Integration of remotely-sensed raster data with a vector-based geographical information system for land-use change detection

Methods of land-use change detection are different for raster and vector data types because of the differences in structures of the two data types. Since large amounts of land-use data (derived from existing maps and aerial photographs) are stored in vector format in a Geographical Information System (GIS), there is a need to develop a change detection algorithm for use with vector-formatted data. Since remotely-sensed images are increasingly being used to derive land-use data, it is necessary to integrate raster data with large volumes of vector data already available in a GIS. This necessitates an efficient and effective data integration technique using which raster data are to be integrated with a vector-based GIS. This paper presents a methodology of data integration of remotely-sensed raster data with vector data. A new approach is developed for land-use change detection for use with vector data in a GIS environment. The approach is based on the mathematical concepts of Sets and Groups, and is successfully implemented for the analysis of historical land-use change from 1931 to 1989 in the River Glen catchment, U.K. Algorithms have been developed for automatic derivation of dynamic statistics of land-use. It is shown that this approach can be efficiently adopted for operational use incorporating products derived from both coarse- and fine-resolution remotely-sensed satellite images once these are integrated with the vector-based GIS.     

The simulation of land-cover change using a distributed computing environment

Computer models are used in landscape ecology to simulate the effects of human land-use decisions on the environment. Many socioeconomic as well as ecological factors must be considered, requiring the integration of spatially explicit multidisciplinary data. The Land-Use Change Analysis System or LUCAS has been developed to study the effects of land-use on landscape structure in such areas as the Little Tennessee river basin in western North Carolina and the Olympic Peninsula of Washington state. These effects include land-cover change and species habitat suitability. The map layers used by LUCAS are derived from remotely sensed images, census and ownership maps, topological maps and output from econometric models. A public-domain geographic information system (GIS) is used to store, display and analyze these map layers. A parallel version of LUCAS (pLUCAS) was developed using the parallel virtual machine (PVM) on a network of workstations giving a speedup factor of 10.77 with 20 nodes. A parallel model is necessary for simulations on larger domains or for maps with a much higher resolution.     

An erosion model for evaluating regional land-use scenarios

The conversion to pasture of indigenous forest on New Zealand hill country has led to increased mass-movement erosion and consequently increased sedimentation of waterways. Effective soil conservation requires a model that can evaluate erosion and sedimentation for different land-use scenarios. In this paper, we develop a model of mean sediment discharge related to mean erosion rates through a sediment delivery ratio. Mean erosion rate in a particular terrain (“erosion terrain”) is the product of (i) the square of mean annual rainfall with (ii) a cover factor and (iii) an erosion coefficient that depends on erosion terrain. Measurements of mean sediment discharge are used to estimate erosion coefficients for each erosion terrain. The model can be used to predict mean sediment discharge in response to land-cover/land-use scenarios. It is easy to execute and uses input data readily available in GIS layers in New Zealand. This makes it suitable for widespread management application, in contrast to physically based models which are presently only suitable for research catchments. We demonstrate the utility of the model for three different applications: evaluating land-use scenarios in the Motueka catchment; setting priorities for soil conservation in the Manawatu catchment; and determining national trends in agricultural erosion over a 30-year period. The general methodology is applicable to countries dominated by mountains and steep hills with high erosion rates.     

Development of an integrated model for assessing the impact of diffuse and point source pollution on coastal waters

Pollution loads from land sources and their impact on the receiving waters can be predicted by using land-use and surface water quality models, respectively. In this paper details are given of the development of an integrated modelling system for managing water quality in coastal basins. The system includes a model linking the pollution input loads to land-use and a model for simulating surface flow and chemical and biological processes. The land-use model consists of two main components: a database and a model base. It uses a GIS system, namely ArcGIS, as the model platform. The database, built in the Geo-database format, includes six data sets containing information on social, economical, bathymetrical and hydrological aspects of a study area. The model base includes a series of transfer functions that link the pollution loads to key sources, including those from: industrial, domestic and agricultural inputs, and fish and animal farming. The water quality model is a numerical model which solves the governing equations representing the physical, chemical and biological processes in coastal waters. The modelling system was set up for Bohai Bay in China, with the land-use model being used to provide nutrient loadings from individual inputs and the water quality model used to predict the impact of these inputs on the receiving waters. Model simulations were also undertaken to predict the water quality conditions for various development and management scenarios.     

Assessing pollution risks to water supply intakes using geographical information systems (GIS)

The process of pollution risk assessment requires the assimilation of data that are spatially variable in nature, making geographical information systems (GIS) an ideal tool for such assessments. Over half of Britain's drinking water is obtained from surface water abstractions, many of which are situated in upland areas. In order to optimise the quality of abstracted waters it is important to assess the possible risks of pollution upstream from the point of abstraction. This paper describes the use of the PC-based WINGS™ and MapInfo Professional™ geographical information systems in the evolution of a risk assessment methodology to assess catchment risk. The work illustrates how such technology can assist in environmental decision-making to optimise the quality of drinking water supplies and enhance treatment efficiencies. Examples are given showing how raster and vector-based data can be used within a GIS framework to produce maps indicating areas of potential hazard to water quality, and coupled with existing models to predict and quantify risk frequency and impact. GIS techniques are further utilised in the formulation of a raw water monitoring programme to assist in intake operation and land-use planning in the catchment. The availability of suitable digital data was found to be variable, and some problems encountered in their integration and implementation within the system framework were resolved. Comment is given on the suitability and relative performance of the two software packages in the assessment of catchment risk. The work was carried out on a medium specification desktop PC, and therefore has the potential to be utilised across the intranet of a large utility company.     

Linking GIS and water resources management models: an object-oriented method

Many challenges are associated with the integration of geographic information systems (GISs) with models in specific applications. One of them is adapting models to the environment of GISs. Unique aspects of water resource management problems require a special approach to development of GIS data structures. Expanded development of GIS applications for handling water resources management analysis can be assisted by use of an object oriented approach. In this paper, we model a river basin water allocation problem as a collection of spatial and thematic objects. A conceptual GIS data model is formulated to integrate the physical and logical components of the modeling problem into an operational framework, based on which, extended GIS functions are developed to implement a tight linkage between the GIS and the water resources management model. Through the object-oriented approach, data, models and users interfaces are integrated in the GIS environment, creating great flexibility for modeling and analysis. The concept and methodology described in this paper is also applicable to connecting GIS with models in other fields that have a spatial dimension and hence to which GIS can provide a powerful additional component of the modeler’s tool kit.     

A model library for simulation and benchmarking of integrated urban wastewater systems

This paper presents a freely distributed, open-source toolbox to predict the behaviour of urban wastewater systems (UWS). The proposed library is used to develop a system-wide Benchmark Simulation Model (BSM-UWS) for evaluating (local/global) control strategies in urban wastewater systems (UWS). The set of models describe the dynamics of flow rates and major pollutants (COD, TSS, N and P) within the catchment (CT), sewer network (SN), wastewater treatment plant (WWTP) and river water system (RW) for a hypothetical, though realistic, UWS. Evaluation criteria are developed to allow for direct assessment of the river water quality instead of the traditional emission based metrics (for sewer overflows and WWTP discharge). Three case studies are included to illustrate the applicability of the proposed toolbox and also demonstrate the potential benefits of implementing integrated control in the BSM-UWS platform. Simulation results show that the integrated control strategy developed to maximize the utilization of the WWTP's capacity represents a balanced choice in comparison to other options. It also improves the river water quality criteria for unionized ammonia and dissolved oxygen by 62% and 6%, respectively.     

Scenario analysis and management options for sustainable river basin management: Application of the Elbe DSS

We developed a decision support system (DSS) for sustainable river basin management in the German Elbe catchment (～100,000 km²), called Elbe-DSS. The system integrates georeferenced simulation models and related data sets with a user friendly interface and includes a library function. Design and content of the DSS have been developed in close cooperation with end users and stakeholders. The user can evaluate effectiveness of management actions like reforestation, improvement of treatment plant technology or the application of buffer strips under the influence of external constraints on climate, demographic and agro-economic changes to meet water management objectives such as water quality standards and discharge control. The paper (i) describes the conceptual design of the Elbe-DSS, (ii) demonstrates the applicability of the integrated catchment model by running three different management options for phosphate discharge reduction (reforestation, erosion control and ecological-farming) under the assumption of regional climate change based on IPCC scenarios, (iii) evaluates the effectiveness of the management options, and (iv) provides some lessons for the DSS-development in similar settings. The georeferenced approach allows the identification of local inputs in sub-catchments and their impact on the overall water quality, which helps the user to prioritize his management actions in terms of spatial distribution and effectiveness.     

基于城镇居民用地再分类的人口数据空间化方法研究——以长江中游4省为例

基于土地利用数据的人口统计数据空间化方法,在处理过程中会出现同一土地利用类型下人口难以细分的情况,从而影响人口空间数据精度。引入夜间灯光信息并提出了一种基于夜间灯光强度对城镇居民地再分类的人口空间化方法,以改善人口空间数据精度。基于DMSP/OLS夜间灯光及土地利用数据,以长江中游4省为研究区进行方法试验。研究结果显示:利用夜间灯光数据对城镇居民地再分类后,各分区模型的调整R2都提高到了0.8以上,人口空间数据总体平均相对误差较重分类前降低了12.32%。说明该方法在提高传统人口数据空间化模型精度的基础上能够细化城镇居民地人口空间分布。     

浦东新区城乡中小河道整治信息管理系统研究

为解决城乡中小河道整治管理工作项目多、过程繁杂等问题,动态掌握施工全周期进度和质量,建立浦东新区城乡中小河道整治信息管理系统。以浦东新区已有水务应用支撑平台为依托,通过数据服务和GIS技术实现河道整治工程科学、规范、精细化管理,加大对水务工程质量与安全监督力度,提高监督效率和管理效能。     

Data‐driven model for river flood forecasting based on a Bayesian network approach

Uncertainty analysis of hydrological models often requires a large number of model runs, which can be time consuming and computationally intensive. In order to reduce the number of runs required for uncertainty prediction, Bayesian networks (BNs) are used to graphically represent conditional probability dependence between the set of variables characterizing a flood event. Bayesian networks (BNs) are relevant due to their capacity to handle uncertainty, combine statistical data and expertise and introduce evidences in real‐time flood forecasting. In the present study, a runoff–runoff model is considered. The discharge at a gauging station located is estimated at the outlet of a basin catchment based on discharge measurements at the gauging stations upstream. The BN model shows good performances in estimating the discharges at the basin outlet. Another application of the BN model is to be used as a reverse method. Knowing discharges values at the outlet of the basin, we can propagate back these values through the model to estimate discharges at upstream stations. This turns out to be a practical method to fill the missing data in streamflow records which are critical to the sustainable management of water and the development of hydrological models.     

OpenMI-based integrated sediment transport modelling of the river Zenne,Belgium

Recent observations show that the river Zenne (Belgium) remains well below the water quality goals stated by the European Union Water Framework Directive. An interuniversity, multidisciplinary research project was therefore launched to evaluate the effects of wastewater management plans on the ecological functioning of the river. To this end, different water quantity and quality processes had to be considered and modelled, e.g., the hydrology in the river basin, hydraulics in the river and sewers, erosion and sediment transport, faecal bacteria transport and decay. This paper considers the development of an Open Modelling Interface (OpenMI) based integrated model for the purpose of simulating the river's sediment dynamics. We used the Soil and Water Assessment Tool (SWAT) to model water and sediment fluxes from rural areas. The Storm Water Management Model (SWMM) was used to simulate the hydraulics of the river, canal, and sewer systems in urban catchments. New model codes for sediment transport and stream water temperature were developed to complement SWMM. The results show that the integrated sediment transport model reproduced the sediment concentrations in the river Zenne with ‘good’ to ‘satisfactory’ accuracy. We may therefore conclude that the OpenMI has been successfully implemented to integrate water quality models into a hydraulic one. While the OpenMI run-time data communication inflicted calculation time overhead, we found that the overhead was not significant with respect to the total run-time of the integrated model.     

A simple model to predict soil moisture: Bridging Event and Continuous Hydrological (BEACH) modelling

This paper introduces a simple two-layer soil water balance model developed to Bridge Event And Continuous Hydrological (BEACH) modelling. BEACH is a spatially distributed daily basis hydrological model formulated to predict the initial condition of soil moisture for event-based soil erosion and rainfall–runoff models. The latter models usually require the spatially distributed values of antecedent soil moisture content and other input parameters at the onset of an event. BEACH uses daily meteorological records, soil physical properties, basic crop characteristics and topographical data. The basic processes incorporated in the model are precipitation, infiltration, transpiration, evaporation, lateral flow, vertical flow and plant growth. The principal advantage of this model lies in its ability to provide timely information on the spatially distributed soil moisture content over a given area without the need for repeated field visits. The application of this model to the CATSOP experimental catchment showed that it has the capability to estimate soil moisture content with acceptable accuracy. The root mean squared error of the predicted soil moisture content for 6 monitored locations within the catchment ranged from 0.011 to 0.065 cm³ cm^?3. The predicted daily discharge at the outlet of the study area agreed well with the observed data. The coefficient of determination and Nash–Sutcliffe efficiency of the predicted discharge were 0.824 and 0.786, respectively. BEACH has been developed within freely available GIS and programming language, PCRaster. It is a useful teaching tool for learning about distributed water balance modelling and land use scenario analysis.     

A Reduced Parameter Stream Temperature Model (RPSTM) for basin-wide simulations

Water temperature is a crucial variable that shapes biological communities and controls rates of ecosystem processes in rivers. Fully parameterized heat balance models have been used to provide accurate estimates, but high parameterization costs make them difficult to apply at basin-wide scales. As parts of a collaborative modeling project to address future impacts of climate and land-use management on the Muskegon River, we developed a Reduced Parameter Stream Temperature Model (RPSTM), a mechanistic, spatially explicit but easier to parameterize model. Here we describe and test RPSTM's applicability by conducting a series of daily water temperature simulations (1985–2005). RPSTM performed well along the river network. The predictions were most sensitive to air temperature, depth, and solar radiation, but relatively insensitive to rates of surface runoff. This modeling approach is easily integrated into complex multi-modeling systems to evaluate effects of long-term changes in watershed hydrology, climate, and land management across river networks.     

Soil wetness as an indicator of stream salinity: a landscape position index approach

Dryland salinity is a major environmental issue in much of Australia’s agricultural lands and is expressed as salt affected land or degraded stream water quality. Maps showing areas at risk of land and stream degradation are needed by regional, state and national management and planning authorities, as well as farmers. Part of the management involves establishing end-of-valley targets for water quality. Developing maps of salinity risk is limited by the availability of appropriate spatial data. Elevation data at appropriate scales are available for all Australia.This paper explores the potential to develop catchment and regional scale soil wetness maps, based only on elevation data, as a surrogate for stream salinity risk. Soil wetness indices were derived through the Fuzzy Landscape Analysis GIS (FLAG) model. While FLAG avoids the direct use of process models it uses process understanding. It does this through an index-based approach that requires a training set of areas of wetness, salinity or other attribute associated with position in the landscape. We test whether only one of the FLAG landscape position indices (UPNESS), that has been shown to characterise depositional zones, is correlated to baseflow stream salinity.UPNESS is the uphill area monotonically above each point in the landscape, and is a specialised form of contributing area, a measure of surface and sub-surface water accumulation. This measure characterises catchments as the ‘connectedness’ of drainage or prevalence of runoff sinks. It distinguishes, for example, between freely drained catchments and those with more extensive depositional zones that allow the accumulation and storage of salt and formation of preferential pathways in the system.FLAG analysis was applied over an area of ~12 000 km² in southeastern Australia where salinity research was being conducted by state agencies. Stream electrical conductivity measurements were obtained to compare with the UPNESS index. The results suggest that the model is useful for targeting further investigations in regional scale salinity management planning and research. FLAG is suggested as a first step for obtaining a highly visual rapid assessment of potential wetness, discharge and salinisation at catchment scales.     

Bridging rigorous assessment of water availability from field to catchment scale with a parsimonious agro-hydrological model

While simple crop and hydrological models are limited with respect to the number and accuracy of the processes they incorporate, complex models have high demand for data. Due to the limitations of both categories of models, there is a need for new agro-hydrological models that simulate both crop productivity and water availability in agricultural catchments, with low data and calibration requirements. This study aimed at developing a widely applicable parsimonious agro-hydrological model, AquaCrop-Hydro, which couples the AquaCrop crop water productivity model with a conceptual hydrological model. AquaCrop-Hydro, simulating crop productivity, the daily soil water balance and discharge at the catchment outlet, performed well for an agricultural catchment in Belgium. The model can be used to investigate the effect of agricultural management and environmental changes from field to catchment scale in support of sustainable water management in agricultural areas.     

Non-point source critical area analysis in the Gisselö watershed using GIS

In the southeast in Norrköping, Sweden, is a small fjord-like bay called Slätbaken. The water quality in Slätbaken—with its narrow outlet to the Baltic Sea—depends highly on the water quality of the streams that flow in it. While point pollution sources can be identified easily in general, the non-point sources are harder to find. The most important sources for non-point pollution are agricultural areas, and the pollutants are mostly nutrients like phosphorus, which come from the fertilisation of the fields. One important catchment area for Slätbaken is the 57.7 km² Gisselö river basin (part of the topographic map 8GNO), which contains large agricultural areas.The transport of water pollutants is based on the same hydrological processes as erosion and sediment transport. The implementation of such a model in a GIS allows the analysis of a large area with a high resolution. When choosing the model, special attention was paid to the possibility of using a verified model that is easy to implement in a commercial GIS without the need of too much expert knowledge. This may allow its widespread use in many administrative applications that need non-point source information. A feasibility test for an enhanced GIS USLE model was done in the Gisselö drainage basin before it was implemented for all river basins in the whole administrative area of Norrköpings kommun.It is possible to use the suggested simplified USLE model to estimate the load of both pollutants and sediments, and it is able to show the areas that are critical for the water quality at the outlet of the water basin. The model has been evaluated in three studies [Int. J. Geogr. Inf. Syst. 2 (4) (1988) 365; A GIS to target critical areas for non point source management, in: Proceedings of the International Non Point Source Management Symposium, Austin, TX, November 7, 1989; Vatten 48 (1992) 117]. Then, implemented in a very simple GIS that allowed only rough estimates of terrain models and distances, the model was able to estimate the total suspended solids (TSS) and total phosphorus (TP) loads in the Svartå river basin of 1539 km² in the same region as Gisselö and the Bornsjö river basin outside Stockholm. Besides an estimated R² of 0.91–0.98 (verified by a more than one year measurement from manual and automated sampling stations in the whole river basin), the benefit with the GIS implemented USLE was the possibility to identify the risk areas with high spatial accuracy. During the last decade, both available databases and software have changed the possibilities to identify areas at risk of nutrient leakage. Schein [GIS Methods for Monitoring Sustainable Development by Analysis of Land-use and Land Cover Changes in the Surroundings of Linköping (Sweden), Institut für Photogrammetrie und Fernerkundung, Technische Universität Dresden, Germany] and Schein and Sivertun [Method and models for sustainable development monitoring and analyses in GIS, in: Proceedings of the International Workshop on Geo-Spatial Knowledge Processing for Natural Resource Management, University of Insubria, Varese, Italy, June 28–29, 2001] show that the enhanced land use data available through the European Union agricultural support program can be used together with remote sensing data to fine tune the modified GIS USLE model. The problems with the new 50×50 m digital elevation data now available are also pointed out here. Obvious errors in the data and possibilities to enhance the model by introducing a better terrain model were two important suggestions in these works. In this article, two modifications to the original model are suggested. One is enhancement of the digital terrain model by using height curves from the digital 1:50 000 scale topographic map, and the other is a smooth distance function that better reflects the impact of nutrients on water bodies.Because of its easy implementation on standard low cost systems, the GIS USLE model is suitable for analysing huge areas for critical places. The results can lead to more detailed studies in the risk areas thus identified or to investigations on the effect of land use changes, or can be used simply for taking care in the use of fertilisers and other chemicals in the critical agricultural areas.     

A new approach to testing an integrated water systems model using qualitative scenarios

Integrated systems models have been developed over decades, aiming to support the decision-makers in the planning and managing of natural resources. The inherent model complexity, lack of knowledge about the linkages among model components, scarcity of field data, and uncertainty involved with internal and external factors of the real system call their practical usefulness into doubt. Validation tests designed for such models are just immature, and are argued to have some characteristics that differ from the ones used for validating other types of models. A new approach for testing integrated water systems models is proposed, and applied to test the RaMCo model. Expert knowledge is elicited in the form of qualitative scenarios and translated into quantitative projections using fuzzy set theory. Trend line comparison of the projections made by the RaMCO model and the qualitative projections based on expert knowledge revealed an insufficient number of land-use types adopted by the RaMCo model. This insufficiency makes the model inadequate to describe the consequences of the changes in socio-economic factors and policy options on the erosion from the catchment and the sediment yields at the inlet of a storage lake.     

改进的QGA-BP模型在复杂水质预测中的应用

水质预测是实现非线性水系统的柔性管理、防治水污染的前提工作.机理性水质预测模型的构建往往较复杂并且需要大量运算与数据,预测效果有时不够精确,其进一步推广应用也受到限制.文中以淮河复杂水环境非机理性水质预测为目的,构建改进的量子遗传算法优化BP神经网络模型,采用动态改进策略和灾变策略作为进化操作准则来优化BP模型的权值和阈值,用历史观测数据作为学习范例训练模型.对比实验结果发现,模型改进以后,进化代数、收敛速度和预测结果的准确率有较大提高.该模型用于水质预测的黑箱问题是可行的,拓展水环境管理的思路.