Coset-Effective Placement of Best Management Practices in a Watershed: Lessons Learned from Conservation Effects Assessment Project
Title: Coset-Effective Placement of Best Management Practices in a Watershed: Lessons Learned from Conservation Effects Assessment Project
Category: Academic Article
File: Kurkalova-2015_0464_JAWRA-Cost-effective-prioritization-of-watershed-restoration-actions.pdf
Updated Date: 20.04.2018
Author(s)/Source(s): Lyubov A. Kurkalova
Publication Date: 2015
Focal Topic: Adaptive Management
Location: United States
This article reviews the key, cross-cutting findings concerning watershed-scale cost-effective placement
of best management practices (BMPs) emerging from the National Institute of Food and Agriculture
Conservation Effects Assessment Project (CEAP) competitive grants watershed studies. The synthesis focuses on two fundamental aspects of the cost-effectiveness problem: (1) how to assess the location- and farmer-specific costs of BMP implementation, and (2) how to decide on which BMPs need to be implemented and where within a given watershed. Major lessons learned are that (1) data availability remains a significant limiting factor in capturing within-watershed BMP cost variability; (2) strong watershed community connections help overcome the cost estimation challenges; (3) detailing cost components facilitates the transferability of estimates to alternative locations and/or economic conditions; and (4) implicit costs vary significantly across space and farmers. Furthermore, CEAP studies showed that (5) evolutionary algorithms provide workable ways to identify costeffective BMP placements; (6) tradeoffs between total conservation costs and watershed-scale cost-effective water quality improvements are commonly large; (7) quality baseline information is essential to solving cost-effectiveness problem; and (8) systemic and modeling uncertainties alter cost-effective BMP placements considerably.
BMPs, watershed management, water quality economics, optimization, cost-effective BMP placement, costs of BMPs, evolutionary algorithms