Coherent Streamflow Variability in Monsoon Asia Over the Past Eight Centuries—Links to Oceanic Drivers

Abstract

The Monsoon Asia region is home to ten of the world's biggest rivers, supporting the lives of 1.7 billion people who rely on streamflow for water, energy, and food. Yet a synthesized understanding of multicentennial streamflow variability for this region is lacking. To fill this gap, we produce the first large scale streamflow reconstruction over Monsoon Asia (62 stations in 16 countries, 813 years of mean annual flow). In making this reconstruction, we develop a novel, automated, climate-informed, and dynamic reconstruction framework that is skillful over most of the region. We show that streamflow in Monsoon Asia is spatially coherent, owing to common drivers from the Pacific, Indian, and Atlantic Oceans. We also show how these oceanic teleconnections change over space and time. By characterizing past and present hydroclimatic variability, we provide a platform for assessing the impact of future climatic changes and informing water management decisions. Plain Language Summary Ten of the world's biggest rivers are located entirely within the Asian Monsoon region. They provide water, energy, and food for 1.7 billion people. To manage these critical resources, we need a better understanding of river discharge-how does it change over a long time? Are there common variation patterns among rivers? To answer these questions, we use information derived from tree rings to reconstruct average annual river discharge history at 62 gauges in 16 Asian countries. Our reconstruction reveals the riparian footprint of megadroughts and large volcanic eruptions over the past eight centuries. We show that simultaneous droughts and pluvials have often occurred at adjacent river basins in the past, because Asian rivers share common influences from the Pacific, Indian, and Atlantic Oceans. We also show how these oceanic teleconnections change over space and time. Our findings can inform big decisions made on water-dependent infrastructure, thus benefiting the riparian people of the Asian Monsoon region.

The Greater Mekong's Climate‐Water‐Energy Nexus: How ENSO‐Triggered Regional Droughts Affect Power Supply and CO2 Emissions

“…Yet, conclusions drawn on the grid's exposure and response to hydroclimatic variability should be taken with caution, owing to the nonstationarity in the ENSO-monsoon teleconnection. Analyses conducted over the past centuries-combining observed and paleo-reconstructed data-revealed that the strength of the teleconnection varied over space and time, alternating decades of weaker and stronger effects (Nguyen et al, 2020;Räsänen et al, 2016). An explanation for this behavior may be sought in the amplitude, temporal evolution, and spatial patterns of ENSO events.…”

Multi‐Proxy, Multi‐Season Streamflow Reconstruction With Mass Balance Adjustment

“…R 2 is calculated on the calibration chunks while RE and CE are calculated on the validation chunks. The contiguous chunks aim to test whether the reconstruction can capture regime shifts in the time series, in line with the traditional split-sample scheme; meanwhile, the 50 repetitions provide a distribution for each skill metric, allowing more robust estimation of the mean skill score (Nguyen et al, 2020). More importantly, the distributions enable us to compare skills statistically among models.…”

Time to Use Dendrohydrological Data in Water Resources Management?

“…Reconstructions often fail to capture extremes on the upper tail of the distribution of annual and seasonal flows. In warm regions, for instance, data derived from moisture-limited trees may not reflect saturated overland flow, which is necessary to reconstruct peak discharge events (Nguyen et al 2020b). Another issue is that reconstructions over large spatial domains may fail to preserve the physical consistency of discharge in a river network.…”

“…Suppose, for example, that we are modeling streamflow at two tributaries as well as the main stem of a river: the total flow of the tributaries should equal the flow on the main stem. This simple mass balance check is not explicitly accounted for by the vast majority of the reconstruction frameworks, generally based on point-by-point regression (Nguyen et al 2020b)-where one models the discharge data independently for each station and relies on the proxy network to account for the spatial patterns. Because accuracy is problematic, streamflow reconstructions may generally be considered speculative, and therefore discounted in modeling and decision-making contexts.…”