Predictive models of turbidity and water depth in the Doñana marshes using Landsat TM and ETM+ images

We have used Landsat-5 TM and Landsat-7 ETM+ images together with simultaneous ground-truth data at sample points in the Doñana marshes to predict water turbidity and depth from band reflectance using Generalized Additive Models. We have point samples for 12 different dates simultaneous with 7 Landsat-5 and 5 Landsat-7 overpasses. The best model for water turbidity in the marsh explained 38% of variance in ground-truth data and included as predictors band 3 (630–690 nm), band 5 (1550–1750 nm) and the ratio between bands 1 (450–520 nm) and 4 (760–900 nm). Water turbidity is easier to predict for water bodies like the Guadalquivir River and artificial ponds that are deep and not affected by bottom soil reflectance and aquatic vegetation. For the latter, a simple model using band 3 reflectance explains 78.6% of the variance. Water depth is easier to predict than turbidity. The best model for water depth in the marsh explains 78% of the variance and includes as predictors band 1, band 5, the ratio between band 2 (520–600 nm) and band 4, and bottom soil reflectance in band 4 in September, when the marsh is dry. The water turbidity and water depth models have been developed in order to reconstruct historical changes in Doñana wetlands during the last 30 years using the Landsat satellite images time series.     

Equivalent roaded area as a measure of cumulative effect of logging

A watershed disturbance index developed by the USDA Forest Service called equivalent roaded area (ERA) was used to assess the cumulative effect from forest management in California's Sierra Nevada and Klamath mountain ranges. The basins' ERA index increased as logging and road-building occurred and then decreased over time as management ceased and vegetation recovered. A refinement of the standard index emphasized disturbances in sensitive, near-channel areas, and evaluated recovery periods of 20, 30, and 50 years. Shorter recovery periods yielded better correlations between recovering forest systems and aquatic response than the longer recovery period, as represented by ERA and diversity or dominance, respectively. The refined ERA index correlated more closely with macroinvertebrate dominance and diversity information that was available for part of the study period. A minimum ERA threshold of 5% was detected, below which no effect to the macroinvertebrate community was observed. Above this threshold, elevated ERA values were associated with a decline in macroinvertebrate diversity and an increase in dominance of the top five taxa. Use of an ERA technique that emphasizes near-channel areas and biological thresholds would contribute to the Forest Service's implementation of ecosystem management.     

Backfilling canals to mitigate Wetland dredging in Louisiana coastal marshes

Returning canal spoil banks into canals, or backfilling, is used in Louisiana marshes to mitigate damage caused by dredging for oil and gas extraction. We evaluated 33 canals backfilled through July 1984 to assess the success of habitat restoration. We determined restoration success by examining canal depth, vegetation recolonization, and regraded spoil bank soils after backfilling. Restoration success depended on: marsh type, canal location, canal age, marsh soil characteristics, the presence or absence of a plug at the canal mouth, whether mitigation was on- or off-site, and dredge operator performance.Backfilling reduced median canal depth from 2.4 to 1.1 m, restored marsh vegetation on the backfilled spoil bank, but did not restore emergent marsh vegetation in the canal because of the lack of sufficient spoil material to fill the canal and time. Median percentage of cover of marsh vegetation on the canal spoil banks was 51.6%. Median percentage of cover in the canal was 0.7%. The organic matter and water content of spoil bank soils were restored to values intermediate between spoil bank levels and predredging marsh conditions.The average percentage of cover of marsh vegetation on backfilled spoil banks was highest in intermediate marshes (68.6%) and lowest in fresh (34.7%) and salt marshes (33.9%). Average canal depth was greatest in intermediate marshes (1.50 m) and least in fresh marshes (0.85 m). Canals backfilled in the Chenier Plain of western Louisiana were shallower (average depth = 0.61 m) than in the eastern Deltaic Plain (mean depth range = 1.08 to 1.30 m), probably because of differences in sediment type, lower subsidence rate, and lower tidal exchange in the Chenier Plain. Canals backfilled in marshes with more organic soils were deeper, probably as a result of greater loss of spoil volume caused by oxidation of soil organic matter. Canals ten or more years old at the time of backfilling had shallower depths after backfilling. Depths varied widely among canals backfilled within ten years of dredging. Canal size showed no relationship to canal depth or amount of vegetation reestablished. Plugged canals contained more marsh reestablished in the canal and much greater chance of colonization by submerged aquatic vegetation compared with unplugged canals. Dredge operator skill was important in leveling spoil banks to allow vegetation reestablishment. Wide variation in dredge performance led to differing success of vegetation restoration.Complete reestablishment of the vegetation was not a necessary condition for successful restoration. In addition to providing vegetation reestablishment, backfilling canals resulted in shallow water areas with higher habitat value for benthos, fish, and waterfowl than unfilled canals. Spoil bank removal also may help restore water flow patterns over the marsh surface. Increased backfilling for wetland mitigation and restoration is recommended.     

Soil biogeochemical characteristics influenced by alum application in a municipal wastewater treatment wetland

Constructed treatment wetlands are a relatively low-cost alternative used for tertiary treatment of wastewater. Phosphorus (P) removal capacity of these wetlands may decline, however, as P is released from the accrued organic soils. Little research has been done on methods to restore the treatment capacity of aging constructed wetlands. One possibility is the seasonal addition of alum during periods of low productivity and nutrient removal. Our 3-mo mesocosm study investigated the effectiveness of alum in immobilizing P during periods of reduced treatment efficiency, as well as the effects on soil biogeochemistry. Eighteen mesocosms were established, triplicate experimental and control units for Typha sp., Schoenoplectus californicus, and submerged aquatic vegetation (SAV) (Najas guadalupensis dominated). Alum was slowly dripped to the water column of the experimental units at a rate of 0.91 g Al m(-2) d(-1) and water quality parameters were monitored. Soil cores were collected at experiment initiation and completion and sectioned into 0- to 5- and 5- to 10-cm intervals for characterization. The alum floc remained in the 0- to 5-cm surface soil, however, soil pH and microbial parameters were impacted throughout the upper 10 cm with the lowest pH found in the Typha treatment. Plant type did not impact most biogeochemical parameters; however, data were more variable in the SAV mesocosms. Amorphous Al was greater in the surface soil of alum-treated mesocosms, inversely correlated with soil pH and microbial biomass P in both soil layers. Microbial activity was also suppressed in the surface soil of alum-treated mesocosms. This research suggests alum may significantly affect the biogeochemistry of treatment wetlands and needs further investigation.     

Land Surface Phenology and Land Surface Temperature Changes Along an Urban–Rural Gradient in Yangtze River Delta, China

Using SPOT/VGT NDVI time series images (2002–2009) and MODIS/LST images (2002–2009) smoothed by a Savitzky–Golay filter, the land surface phenology (LSP) and land surface temperature (LST), respectively, are extracted for six cities in the Yangtze River Delta, China, including Shanghai, Hangzhou, Nanjing, Changzhou, Wuxi, and Suzhou. The trends of the averaged LSP and LST are analyzed, and the relationship between these values is revealed along the urban–rural gradient. The results show that urbanization advances the start of the growing season, postpones the end of the growing season, prolongs the growing season length (GSL), and reduces the difference between maximal NDVI and minimal NDVI in a year (NDVI_amp). More obvious changes occur in surface vegetation phenology as the urbanized area is approached. The LST drops monotonously and logarithmically along the urban–rural gradient. Urbanization generally affects the LSP of the surrounding vegetation within 6 km to the urban edge. Except for GSL, the difference in the LSP between urban and rural areas has a significant logarithmic relationship with the distance to the urban edge. In addition, there is a very strong linear relationship between the LSP and the LST along the urban–rural gradient, especially within 6 km to the urban edge. The correlations between LSP and gross domestic product and population density reveal that human activities have considerable influence on the land surface vegetation growth.     

Modelling land use change with generalized linear models--a multi-model analysis of change between 1860 and 2000 in Gallatin Valley, Montana

This paper develops an approach to modelling land use change that links model selection and multi-model inference with empirical models and GIS. Land use change is frequently studied, and understanding gained, through a process of modelling that is an empirical analysis of documented changes in land cover or land use patterns. The approach here is based on analysis and comparison of multiple models of land use patterns using model selection and multi-model inference. The approach is illustrated with a case study of rural housing as it has developed for part of Gallatin County, Montana, USA. A GIS contains the location of rural housing on a yearly basis from 1860 to 2000. The database also documents a variety of environmental and socio-economic conditions. A general model of settlement development describes the evolution of drivers of land use change and their impacts in the region. This model is used to develop a series of different models reflecting drivers of change at different periods in the history of the study area. These period specific models represent a series of multiple working hypotheses describing (a) the effects of spatial variables as a representation of social, economic and environmental drivers of land use change, and (b) temporal changes in the effects of the spatial variables as the drivers of change evolve over time. Logistic regression is used to calibrate and interpret these models and the models are then compared and evaluated with model selection techniques. Results show that different models are 'best' for the different periods. The different models for different periods demonstrate that models are not invariant over time which presents challenges for validation and testing of empirical models. The research demonstrates (i) model selection as a mechanism for rating among many plausible models that describe land cover or land use patterns, (ii) inference from a set of models rather than from a single model, (iii) that models can be developed based on hypothesised relationships based on consideration of underlying and proximate causes of change, and (iv) that models are not invariant over time.     

Statistical Models to Predict and Assess Spatial and Temporal Low‐Flow Variability in New England Rivers and Streams

In the northern hemisphere, summer low flows are a key attribute defining both quantity and quality of aquatic habitat. I developed one set of models for New England streams/rivers predicting July/August median flows averaged across 1985–2015 as a function of weather, slope, % imperviousness, watershed storage, glacial geology, and soils. These models performed better than most United States Geological Survey models for summer flows developed at a statewide scale. I developed a second set of models predicting interannual differences in summer flows as a function of differences in air temperature, precipitation, the North Atlantic Oscillation (NAO) index, and lagged NAO. Use of difference equations eliminated the need for transformations and accounted for serial autocorrelations at lag 1. The models were used in sequence to estimate time series for monthly low flows and for two derived flow metrics (tenth percentile [Q10] and minimum 3‐in‐5 year average flows). The first metric is commonly used in assessing risk to low‐flow conditions over time, while the second has been correlated with increased probability of localized extinctions for brook trout. The flow metrics showed increasing trends across most of New England for 1985–2015. However, application of summer flow models with average and extreme climate projections to the Taunton River, Massachusetts, a sensitive watershed undergoing rapid development, projected that low‐flow metrics will decrease over the next 50 years.     

Cluster analysis of structural stage classes to map wildland fuels in a Madrean ecosystem

Geospatial information technology is changing the nature of fire mapping science and management. Geographic information systems (GIS) and global positioning system technology coupled with remotely sensed data provide powerful tools for mapping, assessing, and understanding the complex spatial phenomena of wildland fuels and fire hazard. The effectiveness of these technologies for fire management still depends on good baseline fuels data since techniques have yet to be developed to directly interrogate understory fuels with remotely sensed data. We couple field data collections with GIS, remote sensing, and hierarchical clustering to characterize and map the variability of wildland fuels within and across vegetation types. One hundred fifty six fuel plots were sampled in eight vegetation types ranging in elevation from 1150 to 2600 m surrounding a Madrean 'sky island' mountain range in the southwestern US. Fuel plots within individual vegetation types were divided into classes representing various stages of structural development with unique fuel load characteristics using a hierarchical clustering method. Two Landsat satellite images were then classified into vegetation/fuel classes using a hybrid unsupervised/supervised approach. A back-classification accuracy assessment, which uses the same pixels to test as used to train the classifier, produced an overall Kappa of 50% for the vegetation/fuels map. The map with fuel classes within vegetation type collapsed into single classes was verified with an independent dataset, yielding an overall Kappa of 80%.     

Chemical residence time and hydrological conditions influence treatment of fipronil in vegetated aquatic mesocosms

Fipronil, a phenyl-pyrazole insecticide, is often used in rice (Oryza sativa L.) production agriculture, with elevated runoff concentrations and loads having potential toxicological effects on downstream aquatic environments. This study evaluated two species of aquatic plants-broadleaf cattail (Typha latifolia L.) and powdery alligator-flag (Thalia dealbata Fraser ex Roscoe)-placed in series against a nonvegetated mesocosm in reducing concentrations and loads of fipronil, and associated metabolites. Vegetation type and hydrological condition (inundated vs. dry) were treatment effects used for comparison. The vegetated mesocosms significantly reduced higher loads and concentrations of fipronil, fipronil sulfone, and sulfide in both inundated and dry hydrological conditions over nonvegetated nesocosms. Under inundation conditions, vegetated mesocosms reduced >50% of influent fipronil concentrations and betweeen 60 and 70% of fipronil loads, which was significantly higher than the dry conditions (10-32% concentration and load). These results show that agricultural management strategies usingephemeral aquatic zones, such as drainage ditches, can be optimized to couple chemical applications with vegetation presence and hydrology to facilitate the reduction in chemical waste loads entering downstream aquatic ecosystems. Such reduction is critical for use with fipronil, where negative impacts have been demonstrated with several nontarget species.     

MULTIPLICATIVE,SEASONAL ARIMA MODELS FOR LAKE ERIE AND LAKE ONTARIO WATER LEVELS1

ABSTRACT: Federal agencies in the U.S. and Canada continuously examine methods to improve understanding and forecasting of Great Lakes water level dynamics in an effort to reduce the negative impacts of fluctuating levels incurred by interests using the lakes. The short term, seasonal and long term water level dynamics of lakes Erie and Ontario are discussed. Multiplicative, seasonal ARIMA models are developed for lakes Erie and Ontario using standardized, monthly mean level data for the period 1900 to 1986. The most appropriate model identified for each lake had the general form: (1 0 1)(0 1 1)₁₂. The data for each lake were subdivided by time periods (1900 to 1942;1 943 to 1986) and the model coefficients estimated for the subdivided data were similar, indicating general model stability for the entire period of record. The models estimated for the full data sets were used to forecast levels 1,2,3, and 6 months ahead for a period of high levels (1984 to 1986). The average absolute forecast error for Lake Erie was 0.049m, 0.076m, 0.091 m and 0.128m for the 1, 2,3, and 6 month forecasts, respectively. The average absolute forecast error for Lake Ontario was 0.058m, 0.095m, 0.120m and 0.136m for the 1,2,3, and 6 month forecasts, respectively. The ARIMA models provide additional information on water level time series structure and dynamics. The models also could be coordinated with current forecasting methods, possibly improving forecasting accuracy.     

EVAPOTRANSPIRATION AND CANOPY RESISTANCE AT AN UNDEVELOPED PRAIRIE IN A HUMID SUBTROPICAL CLIMATE1

ABSTRACT: Reliable estimates of evapotranspiration from areas of wildland vegetation are needed for many types of water-resource investigations. However, little is known about surface fluxes from many areally important vegetation types, and relatively few comparisons have been made to examine how well evapotranspiration models can predict evapotranspiration for soil-, climate-, or vegetation-types that differ from those under which the models have been calibrated. In this investigation at a prairie site in west-central Florida, latent heat flux (λE) computed from the energy balance and alternatively by eddy covariance during a 15-month period differed by 4 percent and 7 percent on hourly and daily time scales, respectively. Annual evapotranspiration computed from the energy balance and by eddy covariance were 978 and 944 mm, respectively. An hourly Penman-Monteith (PM) evapotranspiration model with stomatal control predicated on water-vapor-pressure deficit at canopy level, incoming solar radiation intensity, and soil water deficit was developed and calibrated using surface fluxes from eddy covariance. Model-predicted λE agreed closely with λE computed from the energy balance except when moisture from dew or precipitation covered vegetation surfaces. Finally, an hourly PM model developed for an Amazonian pasture predicted λE for the Florida prairie with unexpected reliability. Additional comparisons of PM-type models that have been developed for differing types of short vegetation could aid in assessing interchangeability of such models.     

Monitoring effects of a controlled subsurface carbon dioxide release on vegetation using a hyperspectral imager

A hyperspectral imaging system was used to monitor vegetation during a subsurface controlled release of carbon dioxide (CO₂). From August 3 to 10, 2007, 0.3 tons CO₂/day were released through a 70 m horizontal pipe located at a nominal depth of 1.8 m below the surface. Hyperspectral images of alfalfa plants were collected during the controlled release and used along with classification tree analysis to study changes in the reflectance spectra as a function of perpendicular distance from the horizontal pipe. Changes in the reflectance spectra near the red edge (650–750 nm) were observed over the course of the controlled release experiment for plants within a perpendicular distance of 1 m of the release pipe. These results indicate monitoring vegetation over a carbon sequestration site has the potential to allow monitoring of the integrity of the CO₂ storage.     

Engaging an ecovillage and measuring its ecological footprint

As ecovillages present themselves as models of low-carbon living measuring the Ecological Footprint (EF) of an ecovillage serves both to validate that claim and to examine the component features of how the EF is achieved. This article examines the first measurement of the EF of Ireland’s only ecovillage, situated in the village of Cloughjordan in county Tipperary. The objectives here were to measure the EF of the ecovillage at the household scale and then to use the EF to provide meaningful feedback and reflective learning on human carbon intensity to the ecovillage residents. Various methods were applied in this action research to achieve high levels of engagement and potent communication of what could be learnt from the EF. This article places a particular focus on the necessary adaptation of an original EF method, on how it was implemented in the ecovillage, on the results obtained and on how these were communicated to the residents. The bottom-up component EF method samples consumption data at source and in so doing appoints consumption reflection and responsibility in ways the more remote compound method can not. The strategic combination of this specific quality with co-creation method aims to meaningfully engage and motivate a settlement to reduce its carbon intensity. According to the methodology, the ecovillage residents overshoot the fair earth share by 10% needing 1.1 planets to sustain their lifestyles. It is planned that subsequent to this intervention future measurements will show whether the overshoot has reduced.     

Anthropogenic effects on the biodiversity of riparian wetlands of a northern temperate landscape

Land uses such as forestry and agriculture are presumed to degrade the biodiversity of riparian wetlands in the northern temperate regions of the United States. In order to improve land use decision making in this landscape, floral and faunal communities of 15 riparian wetlands associated with low-order streams were related to their surrounding land cover to establish which organismal groups are affected by anthropogenic disturbance and whether these impacts are scale-specific. Study sites were chosen to represent a gradient of disturbance. Vascular plants of wet meadow and shrub carr communities, aquatic macro-invertebrates, amphibians, fish and birds were surveyed, and total abundance, species richness and Shannon diversity were calculated. For each site, anthropogenic disturbances were evaluated at local and landscape scales (500, 1000, 2500 and 5000 m from the site and the site catchment) from field surveys and a geographic information system (GIS). Land use data were grouped into six general land use types: urban, cultivated, rangeland, forest, wetland and water. Shrub carr vegetation, bird and fish diversity and richness generally decrease with increasing cultivation in the landscape. Amphibian abundance decreases and fish abundance increases as the proportions of open water and rangeland increases; bird diversity and richness increase with forest and wetland extent in the landscape. Wet meadow vegetation, aquatic macro-invertebrates, amphibians and fish respond to local disturbances or environmental conditions. Shrub carr vegetation, amphibians and birds are influenced by land use at relatively small landscape scales (500 and 1000 m), and fish respond to land use at larger landscape scales (2500, 5000 m and the catchment). Effective conservation planning for these riparian wetlands requires assessment of multiple organismal groups, different types of disturbance and several spatial scales.1998 Academic Press     

EFFICACY AND COST OF AQUATIC WEED CONTROL IN SMALL PONDS'

ABSTRACT: Twenty, 0.2 hectare ponds were utilized for a four-year evaluation of three aquatic vegetation control techniques: a combination of inorganic fertilization and mechanical harvesting, aquatic herbicides, and grass carp (Ctenopharyngodon idella). Ponds used for herbicide and grass carp treatments were managed at three levels of aquatic vegetation (none, 40 and 70 percent plant occupation). Submersed vegetation was not controlled with inorganic fertilization. Vegetation levels were maintained for less than 30 days after mechanicai harvesting. Submersed macrophytes were not completely eliminated with herbicides, but the herbicide treatments utilized were effective at maintaining aquatic vegetation above 30 percent pond volume occupation. Grass carp consumed all species of submersed vegetation at the stocking densities used in this study; therefore, planned levels of submersed macrophytes were not maintained. Grass carp did not consume all floating leaf vegetation, but after four years some grass carp ponds did have lower densities of floating leaf plants. Fertilization costs were $608/hectare/year, and mechanical harvesting costs were $1979/hectare/year, resulting in a total aquatic vegetation treatment cost of $2587/hectare/ year. Herbicide costs for the different treatment levels ranged from $417/hectare/year to $1339/hectare/year over the four-year period. Grass carp were the most economical vegetation control measure tested, with costs ranging from $159/hectare/year to $248/hectare/year for the four-year study.     

Phosphorus load to surface water from bank erosion in a Danish lowland river basin

Phosphorus loss from bank erosion was studied in the catchment of River Odense, a lowland Danish river basin, with the aim of testing the hypothesis of whether stream banks act as major diffuse phosphorus (P) sources at catchment scale. Furthermore, the study aimed at analyzing the impact of different factors influencing bank erosion and P loss such as stream order, anthropogenic disturbances, width of uncultivated buffer strips, and the vegetation of buffer strips. A random stratified procedure in geographical information system (GIS) was used to select two replicate stream reaches covering different stream orders, channelized vs. naturally meandering channels, width of uncultivated buffer strips (≤ 2 m and ≥ 10 m), and buffer strips with different vegetation types. Thirty-six 100-m stream reaches with 180 bank plots and a total of 3000 erosion pins were established in autumn 2006, and readings were conducted during a 3-yr period (2006-2009). The results show that neither stream size nor stream disturbance measured as channelization of channel or the width of uncultivated buffer strip had any significant ( < 0.05) influence on bank erosion and P losses during each of the 3 yr studied. In buffer strips with natural trees bank erosion was significantly ( < 0.05) lower than in buffer strips dominated by grass and herbs. Gross and net P input from bank erosion amounted to 13.8 to 16.5 and 2.4 to 6.3 t P, respectively, in the River Odense catchment during the three study years. The net P input from bank erosion equaled 17 to 29% of the annual total P export and 21 to 62% of the annual export of P from diffuse sources from the River Odense catchment. Most of the exported total P was found to be bioavailable (71.7%) based on a P speciation of monthly suspended sediment samples collected at the outlet of the river basin. The results found in this study have a great importance for managers working with P mitigation and modeling at catchment scale.     

Seasonal change detection of riparian zones with remote sensing images and genetic programming in a semi-arid watershed

Riparian zones are deemed significant due to their interception capability of non-point source impacts and the maintenance of ecosystem integrity region wide. To improve classification and change detection of riparian buffers, this paper developed an evolutionary computational, supervised classification method--the RIparian Classification Algorithm (RICAL)--to conduct the seasonal change detection of riparian zones in a vast semi-arid watershed, South Texas. RICAL uniquely demonstrates an integrative effort to incorporate both vegetation indices and soil moisture images derived from LANDSAT 5 TM and RADARSAT-1 satellite images, respectively. First, an estimation of soil moisture based on RADARSAT-1 Synthetic Aperture Radar (SAR) images was conducted via the first-stage genetic programming (GP) practice. Second, for the statistical analyses and image classification, eight vegetation indices were prepared based on reflectance factors that were calculated as the response of the instrument on LANDSAT. These spectral vegetation indices were then independently used for discriminate analysis along with soil moisture images to classify the riparian zones via the second-stage GP practice. The practical implementation was assessed by a case study in the Choke Canyon Reservoir Watershed (CCRW), South Texas, which is mostly agricultural and range land in a semi-arid coastal environment. To enhance the application potential, a combination of Iterative Self-Organizing Data Analysis Techniques (ISODATA) and maximum likelihood supervised classification was also performed for spectral discrimination and classification of riparian varieties comparatively. Research findings show that the RICAL algorithm may yield around 90% accuracy based on the unseen ground data. But using different vegetation indices would not significantly improve the final quality of the spectral discrimination and classification. Such practices may lead to the formulation of more effective management strategies for the handling of non-point source pollution, bird habitat monitoring, and grazing and live stock management in the future.     

Multi‐Decadal Remote‐Sensing Analysis of Irrigated Areas in the Lower Rio Grande Valley,New Mexico

A time series of estimates of irrigated area was developed for the Lower Rio Grande valley (LRG) in New Mexico from the 1970s to present day. The objective of the project was to develop an independent, accurate, and scientifically justifiable evaluation of irrigated area in the region for the period spanning from the mid‐1970s to the present. These area estimates were used in support of groundwater modeling of the LRG region, as well as for other analyses. This study used a remote‐sensing‐based methodology to evaluate overall irrigated area within the LRG. We applied a methodology that involved the normalization of vegetation indices derived from satellite imagery to get a more accurate estimation of irrigated area across multiple time periods and multiple Landsat platforms. The normalization allows more accurate evaluation of vegetation index data that span several decades. An accuracy assessment of the methodology and results from this study was performed using field‐collected crop data from the 2008 growing season. The comparisons with field data indicate that the accuracy of the remote‐sensing‐based estimates of historical irrigated area is very good, with rates of false positives (areas identified as irrigated that are not truly irrigated) of only about 4%, and rates of false negatives (areas identified as not irrigated that are truly irrigated) in the range of 0.6‐2.0%.     

Riparian vegetation instream flow requirements: A case study from a diverted stream in the Eastern Sierra Nevada,California, USA

A methodology is described that allows determination of instream flow requirements for maintenance of riparian trees. Tree-ring data revealed strong relationships between tree growth and stream flow volume for riparian species at Rush Creek, an alluvial stream within an arid setting; these relationships allowed development of models that predict growth rates from hydrologic variables. The models can be used to assess instream flow requirements under the assumption that certain levels of growth are necessary to maintain the population. There is a critical need for development and use of instream flow methodologies for riparian vegetation, since present methodologies focus on needs of aquatic animals (e.g., fish) and may underestimate needs of the entire riparian ecosystem.     

Sediment retention in rangeland riparian buffers

Controlling nonpoint-source sediment pollution is a common goal of riparian management, but there is little quantitative information about factors affecting performance of rangeland riparian buffers. This study evaluated the influence of vegetation characteristics, buffer width, slope, and stubble height on sediment retention in a Montana foothills meadow. Three vegetation types (sedge wetland, rush transition, bunchgrass upland) were compared using twenty-six 6- x 2-m plots spanning 2 to 20% slopes. Plots were clipped moderately (10-15 cm stubble) or severely (2-5 cm stubble). Sediment (silt + fine sand) was added to simulated overland runoff 6, 2, or 1 m above the bottom of each plot. Runoff was sampled at 15-s to > 5-min intervals until sediment concentrations approached background levels. Sediment retention was affected strongly by buffer width and moderately by vegetation type and slope, but was not affected by stubble height. Mean sediment retention ranged from 63 to > 99% for different combinations of buffer width and vegetation type, with 94 to 99% retention in 6-m-wide buffers regardless of vegetation type or slope. Results suggest that rangeland riparian buffers should be at least 6 m wide, with dense vegetation, to be effective and reliable. Narrower widths, steep slopes, and sparse vegetation increase risk of sediment delivery to streams. Vegetation characteristics such as biomass, cover, or density are more appropriate than stubble height for judging capacity to remove sediment from overland runoff, though stubble height may indirectly indicate livestock impacts that can affect buffer performance.