A vulnerability driven approach to identify adverse climate and land use change combinations for critical hydrologic indicator thresholds: Application to a watershed in Pennsylvania, USA

Abstract

Large uncertainties in streamflow projections derived from downscaled climate projections of precipitation and temperature can render such simulations of limited value for decision making in the context of water resources management. New approaches are being sought to provide decision makers with robust information in the face of such large uncertainties. We present an alternative approach that starts with the stakeholder's definition of vulnerable ranges for relevant hydrologic indicators. Then the modeled system is analyzed to assess under what conditions these thresholds are exceeded. The space of possible climates and land use combinations for a watershed is explored to isolate subspaces that lead to vulnerability, while considering model parameter uncertainty in the analysis. We implement this concept using classification and regression trees (CART) that separate the input space of climate and land use change into those combinations that lead to vulnerability and those that do not. We test our method in a Pennsylvania watershed for nine ecological and water resources related streamflow indicators for which an increase in temperature between 3 C and 6 C and change in precipitation between 217% and 19% is projected. Our approach provides several new insights, for example, we show that even small decreases in precipitation ( 5%) combined with temperature increases greater than 2.5 C can push the mean annual runoff into a slightly vulnerable regime. Using this impact and stakeholder driven strategy, we explore the decisionrelevant space more fully and provide information to the decision maker even if climate change projections are ambiguous.

Sensitivity Analysis of Environmental Models: A Systematic Review with Practical Workflow

“…A particularly interesting class of nonlinear regression methods in the context of Sensitivity Analysis is that of Classification And Regression Trees (CART, for application examples see e.g. Harper et al (2011) and Singh et al (2014)). CART provides several advantages, including that they can easily handle non-numerical inputs and outputs, and that they can be used for both ranking and mapping.…”

“…Applications of SA for this purpose are far less numerous than those for uncertainty investigation and model calibration. However, they are increasingly investigated, see for example Brown et al (2011), Singh et al (2014) and references therein.…”

“…the intensity or the duration of a design storm event as in Hamm et al (2006)) or with the scalar multiplier used to obtain it by perturbation of a reference time series (e.g. Singh et al, 2014). A more flexible procedure is the one described in Baroni and Tarantola (2014) (and references therein).…”

“…Pastres et al, 1999); to support robust decision-making (e.g. Nguyen and de Kok, 2007;Singh et al, 2014;Anderson et al, 2014).…”

Reductionist and integrative research approaches to complex water security policy challenges

“…This holds for social appraisals of sustainability (e.g. Stirling et al, 2007: Ch 3), to define 'critical' hydrologic indicator thresholds (Singh et al, 2014), or for the design of water resource infrastructure systems (Brown, 2010), for example. Lessons that this body of work hold for water security research and policy include the rationale for broadened, precautionary, and more humble approaches and perspectives in the face of unknown unknowns.…”