Streamflow droughts aggravated by human activities despite management

Abstract

Human activities both aggravate and alleviate streamflow drought. Here we show that aggravation is dominant in contrasting cases around the world analysed with a consistent methodology. Our 28 cases included different combinations of human-water interactions. We found that water abstraction aggravated all drought characteristics, with increases of 20 to 305% in total time in drought found across the case studies, and increases in total deficit of up to almost 3000%. Water transfers reduced drought time and deficit by up to 97%. In cases with both abstraction and water transfers into the catchment or augmenting streamflow from groundwater, the water inputs could not compensate for the aggravation of droughts due to abstraction and only shift the effects in space or time. Reservoir releases for downstream water use alleviated droughts in the dry season, but also led to deficits in the wet season by changing flow seasonality. This led to minor changes in average drought duration (-26 to +38%) and moderate changes in average drought deficit (-86 to +369%). Land use showed a smaller impact on streamflow drought, also with both increases and decreases observed (-48 to +98%). Sewage return flows and pipe leakage possibly counteracted the effects of increased imperviousness in urban areas; however, untangling the effects of land use change on streamflow drought is challenging. This synthesis of diverse global cases highlights the complexity of the human influence on streamflow drought and the added value of empirical comparative studies. Results indicate both intended and unintended consequences of water management and infrastructure on downstream society and ecosystems.

Temporal hydrological drought clustering varies with climate and land-surface processes

“…These findings suggest that while reservoirs are able to alleviate drought magnitude, they may not necessarily prevent the occurrence of drought altogether, which results in small impacts on the temporal clustering behavior of hydrological drought as defined in this study. How other types of regulation such as groundwater abstraction affect the temporal clustering behavior of hydrological droughts remains to be investigated (Tijdeman et al 2018, Van Loon et al 2022. Overall, our finding that the temporal clustering behavior of hydrological droughts varies with climate and catchment characteristics stresses that the influence of climate and catchment characteristics influence a range of drought characteristics not limited to magnitude and frequency (Van Loon and Laaha 2015, Barker et al 2016, Parry et al 2016, Apurv and Cai 2020, Konapala and Mishra 2020, Ganguli et al 2022.…”

A coupled agent-based model to analyse human-drought feedbacks for agropastoralists in dryland regions

“…Hydrological variables relate to different types of drought: precipitation (meteorological drought), soil moisture (soil moisture drought), and discharge and groundwater level (hydrological drought). The different types of drought indicators (precipitation, soil moisture, discharge and groundwater deficit) are based on the 80th percentile threshold of the natural model run without human adaptation (Van Loon et al, 2022). Additionally, this threshold can be used to compare drought events between natural model runs (no influence from agents) and model runs including agents (affecting the environment).…”

Hybrid forecasting: using statistics and machine learning to integrate predictions from dynamical models

“…One emerging challenge is assimilating human influences on the water cycle to obtain better predictions of hydroclimate variables, and especially droughts (Brunner et al, 2021;Van Loon et al, 2022). Limited data exist on human impacts such as water storage, groundwater depletion, irrigation, land cover changes, and water transfers.…”