MODELING SEDIMENT AND PHOSPHORUS LOSSES IN AN AGRICULTURAL WATERSHED TO MEET TMDLs1

ABSTRACT: This paper studies the effectiveness of alternative farm management strategies at improving water quality to meet Total Maximum Daily Loads (TMDLs) in agricultural watersheds. A spatial process model was calibrated using monthly flow, sediment, and phosphorus (P) losses (1994 to 1996) from Sand Creek watershed in south‐central Minnesota. Statistical evaluation of predicted and observed data gave r² coefficients of 0.75, 0.69, and 0.49 for flow (average 4.1 m³/s), sediment load (average 0.44 ton/ha), and phosphorus load (average 0.97 kg/ha), respectively. The calibrated model was used to evaluate the effects of conservation tillage, conversion of crop land to pasture, and changes in phosphorus fertilizer application rate on pollutant loads. TMDLs were developed for sediment and P losses based on existing water quality standards and guidelines. Observed annual sediment and P losses exceeded these TMDLs by 59 percent and 83 percent, respectively. A combination of increased conservation tillage, reduced application rates of phosphorus fertilizer, and conversion of crop land to pasture could reduce sediment and phosphorus loads by 23 percent and 20 percent of existing loads, respectively. These reductions are much less than needed to meet TMDLs, suggesting that control of sediment using buffer strips and control of point sources of phosphorus are needed for the remaining reductions.     

TRANSIENT RESPONSE FUNCTIONS FOR CONJUNCTIVE WATER MANAGEMENT IN THE SNAKE RIVER PLAIN,IDAHO1

ABSTRACT: Increasing demands on western water are causing a mounting need for the conjunctive management of surface water and ground water resources. Under western water law, the senior water rights holder has priority over the junior water rights holder in times of water shortage. Water managers have been reluctant to conjunctively manage surface water and ground water resources because of the difficulty of quantification of the impacts to surface water resources from ground water stresses. Impacts from ground water use can take years to propagate through an aquifer system. Prediction of the degree of impact to surface water resources over time and the spatial distribution of impacts is very difficult. Response functions mathematically describe the relationship between a unit ground water stress applied at a specific location and stream depletion or aquifer water level change elsewhere in the system. Response functions can be used to help quantify the spatial and temporal impacts to surface water resources caused by ground water pumping. This paper describes the theory of response functions and presents an application of transient response functions in the Snake River Plain, Idaho. Transient response functions can be used to facilitate the conjunctive management of surface and ground water not only in the eastern Snake River Plain basin, but also in similar basins throughout the western United States.     

基于ArcIMS的旅游安全管理系统

结合旅游业的特点,即综合性、敏感性、涉外性或国际性,提出旅游安全管理系统应该包括:灾前的防范系统、灾时的抗灾系统以及灾后的评估善后系统3大部分的设计思路。将相应的旅游重大危险源监控系统的功能定为:以行政监察、社会监督、行业自律和应急救援体系为主的宏观管理系统。阐述了Web GIS的优点并推荐了一种构建Web GIS的新技术———ArcIMS,利用ArcIMS的系统构建的旅游安全管理系统具有功能健全、管理方便、系统成熟和安全可靠的诸多优点;同时整个系统的构建相对于其他Web GIS系统的开发而言,技术难度比较低、开发速度比较快,而且系统运行相对稳定,减轻了系统维护的负担。最后,结合旅游安全信息流的特点,具体阐述了运用ArcIMS作为旅游安全管理系统的平台的合理性和可行性。     

道路交通安全管理措施比较研究

根据近五年来我国道路交通安全状况的实际,针对目前我国道路交通安全管理的现状,本文就道路交通法规建设、道路交通安全宣传教育、道路交通执法、道路事故紧急救援措施等相关内容与日本、美国、欧洲交通发达国家进行了对比分析,以图找出我国现行的道路交通安全管理对策中的薄弱环节及完善的途径.     

湘钢2#高炉拆除大修工程安全技术管理

通过对拆除前、拆除中、拆除后以及大修整个过程实施全方位安全技术管理，实现了全面的管理目标．取得了良好的社会效益和经济效益。     

浅析分布式防火墙技术

随着计算机网络的不断发展,现有的防火墙体系已不能满足要求,发展新的网络防火墙技术已非常重要.分布式防火墙具有明显的防护优势,了解分布式防火墙技术,并在实际应Ζ用中用好它,已成为保障我们网络安全的必要.     

Information Network Topologies for Enhanced Local Adaptive Management

We examined the principal effects of different information network topologies for local adaptive management of natural resources. We used computerized agents with adaptive decision algorithms with the following three fundamental constraints: (1) Complete understanding of the processes maintaining the natural resource can never be achieved, (2) agents can only learn by experimentation and information sharing, and (3) memory is limited. The agents were given the task to manage a system that had two states: one that provided high utility returns (desired) and one that provided low returns (undesired). In addition, the threshold between the states was close to the optimal return of the desired state. We found that networks of low to moderate link densities significantly increased the resilience of the utility returns. Networks of high link densities contributed to highly synchronized behavior among the agents, which caused occasional large-scale ecological crises between periods of stable and high utility returns. A constructed network involving a small set of experimenting agents was capable of combining high utility returns with high resilience, conforming to theories underlying the concept of adaptive comanagement. We conclude that (1) the ability to manage for resilience (i.e., to stay clear of the threshold leading to the undesired state as well as the ability to re-enter the desired state following a collapse) resides in the network structure and (2) in a coupled social–ecological system, the systemwide state transition occurs not because the ecological system flips into the undesired state, but because managers lose their capacity to reorganize back to the desired state. An erratum to this article can be found at .     

A multi-objective optimisation approach to water management

The management of river basins is complex especially when decisions about environmental flows are considered in addition to those concerning urban and agricultural water demand. The solution to these complex decision problems requires the use of mathematical techniques that are formulated to take into account conflicting objectives. Many optimization models exist for water management systems but there is a knowledge gap in linking bio-economic objectives with the optimum use of all water resources under conflicting demands. The efficient operation and management of a network of nodes comprising storages, canals, river reaches and irrigation districts under environmental flow constraints is challenging. Minimization of risks associated with agricultural production requires accounting for uncertainty involved with climate, environmental policy and markets. Markets and economic criteria determine what crops farmers would like to grow with subsequent effect on water resources and the environment. Due to conflicts between multiple goal requirements and the competing water demands of different sectors, a multi-criteria decision-making (MCDM) framework was developed to analyze production targets under physical, biological, economic and environmental constraints. This approach is described by analyzing the conflicts that may arise between profitability, variable costs of production and pumping of groundwater for a hypothetical irrigation area.     

BASIN SCALE WATER MANAGEMENT AND FORECASTING USING ARTIFICIAL NEURAL NETWORKS1

ABSTRACT: Water scarcity in the Sevier River Basin in south‐central Utah has led water managers to seek advanced techniques for identifying optimal forecasting and management measures. To more efficiently use the limited quantity of water in the basin, better methods for control and forecasting are imperative. Basin scale management requires advanced forecasts of the availability of water. Information about long term water availability is important for decision making in terms of how much land to plant and what crops to grow; advanced daily predictions of streamflows and hydraulic characteristics of irrigation canals are of importance for managing water delivery and reservoir releases; and hourly forecasts of flows in tributary streams to account for diurnal fluctuations are vital to more precisely meet the day‐to‐day expectations of downstream farmers. A priori streamflow information and exogenous climate data have been used to predict future streamflows and required reservoir releases at different timescales. Data on snow water equivalent, sea surface temperatures, temperature, total solar radiation, and precipitation are fused by applying artificial neural networks to enhance long term and real time basin scale water management information. This approach has not previously been used in water resources management at the basin‐scale and could be valuable to water users in semi‐arid areas to more efficiently utilize and manage scarce water resources.