Carbon Sequestration Potential of Indian Forests

The forestry sector can not only sustain its carbon but also has the potential to absorb carbon from the atmosphere. India has maintained approximately 64 Mha of forest cover for the last decade. The rate of afforestation in India is one of the highest among the tropical countries, currently estimated to be 2 Mha per annum. The annual productivity has increased from 0.7 m³ per hactare in 1985 to 1.37 m³ per hectare in 1995. Increase in annual productivity directly indicates an increase in forest biomass and hence higher carbon sequestration potential. The carbon pool for the Indian forests is estimated to be 2026.72 Mt for the year 1995. Estimates of annual carbon uptake increment suggest that our forests and plantations have been able to remove at least 0.125 Gt of CO₂ from the atmosphere in the year 1995. Assuming that the present forest cover in India will sustain itself with a marginal annual increase by 0.5 Mha in area of plantations, we can expect our forests to continue to act as a net carbon sink in future.     

Using landsat data to determine land use/land cover changes in Samsun, Turkey

The rapid industrialization and urbanization of an area require quick preparation of actual land use/land cover (LU/LC) maps in order to detect and avoid overuse and damage of the landscape beyond sustainable development limits. Remote sensing technology fits well for long-term monitoring and assessment of such effects. The aim of this study was to analyze LU/LC changes between 1980 and 1999 in Samsun, Turkey, using satellite images. Three Landsat images from 1980, 1987 and 1999 were used to determine changes. A post classification technique was used based on a hybrid classification approach (unsupervised and supervised). Images were classified into six LU/LC types; urban, agriculture, dense forest, open forest-hazelnut, barren land and water area. It is found that significant changes in land cover occurred over the study period. The results showed an increase in urban, open forest/hazelnut, barren land and water area and a decrease in agriculture and dense forest in between 1980 and 1999. In this period, urban land increased from 0.77% to 2.47% of the total area, primarily due to conversions from agricultural land and forest to a lesser degree. While the area of dense forest decreased from 41.09% to 29.64% of the total area, the area of open forest and hazelnut increased from 6.73% to 11.88%.     

Changes in aquatic vegetation and floodplain land cover in the Upper Mississippi and Illinois rivers (1989–2000–2010)

Quantifying changes in the cover of river-floodplain systems can provide important insights into the processes that structure these landscapes as well as the potential consequences to the ecosystem services they provide. We examined net changes in 13 different aquatic and floodplain land cover classes using photo interpreted maps of the navigable portions of the Upper Mississippi River (UMR, above the confluence with the Ohio River) and Illinois River from 1989 to 2000 and from 2000 to 2010. We detected net decreases in vegetated aquatic area in nearly all river reaches from 1989 to 2000. The only river reaches that experienced a subsequent recovery of vegetated aquatic area from 2000 to 2010 were located in the northern portion of the UMR (above navigation pool 14) and two reaches in the Illinois River. Changes on the floodplain were dominated by urban development, which increased in nearly every river reach studied from 1989 to 2000. Agricultural lands declined in most river reaches from 2000 to 2010. The loss of agricultural land cover in the northern UMR was accompanied by increases in forest cover, whereas in the lower UMR and Illinois River, declines in agriculture were accompanied by increases in forest and shallow marsh communities. The changes in aquatic vegetation occupied between 5 and 20% of the total aquatic area and are likely associated with previously reported regional improvements in water clarity, while smaller (1–15% of the total floodplain area) changes in anthropogenic land cover types on the floodplain are likely driven by broad-scale socio-economic conditions.     

Soil microarthropod communities from Mediterranean forest ecosystems in Central Italy under different disturbances

The aim of this study is to assess soil quality in Mediterranean forests of Central Italy, from evergreen to deciduous, with different types of management (coppice vs. high forest vs. secondary old growth) and compaction impacts (machinery vs. recreational). Soil quality was evaluated studying soil microarthropod communities and applying a biological index (QBS-ar) based on the concept that the higher is the soil quality, the higher will be the number of microarthropod groups well adapted to the soil habitat. Our results confirm that hardwood soils are characterised by the highest biodiversity level among terrestrial communities and by a well-structured and mature microarthropod community, which is typical of stable ecosystems (QBS value, >200). While silvicultural practices and forest composition do not seem to influence QBS-ar values or microarthropod community structure, the index is very efficient in detecting soil impacts (soil compaction due to logging activities). Several taxa (Protura, Diplura, Coleoptera adults, Pauropoda, Diplopoda, Symphyla, Chilopoda, Diptera larvae and Opiliones) react negatively to soil compaction and degradation (QBS value, <150). In particular, Protura, Diplura, Symphyla and Pauropoda, are taxonomic groups linked to undisturbed soil. This index could also be a useful tool in monitoring soil biodiversity in protected areas and in urban forestry to prevent the negative effects of trampling. QBS-ar is a candidate index for biomonitoring of soil microarthropod biodiversity across the landscape to provide guidance for the sustainable management of renewable resource and nature conservation.     

Accounting for forest carbon pool dynamics in product carbon footprints: Challenges and opportunities

Modification and loss of forests due to natural and anthropogenic disturbance contribute an estimated 20% of annual greenhouse gas (GHG) emissions worldwide. Although forest carbon pool modeling rarely suggests a ‘carbon neutral’ flux profile, the life cycle assessment community and associated product carbon footprint protocols have struggled to account for the GHG emissions associated with forestry, specifically, and land use generally. Principally, this is due to underdeveloped linkages between life cycle inventory (LCI) modeling for wood and forest carbon modeling for a full range of forest types and harvest practices, as well as a lack of transparency in globalized forest supply chains. In this paper, through a comparative study of U.S. and Chinese coated freesheet paper, we develop the initial foundations for a methodology that rescales IPCC methods from the national to the product level, with reference to the approaches in three international product carbon footprint protocols. Due to differences in geographic origin of the wood fiber, the results for two scenarios are highly divergent. This suggests that both wood LCI models and the protocols need further development to capture the range of spatial and temporal dimensions for supply chains (and the associated land use change and modification) for specific product systems. The paper concludes by outlining opportunities to measure and reduce uncertainty in accounting for net emissions of biogenic carbon from forestland, where timber is harvested for consumer products.     

An assessment of the optimal scale for monitoring of MODIS and FIA NPP across the eastern USA

Robust monitoring of carbon sequestration by forests requires the use of multiple data sources analyzed at a common scale. To that end, model-based Moderate Resolution Imaging Spectroradiometer (MODIS) and field-based Forest Inventory and Analysis (FIA) data of net primary productivity (NPP) were compared at increasing levels of spatial aggregation across the eastern USA. A total of 52,167 FIA plots and colocated MODIS forest cover NPP pixels were analyzed using a hexagonal tiling system. A protocol was developed to assess the optimal scale as an optimal size of landscape patches at which to map spatially explicit estimates of MODIS and FIA NPP. The optimal mapping resolution (hereafter referred to as optimal scale) is determined using spatially scaled z-statistics as the tradeoff between increased spatial agreement as measured by Pearson’s correlation coefficient and decreased details of coverage as measured by the number of hexagons. Spatial sensitivity was also assessed using land cover assessment and forest homogeneity using spatially scaled z-statistics. Pearson correlations indicate that MODIS and FIA NPP are most highly correlated when using large hexagons, while z-statistics indicate an optimal scale at an intermediate hexagon size of 390 km². This optimal scale had more spatial detail than was obtained for larger hexagons and greater spatial agreement than was obtained for smaller hexagons. The z-statistics for land cover assessment and forest homogeneity also indicated an optimal scale of 390 km².     

A framework for assessment and monitoring of small mammals in a lowland tropical forest

Development projects in tropical forests can impact biodiversity.Assessment and monitoring programs based on the principles of adaptive management assist managers to identify and reduce suchimpacts. The small mammal community is one important component ofa forest ecosystem that may be impacted by development projects. In 1996, a natural gas exploration project was initiated in a Peruvian rainforest. The Smithsonian Institution's Monitoring andAssessment of Biodiversity program cooperated with Shell Prospecting and Development Peru to establish an adaptive management program to protect the region's biodiversity. In thisarticle, we discuss the role of assessing and monitoring small mammals in relation to the natural gas project. We outline theconceptual issues involved in establishing an assessment andmonitoring program, including setting objectives, evaluating the results and making appropriate decisions. We also summarizethe steps taken to implement the small mammal assessment, provideresults from the assessment and discuss protocols to identifyappropriate species for monitoring.     

Assessment and monitoring of long-term forest cover changes in Odisha, India using remote sensing and GIS

Deforestation and fragmentation are important concerns in managing and conserving tropical forests and have global significance. In the Indian context, in the last one century, the forests have undergone significant changes due to several policies undertaken by government as well as increased population pressure. The present study has brought out spatiotemporal changes in forest cover and variation in forest type in the state of Odisha (Orissa), India, during the last 75 years period. The mapping for the period of 1924–1935, 1975, 1985, 1995 and 2010 indicates that the forest cover accounts for 81,785.6 km² (52.5 %), 56,661.1 km² (36.4 %), 51,642.3 km² (33.2 %), 49,773 km² (32 %) and 48,669.4 km² (31.3 %) of the study area, respectively. The study found the net forest cover decline as 40.5 % of the total forest and mean annual rate of deforestation as 0.69 %?year^?1 during 1935 to 2010. There is a decline in annual rate of deforestation during 1995 to 2010 which was estimated as 0.15 %. Forest type-wise quantitative loss of forest cover reveals large scale deforestation of dry deciduous forests. The landscape analysis shows that the number of forest patches (per 1,000) are 2.463 in 1935, 10.390 in 1975, 11.899 in 1985, 12.193 in 1995 and 15.102 in 2010, which indicates high anthropogenic pressure on the forests. The mean patch size (km²) of forest decreased from 33.2 in 1935 to 5.5 in 1975 and reached to 3.2 by 2010. The study demonstrated that monitoring of long term forest changes, quantitative loss of forest types and landscape metrics provides critical inputs for management of forest resources.     

Geospatial assessment and monitoring of historical forest cover changes (1920–2012) in Nilgiri Biosphere Reserve,Western Ghats,India

Deforestation in the biosphere reserves, which are key Protected Areas has negative impacts on biodiversity, climate, carbon fluxes and livelihoods. Comprehensive study of deforestation in biosphere reserves is required to assess the impact of the management effectiveness. This article assesses the changes in forest cover in various zones and protected areas of Nilgiri Biosphere Reserve, the first declared biosphere reserve in India which forms part of Western Ghats-a global biodiversity hotspot. In this study, we have mapped the forests from earliest available topographical maps and multi-temporal satellite data spanning from 1920’s to 2012 period. Mapping of spatial extent of forest cover, vegetation types and land cover was carried out using visual interpretation technique. A grid cell of 1 km?×?1 km was generated for time series change analysis to understand the patterns in spatial distribution of forest cover (1920–1973–1989–1999–2006–2012). The total forest area of biosphere reserve was found to be 5,806.5 km² (93.8 % of total geographical area) in 1920. Overall loss of forest cover was estimated as 1,423.6 km² (24.5 % of the total forest) with reference to 1920. Among the six Protected Areas, annual deforestation rate of >0.5 was found in Wayanad wildlife sanctuary during 1920–1973. The deforestation in Nilgiri Biosphere Reserve is mainly attributed to conversion of forests to plantations and agriculture along with submergence due to construction of dams during 1920 to 1989. Grid wise analysis indicates that 851 grids have undergone large-scale negative changes of >75 ha of forest loss during 1920–1973 while, only 15 grids have shown >75 ha loss during 1973–1989. Annual net rate of deforestation for the period of 1920 to 1973 was calculated as 0.5 followed by 0.1 for 1973 to 1989. Our analysis shows that there was large-scale deforestation before the declaration of area as biosphere reserve in 1986; however, the deforestation has drastically reduced after the declaration due to high degree of protection, thus indicating the secure future of reserve in the long term under the current forest management practices. The present work will stand as the most up-to-date assessment on the forest cover of the Nilgiri Biosphere Reserve with immediate applications in monitoring and management of forest biodiversity.     

Land use impacts on river health of Uma Oya,Sri Lanka: implications of spatial scales

Human actions on landscapes are a principal threat to the ecological integrity of river ecosystems worldwide. Tropical landscapes have been poorly investigated in terms of the impact of catchment land cover alteration on water quality and biotic indices in comparison to temperate landscapes. Effects of land cover in the catchment at two spatial scales (catchment and site) on stream physical habitat quality, water quality, macroinvertebrate indices and community composition were evaluated for Uma Oya catchment in the upper Mahaweli watershed, Sri Lanka. The relationship between spatial arrangement of land cover in the catchment and water quality, macroinvertebrate indices and community composition was examined using univariate and multivariate approaches. Results indicate that chemical water quality variables such as conductivity and total dissolved solids are mostly governed by the land cover at broader spatial scales such as catchment scale. Shannon diversity index was also affected by catchment scale forest cover. In stream habitat features, nutrients such as N-NO₃ ^?, macroinvertebrate family richness, %shredders and macroinvertebrate community assemblages were predominantly influenced by the extent of land cover at 200 m site scale suggesting that local riparian forest cover is important in structuring macroinvertebrate communities. Thus, this study emphasizes the importance of services provided by forest cover at catchment and site scale in enhancing resilience of stream ecosystems to natural forces and human actions. Findings suggest that land cover disturbance effects on stream ecosystem health could be predicted when appropriate spatial arrangement of land cover is considered and has widespread application in the management of tropical river catchments.     

Water quality monitoring in Washington's Timber/Fish/Wildlife program

The Timber, Fish, and Wildlife program (TFW) in Washington is a consensus approach to implementing reforms in forest practice regulations involving industrial timberland owners, state agencies, environmental groups, Indian tribes, and non-industrial forest landowners. A cooperative monitoring and research effort (CMER) has been included as a part of this program. Technical projects undertaken by CMER are overseen by a series of steering committees, one of which is the Water Quality Steering Committee. Projects currently being addressed by the Water Quality Steering Committee include: forestry impacts on water temperature, water quality impacts from forestry derived sediment, use of bio-indicators to assess the water quality impacts of forest practices, and the effect of forest chemical applications on water quality. A close link between the research efforts in TFW and the procedure for implementing regulatory change has greatly improved the responsiveness of the rule making process to new information. Results from the water temperature and forest chemical work is currently being incorporated into the forest practice regulations.     

Adapting forest health assessments to changing perspectives on threats—a case example from Sweden

A revised Swedish forest health assessment system is presented. The assessment system is composed of several interacting components which target information needs for strategic and operational decision making and accommodate a continuously expanding knowledge base. The main motivation for separating information for strategic and operational decision making is that major damage outbreaks are often scattered throughout the landscape. Generally, large-scale inventories (such as national forest inventories) cannot provide adequate information for mitigation measures. In addition to broad monitoring programs that provide time-series information on known damaging agents and their effects, there is also a need for local and regional inventories adapted to specific damage events. While information for decision making is the major focus of the health assessment system, the system also contributes to expanding the knowledge base of forest conditions. For example, the integrated monitoring programs provide a better understanding of ecological processes linked to forest health. The new health assessment system should be able to respond to the need for quick and reliable information and thus will be an important part of the future monitoring of Swedish forests.     

Spatiotemporal changes of landscape pattern in response to deforestation in Northeastern Turkey: a case study in Rize

Recognition and understanding of landscape dynamics as a historical legacy of disturbances are necessary for sustainable management of forest ecosystems. This study analyzes spatial and temporal changes in land use and forest cover patterns in a typical mountain forest area in Rize Forest Enterprise of the Northeastern part of Turkey. The area is investigated by evaluated the temporal changes of spatial structure of forest conditions through spatial analysis of forest cover type maps from 1984 and 2007 using GIS and FRAGSTATS. The quantative evidences presented here showed that there were drastic changes in the temporal and spatial dynamics of land use/forest cover. As an overall change between 1984 and 2007, there was a net decrease of 2.30% in total forested areas. On one hand, productive forest areas decreased 12,506 ha, on the other hand, degraded forest areas increased 14,805 ha. In examining the changes of crown closure and development stages of forest ecosystem during the study period, the forest stand area with medium crown closures increased. Regenerated area increased while the other development stages were left to grow to mature development stages in the period. These results regarding to crown closure and development stage showed that forest quality has increased but total forest areas decreased. This is partially due to out-migration of rural population in Rize and Cayeli towns. In terms of spatial configuration, analysis of the metrics revealed that landscape structure in Study area had changed substantially over the 23-year study period, resulting in fragmentation of the landscape as indicated by the large patch numbers and the smaller mean patch sizes due to heavy timber subtraction, illegal cutting, and uncontrolled stand treatments.     

Assessing implications of land use and land cover changes in forest ecosystems of NE Turkey

Monitoring land use and land cover change (LUCC) and understanding forest cover dynamics is extremely important in sustainable development and management of forest ecosystems. This study analyzed the spatial and temporal pattern of LUCC in the Yaln?zçam and U?urlu forest planning units which are located in the northeast corner of Turkey. The investigation also evaluates the temporal changes of the spatial structure of forest conditions through the spatial analysis of forest-cover type maps from 1972 and 2005 using geographical information systems and FRAGSTATS^TM. As an overall change between 1972 and 2005, there was a net increase of 1,823 ha in forested areas, and cumulative forest improvement accounted for 2.06 %. In terms of spatial configuration, the landscape structure in the study area changed substantially over the 33-year study period, resulting in fragmentation of the landscape as indicated by large patch numbers and smaller mean patch sizes, owing to heavy grazing, illegal cutting, and uncontrolled stand treatments.     

Monitoring of Biodiversity Indicators in Boreal Forests: a Need for Improved Focus

The general principles of scale and coarse and fine filters have been widely accepted, but management agencies and industry are still grappling with the question of what to monitor to detect changes in forest biodiversity following forest management. Part of this problem can be attributed to the lack of focused questions for monitoring including absence of null models and predicted effects, a certain level of disconnect between research and management, and recognition that monitoring can be designed as a research question. Considerable research from the past decade has not been adequately synthesized to answer important questions, such as which species or forest attributes might be the best indicators of change. A disproportionate research emphasis has been placed on community ecology, and mostly on a few groups of organisms including arthropods, amphibians, migratory songbirds, and small mammals, while other species, including soil organisms, lichens, bats, raptors, some carnivores, and larger mammals remain less well-known. In most studies of community ecology, the question of what is the importance, if any, of the regularly observed subtle changes in community structures, and causes of observed changes is usually not answered. Hence, our ability to deal with questions of persistence is limited, and demographic research on regionally--defined key species (such as species linked to processes, species whose persistence may be affected, species with large home ranges, species already selected as indicators, and rare and threatened species) is urgently needed. Monitoring programs need to be designed to enable managers to respond to unexpected changes caused by forest management. To do this, management agencies need to articulate null models for monitoring that predict effects, focus fine--scale monitoring on key species (defined by local and regional research) in key habitats (rare, declining, important) across landscapes, and have a protocol in place to adapt management strategies to changes observed. Finally, agencies must have some way to determine and define when a significant change has occurred and to predict the persistence of species; this too should flow from a well--designed null model.     

The use of aerospace methods for forest state assessment

Siberian forests occupy a significant part of the Asian continent. Their role as an essential component of the Earth's surface, biomass and oxygen producer is increasing annually. Expanded reproduction of taiga forests necessitated by the intensive development of Siberian productive forces, results in an evergrowing need of forest productivity constancy and increase. Proper forest exploitation is a crucial part of the solution of such important problems as the rational use of land and water resources, stable crop yields, and the creation of favourable conditions for human life.To solve these important economic problems, the Siberian branch of the USSR Academy of Sciences has devised a long-term programme of ecological monitoring of Siberian forest resources using aerospace techniques. The programme provides for the establishment and improvement of ecogeographical and physicotechnological principles of the remote sensing of forests and the development of fundamental forest-biological research based on new methodologies, the results of which are used to solve urgent forestry and nature protection problems. The research is carried out in the following major directions: studying spectral characteristics of forest vegetation for forest-state indication; thematic mapping of taiga territories; assessing biological productivity of natural complexes; environmental state monitoring; fire protection of forests; pest and disease control; developin instruments and methods for automatized aerospace data processing for real-time use.We consider forest-state monitoring to be one of the crucial tools in providing the optimum use of forest ecosystems for resource and ecological functions.     

Multiscale satellite and spatial information and analysis framework in support of a large-area forest monitoring and inventory update

Many countries undertake a national forest inventory to enable statistically valid monitoring in support of national and international reporting of forest conditions and change. Canada’s National Forest Inventory (NFI) program is designed to operate on a 10-year remeasurement cycle, with an interim report produced at the 5-year mid-point. The NFI is a sample-based inventory, with approximately 18,850 2 ×2-km photo plots across the country, distributed on a 20×20-km grid of sample points; these photo plots are the primary data source for the NFI. Capacity to provide annual monitoring information is required to keep policy and decision makers apprised of current forest conditions. In this study, we implemented a multistage monitoring framework and used a Moderate Resolution Imaging Spectroradiometer (MODIS) change product to successfully identify 78% of the changes in forest cover area that were captured with a Landsat change detection approach. Of the NFI photo plots that were identified by both the Landsat and MODIS approaches as having changes in forest cover, the proportion of change area within the plots was similar (R ²?=?0.78). Approximately 70% of the Landsat-derived change events occupied less than 40% of a single MODIS pixel, and more than 90% of the change events of this size were successfully detected with the MODIS product. Finally, MODIS estimates of the proportion of forest cover change at the NFI photo plot level were comparable to change estimates for the ecoregions as a whole (R ²?=?0.95). High-temporal, low-spatial resolution imagery such as MODIS, in combination with other remotely sensed data sources, can provide information on disturbance events within a national forest inventory remeasurement cycle, thereby satisfying the interim information needs of policy and decision makers as well as the requirements of national and international reporting commitments.     

Using Spatial Pattern to Quantify Relationship Between Samples, Surroundings, and Populations

The need for accurate carbon budgeting, climate change modelling, and sustainable resource management has lead to an increase in the number of large area forest monitoring programs. Large area forest monitoring programs often utilize field and remotely sensed data sources. Sampling, via field or photo plots, enables the collection of data with the desired level of categorical detail in a timely and efficient manner. When sampling, the aim is to collect representative detailed data enabling the statistical reporting upon the characteristics of larger areas. As a consequence, approaches for investigating how well sample data represent larger areas (i.e., the sample neighbourhood and the population) are desired. Presented in this communication is a quantitative approach for assessing the nature of sampled areas in relation to surrounding areas and the overall population of interest. Classified Landsat data is converted to forest/non-forest categories to provide a consistent and uniform data set over a 130,000 km² study region in central British Columbia, Canada. From this larger study area 322 2 × 2 km photo plots on a 20 × 20 km systematic grid are populated with composition and configuration information for comparison to non-sampled areas. Results indicate that typically, within the study area, the spatial pattern of forest within a photo plot is representative of the forest patterns found within primary and secondary neighbourhoods and over the entire population of the study. These methods have implications for understanding the nature of data used in monitoring programs worldwide. The ability to audit photo and field plot information promotes an increased understanding of the results developed from sampling and provides tools identifying locations of possible bias.     

Rangeland and pasture monitoring: an approach to interpretation of high-resolution imagery focused on observer calibration for repeatability

Collection of standardized assessment and monitoring data is critically important for supporting policy and management at local to continental scales. Remote sensing techniques, including image interpretation, have shown promise for collecting plant community composition and ground cover data efficiently. More work needs to be done, however, evaluating whether these techniques are sufficiently feasible, cost-effective, and repeatable to be applied in large programs. The goal of this study was to design and test an image-interpretation approach for collecting plant community composition and ground cover data appropriate for local and continental-scale assessment and monitoring of grassland, shrubland, savanna, and pasture ecosystems. We developed a geographic information system image-interpretation tool that uses points classified by experts to calibrate observers, including point-by-point training and quantitative quality control limits. To test this approach, field data and high-resolution imagery (∼3 cm ground sampling distance) were collected concurrently at 54 plots located around the USA. Seven observers with little prior experience used the system to classify 300 points in each plot into ten cover types (grass, shrub, soil, etc.). Good agreement among observers was achieved, with little detectable bias and low variability among observers (coefficient of variation in most plots <0.5). There was a predictable relationship between field and image-interpreter data (R ² > 0.9), suggesting regression-based adjustments can be used to relate image and field data. This approach could extend the utility of expensive-to-collect field data by allowing it to serve as a validation data source for data collected via image interpretation.     

Economics of place-based monitoring under the safe drinking water act, part I: spatial and temporal patterns of contaminants, and design of screening strategies

The goals of environmental legislation and associated regulations are to protect public health, natural resources, and ecosystems. In this context, monitoring programs should provide timely and relevant information so that the regulatory community can implement legislation in a cost-effective and efficient manner. The Safe Drinking Water Act (SDWA) of 1974 attempts to ensure that public water systems (PWSs) supply safe water to its consumers. As is the case with many other federal environmental statutes, SDWA monitoring has been implemented in relatively uniform fashion across the USA. In this three part series, spatial and temporal patterns in water quality data are utilized to develop, compare, and evaluate the economic performance of alternative place-based monitoring approaches to current monitoring practice. Under the Safe Drinking Water Act (SDWA), a common list of over 90 contaminants is analyzed nationwide using EPA-authorized laboratory procedures. National and state-level summaries of SDWA data have shown that not all contaminants occur in all places at all times. This hypothesis is confirmed and extended by showing that only a few (less than seven) contaminants are of concern in any one of 19 Iowa surface water systems studied. These systems collectively serve about 350,000 people and their sizes vary between 1,200 and 120,000. The distributions of contaminants found in these systems are positively skewed, with many non-detect measurements. A screening strategy to identify such contaminants in individual systems is presented. These findings have significant implications not only for the design of alternative monitoring programs, but also in multi-billion-dollar decisions that influence the course of future drinking water infrastructure, repair, and maintenance investments.