Linkages between Regional Trends in Monthly Maximum Flows and Selected Climatic Variables

Abstract

The potential impact of climate change on the hydrologic regime is a crucial question for water resources management. This study explores regional trends in monthly maximum flows and their possible linkages to trends in selected climatic variables in a hydroclimatologically homogeneous region. Trends are identified using the Mann-Kendall nonparametric test, with a modification for autocorrelated data. The regional significance of trends identified at the local scale is evaluated by means of a regional bootstrap algorithm. A trend significance index that accounts for both local and regional significance levels is proposed as a convenient tool for quantification and visual comparison of different trend results. The index is also used for identifying potential linkages between trends in hydroclimatic records. The plausibility of identified linkages is explored by means of cross-correlation analysis applied on residuals that are obtained from the original records after subtracting all serially dependent components. An uncertainty in regional trend analysis resulting from different observation periods is presented and quantified by calculating trend significance indices for several scenarios of different locations and lengths of a common observation period shifted on a timescale. The results show significant changes in the intraannual flood regime in the case study area of southern British Columbia. A regionally, strongly significant increase in the spring air temperature shifts the timing of the snowmelt process, resulting in a significant increase in early spring maximum flows and a significant decrease in late spring maximum flows. An autumn decrease in flows is related to increasing air temperature in the preceding summer months, which tends to dry out catchments more intensively, and is also related to precipitation activity in the previous months. The regional trend results are highly sensitive to the location and length of a given regional observation period on a timescale. Possible sources of the uncertainty in a low frequency climatic variability such as the Pacific Decadal Oscillation are discussed.