The Annual Condition of Education Report, 2009

The Annual Condition of Education Report includes an expanded Background Demographics section. This section contains information on population, economic, and social data, providing a comparison between Iowa, other states, and the Nation. Geographic Information System (GIS) maps are presented to allow the reader to easily compare between two or more geographies. In some instances, trends are also reported. Information displayed in this section was obtained from a variety of sources and is noted on each table or figure. In all areas, the most recent data available were used.

A flood geodatabase and its climatological applications: the case of Catalonia for the last century

Floods are the natural hazards that produce the highest number of casualties and material damage in the Western Mediterranean. An improvement in flood risk assessment and study of a possible increase in flooding occurrence are therefore needed. To carry out these tasks it is important to have at our disposal extensive knowledge on historical floods and to find an efficient way to manage this geographical data. In this paper we present a complete flood database spanning the 20th century for the whole of Catalonia (NE Spain), which includes documentary information (affected areas and damage) and instrumental information (meteorological and hydrological records). This geodatabase, named Inungama, has been implemented on a GIS (Geographical Information System) in order to display all the information within a given geographical scenario, as well as to carry out an analysis thereof using queries, overlays and calculus. Following a description of the type and amount of information stored in the database and the structure of the information system, the first applications of Inungama are presented. The geographical distribution of floods shows the localities which are more likely to be flooded, confirming that the most affected municipalities are the most densely populated ones in coastal areas. Regarding the existence of an increase in flooding occurrence, a temporal analysis has been carried out, showing a steady increase over the last 30 years.

Hydrologic Simulations of the Maquoketa River Watershed Using SWAT Working Paper 09-WP 49,June 2009

This paper describes the application of the Soil and Water Assessment Tool (SWAT) model to the Maquoketa River watershed, located in northeast Iowa. The inputs to the model were obtained from the Environmental Protection Agency’s geographic information/database system called Better Assessment Science Integrating Point and Nonpoint Sources (BASINS). Climatic data from six weather stations located in and around the watershed, and measured streamflow data from a U.S. Geological Survey gage station at the watershed outlet were used in the sensitivity analysis of SWAT model parameters as well as its calibration and validation for watershed hydrology and streamflow. A sensitivity analysis was performed using an influence coefficient method to evaluate surface runoff and base flow variations in response to changes in model input hydrologic parameters. The curve number, evaporation compensation factor, and soil available water capacity were found to be the most sensitive parameters among eight selected parameters when applying SWAT to the Maquoketa River watershed. Model calibration, facilitated by the sensitivity analysis, was performed for the period 1988 through 1993, and validation was performed for 1982 through 1987. The model performance was evaluated by well-established statistical methods and was found to explain at least 86% and 69% of the variability in the measured stream flow data for the calibration and validation periods, respectively. This initial hydrologic modeling analysis will facilitate future applications of SWAT to the Maquoketa River watershed for various watershed analysis, including water quality.

Morphostructural characterization of soil conventionally tilled with mechanized and animal traction with and without cover crop

The structural stability and restructuring ability of a soil are related to the methods of crop management and soil preparation. A recommended strategy to reduce the effects of soil preparation is to use crop rotation and cover crops that help conserve and restore the soil structure. The aim of this study was to evaluate and quantify the homogeneous morphological units in soil under conventional mechanized tillage and animal traction, as well as to assess the effect on the soil structure of intercropping with jack bean (Canavalia ensiformis L.). Profiles were analyzed in April of 2006, in five counties in the Southern-Central region of Paraná State (Brazil), on family farms producing maize (Zea mays L.), sometimes intercropped with jack bean. The current structures in the crop profile were analyzed using Geographic Information Systems (GIS) and subsequently principal component analysis (PCA) to generate statistics. Morphostructural soil analysis showed a predominance of compact units in areas of high-intensity cultivation under mechanized traction. The cover crop did not improve the structure of the soil with low porosity and compact units that hamper the root system growth. In areas exposed to animal traction, a predominance of cracked units was observed, where roots grew around the clods and along the gaps between them.

Spatial weights : constructing weight-compatible exchange matrices from proximity matrices

Exchange matrices represent spatial weights as symmetric probability distributions on pairs of regions, whose margins yield regional weights, generally well-specified and known in most contexts. This contribution proposes a mechanism for constructing exchange matrices, derived from quite general symmetric proximity matrices, in such a way that the margin of the exchange matrix coincides with the regional weights. Exchange matrices generate in turn diffusive squared Euclidean dissimilarities, measuring spatial remoteness between pairs of regions. Unweighted and weighted spatial frameworks are reviewed and compared, regarding in particular their impact on permutation and normal tests of spatial autocorrelation. Applications include tests of spatial autocorrelation with diagonal weights, factorial visualization of the network of regions, multivariate generalizations of Moran's I, as well as "landscape clustering", aimed at creating regional aggregates both spatially contiguous and endowed with similar features.

Main-Channel Slopes of Selected Streams in Iowa for Estimation of Flood-Frequency Discharges, November 2004

This report describes a statewide study conducted to develop main-channel slope (MCS) curves for 138 selected streams in Iowa with drainage areas greater than 100 square miles. MCS values determined from the curves can be used in regression equations for estimating flood frequency discharges. Multi-variable regression equations previously developed for two of the three hydrologic regions defined for Iowa require the measurement of MCS. Main-channel slope is a difficult measurement to obtain for large streams using 1:24,000-scale topographic maps. The curves developed in this report provide a simplified method for determining MCS values for sites located along large streams in Iowa within hydrologic Regions 2 and 3. The curves were developed using MCS values quantified for 2,058 selected sites along 138 selected streams in Iowa. A geographic information system (GIS) technique and 1:24,000-scale topographic data were used to quantify MCS values for the stream sites. The sites were selected at about 5-mile intervals along the streams. River miles were quantified for each stream site using a GIS program. Data points for river-mile and MCS values were plotted and a best-fit curve was developed for each stream. An adjustment was applied to all 138 curves to compensate for differences in MCS values between manual measurements and GIS quantification. The multi-variable equations for Regions 2 and 3 were developed using manual measurements of MCS. A comparison of manual measurements and GIS quantification of MCS indicates that manual measurements typically produce greater values of MCS compared to GIS quantification. Median differences between manual measurements and GIS quantification of MCS are 14.8 and 17.7 percent for Regions 2 and 3, respectively. Comparisons of percentage differences between flood-frequency discharges calculated using MCS values of manual measurements and GIS quantification indicate that use of GIS values of MCS for Region 3 substantially underestimate flood discharges. Mean and median percentage differences for 2- to 500-year recurrence-interval flood discharges ranged from 5.0 to 5.3 and 4.3 to 4.5 percent, respectively, for Region 2 and ranged from 18.3 to 27.1 and 12.3 to 17.3 percent for Region 3. The MCS curves developed from GIS quantification were adjusted by 14.8 percent for streams located in Region 2 and by 17.7 percent for streams located in Region 3. Comparisons of percentage differences between flood discharges calculated using MCS values of manual measurements and adjusted-GIS quantification for Regions 2 and 3 indicate that the flood-discharge estimates are comparable. For Region 2, mean percentage differences for 2- to 500-year recurrence-interval flood discharges ranged between 0.6 and 0.8 percent and median differences were 0.0 percent. For Region 3, mean and median differences ranged between 5.4 to 8.4 and 0.0 to 0.3 percent, respectively. A list of selected stream sites presented with each curve provides information about the sites including river miles, drainage areas, the location of U.S. Geological Survey stream flowgage stations, and the location of streams Abstract crossing hydro logic region boundaries or the Des Moines Lobe landforms region boundary. Two examples are presented for determining river-mile and MCS values, and two techniques are presented for computing flood-frequency discharges.

Three-dimensional interpolation of soil data: fertility and pedomorphological features in southern Brazil

The graphical representation of spatial soil properties in a digital environment is complex because it requires a conversion of data collected in a discrete form onto a continuous surface. The objective of this study was to apply three-dimension techniques of interpolation and visualization on soil texture and fertility properties and establish relationships with pedogenetic factors and processes in a slope area. The GRASS Geographic Information System was used to generate three-dimensional models and ParaView software to visualize soil volumes. Samples of the A, AB, BA, and B horizons were collected in a regular 122-point grid in an area of 13 ha, in Pinhais, PR, in southern Brazil. Geoprocessing and graphic computing techniques were effective in identifying and delimiting soil volumes of distinct ranges of fertility properties confined within the soil matrix. Both three-dimensional interpolation and the visualization tool facilitated interpretation in a continuous space (volumes) of the cause-effect relationships between soil texture and fertility properties and pedological factors and processes, such as higher clay contents following the drainage lines of the area. The flattest part with more weathered soils (Oxisols) had the highest pH values and lower Al3+ concentrations. These techniques of data interpolation and visualization have great potential for use in diverse areas of soil science, such as identification of soil volumes occurring side-by-side but that exhibit different physical, chemical, and mineralogical conditions for plant root growth, and monitoring of plumes of organic and inorganic pollutants in soils and sediments, among other applications. The methodological details for interpolation and a three-dimensional view of soil data are presented here.

Annual Report Of the State Geologist, March 2012

What we do: Since 1892, the Iowa Geological and Water Survey (IGWS) has provided earth, water, and mapping science to all Iowans. We collect and interpret information on subsurface geologic conditions, groundwater and surface water quantity and quality, and the natural and built features of our landscape. This information is critical for: Predicting the future availability of economic water supplies and mineral resources. Assuring proper function of waste disposal facilities. Delineation of geologic hazards that may jeopardize property and public safety. Assessing trends and providing protection of water quality and soil resources. Applied technical assistance for economic development and environmental stewardship. Our goal: Providing the tools for good decision making to assure the long-term vitality of Iowa’s communities, businesses, and quality of life. Information and technical assistance are provided through web-based databases, comprehensive Geographic Information System (GIS) tools, predictive groundwater models, and watershed assessments and improvement grants. The key service we provide is direct assistance from our technical staff, working with Iowans to overcome real-world challenges. This report describes the basic functions of IGWS program areas and highlights major activities and accomplishments during calendar year 2011. More information on IGWS is available at http://www.igsb.uiowa.edu/.

Field Data Acquisition Technologies for Iowa Transportation Agencies, HR-366 August 1994

This report describes the results of the research project investigating the use of advanced field data acquisition technologies for lowa transponation agencies. The objectives of the research project were to (1) research and evaluate current data acquisition technologies for field data collection, manipulation, and reporting; (2) identify the current field data collection approach and the interest level in applying current technologies within Iowa transportation agencies; and (3) summarize findings, prioritize technology needs, and provide recommendations regarding suitable applications for future development. A steering committee consisting oretate, city, and county transportation officials provided guidance during this project. Technologies considered in this study included (1) data storage (bar coding, radio frequency identification, touch buttons, magnetic stripes, and video logging); (2) data recognition (voice recognition and optical character recognition); (3) field referencing systems (global positioning systems [GPS] and geographic information systems [GIs]); (4) data transmission (radio frequency data communications and electronic data interchange); and (5) portable computers (pen-based computers). The literature review revealed that many of these technologies could have useful applications in the transponation industry. A survey was developed to explain current data collection methods and identify the interest in using advanced field data collection technologies. Surveys were sent out to county and city engineers and state representatives responsible for certain programs (e.g., maintenance management and construction management). Results showed that almost all field data are collected using manual approaches and are hand-carried to the office where they are either entered into a computer or manually stored. A lack of standardization was apparent for the type of software applications used by each agency--even the types of forms used to manually collect data differed by agency. Furthermore, interest in using advanced field data collection technologies depended upon the technology, program (e.g.. pavement or sign management), and agency type (e.g., state, city, or county). The state and larger cities and counties seemed to be interested in using several of the technologies, whereas smaller agencies appeared to have very little interest in using advanced techniques to capture data. A more thorough analysis of the survey results is provided in the report. Recommendations are made to enhance the use of advanced field data acquisition technologies in Iowa transportation agencies: (1) Appoint a statewide task group to coordinate the effort to automate field data collection and reporting within the Iowa transportation agencies. Subgroups representing the cities, counties, and state should be formed with oversight provided by the statewide task group. (2) Educate employees so that they become familiar with the various field data acquisition technologies.

The Annual Condition of Education Report, 2010

The Annual Condition of Education Report includes an expanded Background Demographics section. This section contains information on population, economic, and social data, providing a comparison between Iowa, other states, and the Nation. Geographic Information System (GIS) maps are presented to allow the reader to easily compare between two or more geographies. In some instances, trends are also reported. Information displayed in this section was obtained from a variety of sources and is noted on each table or figure. In all areas, the most recent data available were used.

The Annual Condition of Education Report, 2011

The Annual Condition of Education Report includes an expanded Background Demographics section. This section contains information on population, economic, and social data, providing a comparison between Iowa, other states, and the Nation. Geographic Information System (GIS) maps are presented to allow the reader to easily compare between two or more geographies. In some instances, trends are also reported. Information displayed in this section was obtained from a variety of sources and is noted on each table or figure. In all areas, the most recent data available were used.

Artificial-Intelligence-Based Optimization of the Management of Snow Removal Assets and Resources Final Report, October 2002

Geographic information systems (GIS) and artificial intelligence (AI) techniques were used to develop an intelligent snow removal asset management system (SRAMS). The system has been evaluated through a case study examining snow removal from the roads in Black Hawk County, Iowa, for which the Iowa Department of Transportation (Iowa DOT) is responsible. The SRAMS is comprised of an expert system that contains the logical rules and expertise of the Iowa DOT’s snow removal experts in Black Hawk County, and a geographic information system to access and manage road data. The system is implemented on a mid-range PC by integrating MapObjects 2.1 (a GIS package), Visual Rule Studio 2.2 (an AI shell), and Visual Basic 6.0 (a programming tool). The system could efficiently be used to generate prioritized snowplowing routes in visual format, to optimize the allocation of assets for plowing, and to track materials (e.g., salt and sand). A test of the system reveals an improvement in snowplowing time by 1.9 percent for moderate snowfall and 9.7 percent for snowstorm conditions over the current manual system.

Decision Support Model for Assessing Archaeological Survey Needs for Bridge Replacement Projects in Iowa, 2006

The Bridges Decision Support Model is a geographic information system (GIS) that assembles existing data on archaeological sites, surveys, and their geologic contexts to assess the risk of bridge replacement projects encountering 13,000- to 150-year-old Native American sites. This project identifies critical variables for assessing prehistoric sites potential, examines the quality of available data about the variables, and applies the data to creating a decision support framework for use by the Iowa Department of Transportation (Iowa DOT) and others. An analysis of previous archaeological surveys indicates that subsurface testing to discover buried sites became increasingly common after 1980, but did not become routine until after the adoption of guidelines recommending such testing, in 1993. Even then, the average depth of testing has been relatively shallow. Alluvial deposits of sufficient age, deposited in depositional environments conducive to human habitation, are considerably thicker than archaeologists have routinely tested.

The Annual Condition of Education Report, 2012

The Annual Condition of Education Report includes an expanded Background Demographics section. This section contains information on population, economic, and social data, providing a comparison between Iowa, other states, and the Nation. Geographic Information System (GIS) maps are presented to allow the reader to easily compare between two or more geographies. In some instances, trends are also reported. Information displayed in this section was obtained from a variety of sources and is noted on each table or figure. In all areas, the most recent data available were used.

Optimization of snowmaking in high mountains ski resort

Ski resorts are deploying more and more systems of artificial snow. These tools are necessary to ensure an important economic activity for the high alpine valleys. However, artificial snow raises important environmental issues that can be reduced by an optimization of its production. This paper presents a software prototype based on artificial intelligence to help ski resorts better manage their snowpack. It combines on one hand a General Neural Network for the analysis of the snow cover and the spatial prediction, with on the other hand a multiagent simulation of skiers for the analysis of the spatial impact of ski practice. The prototype has been tested on the ski resort of Verbier (Switzerland).