Models of macro-scale hydrology for use in global change research: Tests on two tropical river systems

The subject of this dissertation is the terrestrial water cycle and development of tools to study the issue of global hydrologic change. A rationale is developed to study the water cycle at regional and continental scales using macro-scale hydrology models coupled to Geographic Information Systems (GIS). A linked Water Balance/Water Transport Model (WBM/WTM) was constructed and tested as part of this research. The model was applied to two tropical river systems, the Amazon River in South America and the Zambezi River in southern Africa. The WBM/WTM is a distributed parameter model, operating at 0.5\sp\circ(latitude x longitude) spatial scale and with monthly timesteps. The WBM transforms spatially complex data on climate, vegetation, soils and topography into predictions of soil moisture, evapotranspiration and runoff. The WTM uses computed runoff, information on fluvial topology, linear transfer through river channels and a simple representation of floodplain storage to generate monthly discharge for any cell within a simulated catchment. For the Amazon, WBM/WTM results were checked against established data sources and found to be in good agreement. The Zambezi simulation was more problematic. This study identified and corrected errors in the precipitation, potential evapotranspiration, and soil water capacity data sets, and demonstrated the importance of checking such calculations against reliable discharge data. Simulations with data from the Amazon and Zambezi River systems identified fluvial transport parameters which best matched observed discharge. Similar parameters captured the dynamics of river flow in these strikingly different river systems. This suggests that large tropical rivers may have convergent properties that can be modeled using simple algorithms. This work produced a set of calibrated, macro-scale hydrology models for two large rivers prior to significant anthropogenic disturbance. Such simulations are prerequisites to the study of hydrologic change. The major impacts of such change, from shifting land use, climate change, and water resources management, can be simulated using macro-scale hydrology models. The dissertation offers a strategy to accomplish this goal

Widespread decline in hydrological monitoring threatens Pan‐Arctic Research

Operational river discharge monitoring is declining in both North America and Eurasia. This problem is especially severe in the Far East of Siberia and the province of Ontario, where 73% and 67% of river gauges were closed between 1986 and 1999, respectively. These reductions will greatly affect our ability to study variations in and alterations to the pan‐Arctic hydrological cycle

Scaling gridded river networks for macroscale hydrology: Development, analysis, and control of error

A simple and robust river network scaling algorithm (NSA) is presented to rescale fine‐resolution networks to any coarser resolution. The algorithm was tested over the Danube River basin and the European continent. Coarse‐resolution networks, at 2.5, 5, 10, and 30 min resolutions, were derived from higher‐resolution gridded networks using NSA and geomorphometric attributes, such as river order, shape index, and width function. These parameters were calculated and compared at each resolution. Simple scaling relationships were found to predict decreasing river lengths with coarser‐resolution data. This relationship can be used to correct river length as a function of grid resolution. The length‐corrected width functions of the major river basins in Europe were compared at different resolutions to assess river network performance. The discretization error in representing basin area and river lengths at coarser resolutions were analyzed, and simple relationships were found to calculate the minimum number of grid cells needed to maintain the catchment area and length within a desired level of accuracy. This relationship among geomorphological characteristics, such as shape index and width function (derived from gridded networks at different resolutions), suggests that a minimum of 200–300 grid cells is necessary to maintain the geomorphological characteristics of the river networks with sufficient accuracy

Effects of Uncertainty in Climate Inputs on Simulated Evapotranspiration and Runoff in the Western Arctic

Hydrological models require accurate precipitation and air temperature inputs in order to adequately depict water fluxes and storages across Arctic regions. Biases such as gauge undercatch, as well as uncertainties in numerical weather prediction reanalysis data that propagate through water budget models, limit the ability to accurately model the terrestrial arctic water cycle. A hydrological model forced with three climate datasets and three methods of estimating potential evapotranspiration (PET) was used to better understand the impact of these processes on simulated water fluxes across the Western Arctic Linkage Experiment (WALE) domain. Climate data were drawn from the NCEP–NCAR reanalysis (NNR) (NCEP1), a modified version of the NNR (NCEP2), and the Willmott–Matsuura (WM) dataset. PET methods applied in the model were Hamon, Penman–Monteith, and Penman–Monteith using adjusted vapor pressure data. High vapor pressures in the NNR lead to low simulated evapotranspiration (ET) in model runs using the Penman–Monteith PET method, resulting in increased runoff. Annual ET derived from simulations using Penman–Monteith PET was half the magnitude of ET simulated when the Hamon method was used. Adjustments made to the reanalysis vapor pressure data increased the simulated ET flux, reducing simulated runoff. Using the NCEP2 or WM climate data, along with the Penman–Monteith PET function, results in agreement to within 7% between the simulated and observed runoff across the Yukon River basin. The results reveal the high degree of uncertainty present in climate data and the range of water fluxes generated from common model drivers. This suggests the need for thorough evaluations of model requirements and potential biases in forcing data, as well as corroborations with observed data, in all efforts to simulate arctic water balances

Global system of rivers: Its role in organizing continental land mass and defining land‐to‐ocean linkages

The spatial organization of the Earth\u27s land mass is analyzed using a simulated topological network (STN‐30p) representing potential flow pathways across the entire nonglacierized surface of the globe at 30‐min (longitude × latitude) spatial resolution. We discuss a semiautomated procedure to develop this topology combining digital elevation models and manual network editing. STN‐30p was verified against several independent sources including map products and drainage basin statistics, although we found substantial inconsistency within the extant literature itself. A broad suite of diagnostics is offered that quantitatively describes individual grid cells, river segments, and complete drainage systems spanning orders 1 through 6 based on the Strahler classification scheme. Continental and global‐scale summaries of key STN‐30p attributes are given. Summaries are also presented which distinguish basins that potentially deliver discharge to an ocean (exorheic) from those that potentially empty into an internal receiving body (endorheic). A total of 59,122 individual grid cells constitutes the global nonglacierized land mass. At 30‐min spatial resolution, the cells are organized into 33,251 distinct river segments which define 6152 drainage basins. A global total of 133.1 × 106 km2 bear STN‐SOp flow paths with a total length of 3.24 × 106 km. The organization of river networks has an important role in linking land mass to ocean. From a continental perspective, low‐order river segments (orders 1‐3) drain the largest fraction of land (90%) and thus constitute a primary source area for runoff and constituents. From an oceanic perspective, however, the small number (n=101) of large drainage systems (orders 4‐6) predominates; draining 65% of global land area and subsuming a large fraction of the otherwise spatially remote low‐order rivers. Along river corridors, only 10% of land mass is within 100 km of a coastline, 25% is within 250 km, and 50% is within 750 km. The global mean distance to river mouth is 1050 km with individual continental values from 460 to 1340 km. The Mediterranean/Black Sea and Arctic Ocean are the most land‐dominated of all oceans with land:ocean area ratios of 4.4 and 1.2, respectively; remaining oceans show ratios from 0.55 to 0.13. We discuss limitations of the STN‐30p together with its potential role in future global change studies. STN‐30p is geographically linked to several hundred river discharge and chemistry monitoring stations to provide a framework for calibrating and validating macroscale hydrology and biogeochemical flux models

History of nutrient inputs to the northeastern United States, 1930–2000

Humans have dramatically altered nutrient cycles at local to global scales. We examined changes in anthropogenic nutrient inputs to the northeastern United States (NE) from 1930 to 2000. We created a comprehensive time series of anthropogenic N and P inputs to 437 counties in the NE at 5 year intervals. Inputs included atmospheric N deposition, biological N2 fixation, fertilizer, detergent P, livestock feed, and human food. Exports included exports of feed and food and volatilization of ammonia. N inputs to the NE increased throughout the study period, primarily due to increases in atmospheric deposition and fertilizer. P inputs increased until 1970 and then declined due to decreased fertilizer and detergent inputs. Livestock consistently consumed the majority of nutrient inputs over time and space. The area of crop agriculture declined during the study period but consumed more nutrients as fertilizer. We found that stoichiometry (N:P) of inputs and absolute amounts of N matched nutritional needs (livestock, humans, crops) when atmospheric components (N deposition, N2 fixation) were not included. Differences between N and P led to major changes in N:P stoichiometry over time, consistent with global trends. N:P decreased from 1930 to 1970 due to increased inputs of P, and increased from 1970 to 2000 due to increased N deposition and fertilizer and decreases in P fertilizer and detergent use. We found that nutrient use is a dynamic product of social, economic, political, and environmental interactions. Therefore, future nutrient management must take into account these factors to design successful and effective nutrient reduction measures

Future impacts of fresh water resource management: sensitivity of coastal deltas

We present an assessment of contemporary and future effective sealevel rise (ESLR) using a sample of 40 deltas distributed worldwide. For any delta, ESLR is a net rate defined by eustatic sea-level rise, natural gross rates of fluvial sediment deposition and subsidence, and accelerated subsidence due to groundwater and hydrocarbon extraction. Present-day ESLR, estimated from geospatial data and a simple model of deltaic dynamics, ranges from 0.5 to 12.5 mm year-1. Reduced accretion of fluvial sediment from upstream siltation of reservoirs and freshwater consumptive irrigation losses are primary determinants of ESLR in nearly 70% of the deltas, while for only 12% eustatic sea-level rise predominates. Future scenarios indicate a much larger impact on deltas than previously estimated. Serious challenges to human occupancy of deltas worldwide are conveyed by upland watershed factors, which have been studied less comprehensively than the climate change and sea-level rise question

Riverine ecosystem services and the thermoelectric sector: strategic issues facing the Northeastern United States

Major strategic issues facing the global thermoelectric sector include environmental regulation, climate change and increasing electricity demand. We have addressed such issues by modeling thermoelectric generation in the Northeastern United States that is reliant on cooling under five sensitivity tests to evaluate losses/gains in power production, thermal pollution and suitable aquatic habitat, comparing the contemporary baseline (2000–2010) with potential future states. Integral to the analysis, we developed a methodology to quantify river water availability for cooling, which we define as an ecosystem service. Projected climate conditions reduce river water available for efficient power plant operations and the river\u27s capacity to absorb waste heat, causing a loss of regional thermoelectric generation (RTG) (2.5%) in some summers that, compared to the contemporary baseline, is equal to the summertime electricity consumption of 1.3 million Northeastern US homes. Vulnerabilities to warm temperatures and thermal pollution can be alleviated through the use of more efficient natural gas (NG) power plants that have a reduced reliance on cooling water. Conversion of once-through (OT) to cooling tower (CT) systems and the Clean Water Act (CWA) temperature limit regulation, both of which reduce efficiencies at the single plant level, show potential to yield beneficial increases in RTG. This is achieved by obviating the need for large volumes of river water, thereby reducing plant-to-plant interferences through lowering the impact of upstream thermal pollution and preserving a minimum standard of cooling water. The results and methodology framework presented here, which can be extrapolated to other regional assessments with contrasting climates and thermoelectric profiles, can identify opportunities and support decision-making to achieve more efficient energy systems and riverine ecosystem protection

Global irrigation water demand: Variability and uncertainties arising from agricultural and climate data sets

Agricultural water use accounts for around 70% of the total water that is withdrawn from surface water and groundwater. We use a new, gridded, global-scale water balance model to estimate interannual variability in global irrigation water demand arising from climate data sets and uncertainties arising from agricultural and climate data sets. We used contemporary maps of irrigation and crop distribution, and so do not account for variability or trends in irrigation area or cropping. We used two different global maps of irrigation and two different reconstructions of daily weather 1963–2002. Simulated global irrigation water demand varied by ∼30%, depending on irrigation map or weather data. The combined effect of irrigation map and weather data generated a global irrigation water use range of 2200 to 3800 km3 a−1. Weather driven variability in global irrigation was generally less than ±300 km3 a−1, globally (\u3c∼10%), but could be as large as ±70% at the national scale