Simulating future salinity dynamics in a coastal marshland under different climate scenarios

Salinization is a well‐known problem in agricultural areas worldwide. In the last 20–30 yr, rising salinity in the upper, unconfined aquifer has been observed in the Freepsumer Meer, a grassland near the German North Sea coast. For investigating long‐term development of salinity and water balance during 1961–2099, the one‐dimensional Soil–Water–Atmosphere–Plant (SWAP) model was set up and calibrated for a soil column in the area. The model setup involves a deep aquifer as the source of salt through upward seepage. In the vertical salt transport equation, dispersion and advection are included. Six different regional outputs of statistical downscaling methods were used as climate scenarios. These comprise different rates of increasing surface temperature and different trends in seasonal rainfall. The simulation results exhibit opposing salinity trends for topsoil and deeper layers. Although projections of some scenarios entail decreasing salinities near the surface, most of them project a rise in subsoil salinity, with the strongest trends of up to +0.9 mg cm−3 100 yr−1 at −65 cm. The results suggest that topsoil salinity trends in the study area are affected by the magnitude of winter rainfall trends, whereas high subsoil salinities correspond to low winter rainfall and high summer temperature. How these projected trends affect the vegetation and thereby future land use will depend on the future management of groundwater levels in the area

Watershed Scale Response to Climate Change— South Fork Flathead River, Montana

In 2008, the U.S. Geological Survey Global Change Program funded a study to examine integrated watershed scale response to global change in selected watersheds across the United States. Fourteen watersheds for which hydrologic models had been created using the Precipitation Runoff Modeling System (PRMS) were selected as study sites. PRMS is a deterministic, distributed-parameter, watershed model developed to evaluate the effects of various combinations of precipitation, temperature, and land use on streamflow and hydrology. The portion of the South Fork Flathead River watershed located upstream from Hungry Horse Dam in northwestern Montana is 1 of the 14 study sites. Results from six General Circulation Models (GCMs), each using three GCM scenarios, were used to develop climate change scenarios for 2001-2099 for input to the existing PRMS model for the South Fork Flathead River. These PRMS simulations using the GCM scenarios were compared to PRMS simulations for current (1988-2000) conditions. All GCM simulations project an overall increase in temperature. Projected changes in precipitation for the South Fork Flathead River watershed were variable, with a slight tendency towards an increase in precipitation in the latter half of the 21st century. PRMS simulations using the GCM scenarios project slightly increased mean annual streamflow in the South Fork Flathead River from about 2020-2099. However, these simulations project that less precipitation falls as snow, resulting in increased mean monthly streamflow January through April and decreased mean monthly streamflow June through September. Information from these climate-change simulations could be useful for management of Hungry Horse Reservoir

Estimating and Comparing Demand Functions forf Personal Use Christmas Tree Cutting at Seven Utah Sites

The travel cost model of recreation demand analysis was applied to seven USDA Forest Service Ranger Districts in Utah. The objectives were to (1) estimate consumers\u27 surplus and total willingness to pay values for the recreational component of personal use Christmas tree gathering, and (2) compare these Utah results with each other and with the Markstrom and Donnelly (1988) results from Colorado, the only other travel cost analysis of Christmas tree gathering from public lands. The results were that per-trip consumer\u27 s surplus estimates ranged from $6.71 to$31.17, compared to Markstrom and Donnelly\u27s (1988) estimate of $10.05. There is sufficient intersite variation that the demand functions from any site cannot be readily applied to any other

Towards simplification of hydrologic modeling: identification of dominant processes

parameter hydrologic model, has been applied to the conterminous US (CONUS). Parameter sensitivity analysis was used to identify: (1) the sensitive input parameters and (2) particular model output variables that could be associated with the dominant hydrologic process(es). Sensitivity values of 35 PRMS calibration parameters were computed using the Fourier amplitude sensitivity test procedure on 110 000 independent hydrologically based spatial modeling units covering the CONUS and then summarized to process (snowmelt, surface runoff, infiltration, soil moisture, evapotranspiration, interflow, baseflow, and runoff) and model performance statistic (mean, coefficient of variation, and autoregressive lag 1). Identified parameters and processes provide insight into model performance at the location of each unit and allow the modeler to identify the most dominant process on the basis of which processes are associated with the most sensitive parameters. The results of this study indicate that: (1) the choice of performance statistic and output variables has a strong influence on parameter sensitivity, (2) the apparent model complexity to the modeler can be reduced by focusing on those processes that are associated with sensitive parameters and disregarding those that are not, (3) different processes require different numbers of parameters for simulation, and (4) some sensitive parameters influence only one hydrologic process, while others may influence many