DOCUMENTED AUTUMNAL STREAMFLOW INCREASE WITHOUT MEASURABLE PRECIPITATION1

ABSTRACT: In the south-central interior of British Columbia, the summer and fall of 1987 were very dry. Streamflow was extremely low throughout the region, and an extended rainless period coincided with the onset of the winter dormant period. During a five-day rainless period from October 9 to October 13, which should have been a period of declining streamflow in all watersheds, 19 of 31 small forested watersheds having suitable natural flow record experienced increasing discharge. The data is reviewed and analyzed with an initial attempt made to explain the streamflow changes among the various watersheds quantitatively. The only explanation for the widespread increases in streamflow in the region during this dry period is that greatly reduced transpiration, as the vegetation went dormant, permitted increased volumes of water in the soil to drain into surface streams rapidly enough to be recorded as increased discharge in 61 percent of the study streams.     

Effect of the Spatial Variability of Land Use,Soil Type,and Precipitation on Streamflows in Small Watersheds1

Abstract: The spatial variability of the data used in models includes the spatial discretization of the system into subsystems, the data resolution, and the spatial distribution of hydrologic features and parameters. In this study, we investigate the effect of the spatial distribution of land use, soil type, and precipitation on the simulated flows at the outlet of “small watersheds” (i.e., watersheds with times of concentration shorter than the model computational time step). The Soil and Water Assessment Tool model was used to estimate runoff and hydrographs. Different representations of the spatial data resulted in comparable model performances and even the use of uniform land use and soil type maps, instead of spatially distributed, was not noticeable. It was found that, although spatially distributed data help understand the characteristics of the watershed and provide valuable information to distributed hydrologic models, when the watershed is small, realistic representations of the spatial data do not necessarily improve the model performance. The results obtained from this study provide insights on the relevance of taking into account the spatial distribution of land use, soil type, and precipitation when modeling small watersheds.     

HYDROCLIMATIC VARIABILITY IN THE ROCKY MOUNTAINS1

ABSTRACT: The spatial and temporal variability of hydroclimatic elements were investigated in the central and northern Rocky Mountains (Colorado, Idaho, Montana, Utah, and Wyoming) during the 1951–1985 period. The three hydroclimatic elements studied were total water-year (October 1-September 30) streamflow (ST), winter (October 1-March 31) accumulated precipitation (PR), and April 1 snowpack (SN). An analysis of 14 virgin watersheds showed wide spatial djfferences in the temporal variability of SN, PR, and ST, and these were found to be caused largely by basin exposure to moist air flows. The more stable (low variability) basins were those exposed to prevailing northerly to westerly flow, while unstable (high variability) basins were exposed to occasional southwesterly to southeasterly moist flow. Snowpack was the better indicator of ST in 11 of the 14 watersheds, explaining 37 to 87 percent of the ST variance. Analysis of the spatial variability, based on all SN and PR data from across the study area, revealed 11 discrete climatic regions. Both SN and PR exhibited coherent regions of stable and unstable temporal variability. The average variability between stable and unstable regions differed by a factor of two, and the differences were best explained by the exposure of the mountain barrier to moist air flows.     

MODELING STREAMFLOW FROM ARTIFICIALLY DRAINED AGRICULTURAL WATERSHEDS IN ILLINOIS1

ABSTRACT: Evaluation of the applicability and validity of hydrologic simulation models for various cropping systems in different hydrogeologic and soil conditions is needed for a range of spatial scales. We calibrated and tested the ADAPT model for simulating streamflow from 552 to 1,985 km² watersheds in central Illinois, where more than 79 percent of the land is used for maize‐soybean production and tile drainage is common. Model calibration was performed with a seven year period (1987 through1993) of measured streamflow from one of the watersheds, and model testing was done using independent weather and measured streamflow data from the two neighboring watersheds for the same seven year period. Simulations of annual streamflow were accurate with a coefficient of determination and Willmott's index of agreement of 0.98 and 0.99, respectively. For simulation of monthly streamflow, Willmott's index of agreement ranged from 0.93 to 0.95. For simulation of daily streamflow, Willmott's index of agreement ranged from 0.84 to 0.85. The daily simulations challenged the temporal and spatial resolution of our measured precipitation data. Discrepancies between simulated and measured data may result from the model's inability to effectively address frozen soils and snowmelt runoff processes and in accurately representing evapotranspiration.     

Quantitative Assessment of the Intertidal Environment of Kuwait II: Controlling Factors

Multivariate analysis of variance, canonical correlation and canonical discriminate analysis were performed on environmental data collected from the Kuwaiti intertidal zone to determine the statistical relationships between the sediment, chemical, biological, spatial and temporal variables. The quantitative analysis showed that the sediment type was the paramount factor influencing the distribution and composition of the intertidal benthic fauna. The muddy, sandy and rocky shores support three distinct faunal communities. The seasonal variation in the benthic fauna community was not statistically significant but variation in biological data due to differences in transect location and tidal level were significant. This spatial variation has been attributed to differences in sediment and substrate types. The physico-chemical parameters were found to correlate positively with the mud content of the sediments but were unimportant in the overall composition of the intertidal fauna. This paper complements the results reported in Al Bakriet al. (1997–Part I) in establishing a valuable benchmark for assessing environmental impacts and for developing sustainable coastal zone management in Kuwait. The integrated approach outlined here could be adopted to develop a sound basis for the protection and management of coastal environments and resources in similar areas.     

Riparian Zone Management in the Pacific Northwest: Who's Cutting What?

Oncorhynchus sp.), regional governments now restrict timber harvest in riparian forests. I summarize and assess the riparian zone management guidelines of the states of California, Oregon, and Washington (USA) and the province of British Columbia (Canada). Only Oregon and British Columbia protect fish-bearing streams with “no-harvest” zones, and only the wider (20–50 m) no-harvest zones for larger fish-bearing streams in British Columbia are likely to maintain near-natural linkages between riparian and stream ecosystems. All four jurisdictions protect most streams with “management zones” of variable width, in which timber harvest activities are restricted. All the management zone guidelines permit the harvest of the largest conifers from riparian forests and will, if applied over a series of timber harvest rotations (60–80 years), result in the continued removal of potential sources of large woody debris from the region's watersheds. All four jurisdictions require additional protection for streams and watersheds that are severely degraded or (in the United States) contain threatened or endangered species. The governments of the PNW have taken a “manage until degraded, then protect” approach to riparian forest management that is unlikely to maintain or restore the full suite of riparian-stream linkages necessary for lotic ecosystems to function naturally at the stream, watershed, basin, or regional scale.     

Estimation of Daily Streamflow of Southeastern Coastal Plain Watersheds by Combining Estimated Magnitude and Sequence

Commonly used methods to predict streamflow at ungauged watersheds implicitly predict streamflow magnitude and temporal sequence concurrently. An alternative approach that has not been fully explored is the conceptualization of streamflow as a composite of two separable components of magnitude and sequence, where each component is estimated separately and then combined. Magnitude is modeled using the flow duration curve (FDC), whereas sequence is modeled by transferring streamflow sequence of gauged watershed(s). This study tests the applicability of the approach on watersheds ranging in size from about 25‐7,226 km² in Southeastern Coastal Plain (U.S.) with substantial surface storage of wetlands. A 19‐point regionalized FDC is developed to estimate streamflow magnitude using the three most selected variables (drainage area, hydrologic soil index, and maximum 24‐h precipitation with a recurrence interval of 100 years) by a greedy‐heuristic search process. The results of validation on four watersheds (Trent River, North Carolina: 02092500; Satilla River, Georgia: 02226500; Black River, South Carolina: 02136000; and Coosawhatchie River, South Carolina: 02176500) yielded Nash‐Sutcliffe efficiency values of 0.86‐0.98 for the predicted magnitude and 0.09‐0.84 for the predicted daily streamflow over a simulation period of 1960‐2010. The prediction accuracy of the method on two headwater watersheds at Santee Experimental Forest in coastal South Carolina was weak, but comparable to simulations by MIKE‐SHE.     

VARIABILITY CHARACTERISTICS OF MONTHLY PRECIPITATION IN CENTRAL OKLAHOMA1

ABSTRACT: To fully take advantage of regional climate forecast information for agricultural applications, the relationship between divisional and station scale precipitation characteristics must be quantified. The spatial variability of monthly precipitation is assumed to consist of two components: a systematic and a random component. The systematic component is defined by differences in long-term mean precipitation between stations within a climate division, and the random component by differences between station and divisional standardized values. For the Central Climate Division of Oklahoma, the systematic component has a positive precipitation gradient from west to east with a slope ranging between 3 to 16 mm of precipitation per 100 km depending on the month of the year. On the other hand, the random component ranges between 27 to 48 percent of the mean temporal variation of the monthly precipitation. This significant random spatial variability leads to large localized departures from divisional values, and clearly demonstrates the critical influence of the random component in the utilization of divisional climate forecasts for local agricultural applications. The results of this study also provide an uncertainty range for local monthly precipitation projections that are derived from divisional climate information.     

Spatial and Temporal Patterns of Low Streamflow and Precipitation Changes in the Chesapeake Bay Watershed

Spatial and temporal patterns in low streamflows were investigated for 183 streamgages located in the Chesapeake Bay Watershed for the period 1939–2013. Metrics that represent different aspects of the frequency and magnitude of low streamflows were examined for trends: (1) the annual time series of seven‐day average minimum streamflow, (2) the scaled average deficit at or below the 2% mean daily streamflow value relative to a base period between 1939 and 1970, and (3) the annual number of days below the 2% threshold. Trends in these statistics showed spatial cohesion, with increasing low streamflow volume at streamgages located in the northern uplands of the Chesapeake Bay Watershed and decreasing low streamflow volume at streamgages in the southern part of the watershed. For a small subset of streamgages (12%), conflicting trend patterns were observed between the seven‐day average minimum streamflow and the below‐threshold time series and these appear to be related to upstream diversions or the influence of reservoir‐influenced streamflows in their contributing watersheds. Using multivariate classification techniques, mean annual precipitation and fraction of precipitation falling as snow appear to be broad controls of increasing and decreasing low‐flow trends. Further investigation of seasonal precipitation patterns shows summer rainfall patterns, driven by the Atlantic Multidecadal Oscillation, as the main driver of low streamflows in the Chesapeake Bay Watershed.     

DETECTING CILANGES IN THE SPATIAL DISTRIBUTION OF NITRATE CONTAMINATION IN GROUND WATER1

ABSTRACT: Many studies of ground water pollution in general and nitrate contamination in particular have often relied on a one-time investigation, tracking of individual wells, or aggregate summaries. Studies of changes in spatial distribution of contaminants over time are lacking. This paper presents a method to compare spatial distributions for possible changes over time. The large-scale spatial distribution at a given time can be considered as a surface over the area (a trend surface). The changes in spatial distribution from period to period can be revealed by the differences in the shape and/or height of surfaces. If such a surface is described by a polynomial function, changes in surfaces can be detected by testing statistically for differences in their corresponding polynomial functions. This method was applied to nitrate concentration in a population of wells in an agricultural drainage basin in Iowa, sampled in three different years. For the period of 1981–1992, the large-scale spatial distribution of nitrate concentration did not show significant change in the shape of spatial surfaces; while the magnitude of nitrate concentration in the basin, or height of the computed surfaces showed significant fluctuations. The change in magnitude of nitrate concentration is closely related to climatic variations, especially in precipitation. The lack of change in the shape of spatial surfaces means that either the influence of land use/nitrogen management was overshadowed by climatic influence, or the changes in land use/management occurred in a random fashion.     

WATER POLLUTION FROM OIL AND GAS RECOVERY IN EASTERN KENTUCKY WATERSHEDS1

The effects of water quality on brine discharged from oil and gas recovery operations are described for surface water and ground water in two small watersheds in eastern Kentucky. The brine, which had salinity that was often several times that of sea water, led to significantly higher concentrations of several minerals in surface water, particularly in the first and second order streams. Concentractions as high as 50,000 mg/I for sodium and 64,000 mg/I for chloride were measured in streams. The. differences in chemical concentrations for various chemicals over the period of the study were ascribed to temporal variability, particularly due to differences between wet and dry seasons, and to spatial variability, particularly due to dilution and other chemical decay processes. Chemical decay coefficients for sodium and chloride were developed as a function of watershed area for possible application to similar watersheds. There was some evidence that the brine was influencing the Licking River, the major stream that drains the eastern part of Kentucky.     

Urbanization and Its Effect On Runoff in the Whiteoak Bayou Watershed,Texas1

Abstract: The capacity of a watershed to urbanize without changing its hydrologic response and the relationship between that response and the spatial configuration of the developed areas was studied. The study was conducted in the Whiteoak Bayou watershed (223 km²), located northwest of Houston, Texas, over an analysis period from 1949 to 2000. Annual development data were derived from parcel data collected by the Harris County Appraisal District. Using these data, measures of the spatial configuration of the watershed urban areas were calculated for each year. Based on regression models, it was determined that the annual runoff depths and annual peak flows depended on the annual precipitation depth, the developed area and the maximum 12‐h precipitation depth on the day and day before the peak flow took place. It was found that, since the early 1970s, when the watershed reached a 10% impervious area, annual runoff depths and peak flows have increased by 146% and 159%, respectively. However, urbanization is responsible for only 77% and 32% of the increase, respectively, while precipitation changes are responsible for the remaining 39% and 96%, respectively. Likewise, an analysis of the development data showed that, starting in the early 1970s, urbanization in the watershed consisted more of connecting already developed areas than of creating new ones, which increases the watershed’s conveyance capacity and explains the change in its response. Before generalizing conclusions, though, further research on other urban watersheds with different urbanization models appears to be necessary.     

Spatial and Temporal Evaluation of Hydrological Response to Climate and Land Use Change in Three South Dakota Watersheds

This study analyzed changes in hydrology between two recent decades (1980s and 2010s) with the Soil and Water Assessment Tool (SWAT) in three representative watersheds in South Dakota: Bad River, Skunk Creek, and Upper Big Sioux River watersheds. Two SWAT models were created over two discrete time periods (1981‐1990 and 2005‐2014) for each watershed. National Land Cover Datasets 1992 and 2011 were, respectively, ingested into 1981‐1990 and 2005‐2014 models, along with corresponding weather data, to enable comparison of annual and seasonal runoff, soil water content, evapotranspiration (ET), water yield, and percolation between these two decades. Simulation results based on the calibrated models showed that surface runoff, soil water content, water yield, and percolation increased in all three watersheds. Elevated ET was also apparent, except in Skunk Creek watershed. Differences in annual water balance components appeared to follow changes in land use more closely than variation in precipitation amounts, although seasonal variation in precipitation was reflected in seasonal surface runoff. Subbasin‐scale spatial analyses revealed noticeable increases in water balance components mostly in downstream parts of Bad River and Skunk Creek watersheds, and the western part of Upper Big Sioux River watershed. Results presented in this study provide some insight into recent changes in hydrological processes in South Dakota watersheds. Editor's note: This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

EVALUATION OF THE APPLICABILITY OF THE SWAT MODEL FOR COASTAL WATERSHEDS IN SOUTHEASTERN LOUISIANA1

ABSTRACT: The Soil and Water Assessment Tool (SWAT) has been used for hydrologic analyses at various watershed scales. However, little is known about the model's performance in coastal watersheds. In this study SWAT was evaluated for its applicability in three Louisiana coastal watersheds: the Amite, Tickfaw, and Tangipahoa River watersheds. The model was calibrated with daily discharge from 1976 to 1977 and validated from 1979 to 1999 for the Amite and Tangipahoa and with daily discharge from 1979 to 1989 for the Tickfaw. Deviation of mean discharge and the Nash‐Sutcliffe model efficiency were used to evaluate model behavior. The study found that Manning's roughness coefficient for the main channel, SCS curve number, and soil evaporation compensation factor were the most sensitive parameters for these coastal watersheds. The Manning's roughness coefficient showed the greatest effect on the response time of surface runoff, suggesting the critical role of channel routing in hydrologic modeling for lowland watersheds. The SWAT model demonstrated an excellent performance, with Nash‐Sutcliffe efficiencies of 0.935, 0.940, and 0.960 for calibrations of the Amite, Tickfaw, and Tangipahoa watersheds, respectively, and of 0.851, 0.811, and 0.867 for validations. The modeling results demonstrate that SWAT is capable of simulating hydrologic processes for medium scale to large scale coastal lowland watersheds in Louisiana.     

MODELING TRANSIENT pH DEPRESSIONS IN COASTAL STREAMS OF BRITISH COLUMBIA USING NEURAL NETWORKS1

ABSTRACT: Transient events in water chemistry in small coastal watersheds, particularly pH depressions, are largely driven by inputs of precipitation. While the response of each watershed depends upon both the nature of the precipitation event and the season of the year, how the response changes over time can provide insight into landscape changes. Neural network models for an urban watershed and a rural‐suburban watershed were developed in an attempt to detect changes in system response resulting from changes in the landscape. Separate models for describing pH depressions for wet season and dry season conditions were developed for a seven year period at each watershed. The neural network models allowed separation of the effects of precipitation variations and changes in watershed response. The ability to detect trends in pH depression magnitudes was improved by analyzing neural network residuals rather than the raw data. Examination of sensitivity plots of the models indicated how the neural networks were affected by different inputs. There were large differences in effects between seasons in the rural‐suburban watershed whereas effects in the urban watershed were consistent between seasons. During the study period, the urban watershed showed no change in pH depression response, while the rural‐suburban watershed showed a significant increase in the magnitude of pH depressions, likely the result of increased urbanization.     

大气汞的时空分布研究进展

大气汞是汞全球循环的组成部分，探索汞在大气中的时空分布对于研究其地球化学循环具有重要意义。本文综述了大气汞时空分布的研究现状，主要包括大气汞的来源，形态分布，空间分布度时间分布。研究表明，大气汞具有扩散范围广，空间变异大，时间变化规律性强的特点，同时还指出扩大时空分布研究范围和建立污染和预测模型是未来的研究重点。     

MODELING DEVELOPED COASTAL WATERSHEDS WITH THE AGRICULTURAL NON-POINT SOURCE MODEL1

ABSTRACT: Many coastal states are facing increasing urban growth along their coast lines. The growth has caused urban non-point source nitrogen runoff to be a major contributor to coastal and estuarine enrichment. Water resource managers are responsible for evaluating the impacts from point and non-point sources in developed watersheds and developing strategies to manage future growth. Non-point source models provide an effective approach to these management challenges. The Agricultural Non-Point Source Model (AGNPS) permits the incorporation of important spatial information (soils, landuse, topography, hydrology) in simulating surface hydrology and nitrogen non-point source runoff. The AGNPS model was adapted for developed coastal watersheds by deriving urban coefficients that reflect urban landuse classes and the amount of impervious surface area. Popperdam Creek watershed was used for model parameter development and model calibration. Four additional watersheds were simulated to validate the model. The model predictions of the peak flow and total nitrogen concentrations were close to the field measurements for the five sub-basins simulated. Measured peak flow varied by 30 fold among the sub-basins. The average simulated peak flow was within 14 percent of the average measured peak flow. Measured total nitrogen loads varied over an order of magnitude among the sub-basins yet error between the measured and simulated loads for a given sub-basin averaged 5 percent. The AGNPS model provided better estimates of nitrogen loads than widely used regression methods. The spatial distribution of important watershed characteristics influenced the impacts of urban landuse and projecting future residential expansion on runoff, sediment and nitrogen yields. The AGNPS model provides a useful tool to incorporate these characteristics, evaluate their importance, and evaluate fieldscale to watershed-scale urban impacts.     

GIS‐Based Spatial Precipitation Estimation: A Comparison of Geostatistical Approaches1

Abstract: As one of the primary inputs that drive watershed dynamics, the estimation of spatial variability of precipitation has been shown to be crucial for accurate distributed hydrologic modeling. In this study, a Geographic Information System program, which incorporates Nearest Neighborhood (NN), Inverse Distance Weighted (IDW), Simple Kriging (SK), Ordinary Kriging (OK), Simple Kriging with Local Means (SKlm), and Kriging with External Drift (KED), was developed to facilitate automatic spatial precipitation estimation. Elevation and spatial coordinate information were used as auxiliary variables in SKlm and KED methods. The above spatial interpolation methods were applied in the Luohe watershed with an area of 5,239 km², which is located downstream of the Yellow River basin, for estimating 10 years’ (1991‐2000) daily spatial precipitation using 41 rain gauges. The results obtained in this study show that the spatial precipitation maps estimated by different interpolation methods have similar areal mean precipitation depth, but significantly different values of maximum precipitation, minimum precipitation, and coefficient of variation. The accuracy of the spatial precipitation estimated by different interpolation methods was evaluated using a correlation coefficient, Nash‐Sutcliffe efficiency, and relative mean absolute error. Compared with NN and IDW methods that are widely used in distributed hydrologic modeling systems, the geostatistical methods incorporated in this GIS program can provide more accurate spatial precipitation estimation. Overall, the SKlm_EL_X and KED_EL_X, which incorporate both elevation and spatial coordinate as auxiliary into SKlm and KED, respectively, obtained higher correlation coefficient and Nash‐Sutcliffe efficiency, and lower relative mean absolute error than other methods tested. The GIS program developed in this study can serve as an effective and efficient tool to implement advanced geostatistics methods that incorporate auxiliary information to improve spatial precipitation estimation for hydrologic models.     

A Hydrologic Data Screening Procedure for Exploring Monotonic Trends and Shifts in Rainfall and Runoff Patterns

A thorough understanding of past and present hydrologic responses to changes in precipitation patterns is crucial for predicting future conditions. The main objectives of this study were to determine temporal changes in rainfall‐runoff relationship and to identify significant trends and abrupt shifts in rainfall and runoff time series. Ninety‐year rainfall and runoff time series datasets from the Gasconade and Meramec watersheds in east‐central Missouri were used to develop data screening procedure to assess changes in the rainfall and runoff temporal patterns. A statistically significant change in mean and variance was detected in 1980 in the rainfall and runoff time series within both watersheds. In addition, both the rainfall and runoff time series indicated the presence of nonstationary attributes such as statistically significant monotonic trends and/or change in mean and variance, which should be taken into consideration when using the time series to predict future scenarios. The annual peak runoff and the annual low flow in the Meramec watershed showed significant temporal changes compared to that in the Gasconade watershed. Water loss in both watersheds was found to be significantly increasing which is potentially due to the increase in groundwater pumping for water supply purposes.     

Phosphorus loss and runoff characteristics in three adjacent agricultural watersheds with claypan soils

Effects of precipitation, runoff, and management on total phosphorus (TP) loss from three adjacent, row-cropped watersheds in the claypan region of northeastern Missouri were examined from 1991 to 1997 to understand factors affecting P loss in watersheds dominated by claypan soils. Runoff samples from each individual runoff event were analyzed for TP and sediment concentration. The annual TP loss ranged from 0.29 to 3.59 kg ha(-1) with a mean of 1.36 kg ha(-1) across all the watersheds during the study period. Significantly higher loss of TP from the watersheds was observed during the fallow period. Multiple small runoff events or several large runoff events contributed to loss of TP from the watersheds. Total P loss in 1993, a year with above-normal precipitation, accounted for 30% of the total TP loss observed over seven years. The five largest runoff events out of a total of 66 events observed over seven years accounted for 27% of the TP loss. The five largest sediment losses were responsible for 24% of the TP loss over seven years. Runoff volume and sediment loss explained 64 to 73% and 47 to 58% of the variation in TP loss on watersheds during the study. Flow duration and maximum flow accounted for 49 and 66% of TP loss, respectively. The results of this study suggest that management practices that reduce runoff volume, flow duration, maximum flow, and sediment loss, and that maintain a suitable vegetative cover throughout the year could lower P loss in claypan soils.