Rain Gauges Provide Critical Data

Accurate rainfall data is just as important as flow data when measuring rainfall-dependent infiltration and inflow.

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What have you accomplished with the money?

Project managers tasked with establishing wastewater system capital improvement programs after rainfall-dependent infiltration and inflow studies will inevitably have to answer that question.

Projects that fail to provide clear conclusions experience many of the same stumbling blocks. Rainfall measurement is critical to any RDII study or project, and while it is necessary for the successful evaluation of sewer system performance, it is often overlooked.

Rainfall issues are at the top of the list because inadequate rainfall data is the most common stumbling block to proper measurement of RDII. People often think of an RDII study primarily as a flowmetering effort. The collection of rainfall data can be an afterthought.

It is not uncommon for a utility’s scope of work to describe in great detail the type of flowmetering technology, field services, and level of data processing that’s expected, while only specifying a few rain gauges or relying solely on existing sources of rain data from the airport or water treatment plant. Yet in the relationship between rainfall and RDII, rainfall data is mathematically just as important as flow data.

The right ratio

Some people use rules of thumb for rain gauge placement based on the number of flowmeters used (e.g., one rain gauge for every 10 or so flowmeters). This approach can result in an adequate number of rain gauges in small areas, but in large sewer sheds, it won’t be enough. 

Small studies often end up using only a single rain gauge, but rain gauges should be treated the same way we treat pumps in pump station designs. We always assume one will fail, so at least two are deployed. Similarly, a flow study should never have less than two rain gauges. Agencies new to RDII measurement seem to be unaware of how primitive tipping-bucket rain gauges are and how easily they become plugged. An uptime of 80 percent for a permanently installed rain gauge network is a high value. 

Rain gauge density is another issue that’s often overlooked. Many agencies view rain gauges as nothing more than an expense that needs to be minimized. In March 2011, participants in an RDII webinar were asked about the importance of accurate flow and rain measurement in quantifying RDII. Over half the respondents believed that rainfall data from any nearby facility was adequate. 

Recommendations for the density of rain gauges for urban hydrology vary considerably. There is a tenfold difference in the recommendations for rain gauge density in the three published references below:

Existing Sewer Evaluation and Rehabilitation, Third Edition, by the Water Environment Federation and American Society of Civil Engineers recommends one rain gauge for every 5 to 10 square miles with a minimum of two gauges even for smaller projects.

Code of Practice for the Hydraulic Modeling of Sewer Systems, Version 3.001, by the Wastewater Planning Users Group recommends the following:

Flat Terrain: 1 + 1 per 1.5 square miles.

Average: 1 + 1 per 0.8 square miles.

Mountainous: 1 + 1 per 0.4 square miles.

A Guide to Short Term Flow Surveys of Sewer Systems by the Water Research Centre provides the same recommendations as the above resource from the Wastewater Planning Users Group.

Radar rainfall service providers can deliver rainfall information at a 1-square-kilometer resolution and generally want to see a network of calibrating rain gauges at a density of one gauge per 10 to 20 square miles. 

With such a wide range of recommendations, it can be difficult to determine the right density for a flowmetering project. The selection depends on whether you ever expect to answer the initial question: What have you accomplished with the money? Remember that in the rain-to-flow relationship, rainfall is the independent — and most important — variable, and RDII is the dependent variable. 

Read the weather

The importance of a dense rain gauge network is obvious when studying rainfall patterns as measured (estimated) by Next-Generation Radar, or NEXRAD, which can be found on the National Weather Service website. One of the NEXRAD products shows the estimated storm total rainfall and the last hour’s accumulated rainfall. 

Storms don’t deposit rain evenly, which is clear when you look at thin bands of yellow within a larger green footprint. A large storm delivering only a 1/2 inch of rain per hour could produce 1.2 inches over small areas within the larger storm.

Imagine that an agency is conducting an RDII study or calibrating a model in a sewer shed in this rainfall footprint. Depending on the rain gauge density, the measured rainfall could have been 0.5 or 1.2 inches for the hour. This can make a huge difference in model calibration or RDII measurement. 

For RDII measurement in large areas, the rain gauges should be laid out in a grid so that a storm with a narrow footprint can’t sneak through undetected. For small areas, the placement of a rain gauge in each sewer shed may be acceptable, but make sure the gauges are no farther than 2 miles apart. 

Rainfall can be calculated for each sewer shed through distribution algorithms. Common algorithms include closest rain gauge, Thiessen polygon, inverse distance, and inverse distance squared.

And remember, rain gauges are low-cost line items. Don’t let a lack of rainfall measurement limit the effectiveness in properly locating sources of RDII or demonstrating the RDII reduction of your rehabilitation project.


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