Hester Biemans

Global water resources affected by human interventions and climate change

Significance Humans alter the water cycle by constructing dams and through water withdrawals. Climate change is expected to additionally affect water supply and demand. Here, model analyses of climate change and direct human impacts on the terrestrial water cycle are presented. The results indicate that the impact of man-made reservoirs and water withdrawals on the long-term global terrestrial water balance is small. However, in some river basins, impacts of human interventions are significant. In parts of Asia and the United States, the effects of human interventions exceed the impacts expected for moderate levels of global warming. This study also identifies areas where irrigation water is currently scarce, and where increases in irrigation water scarcity are projected. Humans directly change the dynamics of the water cycle through dams constructed for water storage, and through water withdrawals for industrial, agricultural, or domestic purposes. Climate change is expected to additionally affect water supply and demand. Here, analyses of climate change and direct human impacts on the terrestrial water cycle are presented and compared using a multimodel approach. Seven global hydrological models have been forced with multiple climate projections, and with and without taking into account impacts of human interventions such as dams and water withdrawals on the hydrological cycle. Model results are analyzed for different levels of global warming, allowing for analyses in line with temperature targets for climate change mitigation. The results indicate that direct human impacts on the water cycle in some regions, e.g., parts of Asia and in the western United States, are of the same order of magnitude, or even exceed impacts to be expected for moderate levels of global warming (+2 K). Despite some spread in model projections, irrigation water consumption is generally projected to increase with higher global mean temperatures. Irrigation water scarcity is particularly large in parts of southern and eastern Asia, and is expected to become even larger in the future.

Impact of reservoirs on river discharge and irrigation water supply during the 20th century

This paper presents a quantitative estimation of the impact of reservoirs on discharge and irrigation water supply during the 20th century at global, continental, and river basin scale. Compared to a natural situation the combined effect of reservoir operation and irrigation extractions decreased mean annual discharge to oceans and significantly changed the timing of this discharge. For example, in Europe, May discharge decreased by 10%, while in February it increased by 8%. At the end of the 20th century, reservoir operations and irrigation extractions decreased annual global discharge by about 2.1% (930 km3 yr-1). Simulation results show that reservoirs contribute significantly to irrigation water supply in many regions. Basins that rely heavily on reservoir water are the Colorado and Columbia River basins in the United States and several large basins in India, China, and central Asia (e.g., in the Krishna and Huang He basins, reservoirs more than doubled surface water supply). Continents gaining the most are North America, Africa, and Asia, where reservoirs supplied 57, 22, and 360 km3 yr-1 respectively between 1981–2000, which is in all cases 40% more than the availability in the situation without reservoirs. Globally, the irrigation water supply from reservoirs increased from around 18 km3 yr-1 (adding 5% to surface water supply) at the beginning of the 20th century to 460 km3 yr-1 (adding almost 40% to surface water supply) at the end of the 20th century. The analysis is performed using a newly developed and validated reservoir operation scheme within a global-scale hydrology and vegetation model (LPJmL)

Effects of Precipitation Uncertainty on Discharge Calculations for Main River Basins

This study quantifies the uncertainty in discharge calculations caused by uncertainty in precipitation input for 294 river basins worldwide. Seven global gridded precipitation datasets are compared at river basin scale in terms of mean annual and seasonal precipitation. The representation of seasonality is similar in all datasets, but the uncertainty in mean annual precipitation is large, especially in mountainous, arctic, and small basins. The average precipitation uncertainty in a basin is 30%, but there are strong differences between basins. The effect of this precipitation uncertainty on mean annual and seasonal discharge was assessed using the uncalibrated dynamic global vegetation and hydrology model Lund‐Potsdam‐Jena managed land (LPJmL), yielding even larger uncertainties in discharge (average 90%). For 95 basins (out of 213 basins for which measurements were available) calibration of model parameters is problematic because the observed discharge falls within the uncertainty of the simulated discharge. A method is presented to account for precipitation uncertainty in discharge simulations.

Global Water Availability and Requirements for Future Food Production

AbstractThis study compares, spatially explicitly and at global scale, per capita water availability and water requirements for food production presently (1971–2000) and in the future given climate and population change (2070–99). A vegetation and hydrology model Lund–Potsdam–Jena managed Land (LPJmL) was used to calculate green and blue water availability per capita, water requirements to produce a balanced diet representing a benchmark for hunger alleviation [3000 kilocalories per capita per day (1 kilocalorie = 4184 joules), here assumed to consist of 80% vegetal food and 20% animal products], and a new water scarcity indicator that relates the two at country scale. A country was considered water-scarce if its water availability fell below the water requirement for the specified diet, which is presently the case especially in North and East Africa and in southwestern Asia. Under climate (derived from 17 general circulation models) and population change (A2 and B1 emissions and population scenarios), wa...

Snowmelt contributions to discharge of the Ganges

Himalayan headwaters supply large quantities of runoff derived from snowmelt and monsoon rainfall to the Ganges River. Actual snowmelt contribution to discharge in the Ganges remains conjectural under both present and future climatic conditions. As snowmelt is likely to be perturbed through climatic warming, four hydrological models, VIC, JULES, LPJmL and SWAT, appropriate for coupling with regional climate models, were used to provide a baseline estimate of snowmelt contribution to flow at seasonal and annual timescales. The models constrain estimates of snowmelt contributions to between 1% and 5% of overall basin runoff. Snowmelt is, however, significant in spring months, a period in which other sources of runoff are scarce.

Future water resources for food production in five South Asian river basins and potential for adaptation — A modeling study

The Indian subcontinent faces a population increase from 1.6 billion in 2000 towards 2 billion around 2050. Therefore, expansion of agricultural area combined with increases in productivity will be necessary to produce the food needed in the future. However, with pressure on water resources already being high, and potential effects of climate change still uncertain, the question rises whether there will be enough water resources available to sustain this production. The objective of this study is to make a spatially explicit quantitative analysis of water requirements and availability for current and future food production in five South Asian basins (Indus, Ganges, Brahmaputra, Godavari and Krishna), in the absence or presence of two different adaptation strategies: an overall improvement in irrigation efficiency, and an increase of reservoir storage capacity. The analysis is performed by using the coupled hydrology and crop production model LPJmL. It is found that the Godavari and Krishna basins will benefit most from an increased storage capacity, whereas in the Ganges and the Indus water scarcity mainly takes place in areas where this additional storage would not provide additional utility. Increasing the irrigation efficiency will be beneficial in all basins, but most in the Indus and Ganges, as it decreases the pressure on groundwater resources and decreases the fraction of food production that would become at risk because of water shortage. A combination of both options seems to be the best strategy in all basins. The large-scale model used in this study is suitable to identify hotspot areas and support the first step in the policy process, but the final design and implementation of adaptation options requires supporting studies at finer scales.

Reconciling irrigated food production with environmental flows for Sustainable Development Goals implementation

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 km3 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.

Flexible Strategies for Coping with Rainfall Variability: Seasonal Adjustments in Cropped Area in the Ganges Basin.

One of the main manifestations of climate change will be increased rainfall variability. How to deal with this in agriculture will be a major societal challenge. In this paper we explore flexibility in land use, through deliberate seasonal adjustments in cropped area, as a specific strategy for coping with rainfall variability. Such adjustments are not incorporated in hydro-meteorological crop models commonly used for food security analyses. Our paper contributes to the literature by making a comprehensive model assessment of inter-annual variability in crop production, including both variations in crop yield and cropped area. The Ganges basin is used as a case study. First, we assessed the contribution of cropped area variability to overall variability in rice and wheat production by applying hierarchical partitioning on time-series of agricultural statistics. We then introduced cropped area as an endogenous decision variable in a hydro-economic optimization model (WaterWise), coupled to a hydrology-vegetation model (LPJmL), and analyzed to what extent its performance in the estimation of inter-annual variability in crop production improved. From the statistics, we found that in the period 1999–2009 seasonal adjustment in cropped area can explain almost 50% of variability in wheat production and 40% of variability in rice production in the Indian part of the Ganges basin. Our improved model was well capable of mimicking existing variability at different spatial aggregation levels, especially for wheat. The value of flexibility, i.e. the foregone costs of choosing not to crop in years when water is scarce, was quantified at 4% of gross margin of wheat in the Indian part of the Ganges basin and as high as 34% of gross margin of wheat in the drought-prone state of Rajasthan. We argue that flexibility in land use is an important coping strategy to rainfall variability in water stressed regions.

Intercomparison of global river discharge simulations focusing on dam operation—multiple models analysis in two case-study river basins, Missouri–Mississippi and Green–Colorado

We performed a twofold intercomparison of river discharge regulated by dams under multiple meteorological forcings among multiple global hydrological models for a historical period by simulation. Paper II provides an intercomparison of river discharge simulated by five hydrological models under four meteorological forcings. This is the first global multimodel intercomparison study on dam-regulated river flow. Although the simulations were conducted globally, the Missouri-Mississippi and Green- Colorado Rivers were chosen as case-study sites in this study. The hydrological models incorporate generic schemes of dam operation, not specific to a certain dam. We examined river discharge on a longitudinal section of river channels to investigate the effects of dams on simulated discharge, especially at the seasonal time scale. We found that the magnitude of dam regulation differed considerably among the hydrological models. The difference was attributable not only to dam operation schemes but also to the magnitude of simulated river discharge flowing into dams. That is, although a similar algorithm of dam operation schemes was incorporated in different hydrological models, the magnitude of dam regulation substantially differed among the models. Intermodel discrepancies tended to decrease toward the lower reaches of these river basins, which means model dependence is less significant toward lower reaches. These case-study results imply that, intermodel comparisons of river discharge should be made at different locations along the rivers course to critically examine the performance of hydrological models because the performance can vary with the locations.

LPJmL4 – a dynamic global vegetation model with managed land – Part 1: Model description

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 in coherently linked through their water, carbon and energy fluxes. These features render LPJmL4 suitable for assessing a broad range 5 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 10 dealing with impacts of historical and future environmental change on the terrestrial biosphere at regional and global scale and provide a comprehensive overview over 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 15 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, not least in support of major activities such as the IPCC and SDG process.