# Aquatic Resource Monitoring - Frequently Asked Questions - Survey Sampling

Upon thoughtful consideration of the sample survey approach, several questions may come to mind. This section answers several commonly asked questions concerning survey sampling. These questions are addressed in fairly general terms. As noted in the introduction, additional technical details are in a series of methods manuals. (Back to Frequently Asked Questions )

Survey Sampling

The way we select the sample (i.e., choose the units from which to collect data) is crucial for obtaining accurate estimates of population parameters. We clearly would not get a good estimate of the percentage of all students at a university who participate in intramural sports if we polled students at the entrance to the gymnasium. This preferential sample would, most likely, include a much higher proportion of athletes than the general population of students.

Similarly in a stream study, preferential sampling occurs if the sample includes only sites downstream of sewage outfalls in a watershed where sewage outfalls affect only a small percentage of total stream length. This kind of sampling program may provide useful information about conditions downstream of sewage outfalls, but it will not produce estimates that accurately represent the condition of the whole watershed. An illustrative example depicting the difference between assessments that rely on preferential (non-probability) sampling and probability sampling is shown for streams.

Preferential selection can be avoided by taking random samples. Simple random sampling ensures that no particular portion of the sampling frame (i.e., groups of students or kinds of river reaches) is favored. Within streams, the chance of selecting a sampling unit that has degraded ecological conditions would be proportional to the number of sampling units within the target population that have degraded conditions. For example, if 30% of the target population has degraded conditions, then on average 30% of the (randomly selected) units in the sample will exhibit degraded conditions. This property of random sampling allows estimates (based only on the sample) to be used to draw conclusions about the target population as a whole. Go to Top

What if more than one target population or sub-populations are of interest?  Can a survey design address this?

One goal of a sample survey may be to compare two parts of a target population (these could be described as sub-populations), or a part of the population to the whole population. For instance, an opinion poll might be used to determine if a higher percentage of the people living in Rhode Island is likely to vote Democratic than in the nation as a whole. Given its small size, Rhode Island probably would receive very little attention in a national poll if samples are allocated by a simple random process. One way to achieve a sample of people in Rhode Island that is sufficient to make this comparison is to increase sampling effort for the nation as a whole until enough people from Rhode Island are included in the randomly selected national sample. This option is not very cost-effective because it requires considerable, unnecessary sampling effort in other areas to achieve a desired sample size in one small area.

Another, preferable, alternative would be to divide the entire target population into two subpopulations,. Voters in the United States could be divided into (1) those living in Rhode Island, and (2) those living elsewhere. A simple random sample of desired size could then be selected from each of these groups.

Stratified sampling could be used in a stream survey to enhance sampling effort in a watershed of special interest so that its condition could be compared with that of a larger area. In a study area with 1000 kilometers of streams, for example, an area of special interest may contain 200 kilometers of streams. If budget constraints limit the size of the total sample to 60 sampling units, 30 could be randomly selected from the special interest area, and 30 from the rest of the sampling frame. If simple random sampling is used, the area of special interest, which represents 20% of the area, will contain only about 12 of the 60 selected sampling units. A sample of 12 would be insufficient to estimate the condition of the special interest area reliably. Go to Top

One aspect of a rotating basin design is to describe the condition of the basin as a whole. Unless the basin will be censused, a sample survey can be used to characterize the overall status of the basin. A combination of a sample survey and targeted monitoring as outlined above can be used to produce an overall description of the basin. In addition, the rotating basin design could be embedded in a state wide sample survey by intensifying the sampling on the particular basin or set of basins for the year(s) that basin or set of basins was under study. A routine ongoing statewide survey could be conducted at some baseline level of intensity, along with intensified sampling in the targeted basins. In this way, a state could track statewide progress as well as progress in individual basins as they are revisited, and determine the condition of the basin relative to the condition of the state as a whole. Go to Top

States are required to identify or list waterbodies that are impaired, for example, by the 303(d) listing process.  How useful are sample surveys for identifying those waterbodies?

Because survey sampling is intended to characterize the status of the resource as a whole, it is generally not useful for enumerating a list of a specific type, for example, a list of all the impaired waterbodies. However, an important aspect of sample surveys is that they can provide a check on the completeness of the list. Suppose that a state agency had submitted a list of impaired waterbodies it had gathered from ongoing monitoring programs, and from reports from other agencies. This list would presumably be a census of the impaired waterbodies. The state agency could then compare the amount of the resource impaired against the magnitude of the total resource to derive a percent of the resource impaired. The state agency could check this proportion by conducting a sample survey and classifying the sample sites into impaired/not impaired. It could then check the proportion impaired based on the sample survey with the proportion calculated from the inventory. Consistency between the two estimates would indicate that the census of the impaired sites is reasonably complete (within the uncertainty of the sample survey); inconsistency between the two estimates would provide information on how good the impairment census was (again within the confidence limits of the sample survey). Go to Top