesoscale heterogeneity in land surface conditions. Lastly, this dissertation examines the upscale effect of land surface heterogeneity on atmospheric condition through fully-coupled WRF-Hydro simulations. A series of process-based experiments were conducted to identify the pathways of soil moisture-rainfall feedback mechanism over the NAM region. While modeling experiments confirm the existence of positive soil moisture/vegetation-rainfall feedback, their exact pathways are slightly different. Interactions between soil moisture, vegetation cover, and rainfall through a series of land surface and atmospheric boundary layer processes highlight the strong land-atmosphere coupling in the NAM region, and have important implications on convective rainfall prediction. Overall, this dissertation advances the study of complex land surface processes over the NAM region, and made important contributions in linking complex hydrologic, ecologic and atmospheric processes through numerical modeling.
Hydrologic simulation using the TIN-based Real-time Integrated Basin Simulator (tRIBS) is firstly carried out to examine the seasonal evolution of land surface conditions. Results reveal that the spatial heterogeneity of land surface temperature and soil moisture increases dramatically with the onset of monsoon, which is related to seasonal changes in topographic and vegetation controls. Similar results are found at regional basin scale using the uncoupled WRF-Hydro model. Meanwhile, the diurnal cycles of surface energy fluxes show large variation between the major ecosystems. Differences in both the peak magnitude and peak timing of plant transpiration induce mesoscale heterogeneity in land surface conditions. Lastly, this dissertation examines the upscale effect of land surface heterogeneity on atmospheric condition through fully-coupled WRF-Hydro simulations. A series of process-based experiments were conducted to identify the pathways of soil moisture-rainfall feedback mechanism over the NAM region. While modeling experiments confirm the existence of positive soil moisture/vegetation-rainfall feedback, their exact pathways are slightly different. Interactions between soil moisture, vegetation cover, and rainfall through a series of land surface and atmospheric boundary layer processes highlight the strong land-atmosphere coupling in the NAM region, and have important implications on convective rainfall prediction. Overall, this dissertation advances the study of complex land surface processes over the NAM region, and made important contributions in linking complex hydrologic, ecologic and atmospheric processes through numerical modeling.
ContributorsXiang, Tiantian (Author) / Vivoni, Enrique R (Thesis advisor) / Gochis, David J (Committee member) / Huang, Huei-Ping (Committee member) / Mascaro, Giuseppe (Committee member) / Wang, Zhihua (Committee member) / Arizona State University (Publisher)
Created2016
Description
Rapid urbanization and population growth occurring in the cities of South Western
United States have led to significant modifications in its environment at local and
regional scales. Both local and regional climate changes are expected to have massive
impacts on the hydrology of Colorado River Basin (CRB), thereby accentuating the need
of study of hydro-climatic impacts on water resource management in this region. This
thesis is devoted to understanding the impact of land use and land cover (LULC) changes
on the local and regional hydroclimate, with the goal to address urban planning issues
and provide guidance for sustainable development.
In this study, three densely populated urban areas, viz. Phoenix, Las Vegas and
Denver in the CRB are selected to capture the various dimensions of the impacts of land
use changes on the regional hydroclimate in the entire CRB. Weather Research and
Forecast (WRF) model, incorporating the latest urban modeling system, is adopted for
regional climate modeling. Two major types of urban LULC changes are studied in this
Thesis: (1) incorporation of urban trees with their radiative cooling effect, tested in
Phoenix metropolitan, and (2) projected urban expansion in 2100 obtained from
Integrated Climate and Land Use Scenarios (ICLUS) developed by the US
Environmental Protection Agency for all three cities.
The results demonstrated prominent nocturnal cooling effect of due to radiative
shading effect of the urban trees for Phoenix reducing urban surface and air temperature
by about 2~9 °C and 1~5 °C respectively and increasing relative humidity by 10~20%
during an mean diurnal cycle. The simulations of urban growth in CRB demonstratedii
nocturnal warming of about 0.36 °C, 1.07 °C, and 0.94 °C 2m-air temperature and
comparatively insignificant change in daytime temperature, with the thermal environment
of Denver being the most sensitive the urban growth. The urban hydroclimatic study
carried out in the thesis assists in identifying both context specific and generalizable
relationships, patterns among the cities, and is expected to facilitate urban planning and
management in local (cities) and regional scales.
United States have led to significant modifications in its environment at local and
regional scales. Both local and regional climate changes are expected to have massive
impacts on the hydrology of Colorado River Basin (CRB), thereby accentuating the need
of study of hydro-climatic impacts on water resource management in this region. This
thesis is devoted to understanding the impact of land use and land cover (LULC) changes
on the local and regional hydroclimate, with the goal to address urban planning issues
and provide guidance for sustainable development.
In this study, three densely populated urban areas, viz. Phoenix, Las Vegas and
Denver in the CRB are selected to capture the various dimensions of the impacts of land
use changes on the regional hydroclimate in the entire CRB. Weather Research and
Forecast (WRF) model, incorporating the latest urban modeling system, is adopted for
regional climate modeling. Two major types of urban LULC changes are studied in this
Thesis: (1) incorporation of urban trees with their radiative cooling effect, tested in
Phoenix metropolitan, and (2) projected urban expansion in 2100 obtained from
Integrated Climate and Land Use Scenarios (ICLUS) developed by the US
Environmental Protection Agency for all three cities.
The results demonstrated prominent nocturnal cooling effect of due to radiative
shading effect of the urban trees for Phoenix reducing urban surface and air temperature
by about 2~9 °C and 1~5 °C respectively and increasing relative humidity by 10~20%
during an mean diurnal cycle. The simulations of urban growth in CRB demonstratedii
nocturnal warming of about 0.36 °C, 1.07 °C, and 0.94 °C 2m-air temperature and
comparatively insignificant change in daytime temperature, with the thermal environment
of Denver being the most sensitive the urban growth. The urban hydroclimatic study
carried out in the thesis assists in identifying both context specific and generalizable
relationships, patterns among the cities, and is expected to facilitate urban planning and
management in local (cities) and regional scales.
ContributorsUpreti, Ruby (Author) / Wang, Zhihua (Thesis advisor) / Vivoni, Enrique R. (Committee member) / Mascaro, Giuseppe (Committee member) / White, Dave (Committee member) / Arizona State University (Publisher)
Created2017
Description
The hydrologic cycle in drylands is complex with large spatiotemporal variationsacross scales and is particularly vulnerable to changes in climate and land cover. To
address the challenges posed by hydrologic changes, a synergistic approach that
combines numerical models, ground and remotely sensed observations, and data analysis
is crucial. This dissertation uses innovative detection and modeling techniques to assess
key hydrologic variables in drylands, including irrigated water use, streamflow, and
snowpack conditions, answering following research questions that also have broad
societal implications: (1) What are the individual and combined effects of future climate
and land use change on irrigation water use (IWU) in the Phoenix Metropolitan Area
(PMA)?; (2) How can temporal changes in streamflow and the impacts of flash flooding
be detected in dryland rivers?; and (3) What are the impacts of rainfall-snow partitioning
on future snowpack and streamflow in the Colorado River Basin (CRB)?
Firstly, I conducted a scenario modeling using the Variable Infiltration Capacity
(VIC) model under future climate and land use change scenarios. Results showed that
future IWU will change from -0.5% to +6.8% in the far future (2071-2100) relative to the
historical period (1981-2010). Secondly, I employed CubeSat imagery to map streamflow
presence in the Hassayampa River of Arizona, finding that the imaging capacity of
CubeSats enabled the detection of ephemeral flow events using the surface reflectance of
the near-infrared (NIR) band. Results showed that 12% of reaches were classified as
intermittent, with the remaining as ephemeral. Finally, I implemented a physically-based
rainfall-snow partitioning scheme in the VIC model that estimates snowfall fraction from
the wet-bulb temperature using a sigmoid function. The new scheme predicts more
significant declines in snowfall (-8 to -11%) and streamflow (-14 to -27%) by the end of
the 21st century over the CRB, relative to historical conditions.
Overall, this dissertation demonstrates how innovative technologies can enhance
the understanding of dryland hydrologic changes and inform decision-making of water
resources management. The findings offer important insights for policymakers, water
managers, and researchers who seek to ensure water resources sustainability under the
effects of climate and land use change.
ContributorsWang, Zhaocheng (Author) / Vivoni, Enrique R (Thesis advisor) / White, Dave D (Committee member) / Mascaro, Giuseppe (Committee member) / Huang, Huei-Ping (Committee member) / Wang, Zhihua (Committee member) / Arizona State University (Publisher)
Created2023
Description
Accelerated climate and land use land cover (LULC) changes are anticipated to significantly impact water resources in the Colorado River Basin (CRB), a major freshwater source in the southwestern U.S. The need for actionable information from hydrologic research is growing rapidly, given considerable uncertainties. For instance, it is unclear if the predicted high degree of interannual precipitation variability across the basin could overwhelm the impacts of future warming and how this might vary in space. Climate change will also intensify forest disturbances (wildfire, mortality, thinning), which can significantly impact water resources. These impacts are not constrained, given findings of mixed post-disturbance hydrologic responses. Process-based models like the Variable Infiltration Capacity (VIC) platform can quantitatively predict hydrologic behaviors of these complex systems. However, barriers limit their effectiveness to inform decision making: (1) simulations generate enormous data volumes, (2) outputs are inaccessible to managers, and (3) modeling is not transparent. I designed a stakeholder engagement and VIC modeling process to overcome these challenges, and developed a web-based tool, VIC-Explorer, to “open the black box” of my efforts. Meteorological data was from downscaled historical (1950-2005) and future projections (2006-2099) of eight climate models that best represent climatology under low- and high- emissions. I used two modeling methods: (1) a “top-down” approach to assess an “envelope of hydrologic possibility” under the 16 climate futures; and (2) a “bottom-up” evaluation of hydrology in two climates from the ensemble representing “Hot/Dry” and “Warm/Wet” futures. For the latter assessment, I modified land cover using projections of a LULC model and applied more drastic forest disturbances. I consulted water managers to expand the legitimacy of the research. Results showed Far-Future (2066-2095) basin-wide mean annual streamflow decline (relative to 1976-2005; ensemble median trends of -5% to -25%), attributed to warming that diminished spring snowfall and melt and year-round increased soil evaporation from the Upper Basin, and overall precipitation declines in the Lower Basin. Forest disturbances partially offset warming effects (basin-wide mean annual streamflow up to 12% larger than without disturbance). Results are available via VIC-Explorer, which includes documentation and guided analyses to ensure findings are interpreted appropriately for decision-making.
ContributorsWhitney, Kristen Marie (Author) / Vivoni, Enrique R (Thesis advisor) / Mascaro, Giuseppe (Committee member) / Whipple, Kelin X (Committee member) / White, Dave D (Committee member) / Xu, Tianfang (Committee member) / Arizona State University (Publisher)
Created2022
Description
Weather radars provide quantitative precipitation estimates (QPEs) with seamless spatial coverage that can complement limitations of sparse rain gage measurements, including those affecting intensity-duration-frequency (IDF) relations used for infrastructure design. The goal of this M.S. thesis is to assess the ability of 4-km, 1-h QPEs from the Stage IV analysis of the Next-Generation Radar (NEXRAD) network to reproduce the statistics of extreme precipitation (P) in central Arizona, USA, using a dense network of 257 rain gages as reference. The generalized extreme value (GEV) distribution is used to model the frequency of annual P maximum series observed at gages and radar pixels for durations, d, from 1 to 24 h. Estimates of P quantiles from radar QPEs are negatively biased (-20% – -30%) for d = 1 h. The bias tends to 0 and errors are small for d ≥ 6 h, independently of the return period. The presence of scaling for the GEV location and scale parameters, needed to apply IDF scaling models, was found for both radar and gage products. Regional frequency analysis methods combined with bias correction of the GEV shape parameter allow reducing the statistical uncertainty and providing seamless spatial distribution of P quantiles at daily and subdaily durations that address limitations of current IDF relations in southwestern U.S. based on NOAA Atlas 14.
ContributorsSrivastava, Nehal Ansh (Author) / Mascaro, Giuseppe (Thesis advisor) / Chester, Mikhail (Committee member) / Garcia, Margaret (Committee member) / Papalexiou, Simon Michael (Committee member) / Arizona State University (Publisher)
Created2022
Description
The Water-Energy Nexus (WEN) is a concept that recognizes the interdependence of water and energy systems. The Phoenix metropolitan region (PMA) in Arizona has significant and potentially vulnerable WEN interactions. Future projections indicate that the population will increase and, with it, energy needs, while changes in future water demand are more uncertain. Climate change will also likely cause a reduction in surface water supply sources. Under these constraints, the expansion of renewable energy technology has the potential to benefit both water and energy systems and increase environmental sustainability by meeting future energy demands while lowering water use and CO2 emissions. However, the WEN synergies generated by renewables have not yet been thoroughly quantified, nor have the related costs been studied and compared to alternative options.Quantifying WEN intercations using numerical models is key to assessing renewable energy synergy. Despite recent advances, WEN models are still in their infancy, and research is needed to improve their accuracy and identify their limitations. Here, I highlight three research needs. First, most modeling efforts have been conducted for large-scale domains (e.g., states), while smaller scales, like metropolitan regions, have received less attention. Second, impacts of adopting different temporal (e.g., monthly, annual) and spatial (network granularity) resolutions on simulation accuracy have not been quantified. Third, the importance of simulating feedbacks between water and energy components has not been analyzed.
This dissertation fills these major research gaps by focusing on long-term water allocations and energy dispatch in the metropolitan region of Phoenix. An energy model is developed using the Low Emissions Analysis Platform (LEAP) platform and is subsequently coupled with a water management model based on the Water Evaluation and Planning (WEAP) platform. Analyses are conducted to quantify (1) the value of adopting coupled models instead of single models that are externally coupled, and (2) the accuracy of simulations based on different temporal resolutions of supply and demand and spatial granularity of the water and energy networks. The WEAP-LEAP integrated model is then employed under future climate scenarios to quantify the potential of renewable energy technologies to develop synergies between the PMA's water and energy systems.
ContributorsMounir, Adil (Author) / Mascaro, Giuseppe (Thesis advisor) / White, Dave (Committee member) / Garcia, Margaret (Committee member) / Xu, Tianfang (Committee member) / Chester, Mikhail (Committee member) / Arizona State University (Publisher)
Created2022