Regionalization of Hydrologic Response in the Great Lakes Basin: Considerations of Temporal Scales of Analysis

Methods for predicting streamflow in areas with limited or nonexistent measures of hydrologic response commonly rely on regionalization techniques, where knowledge pertaining to gauged watersheds is transferred to ungauged watersheds. Hydrologic response indices have frequently been employed in contemporary regionalization research related to predictions in ungauged basins. In this study, we developed regionalization models using multiple linear regression and regression tree analysis to derive relationships between hydrologic response and watershed physical characteristics for 163 watersheds in the Great Lakes basin. These models provide an empirical means for simulating runoff in ungauged basins at a monthly time step without implementation of a rainfall-runoff model. For the dependent variable in these regression models, we used monthly runoff ratio as the indicator of hydrologic response and defined it at two temporal scales: (1) treating all monthly runoff ratios as individual observations and (2) using the mean of these monthly runoff ratios for each watershed as a representative observation. Application of the models to 62 validation watersheds throughout the Great Lakes basin indicated that model simulations were far more sensitive to the temporal characterization of hydrologic response than to the type of regression technique employed, and that models conditioned on individual monthly runoff ratios (rather than long term mean values) performed better. This finding is important in light of the increased usage of hydrologic response indices in recent regionalization studies. Models using individual observations for the dependent variable generally simulated monthly runoff with reasonable skill in the validation watersheds (median Nash-Sutcliffe efficiency = 0.53, median R2 = 0.66, median absolute value of deviation of runoff volume = 13%). These results suggest the viability of empirical 3 approaches to simulate runoff in ungauged basins. This finding is significant given the many regions of the world with sparse gaging networks and limited resources for gathering the field data required to calibrate rainfall-runoff models

Hydrologic-economic Feasibility Study on Precipitation Augmentation Over the Great Lakes

published or submitted for publicationis peer reviewedOpe

Investigating the impact of remotely sensed precipitation and hydrologic model uncertainties on the ensemble streamflow forecasting

In the past few years sequential data assimilation (SDA) methods have emerged as the best possible method at hand to properly treat all sources of error in hydrological modeling. However, very few studies have actually implemented SDA methods using realistic input error models for precipitation. In this study we use particle filtering as a SDA method to propagate input errors through a conceptual hydrologic model and quantify the state, parameter and streamflow uncertainties. Recent progress in satellite-based precipitation observation techniques offers an attractive option for considering spatiotemporal variation of precipitation. Therefore, we use the PERSIANN-CCS precipitation product to propagate input errors through our hydrologic model. Some uncertainty scenarios are set up to incorporate and investigate the impact of the individual uncertainty sources from precipitation, parameters and also combined error sources on the hydrologic response. Also probabilistic measure are used to quantify the quality of ensemble prediction. Copyright 2006 by the American Geophysical Union

Fuels treatment and wildfire effects on runoff from Sierra Nevada mixed-conifer forests

We applied an eco-hydrologic model (Regional Hydro-Ecologic Simulation System [RHESSys]), constrained with spatially distributed field measurements, to assess the impacts of forest-fuel treatments and wildfire on hydrologic fluxes in two Sierra Nevada firesheds. Strategically placed fuels treatments were implemented during 2011–2012 in the upper American River in the central Sierra Nevada (43 km2) and in the upper Fresno River in the southern Sierra Nevada (24 km2). This study used the measured vegetation changes from mechanical treatments and modelled vegetation change from wildfire to determine impacts on the water balance. The well-constrained headwater model was transferred to larger catchments based on geologic and hydrologic similarities. Fuels treatments covered 18% of the American and 29% of the Lewis catchment. Averaged over the entire catchment, treatments in the wetter central Sierra Nevada resulted in a relatively light vegetation decrease (8%), leading to a 12% runoff increase, averaged over wet and dry years. Wildfire with and without forest treatments reduced vegetation by 38% and 50% and increased runoff by 55% and 67%, respectively. Treatments in the drier southern Sierra Nevada also reduced the spatially averaged vegetation by 8%, but the runoff response was limited to an increase of less than 3% compared with no treatment. Wildfire following treatments reduced vegetation by 40%, increasing runoff by 13%. Changes to catchment-scale water-balance simulations were more sensitive to canopy cover than to leaf area index, indicating that the pattern as well as amount of vegetation treatment is important to hydrologic response

Forecasting seasonal hydrologic response in major river basins.

Seasonal precipitation variation due to natural climate variation influences stream flow and the apparent frequency and severity of extreme hydrological conditions such as flood and drought. To study hydrologic response and understand the occurrence of extreme hydrological events, the relevant forcing variables must be identified. This study attempts to assess and quantify the historical occurrence and context of extreme hydrologic flow events and quantify the relation between relevant climate variables. Once identified, the flow data and climate variables are evaluated to identify the primary relationship indicators of hydrologic extreme event occurrence. Existing studies focus on developing basin-scale forecasting techniques based on climate anomalies in El Nino/La Nina episodes linked to global climate. Building on earlier work, the goal of this research is to quantify variations in historical river flows at seasonal temporal-scale, and regional to continental spatial-scale. The work identifies and quantifies runoff variability of major river basins and correlates flow with environmental forcing variables such as El Nino, La Nina, sunspot cycle. These variables are expected to be the primary external natural indicators of inter-annual and inter-seasonal patterns of regional precipitation and river flow. Relations between continental-scale hydrologic flows and external climate variables are evaluated through direct correlations in a seasonal context with environmental phenomenon such as sun spot numbers (SSN), Southern Oscillation Index (SOI), and Pacific Decadal Oscillation (PDO). Methods including stochastic time series analysis and artificial neural networks are developed to represent the seasonal variability evident in the historical records of river flows. River flows are categorized into low, average and high flow levels to evaluate and simulate flow variations under associated climate variable variations. Results demonstrated not any particular method is suited to represent scenarios leading to extreme flow conditions. For selected flow scenarios, the persistence model performance may be comparable to more complex multivariate approaches, and complex methods did not always improve flow estimation. Overall model performance indicates inclusion of river flows and forcing variables on average improve model extreme event forecasting skills. As a means to further refine the flow estimation, an ensemble forecast method is implemented to provide a likelihood-based indication of expected river flow magnitude and variability. Results indicate seasonal flow variations are well-captured in the ensemble range, therefore the ensemble approach can often prove efficient in estimating extreme river flow conditions. The discriminant prediction approach, a probabilistic measure to forecast streamflow, is also adopted to derive model performance. Results show the efficiency of the method in terms of representing uncertainties in the forecasts

Uncertainty quantification of satellite precipitation estimation and Monte Carlo assessment of the error propagation into hydrologic response

The aim of this paper is to foster the development of an end-to-end uncertainty analysis framework that can quantify satellite-based precipitation estimation error characteristics and to assess the influence of the error propagation into hydrological simulation. First, the error associated with the satellite-based precipitation estimates is assumed as a nonlinear function of rainfall space-time integration scale, rain intensity, and sampling frequency. Parameters of this function are determined by using high-resolution satellite-based precipitation estimates and gauge-corrected radar rainfall data over the southwestern United States. Parameter sensitivity analysis at 16 selected 5° × 5° latitude-longitude grids shows about 12-16% of variance of each parameter with respect to its mean value. Afterward, the influence of precipitation estimation error on the uncertainty of hydrological response is further examined with Monte Carlo simulation. By this approach, 100 ensemble members of precipitation data are generated, as forcing input to a conceptual rainfall-runoff hydrologic model, and the resulting uncertainty in the streamflow prediction is quantified. Case studies are demonstrated over the Leaf River basin in Mississippi. Compared with conventional procedure, i.e., precipitation estimation error as fixed ratio of rain rates, the proposed framework provides more realistic quantification of precipitation estimation error and offers improved uncertainty assessment of the error propagation into hydrologic simulation. Further study shows that the radar rainfall-generated streamflow sequences are consistently contained by the uncertainty bound of satellite rainfall generated streamflow at the 95% confidence interval. Copyright 2006 by the American Geophysical Union

Discharge Characteristics and Changes over the Ob River Watershed in Siberia

This study analyzes long-term (1936–90) monthly streamflow records for the major subbasins within the Ob River watershed in order to examine discharge changes induced by human activities (particularly reservoirs and agricultural activities) and natural variations. Changes in streamflow pattern were found to be different between the upper and lower parts of the Ob watershed. Over the upper Ob basin, streamflow decreases in summer months and increases in the winter season. The decreases in summer are mainly due to water uses along the river valley for agricultural and industrial purposes and to reservoir regulation to reduce the summer peak floods. The increases in winter streamflow are caused by reservoir impacts to release water for power generation over winter months. In the lower Ob regions, however, streamflow increased during midsummer and winter months and weakly decreased in autumn. These increases in summer flow are associated with increases in summer precipitation and winter snow cover over the northern Ob basin. Because of reservoir regulations and water uses in the upper parts of the Ob basin, it is a great challenge to determine hydrologic response to climate change and variation at the basin scale. Discharge records observed at the Ob basin outlet do not always represent natural changes and variations mainly due to impacts of large dams; they tend to underestimate the natural runoff trends in summer and overestimate the trends in winter and autumn seasons. This study clearly demonstrates regional differences in hydrologic response to climate changes and variations within a large watershed such as the Ob River. It also illustrates that, relative to climatic effects, human activities are sometimes more important and direct in altering regional hydrologic regimes and affecting their long-term changes particularly at both seasonal and regional scales. It is, therefore, necessary to consider human activities in regional/global environment change analyses and further examine their impacts in other large northern watersheds

Hydrologic Response of Alternative Valley Fill Reclamation Designs

Mountaintop mining (MTM) is a widely practiced surface mining technique in Central Appalachian Conventional reclamation (Approximate Original Contour), involves the construction of valley fills of headwater systems. Recent research suggests that current MTM reclamation techniques increase stormflow response of the affected watersheds when compared to the original, undisturbed conditions. One method that has shown success in reclaiming surface mine sites in semi-arid regions of the western U.S. is geomorphic landform design. Geomorphic reclamation is based upon creating landforms that resemble the mature surrounding watersheds in both topography and hydrologic response. The objective of this research was to predict the hydrologic response of a mine site reclaimed using geomorphic methods for a location in southern West Virginia. Three alternative geomorphic reclamation designs were modeled using Aquaveo\u27s Watershed Modeling System: i) a geomorphic reclamation of the valley fill; ii) a geomorphic reclamation of the valley fill with three detention ponds; and, iii) a geomorphic retrofit design. Results were compared to the response of both the original, undisturbed topography and a conventional valley fill. The peak flowrate, time to peak, and runoff volumes were evaluated at three stages of reclamation (during mining, post-mining ( 5 years)) for a range of storm events (1- through 500-year, 24-hour). The hydrologic response of the geomorphic landform design without detention ponds most closely resembled the values obtained for the original watershed. The geomorphic design with detention ponds lowered the peak flowrate, time of peak, and total runoff volume below the values generated by the original watershed. The runoff storage within the detention ponds provides the potential to allow stream flow in excess of ephemeral conditions. However, the ponds need to be properly sized to allow greater runoff storage if intermittent or perennial stream flow is desired. The effectiveness of the retrofit reclamation design was difficult to determine due to changes in watershed area and drainage pattern. These results indicate that geomorphic landform designs could be used to recreate the approximate hydrologic response of the original watershed for reclaimed mountaintop mine sites in southern West Virginia watersheds