Water Supply, Demand, and Quality Indicators for Assessing the Spatial Distribution of Water Resource Vulnerability in the Columbia River Basin

Abstract

We investigated water resource vulnerability in the US portion of the Columbia River basin (CRB) using multiple indicators representing water supply, water demand, and water quality. Based on the US county scale, spatial analysis was conducted using various biophysical and socio-economic indicators that control water vulnerability. Water supply vulnerability and water demand vulnerability exhibited a similar spatial clustering of hotspots in areas where agricultural lands and variability of precipitation were high but dam storage capacity was low. The hotspots of water quality vulnerability were clustered around the main stem of the Columbia River where major population and agricultural centres are located. This multiple equal weight indicator approach confirmed that different drivers were associated with different vulnerability maps in the sub-basins of the CRB. Water quality variables are more important than water supply and water demand variables in the Willamette River basin, whereas water supply and demand variables are more important than water quality variables in the Upper Snake and Upper Columbia River basins. This result suggests that current water resources management and practices drive much of the vulnerability within the study area. The analysis suggests the need for increased coordination of water management across multiple levels of water governance to reduce water resource vulnerability in the CRB and a potentially different weighting scheme that explicitly takes into account the input of various water stakeholders.RÉSUMÉ [Traduit par la rédaction] Nous étudions la vulnérabilité de la ressource en eau dans la partie étatsunienne du bassin du fleuve Columbia à l'aide d'indicateurs multiples représentant l'apport d'eau, la demande en eau et la qualité de l'eau. En nous basant sur l'échelle des comtés des États-Unis, nous avons fait une analyse spatiale à l'aide de divers indicateurs biophysiques et socio-économiques qui déterminent la vulnérabilité de l'eau. La vulnérabilité de l'apport d'eau et la vulnérabilité de la demande en eau ont exhibé un regroupement spatial similaire de points chauds dans les régions où il y avait beaucoup de terres agricoles et une grande variabilité dans les précipitations mais où il y avait une faible capacité de stockage par des barrages. Les points chauds de vulnérabilité de la qualité de l'eau étaient regroupés autour du bras principal du fleuve Columbia, où sont situés les principaux centres urbains et agricoles. Cette approche basée sur des indicateurs multiples de poids égaux a confirmé que différents facteurs étaient associés à différentes cartes de vulnérabilité dans les sous-bassins du bassin du fleuve Columbia. Les variables de qualité de l'eau sont plus importantes que les variables d'apport d'eau et de demande en eau dans le bassin de la rivière Willamette alors que les variables d'apport d'eau et de demande en eau sont plus importantes que les variables de qualité de l'eau dans les bassins des parties supérieures de la rivière Snake et du fleuve ...

Summer streamflow deficits from regenerating Douglas‐fir forest in the Pacific Northwest, USA

“…Climate warming and associated loss of snowpack is expected to reduce summer streamflow in the region (e.g., Littell et al, ). Declining summer streamflows in the Columbia River basin may be attributed to climate change (Chang, Jung, Steele, & Gannett, ; Chang et al, ; Hatcher & Jones, ), but these declines may also be the result of cumulative forest change due to plantation establishment, fire suppression (Perry et al, ), and forest succession after wildfire and insect outbreaks, which kill old trees and promote growth of young forests (e.g., Biederman et al, ).…”

Mapping ecosystem services demand: A review of current research and future perspectives

“…Including stakeholders is especially useful to assess the dependence of poor, vulnerable or indigenous community groups on ecosystems. Empirical methods are useful for improving the understanding of drivers, dynamics and the spatial variation of demand and for the parameterization and validation of expert based approaches (Lee and Schuett, 2014;Chang et al, 2013). Process based models can capture the underlying processes and spatial dependencies of ecosystem service flows.…”

“…Palomo et al (2013),García-Nieto et al (2013),Bagstad et al (2013) Understand drivers of demandLee and Schuett (2014),Chang et al (2013) Support planning, management and policyInform ecosystem services accounting Burkhard et al (2012) Inform conservation planning Locatelli et al (2013), Lautenbach et al (2012), Nahuelhual et al (2013) Inform ecosystem restoration Schulp et al (2014b), Serna-Chavez et al (2014), Lautenbach et al (2012) Inform land use management Bagstad et al (2013), Lautenbach et al (2012), García-Nieto et al (2013) Inform integrated land and marine spatial planning Liquete et al (2013) Identify environmental management scale Palomo et al (2013), García-Nieto et al (2013) Inform policy Lautenbach et al (2012)…”

Systems thinking and modelling for sustainable water resources management and agricultural development in the Volta River Basin, West Africa

“…Further, as shown in Figure 7.2, surface water availability is governed by a number of factors, including the various demands, surface water inflows and outflows, groundwater discharge, run-off, and climate related factors (such as the amount of precipitation, temperature, and evaporation) (Chang et al, 2013). The total annual runoff for the VRB in Ghana is estimated to be 37.90 km 3 (Barry et al, 2005) and 70% of surface water inflows into the VRB of Ghana comes from outside the country (Gordon et al, 2013).…”

“…Additionally, a global-scale studies have been able to provide adequate insight into the complex dynamics of linked social-ecological systems, particularly at the river basin level (Chang et al, 2013). Further, SDM approach is dichotomised into qualitative conceptual and quantitative/numerical modelling methods and tools (Wolstenholme, 1999;Coyle, 2000;Sterman, 2000).…”