Wis. Admin. Code NR 155.23

Cost containment

Last amended: 2011Year: 2026Length: 584 wordsOfficial source

Cite as Wis. Admin. Code NR § 155.23

Cost containment. (1) Governmental units as providers of cost-share agreements shall identify and agree to use one or more of the following cost containment procedures for each urban best management practice identified in the runoff management grant agreement: (a) Average cost. Based on past cost information, a governmental unit determines an average cost per unit of materials and labor for the installation of a urban best management practice which may not be exceeded. A governmental unit may use its own experience, or information obtained from the department or other sources, to estimate typical costs. (b) Range of costs. Based on past cost information, a governmental unit establishes a cost range for the installation of an urban best management practice. Eligible costs may not exceed the maximum cost of the range. A governmental unit may use its own experience, or information obtained from the department or other sources, to estimate typical costs. (c) Competitive bidding. A governmental unit requires the landowner or land operator to request bids from contractors for the installation of an urban best management practice. The cost-share payment shall be calculated based on the lowest bid meeting acceptable qualifications. The governmental unit shall identify criteria for determining acceptable qualifications. The landowner or land operator may select a qualified contractor other than the low qualified bidder, but shall contribute 100% of the difference between the bids. (d) Maximum cost-share limit. A governmental unit or the department establishes a maximum cost-share rate limit not to exceed the rates specified in ch. NR 154 and this chapter for installation of an urban best management practice. (e) Municipal work group. A governmental unit hires or assigns its employees to install an urban best management practice for landowners and land operators if the employees are able to perform the work at a cost lower than the private sector. (g) Other cost containment procedures. If a governmental unit determines another cost containment procedure would be at least as or more effective than the cost containment procedures described in this subsection, it shall include the alternative in the project application and the department shall include the alternative in the runoff management grant agreement. (2) The cost-containment procedures in this subsection shall be used to control the cost of in-kind contributions, including the substantiated value of donated materials, equipment, services and labor by landowners or land operators installing urban best management practices: (a) All sources of local share donation shall be indicated in the project application submitted under s. NR 155.17 . (b) The maximum value of donated labor may not exceed the local market wage for equivalent work. (c) The value of donated equipment may not exceed the equipment rates for highways established by the Wisconsin department of transportation. (d) The value of donated materials and services may not exceed market rates and shall be established by invoice. (3) Governmental units installing best management practices under a department cost-share grant shall follow the bidding and advertising provisions of their applicable municipal statutes. All contracts shall be subject to approval by the departmental project manager, with respect to reimbursement eligibility, technical standards, and storm water permitting requirements. (4) Governmental units that contract with an outside consultant to perform services under a local assistance grant shall, at a minimum, use a quality-based selection approach and interview firms with proven experience in the field of storm water planning. All contracts shall be subject to approval by the departmental project manager, with respect to reimbursement eligibility, technical standards, and storm water permitting requirements.
Wis. Admin. Code NR 155.23: Cost containment | Justis AI