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%.     

Liver segmentation in MRI: A fully automatic method based on stochastic partitions

There are few fully automated methods for liver segmentation in magnetic resonance images (MRI) despite the benefits of this type of acquisition in comparison to other radiology techniques such as computed tomography (CT). Motivated by medical requirements, liver segmentation in MRI has been carried out. For this purpose, we present a new method for liver segmentation based on the watershed transform and stochastic partitions. The classical watershed over-segmentation is reduced using a marker-controlled algorithm. To improve accuracy of selected contours, the gradient of the original image is successfully enhanced by applying a new variant of stochastic watershed. Moreover, a final classifier is performed in order to obtain the final liver mask. Optimal parameters of the method are tuned using a training dataset and then they are applied to the rest of studies (17 datasets). The obtained results (a Jaccard coefficient of 0.91 ± 0.02) in comparison to other methods demonstrate that the new variant of stochastic watershed is a robust tool for automatic segmentation of the liver in MRI.     

The Los Angeles River Reimagined: 51 Miles of Connected Public Open Space

The concrete channel of the Los Angeles (LA) River is probably one of the most recognizable rivers in the world. Channelized to manage the risk of flooding as the Los Angeles region urbanized, the river today is an architectural and engineering feat in the eyes of some people but an ecological disaster to others. The river flows adjacent to 17 cities and among some of the most environmentally burdened, park poor, and underserved communities of LA County. With over 2,300 acres of largely publicly owned land within the river right-of-way, a reimagined LA River can impact the lives of the one million people that live within a mile of the river. The LA River Master Plan, led by Los Angeles County and scheduled to be completed in fall 2021, proposes 51 miles of connected public open space with multi-benefit projects supporting nine goals ranging from flood resilience to housing affordability, to ecological function, and to arts, education, and culture. The data-based plan for the next 25 years includes a watershed-wide research effort to document and understand water quality, water conservation, and flood risk in relation to environmental and social issues. The plan includes traditional and innovative strategies within a “kit of parts,” interventions that include over 65 components ranging from habitat bridges to dry arroyo side channels demonstrating opportunities for enhancing ecosystem services to create a thriving urban habitat and connected network of parks along the river.     

峡谷区尾矿库小流域洪峰流量计算方法探讨

峡谷区地形条件复杂,汇水区多为山地地形,汇流速度快,因此峡谷区内尾矿库的选址与设计,首先要考虑其所在小流域洪峰流量的大小。探讨了目前普遍采用的流域洪峰流量计算方法后,选择了适合峡谷区小流域洪峰流量的计算公式,并以云南省某峡谷区尾矿库为例,进行了实地的计算。通过实际调查后,计算结果接近实际情况,计算方法值得在其他峡谷区推广应用。     

Land-use and land-cover change and its environmental implications in a tropical highland watershed,Ethiopia

This study analysed long-term land-use and land-cover change (LUCC) in a highland watershed covering an area of about 154?km² in the Blue Nile basin of Ethiopia. Two sets of panchromatic aerial photographs (1957 and 1982) and a Landsat TM image (2001) were the main input data from which three land-use and land-cover maps were produced by employing geographical information systems/remote sensing techniques. These data were complemented by some socio-economic data that were generated by using household survey, key-informant interview and group discussion methods. The results show that in regard to land-use and land-cover, the major change has been the reduction of areas under natural vegetation cover and expansion of open grassland, cultivated areas and settlements. Over the four and a half decades considered, areas of forest and dense tree cover and shrub grassland decreased by 64 and 6%, respectively. Forest and dense tree cover experienced the greatest change; from accounting for ～9% of the total area of the watershed in 1957 to only ～3% in 2001. In general, much of the de-vegetation occurred between 1982 and 2001. Cropland and rural settlement showed a small but consistent increase between 1957 and 2001. Riparian vegetation decreased during the first period, but increased almost to the same level during the second period by gaining land from the other land-use and land-cover types. The observed LUCCs were driven by a combination of proximate and underlying causes. These include increasing demographic pressure and associated demands on environmental resources, widespread rural poverty and inadequate management of common property resources owing to poorly defined ownership arrangements. There is a need for short-term and long-term strategies to ensure sustainable land management and agricultural development in the watershed.     

Large watershed management and restoration: dioxin sediment remediation case study

This paper reviews continuing, long-term remediation of river sediments containing dioxin and other chemical compounds in a large watershed of the Great Lakes Region. Chlorinated dibenzo-p-dioxins are a ‘family’ of chemically related compounds commonly known as chlorinated dioxins or simply, dioxins. The highest levels are usually found in sediments, soil and animal fats. The most toxic chemical in this group is 2,3,7,8-tetrachlorodibenzo-para-dioxin, the ‘standard’ to which other dioxins are compared and which has been shown to be very toxic in animal studies. The US Environmental Protection Agency (EPA) and Michigan Department of Environmental Quality (MDEQ) have made a lengthy effort to assess and remediate portions of the Saginaw Bay Watershed, including the Tittabawassee River. The paper reviews the EPA-proposed ‘phased approach’ to restoration and remediation of a short segment (Segment 1) of the Tittabawassee River sediments. Sediments are contaminated with a number of chemical pollutants other than dioxins, including arsenic, cholorbenzenes, cholorphenols, ethyl parathion, o-phenylphenol and polycyclic aromatic hydrocarbons. The paper evaluates three proposed ‘cleanup alternatives’, with final action method suggested based on effectiveness, feasibility for implementation and cost.     

Stereo matching using cost volume watershed and region merging

Segment based disparity estimation methods have been proposed in many different ways. Most of these studies are built upon the hypothesis that no large disparity jump exists within a segment. When this hypothesis does not hold, it is difficult for these methods to estimate disparities correctly. Therefore, these methods work well only when the images are initially over segmented but do not work well for under segmented cases. To solve this problem, we present a new segment based stereo matching method which consists of two algorithms: a cost volume watershed algorithm (CVW) and a region merging (RM) algorithm. For incorrectly under segmented regions where pixels on different objects are grouped into one segment, the CVW algorithm regroups the pixels on different objects into different segments and provides disparity estimation to the pixels in different segments accordingly. For unreliable and occluded regions, we merge them into neighboring reliable segments for robust disparity estimation. The comparison between our method and the current state-of-the-art methods shows that our method is very competitive and is robust particularly when the images are initially under segmented.