Glenn E. Moglen

Space-time scale sensitivity of the Sacramento model to radar-gage precipitation inputs

Runoff timing and volume biases are investigated when performing hydrologic forecasting at space-time scales different from those at which the model parameters were calibrated. Hydrologic model parameters are inherently tied to the space-time scales at which they were calibrated. The National Weather Service calibrates rainfall runoff models using 6-hour mean areal precipitation (MAP) inputs derived from gage networks. The space-time scale sensitivity of the Sacramento model runoff volume is analyzed using 1-hour, 4 × 4 km2 next generation weather radar (NEXRAD) precipitation estimates to derive input MAPs at various space-time scales. Continuous simulations are run for 9 months for time scales of 1, 3 and 6 hours, and spatial scales ranging from 4 × 4 km2 up to 256 × 256 km2. Results show surface runoff, interflow, and supplemental baseflow runoff components are the most sensitive to the space-time scales analyzed. Water balance components of evapotranspiration and total channel inflow are also sensitive. A preliminary approach for adjusting model parameters to account for spatial and temporal variation in rainfall input is presented.

How to Avoid Train Wrecks When Using Science in Environmental Problem Solving

I collaborations are increasingly common in many areas of science, but particularly in fields involved with environmental problems. This is because problems related to human interactions with the environment typically contain numerous parameters, reflect extensive human alterations of ecosystems, require understanding of physical–biological interactions at multiple spatial and temporal scales, and involve economic and social capital. Distilling useful scientific information in collaborative interactions is a challenge, as is the transfer of this information to others, including scientists, stakeholders, resource managers, policymakers, and the public. While this problem has been recognized by historians and philosophers of science, it has rarely been recognized and openly discussed by scientists themselves (but see NAS 1986). The participation of individuals from a diverse set of scientific disciplines has the potential to enhance the success of problem solving (USGS/ESA 1998). However, obstacles often arise in collaborative efforts for several well-known reasons. First, it is often difficult to find a common language because of disciplinary specialization (Wear 1999, Sarewitz et al. 2000). Second, existing scientific knowledge (theories, models, etc.) may reflect a historical scientific and sociopolitical context that may make it ill suited to address current environmental problems and questions (see, for example, Ford 2000, NSB 2000). Third, collaborations involving multiple disciplines may create difficulties owing to mismatches in space and time scales, in forms of knowledge (e.g., qualitative versus quantitative), and in levels of precision and accuracy (see, for example, Herrick 2000). Fourth, scientists are partly conditioned by nonscientific values. A social fabric may dictate scientists’ worldviews, lead them to favor certain assumptions over others, and underlie the way they study ecosystems (Boyd et al. 1991). In this article, we argue that the success of interdisciplinary collaborations among scientists can be increased by adopting a formal methodology that considers the structure of knowledge in cooperating disciplines. For our purposes, the structure of knowledge comprises five categories of information: (1) disciplinary history and attendant forms of available scientific knowledge; (2) spatial and temporal scales at which that knowledge applies; (3) precision (i.e., qualitative versus quantitative nature of understanding across different scales); (4) accuracy of predictions; and (5) availability of data to construct, calibrate, and test predictive models. By definition, therefore, evaluating a structure of knowledge reveals limitations in scientific understanding, such as what knowledge is lacking or what temporal or spatial scale mismatches exist among disciplines. The epistemological exercise of defining knowledge structures at the onset of a collaborative exercise can be used to construct solvable problems: that is, questions that can be an-

Ecological Forecasting and the Urbanization of Stream Ecosystems: Challenges for Economists, Hydrologists, Geomorphologists, and Ecologists

The quantity and quality of freshwater resources are now being seriously threatened, partly as a result of extensive worldwide changes in land use, and scientists are often called upon by policy makers and managers to predict the ecological consequences that these alterations will have for stream ecosystems. The effects of the urbanization of stream ecosystems in the United States over the next 20 years are of particular concern. To address this issue, we present a multidisciplinary research agenda designed to improve our forecasting of the effects of land-use change on stream ecosystems. Currently, there are gaps in both our knowledge and the data that make it difficult to link the disparate models used by economists, hydrologists, geomorphologists, and ecologists. We identify a number of points that practitioners in each discipline were not comfortable compromising on—for example, by assuming an average condition for a given variable. We provide five instructive examples of the limitations to our ability to forecast the fate of stream and riverine ecosystems one drawn from each modeling step: (a) Accurate economic methods to forecast land-use changes over long periods (such as 20 years) are not available, especially not at spatially explicit scales; (b) geographic data are not always available at the appropriate resolution and are not always organized in categories that are hydrologically, ecologically, or economically meaningful; (c) the relationship between low flows and land use is sometimes hard to establish in anthropogenically affected catchments; (d) bed mobility, suspended sediment load, and channel form—all of which are important for ecological communities in streams—are difficult to predict; and (e) species distributions in rivers are not well documented, and the data that do exist are not always publicly available or have not been sampled at accurate scales, making it difficult to model ecological responses to specified levels of environmental change. Meeting these challenges will require both interdisciplinary cooperation and a reviewed commitment to intradisciplinary research in the fields of economics, geography, quantitative spatial analysis, hydrology, geomorphology, and ecology.

On the sensitivity of drainage density to climate change

Drainage density reflects the signature of climate on the topography and dictates the boundary conditions for surface hydrology. Hence defining the relationship between drainage density and climate is important in assessing the sensitivity of water resources and hydrology to climate change. Here we analyze the equilibrium relationship between drainage density and climate and estimate the relative sensitivity of drainage density to climate change. We conclude that the sign of the resulting change in drainage density depends not only on the direction of the change in climate but also on the prevailing climatic regime.

Stochastic model of the width function

A new class of probabilistic models of the width function, based on so-called iterated random pulse (IRP) processes, is proposed. IRP processes reproduce the main characteristics of empirical width functions (nonnegativity, nonstationarity, and power law decay of the spectrum) and require few and easily accessible parameters. IRP models are based on a simple conceptualization of the geometrical structure of river basins and exploit in a natural way the self-similarity of natural channel networks. A result that is derived from the IRP representation is that the exponent α of Hacks law, L ∼ Aα, and the exponent β of the power spectral density of the width function, S(ω) ∼ |ω|−β, are related as α = 1/β. Empirical values of β are typically in the range 1.8–2.0 and are consistent with this theoretical result and the usual range of α.

Hydro‐Ecologic Responses to Land Use in Small Urbanizing Watersheds within the Chesapeake Bay Watershed

Urbanization in the Chesapeake Bay watershed is having dramatic impacts on the streams and rivers that feed the Bay. Increasing imperviousness has led to higher peak flows and lower base flows. The movement of pollutants and other materials to receiving waters has increased and stream water temperatures have risen. These changes alter the structure and functioning of rivers, streams, and associated riparian corridors and result in changes in ecosystem services. We define a hydrologic disturbance index that indicates varying degrees of disturbance on a reach-by-reach basis, dependent on the aggregate amount of urbanization upstream of each reach. For current conditions this index is more variable than for future conditions, because current land use in the study watershed is more variable, containing mixtures of urban, agricultural, and forested land. In contrast, future land use is projected to be more uniformly urban, leading to a less variable but greater overall degree of hydrologic disturbance. Two effects of urbanization on fish are explored through ecological modeling: effects of streambed disturbance on food availability and effects of stream temperature on spawning. We tabulate food availability as a function of bed-mobility for 30 different fish species. We show that additional stress occurs with additional urbanization of the watershed. We show that the urban-related increase in stream temperatures may cause several warm-water species to actually gain opportunities to spawn in some cases. However, combining food availability and spawning day availability into a single index reveals highly stressful conditions for all fish species under the fully developed scenario.

Effects of detention basins on in-stream sediment movement

Abstract Detention basins, which are designed to control peak discharge rates, appear to increase bed transport rates. The effect of designing detention basins for controlling bed-material loads, rather than peak discharge control, on both bed-material loads and discharge rates is evaluated. The results indicate that the proper sizing of outlet structures of detention basins can reduce channel degradation to normal levels, as well as control peak discharge rates. Detention basins also serve to reduce wash loads. A method is provided for sizing detention basin outlet structures so that the detention time is sufficient to attain a preselected trap efficiency. Data from two small watersheds with detention basins were used to derive the trap efficiency and detention time curves.

Climate Change and Storm Water Infrastructure in the Mid-Atlantic Region: Design Mismatch Coming?

AbstractClimate change is anticipated to result in changes to the statistical properties of both precipitation depths and precipitation intensity. As a general representative for storm water infrastructure, this work examines changes in detention basin performance under several different climate change model scenarios at the study location north of Washington, DC. Frequency analysis of simulated climate model precipitation data indicates that both precipitation depths and intensities are predicted to change under future climate. The magnitude and direction of these changes vary from one climate model to the next. 24-h design storms consistent with the future climate precipitation data are used to drive a rainfall-runoff model simulating a watershed/detention basin system. In most cases, the performance of a detention basin design based on present climate is inadequate under future climate conditions. This work explores detention basin performance based on future precipitation depths only, storm intensity ...

Changes to Bridge Flood Risk under Climate Change

AbstractBridge designs are commonly based on a criterion to withstand the n-year flood event. For example, a highway bridge might be designed to pass the 100-year flood. Failure may occur if the structure faces an event larger than this. Climate change may necessitate different design criteria because of changes to flood frequency behavior. This study examines the consequences for bridge design for flooding under the influence of climate change. In this study, climate change is quantified simply as a change in the frequency of a given precipitation or flood event. Flood discharges for current conditions are estimated from the applicable U.S. Geological Survey regression equations. Natural Resources Conservation Service methods are used to inverse calculate the causal precipitation for such floods. Return frequency for this causal precipitation is determined from both the current national precipitation frequency source and future climate intensity-duration-frequency curves. This study specifically looks at...

Evolutionary Algorithm Optimization of a Multireservoir System with Long Lag Times

AbstractA scenario of particular importance in water resources management occurs when reservoir release decisions must be made well in advance of accurate hydrologic forecasts because of long travel times between reservoir releases and demand. This type of situation is evaluated using the Washington metropolitan area (WMA) water supply as a case study. Several classes of operating rules are evaluated using a state-of-the-art multiobjective evolutionary algorithm linked to a hydrologic simulation/decision model. Operating rules were evaluated using historical Potomac River streamflows (1929–2007) and synthetically generated time series. The proposed optimization framework is effective for a wide range of water resources vulnerability studies and was successful in improving the efficiency of the WMA system with respect to competing objectives ranging from reservoir storage to recreation and environmental flow requirements.