2022, Pastor, A.V., Biemans, H., Franssen, W., Gerten, D., Hoff, H., Ludwig, F., Kabat, P.

Freshwater ecosystems have been degraded due to intensive freshwater abstraction. Therefore, environmental flow requirements (EFRs) methods have been proposed to maintain healthy rivers and/or restore river flows. In this study, we used the Variable Monthly Flow (VMF) method to calculate the transgression of freshwater planetary boundaries: (1) natural deficits in which flow does not meet EFRs due to climate variability, and (2) anthropogenic deficits caused by water abstractions. The novelty is that we calculated spatially and cumulative monthly water deficits by river types including the frequency, magnitude and causes of environmental flow (EF) deficits (climatic and/or anthropogenic). Water deficit was found to be a regional rather than a global concern (less than 5% of total discharge). The results show that, from 1960 to 2000, perennial rivers with low flow alteration, such as the Amazon, had an EF deficit of 2–12% of the total discharge, and that the climate deficit was responsible for up to 75% of the total deficit. In rivers with high seasonality and high water abstractions such as the Indus, the total deficit represents up to 130% of its total discharge, 85% of which is due to withdrawals. We highlight the need to allocate water to humans and ecosystems sustainably. This article is part of the Royal Society Science+ meeting issue ‘Drought risk in the Anthropocene’.

2014, Pastor, A.V., Ludwig, F., Biemans, H., Hoff, H., Kabat, P.

As the water requirement for food production and other human needs grows, quantification of environmental flow requirements (EFRs) is necessary to assess the amount of water needed to sustain freshwater ecosystems. EFRs are the result of the quantification of water necessary to sustain the riverine ecosystem, which is calculated from the mean of an environmental flow (EF) method. In this study, five EF methods for calculating EFRs were compared with 11 case studies of locally assessed EFRs. We used three existing methods (Smakhtin, Tennant, and Tessmann) and two newly developed methods (the variable monthly flow method (VMF) and the Q90-Q50 method). All methods were compared globally and validated at local scales while mimicking the natural flow regime. The VMF and the Tessmann methods use algorithms to classify the flow regime into high, intermediate, and low-flow months and they take into account intra-annual variability by allocating EFRs with a percentage of mean monthly flow (MMF). The Q90-Q50 method allocates annual flow quantiles (Q90 and Q50) depending on the flow season. The results showed that, on average, 37% of annual discharge was required to sustain environmental flow requirement. More water is needed for environmental flows during low-flow periods (46-71% of average low-flows) compared to high-flow periods (17-45% of average high-flows). Environmental flow requirements estimates from the Tennant, Q90-Q50, and Smakhtin methods were higher than the locally calculated EFRs for river systems with relatively stable flows and were lower than the locally calculated EFRs for rivers with variable flows. The VMF and Tessmann methods showed the highest correlation with the locally calculated EFRs (R2 = 0.91). The main difference between the Tessmann and VMF methods is that the Tessmann method allocates all water to EFRs in low-flow periods while the VMF method allocates 60% of the flow in low-flow periods. Thus, other water sectors such as irrigation can withdraw up to 40% of the flow during the low-flow season and freshwater ecosystems can still be kept in reasonable ecological condition. The global applicability of the five methods was tested using the global vegetation and the Lund-Potsdam-Jena managed land (LPJmL) hydrological model. The calculated global annual EFRs for fair ecological conditions represent between 25 and 46% of mean annual flow (MAF). Variable flow regimes, such as the Nile, have lower EFRs (ranging from 12 to 48% of MAF) than stable tropical regimes such as the Amazon (which has EFRs ranging from 30 to 67% of MAF).

2017, Jägermeyr, J., Pastor, A., Biemans, H., Gerten, D.

Safeguarding river ecosystems is a precondition for attaining the UN Sustainable Development Goals (SDGs) related to water and the environment, while rigid implementation of such policies may hamper achievement of food security. River ecosystems provide life-supporting functions that depend on maintaining environmental flow requirements (EFRs). Here we establish gridded process-based estimates of EFRs and their violation through human water withdrawals. Results indicate that 41% of current global irrigation water use (997 km 3 per year) occurs at the expense of EFRs. If these volumes were to be reallocated to the ecosystems, half of globally irrigated cropland would face production losses of ≥10%, with losses of ∼20-30% of total country production especially in Central and South Asia. However, we explicitly show that improvement of irrigation practices can widely compensate for such losses on a sustainable basis. Integration with rainwater management can even achieve a 10% global net gain. Such management interventions are highlighted to act as a pivotal target in supporting the implementation of the ambitious and seemingly conflicting SDG agenda.

2018, Schaphoff, S., Von Bloh, W., Rammig, A., Thonicke, K., Biemans, H., Forkel, M., Gerten, D., Heinke, J., Jägermeyr, J., Knauer, J., Langerwisch, F., Lucht, W., Müller, C., Rolinski, S., Waha, K.

This paper provides a comprehensive description of the newest version of the Dynamic Global Vegetation Model with managed Land, LPJmL4. This model simulates - internally consistently - the growth and productivity of both natural and agricultural vegetation as coherently linked through their water, carbon, and energy fluxes. These features render LPJmL4 suitable for assessing a broad range of feedbacks within and impacts upon the terrestrial biosphere as increasingly shaped by human activities such as climate change and land use change. Here we describe the core model structure, including recently developed modules now unified in LPJmL4. Thereby, we also review LPJmL model developments and evaluations in the field of permafrost, human and ecological water demand, and improved representation of crop types. We summarize and discuss LPJmL model applications dealing with the impacts of historical and future environmental change on the terrestrial biosphere at regional and global scale and provide a comprehensive overview of LPJmL publications since the first model description in 2007. To demonstrate the main features of the LPJmL4 model, we display reference simulation results for key processes such as the current global distribution of natural and managed ecosystems, their productivities, and associated water fluxes. A thorough evaluation of the model is provided in a companion paper. By making the model source code freely available at https://gitlab.pik-potsdam.de/lpjml/LPJmL we hope to stimulate the application and further development of LPJmL4 across scientific communities in support of major activities such as the IPCC and SDG process.

2017, Guimberteau, M., Ciais, P., Pablo, Boisier, J., Paula Dutra Aguiar, A., Biemans, H., De Deurwaerder, H., Galbraith, D., Kruijt, B., Langerwisch, F., Poveda, G., Rammig, A., Andres Rodriguez, D., Tejada, G., Thonicke, K., Von, Randow, C., Randow, R., Zhang, K., Verbeeck, H.

Deforestation in Amazon is expected to decrease evapotranspiration (ET) and to increase soil moisture and river discharge under prevailing energy-limited conditions. The magnitude and sign of the response of ET to deforestation depend both on the magnitude and regional patterns of land-cover change (LCC), as well as on climate change and CO2 levels. On the one hand, elevated CO2 decreases leaf-scale transpiration, but this effect could be offset by increased foliar area density. Using three regional LCC scenarios specifically established for the Brazilian and Bolivian Amazon, we investigate the impacts of climate change and deforestation on the surface hydrology of the Amazon Basin for this century, taking 2009 as a reference. For each LCC scenario, three land surface models (LSMs), LPJmL-DGVM, INLAND-DGVM and ORCHIDEE, are forced by bias-corrected climate simulated by three general circulation models (GCMs) of the IPCC 4th Assessment Report (AR4). On average, over the Amazon Basin with no deforestation, the GCM results indicate a temperature increase of 3.3ĝ€°C by 2100 which drives up the evaporative demand, whereby precipitation increases by 8.5 %, with a large uncertainty across GCMs. In the case of no deforestation, we found that ET and runoff increase by 5.0 and 14ĝ€%, respectively. However, in south-east Amazonia, precipitation decreases by 10ĝ€% at the end of the dry season and the three LSMs produce a 6ĝ€% decrease of ET, which is less than precipitation, so that runoff decreases by 22 %. For instance, the minimum river discharge of the Rio Tapajós is reduced by 31ĝ€% in 2100. To study the additional effect of deforestation, we prescribed to the LSMs three contrasted LCC scenarios, with a forest decline going from 7 to 34ĝ€% over this century. All three scenarios partly offset the climate-induced increase of ET, and runoff increases over the entire Amazon. In the south-east, however, deforestation amplifies the decrease of ET at the end of dry season, leading to a large increase of runoff (up to +27ĝ€% in the extreme deforestation case), offsetting the negative effect of climate change, thus balancing the decrease of low flows in the Rio Tapajós. These projections are associated with large uncertainties, which we attribute separately to the differences in LSMs, GCMs and to the uncertain range of deforestation. At the subcatchment scale, the uncertainty range on ET changes is shown to first depend on GCMs, while the uncertainty of runoff projections is predominantly induced by LSM structural differences. By contrast, we found that the uncertainty in both ET and runoff changes attributable to uncertain future deforestation is low.