Deciding Alternative Land Use Options in a Watershed Using GIS

The present approach adopted for suggesting alternative sustainable land use comprises taking into consideration present land use/land cover, soils, slope, and geomorphology. However, this paper deals with watershed management from a different perspective, by stressing the development of the watershed for agriculture activities; first, by implementing soil and water conservation works. The next step is to suggest alternative sustainable land uses based on soil and water conservation measures, groundwater prospects, land capability, and present land use/land cover in the area. The new approach is found to be very useful, as it takes into consideration basic factors necessary for the overall development and management of the watershed, and ensures stoppage of further degradation of the resources through appropriate soil conservation measures and land uses.     

基于改进分水岭算法的医学图像分割的研究

本文针对医学图象的特点，改进了医学图像的分水岭算法，并用于医学图像的分割处理。这种分割通常应用分水岭算法，但是它有过分割的严重问题。本文闸述了在分水岭算法的基础上做的一些改进，其内容是：在分水岭算法之前，引入浮点，活动图像作为分水岭算法的输入，在分水岭算法之后，在面积控制的基础上，同时根据面积控制和对比度控制的准则，将某些被分割的小区并入邻近较大的区域。这种改进的方法使过分割现象得到了很好的抑制，而且医学图像中的病变小区被分割出来了，效果很好。     

Probabilistic Approach for Design and Hydrologic Performance Assessment of Reconstructed Watersheds

The oil sands mining industry in Canada has made a commitment to reclaim mining areas to an equivalent capability to that which existed prior to mining. An essential requirement in the design of reclamation covers to meet this objective is that all covers must have a sufficient available water holding capacity (AWHC) in order to supply sufficient moisture for vegetation over the summer moisture deficit typical in the region. AWHC is currently based on static evaluations of wilting point and field capacity under a constant annual evapotranspiration demand. This paper presents an alternative probabilistic approach by which the hydrologic performance of these reclamation soil covers can be assessed. A field-calibrated water balance model is used along with the available historical meteorological record to estimate the maximum soil moisture deficit that a soil cover is able to sustain over the growing season. Frequency curves of the maximum annual moisture deficit are used to assess the probability that a cover is able to provide any particular threshold of moisture demand. The method also allows for a quantification of the predictive uncertainty of the model. The predictive uncertainty is used as a margin of safety to estimate a design value of moisture deficit for various alternative cover designs. This paper recommends procedures for a frequency-based assessment and design of reclamation soil covers in the oil sands industry. This method takes into account climatic variability as well as parameter uncertainty in estimating the soil moisture deficit.     

Simulating dynamic load of naturally occurring TOC from watershed into a river

Naturally occurring total organic carbon (TOC) is an important feature of stream water quality. This study investigates the dynamic load of TOC from the deep creek watershed into the lower St. Johns River (LSJR), FL, USA, using numerical simulations and field measurements. An existing St. Johns River watershed assessment model for simultaneous loading of nutrients from watersheds into rivers is modified to include the TOC component for the purpose of this study. Three simulation scenarios (i.e., daily, monthly, and annually) are performed to estimate the dynamic load of TOC in response to rainfall events. Simulations show that rainfall events have decisive effects on TOC loads from the Deep Creek watershed into the LSJR. In general, the highly frequent the rainfall events occur, the higher the TOC loads into the river. Simulations also illustrate that effects of rainfall events on daily changes of TOC are minimal in winter, but are profound in late summer. Results suggest that TOC load into the river is not only a rainfall-driven but also a temperature-driven biological process.     

Model of pathogen transmission between livestock and white-tailed deer in fragmented agricultural and forest landscapes

The study summarizes the current knowledge on infection and recovery of white-tailed deer and cattle, and integrates this knowledge into the Soil and Water Assessment Tool (SWAT) via a new add-on module SIR (Susceptible - Infected - Recovered) for predicting pathogen transmission between livestock and deer. New processes modeled by the SWAT-SIR model include: (a) seasonal changes in deer population and habitat; (b) resource selection and seasonal changes in foliage consumption by deer; (c) ingestion of pathogens with water, foliage and via grooming soiled hide by deer and grazing cattle; (d) infection and recovery of deer and co-grazing cattle; (e) pathogen shedding by infected animals; (f) survival of pathogens in manure; (g) kinetic release of pathogens from applied manure and fecal material. The model output is linked with ARC-GIS to allow spatial and temporal analysis of pathogen distribution across the watershed for specific land use, weather and management scenarios.     

Estimation of water and salt generation from unregulated upland catchments

Water and salt export to rivers is of particular importance in large catchments, such as Australia’s Murray-Darling Basin, where there are multiple users of the water resource. Comparing estimates of water and salt generated from upland catchments across large areas is difficult due to the lack of a comparable, consistent approach. River routing models are currently used to model water and salt movement along regulated reaches. However methods are still required to predict the individual contributions of water and salt from unregulated upland catchments to feed into these river routing models. The 2CSalt model has been developed to predict monthly water and salt export from these upland catchments. 2CSalt makes use of existing regional data sets such as topography (digital elevation models) and hydrogeology/salinity (Groundwater Flow Systems). 2CSalt was developed using the “TIME” modelling framework which allowed for a rapid development cycle through the reuse of existing and tested components. The results from current applications of the model show a strong match with measured data.     

Calibration of SWAT models using the cloud

This paper evaluates a recently created Soil and Water Assessment Tool (SWAT) calibration tool built using the Windows Azure Cloud environment and a parallel version of the Dynamically Dimensioned Search (DDS) calibration method modified to run in Azure. The calibration tool was tested for six model scenarios constructed for three watersheds of increasing size each for a 2 year and 10 year simulation duration. Results show significant speedup in calibration time and, for up to 64 cores, minimal losses in speedup for all watershed sizes and simulation durations. An empirical relationship is presented for estimating the time needed to calibration a SWAT model using the cloud calibration tool as a function of the number of Hydrologic Response Units (HRUs), time steps, and cores used for the calibration.     

Assessment of contaminants transport in a watershed affected by acid mine drainage,by coupling hydrological and geochemical modeling tools

Erini Stream (Thrace, northeastern Greece) is adversely affected by the presence of an abandoned mixed sulfide mine located in the upper watershed. The GIS based model SWAT (Soil Water and Assessment Tool) was applied to characterize hydrologic processes in the watershed. Model performance was evaluated by comparing the simulation results with field data including flow and concentration measurements from 12 monitoring points, for the time period from June 2005 to July 2006. Flow rate results indicated good agreement between simulated and measured data, with coefficient correlations R² in the range of 0.74–0.89. Simulation was focused on the dispersion of three pollutants, Zn, Cd and Mn. Using SWAT alone, simulation results systematically overestimated pollutants levels in Erini Stream.Geochemical model PHREEQC was used in combination with SWAT to obtain more accurate predictions regarding contaminants concentrations along the course of Erini Stream. The profiles of main metal contaminants, i.e. Zn, Cd and Mn, under wet conditions, were described with satisfactory precision assuming equilibrium with the carbonate minerals ZnCO₃·H₂O and otavite and partial supersaturation with respect to rhodochrosite. However, precipitation of discrete carbonate phases does not seem to be the predominant attenuation mechanism under dry conditions. Coprecipitation or sorption on the surface of precipitating calcite is another potential removal mechanism under these conditions.The methodology presented allows the reliable assessment of acid mine drainage impacts in the downstream aquatic environment and the design of effective measures for its mitigation based on an optimized number of monitoring data.     

Information extraction from sensor networks using the Watershed transform algorithm

Wireless sensor networks are an effective tool to provide fine resolution monitoring of the physical environment. Sensors generate continuous streams of data, which leads to several computational challenges. As sensor nodes become increasingly active devices, with more processing and communication resources, various methods of distributed data processing and sharing become feasible. The challenge is to extract information from the gathered sensory data with a specified level of accuracy in a timely and power-efficient approach. This paper presents a new solution to distributed information extraction that makes use of the morphological Watershed algorithm. The Watershed algorithm dynamically groups sensor nodes into homogeneous network segments with respect to their topological relationships and their sensing-states. This setting allows network programmers to manipulate groups of spatially distributed data streams instead of individual nodes. This is achieved by using network segments as programming abstractions on which various query processes can be executed. Aiming at this purpose, we present a reformulation of the global Watershed algorithm. The modified Watershed algorithm is fully asynchronous, where sensor nodes can autonomously process their local data in parallel and in collaboration with neighbouring nodes. Experimental evaluation shows that the presented solution is able to considerably reduce query resolution cost without scarifying the quality of the returned results. When compared to similar purpose schemes, such as “Logical Neighborhood”, the proposed approach reduces the total query resolution overhead by up to 57.5%, reduces the number of nodes involved in query resolution by up to 59%, and reduces the setup convergence time by up to 65.1%.