Date of Award


Document Type


Degree Name

Doctor of Philosophy (PhD)


College of Science and Mathematics


Earth and Environmental Studies

Thesis Sponsor/Dissertation Chair/Project Chair

Clement A. Alo

Committee Member

Duke Ophori

Committee Member

Huan Feng

Committee Member

Josh Galster

Committee Member

Menberu Meles


Streamflow dynamics in a basin is known to be a major driver of available water resources. In the context of climate change, it is expected that global warming will accelerate the global hydrologic cycle, which will drive more intense floods and droughts leading to changes in streamflow and water resource availability. Most researchers agree that the amount and intensity of precipitation have a direct impact on runoff. Yet, there is no consensus as to how warming can affect streamflow. Evapotranspiration (ET) plays a crucial role here. However, there is a shortage of real-world observations on it. And yet, ET is considered as the primary determinant of available water resources. It is the water that would otherwise become streamflow if not released into the atmosphere. In the Passaic River Basin (PRB), this water loss constitutes on average 50 percent of the approximately 49-inches precipitation. Because of its substantial heterogeneity in land use, soils, geology, reservoirs, vegetation, slope, and topography, the PRB exhibit a highly complex river system. This complexity amidst the heterogeneous biophysical arrangement within the basin present a multifaceted mix of competing interests and water related issues. In a region where predicted temperature increases are anticipated to amplify evapotranspiration and reduce snowpack, the resulting impact on streamflow could be significant. It is with this consideration that this dissertation attempts to better understand the mechanism behind streamflow dynamics in the basin, noting that it is a major driver of available water resource. That way, the impacts of climate change can be properly assessed. In this work, three independent research studies using available hydrological and climate data for the Passaic River Basin were conducted to achieve this goal.

In the first study, I used Gridded datasets from Parameter-elevation Regressions on Independent Slopes Model (PRISM), TerraClimate, and Moderate Resolution Imaging Spectroradiometer (MODIS) LAI product to develop spatially-varying monthly ET models. Beyond the widely used traditional type regression that has the effect of producing ‘global’ parameter estimates, assumed to be uniform throughout a study area, a more localized spatially non-stationary technique — the geographically weighted regression (GWR) — was utilized to estimate mean monthly ET in the Passaic River Basin (PRB). Key environmental controls of ET have been identified and new sets of spatially varying empirical ET models based on variable combinations that produced the best- fit model have been developed. The analysis showed that temporal and spatial variabilities in ET over the PRB are driven by climatic and biophysical factors. It was found that the key controlling factors were different from month to month, with wind speed being dominant throughout the year in the study basin. Monthly mean ET index map was further generated from the model to illustrate areas where ET exceeds precipitation.

In the second study, I bypassed the frequently used Mann-Kendal trend test in a novel application using the wavelet transform tool to identify the hidden monotonic trends in the inherently noisy hydro-climatic data. By this approach, the use of Mann Kendal trend test directly on the raw data whose results are almost always ambiguous and statistically insignificant in respect of precipitation data for instance, no longer pose a challenge to the reliability of trend results. The results showed that whereas trends in temperature and precipitation are increasing in the PRB, streamflow trends are decreasing. Based on results from the hydrological modelling, streamflow is more sensitive to actual ET than it is to precipitation. The general observation from climate elasticity results showed that in decades where water is available, energy limits actual evapotranspiration which makes streamflow more sensitive to precipitation increase. However, in meteorologically stressed or dry decades, water limits actual ET thereby making streamflow more sensitive to increases in actual evapotranspiration. It was found that the choice of baseline condition constitutes an important source of uncertainty in the sensitivities of streamflow to precipitation and evapotranspiration changes and should routinely be considered in any climate impact assessment.

In the third study, I forced a duly calibrated and verified hydrological model with advanced downscaled and bias-corrected climate scenarios in a rare application in the Rockaway sub- catchment of the Passaic River Basin to assess the impacts of climate change on water resource availability. A priori analysis however involved the selection of subset models from twenty (20) Multivariate Adaptive Constructed Analog (MACA) climate models that characterized the change in temperature and precipitation according to LEAST WARM, HOT, DRY, and WET at mid-21st century (2041—2070) as well as a mild future that typifies the MIDDLE of the temperature and precipitation range. In all, nine (9) different models, relative to two baseline periods, and under two different climate scenarios were selected. Results showed that against the 2041—2070 period, the margin of error owing to the use of different baseline conditions were +/- 0.3 — +/-0.23 oC for temperature and +/-8.15— +/-6.9% for precipitation, indicating the extent to which the time perspective used in climate change impacts assessment significantly affect outcomes. Across all five (5) climate projections, and the two scenarios, a consistent warming from +1.21 to + 4.70 oC is projected in the Rockaway catchment at mid-21st century relative to the 1981—2010 baseline period. While precipitation is generally projected to increase, streamflow prediction shows an overall decreasing signal, a trend likely induced by the projected increase in actual evapotranspiration. In terms of climate extremes, an increase in the number heavy rainy days of approximately 2 days is projected in the coldest future whiles an increase of about 4 days is expected in the wettest future. In similar vein, the number days with consecutive dry spells is expected to decrease by approximately 2 days in the driest future whereas an increase of about 3 days is projected in the wettest future. Overall, climate change is expected to fuel flooding and drought conditions in the study catchment, and to cause alterations in river flows which will in turn affect reservoir operations. With this advance knowledge in hand, swift mitigation and adaptation plans are therefore needed.

The results presented in this dissertation show that climate change will threatened available water resources through evapotranspiration. Because the availability of water resource is largely driven by river flows in channels, possible increase or decrease in flow as depicted in the study will fuel flooding and drought conditions. Given that streamflow is highly sensitive to precipitation increases in decades where water is sufficiently available, even higher risk of extreme floods can be expected. On the other hand, longer dry spells will lead to water scarcity and higher risk of drought potentials. Either way, alterations in river flows will affect routine reservoir operations under a changing climate. Particularly, a crucial basis for examining possible environmental impacts on dam failure, including physical sedimentation, erosion from floodwaters, and chemical contamination has been established in this study. With this advance knowledge in hand, swift mitigation and adaptation plans are therefore needed.

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