A Watershed-based Land Prioritization Model for Water Supply Protection

1. A Watershed-based Land Prioritization Model for Water Supply Protection Paper by Randhir, T. O., R. O’Connor, P. R. Penner, D. W. Goodwin. 2001. A watershed-based land prioritization model for water supply protection. Forest Ecology and Management, 143(1):47-56 Presented by Alexis J. Trost, ENST/POLI, GEOG 370, 2/22/10

2. Importance of Prioritization Models • Problem: Escalating costs of water treatment and downstream restoration efforts. Preventive measures at a watershed scale can be cost effective. • Objective: Develop a watershed-based prioritization model for water quality protection. • To develop a land prioritization model to protect water quality in a watershed • To develop a method to evaluate relative time-of-travel distribution on a landscape • To identify locations in Ware River watershed that are sensitive to water quality degradation in designing a land acquisition program • Hypothesis: That prioritization to manage watershed land can be efficient in protecting water quality through targeted acquisition.

3. Methods • Site: The study focuses on Ware River watershed, one of the three watersheds that influence Boston water supplies • Forest (74.61%), wetlands (11.4%), agricultural/open (6.85%), urban/residential (3.34%), and urban/non-residential (1.11%), and water (2.56%) • Watershed land prioritization (WLP) model (2 sources of input) • Geographic information on landscape features and hydrology (used to evaluate travel-time for pollutants from each point source or non-point source in the watershed to the outlet). Derived using GIS. • Develops Criteria • Needs Time Travel sub-model - used to quantify the time-of-travel for pollutants • Expert Elucidation - Causal information on the effect of various geographic criteria on water quality • Criteria Ranking • Criteria Weights

4. Results • The distribution of relative travel-time coincided well with land usage • This distribution is influenced by topography and land use in a watershed • Non-linear distribution • Priority index successfully predicted those areas that are sensitive to water quality as characterized by higher slope, riparian buffers and less travel-time • Lower priority areas account for the largest area in the watershed • As priority index increased the acreage under each priority class decreased

5. Figures Fig 2. Distribution of land by prioritization index (I), Ware River watershed, Massachusetts. Fig 1. Distribution of relative travel-time (t), Ware River watershed, Massachusetts

6. Conclusion • Traditional approaches that use linear distance from an outlet as a proxy for travel-time can be inefficient in quantifying the relative travel time. • Early land acquisition strategies may be inefficient in protecting water quality because of the nature of the priority distribution observed in the indexes. • The distribution of high priority classes to a relatively low area of land indicates possibility of targeting a smaller acreage • Since high priority areas are limited in coverage, program costs are reduced and benefits of water quality improvement are higher compared to solutions using single criterion methods

7. Critiques • Mentions many policy options that are not fully explored in the paper (outside of targeting and land acquisition policies) • Ex: states educational outreach efforts but does not show relationship to the model • Future extensions of the study • How else the model can be used to predict or assist in water management