Simulating second-generation herbaceous bioenergy crop yield using the global hydrological model H08 (v.bio1)

Large-scale deployment of bioenergy plantations would have adverse effects on water resources. There is an increasing need to ensure the appropriate inclusion of the bioenergy crops in global hydrological models. Here, through parameter calibration and algorithm improvement, we enhanced the global hydrological model H08 to simulate the bioenergy yield from two dedicated herbaceous bioenergy crops: Miscanthus and switchgrass. Site-specific evaluations showed that the enhanced model had the ability to simulate yield for both Miscanthus and switchgrass, with the calibrated yields being well within the ranges of the observed yield. Independent country-specific evaluations further confirmed the performance of the H08 (v.bio1). Using this improved model, we found that unconstrained irrigation more than doubled the yield under rainfed condition, but reduced the water use efficiency (WUE) by 32 % globally. With irrigation, the yield in dry climate zones can exceed the rainfed yields in tropical climate zones. Nevertheless, due to the low water consumption in tropical areas, the highest WUE was found in tropical climate zones, regardless of whether the crop was irrigated. Our enhanced model provides a new tool for the future assessment of bioenergy–water tradeoffs

Magnitude and robustness associated with the climate change impacts on global hydrological variables for transient and stabilized climate states

Recent studies have assessed the impacts of climate change at specific global temperature targets using relatively short (30 year ) transient time-slice periods which are characterized by a steady increase in global mean temperature with time. The Inter-Sectoral Impacts Model Intercomparison Project Phase 2b (ISIMIP2b) provides trend-preserving bias-corrected climate model datasets over six centuries for four global climate models (GCMs) which therefore can be used to evaluate the potential effects of using time-slice periods from stabilized climate state rather than time-slice periods from transient climate state on climate change impacts. Using the H08 global hydrological model, the impacts of climate change, quantified as the deviation from the pre-industrial era, and the signal-to-noise (SN) ratios were computed for five hydrological variables, namely evapotranspiration (EVA), precipitation (PCP), snow water equivalent (SNW), surface temperature (TAR), and total discharge (TOQ) over 20 regions comprising the global land area. A significant difference in EVA for the transient and stabilized climate states was systematically detected for all four GCMs. In addition, three out of the four GCMs indicated that significant differences in PCP, TAR, and TOQ for the transient and stabilized climate states could also be detected over a small fraction of the globe. For most regions, the impacts of climate change toward EVA, PCP, and TOQ are indicated to be underestimated using the transient climate state simulations. The transient climate state was also identified to underestimate the SN ratios compared to the stabilized climate state. For both the global and regional scales, however, there was no indication that surface areas associated with the different classes of SN ratios changed depending on the two climate states (t-test, p > 0.01). Transient time slices may be considered a good approximation of the stabilized climate state, for large-scale hydrological studies and many regions and variables, as: (1) impacts of climate change were only significantly different from those of the stabilized climate state for a small fraction of the globe, and (2) these differences were not indicated to alter the robustness of the impacts of climate change

Balancing water resources conservation and food security in China

China’s economic growth is expected to continue into the next decades, accompanied by sustained urbanization and industrialization. The associated increase in demand for land, water resources, and rich foods will deepen the challenge of sustainably feeding the population and balancing agricultural and environmental policies. We combine a hydrologic model with an economic model to project China’s future food trade patterns and embedded water resources by 2030 and to analyze the effects of targeted irrigation reductions on this system, notably on national agricultural water consumption and food self-sufficiency. We simulate interprovincial and international food trade with a general equilibrium welfare model and a linear programming optimization, and we obtain province-level estimates of commodities’ virtual water content with a hydrologic model. We find that reducing irrigated land in regions highly dependent on scarce river flow and nonrenewable groundwater resources, such as Inner Mongolia and the greater Beijing area, can improve the efficiency of agriculture and trade regarding water resources. It can also avoid significant consumption of irrigation water across China (up to 14.8 km3/y, reduction by 14%), while incurring relatively small decreases in national food self-sufficiency (e.g., by 3% for wheat). Other researchers found that a national, rather than local, water policy would have similar effects on food production but would only reduce irrigation water consumption by 5%

The water footprint of staple crop trade under climate and policy scenarios

Trade in staple crop commodities has become increasingly important in the global food system, with ramifications for both food security and water resources sustainability. It is thus essential to understand how the water footprint (WF) of staple crop trade may change in the future. To this end, we project international staple crop trade and its WF under climate and policy scenarios for the year 2030. We use the H08 global hydrologic model to determine the impact of climatic changes to staple crop yields and evapotranspiration. Using the yield changes projected with the H08 model, we estimate the bilateral trade of staple crops using the Global Trade Analysis Project model. We combine these projections to obtain the total and blue WF of agricultural trade and global water savings (GWS) across scenarios. This approach enables us to determine the direct impact of climate change and trade liberalization—together and in isolation—on the WF of staple crop trade. Importantly, we show that trade liberalization leads to greater WF, making it a potentially important adaptation measure to a changing climate, although future work is needed to distinguish high resolution crop water use, water stress, and commodity transfers.Keywords: agricultural trade, climate change, virtual water, water footprint, trade policy, global water savings, adaptatio

Use of satellite remote sensing to validate reservoir operations in global hydrological models: a case study from the CONUS

Although river discharge simulations from global hydrological models have undergone extensive validation, there has been less validation of reservoir operations, primarily because of limited observational data. However, recent advancements in satellite remote sensing technology have facilitated the collection of valuable data regarding water surface area and elevation, thereby providing the ability to validate reservoir storage. In this study, we sought to establish a methodology for validation and intercomparison of reservoir storage within global hydrological model simulations using satellite-derived data. Accordingly, we chose two satellite-derived reservoir operation products, DAHITI and GRSAD, to create monthly time series storage data for seven reservoirs in the contiguous United States (CONUS) , with access to long-term ground truth data (the total catchment area accounts for about 9 % of CONUS). We assessed two global hydrological models that participated in the Inter Sectoral Model Intercomparison Project (ISIMIP) Phase 3 project, H08 and WaterGAP2, with three distinct forcing datasets: GSWP3-W5E5 (GW), CR20v3-W5E5 (CW), and CR20v3-ERA5 (CE). The results indicated that WaterGAP2 generally outperforms H08; the CW forcing dataset demonstrated superior results compared with GW and CE; the DAHITI showed better consistency with ground observations than GRSAD if temporal coverage is sufficient. Overall, our study emphasizes the potential uses of satellite remote sensing data in reservoir operations validation and underscores the importance of normalization and decomposition techniques for improved validation efficacy. The results highlight the relative performances of different hydrological models and forcing datasets, yielding insights concerning future advancements in reservoir simulation and operational studies

Reconstruction of global gridded monthly sectoral water withdrawals for 1971-2010 and analysis of their spatiotemporal patterns

Human water withdrawal has increasingly altered the global water cycle in past decades, yet our understanding of its driving forces and patterns is limited. Reported historical estimates of sectoral water withdrawals are often sparse and incomplete, mainly restricted to water withdrawal estimates available at annual and country scale, due to a lack of observations at local and seasonal time scales. In this study, through collecting and consolidating various sources of reported data and developing spatial and temporal statistical downscaling algorithms, we reconstruct a global monthly gridded (0.5 degree) sectoral water withdrawal dataset for the period 1971–2010, which distinguishes six water use sectors, i.e. irrigation, domestic, electricity generation (cooling of thermal power plants), livestock, mining, and manufacturing. Based on the reconstructed dataset, the spatial and temporal patterns of historical water withdrawal are analyzed. Results show that global total water withdrawal has increased significantly during 1971–2010, mainly driven by the increase of irrigation water withdrawal. Regions with high water withdrawal are those densely populated or with large irrigated cropland production, e.g., the United States (US), eastern China, India, and Europe. Seasonally, irrigation water withdrawal in summer for the major crops contributes a large percentage of annual total irrigation water withdrawal in mid and high-latitude regions, and the dominant season of irrigation water withdrawal is also different across regions. Domestic water withdrawal is mostly characterized by a summer peak, while water withdrawal for electricity generation has a winter peak in high-latitude regions and a summer peak in low-latitude regions. Despite the overall increasing trend, irrigation in the western US and domestic water withdrawal in western Europe exhibit a decreasing trend. Our results highlight the distinct spatial pattern of human water use by sectors at the seasonal and annual scales. The reconstructed gridded water withdrawal dataset is open-access, and can be used for examining issues related to water withdrawals at fine spatial, temporal and sectoral scales

Limited Role of Working Time Shift in Offsetting the Increasing Occupational‐Health Cost of Heat Exposure

Climate change increases workers\u27 exposure to heat stress. To prevent heat‐related illnesses, according to occupational‐health recommendations, labor capacity must be reduced. However, this preventive measure is expected to be costly, and the costs are likely to rise as the scale and scope of climate change impacts increase over time. Shifting the start of the working day to earlier in the morning could be an effective adaptation measure for avoiding the impacts of labor capacity reduction. However, the plausibility and efficacy of such an intervention have never been quantitatively assessed. Here we investigate whether working time shifts can offset the economic impacts of labor capacity reduction due to climate change. Incorporating a temporally (1 hr) and spatially (0.5° × 0.5°) high‐resolution heat exposure index into an integrated assessment model, we calculated the working time shift necessary to offset labor capacity reduction and economic loss under hypothetical with‐ and without‐realistic‐adaptation scenarios. The results of a normative scenario analysis indicated that a global average shift of 5.7 (4.0–6.1) hours is required, assuming extreme climate conditions in the 2090s. Although a realistic (<3 hr) shift nearly halves the economic cost, a substantial cost corresponding to 1.6% (1.0–2.4%) of global total gross domestic product is expected to remain. In contrast, if stringent climate‐change mitigation is achieved, a realistic shift limits the remaining cost to 0.14% (0.12–0.47%) of global total gross domestic product. Although shifting working time is shown to be effective as an adaptation measure, climate‐change mitigation remains indispensable to minimize the impact

Performance evaluation of global hydrological models in six large Pan-Arctic watersheds

Global Water Models (GWMs), which include Global Hydrological, Land Surface, and Dynamic Global Vegetation Models, present valuable tools for quantifying climate change impacts on hydrological processes in the data scarce high latitudes. Here we performed a systematic model performance evaluation in six major Pan-Arctic watersheds for different hydrological indicators (monthly and seasonal discharge, extremes, trends (or lack of), and snow water equivalent (SWE)) via a novel Aggregated Performance Index (API) that is based on commonly used statistical evaluation metrics. The machine learning Boruta feature selection algorithm was used to evaluate the explanatory power of the API attributes. Our results show that the majority of the nine GWMs included in the study exhibit considerable difficulties in realistically representing Pan-Arctic hydrological processes. Average APIdischarge (monthly and seasonal discharge) over nine GWMs is > 50% only in the Kolyma basin (55%), as low as 30% in the Yukon basin and averaged over all watersheds APIdischarge is 43%. WATERGAP2 and MATSIRO present the highest (APIdischarge > 55%) while ORCHIDEE and JULES-W1 the lowest (APIdischarge ≤ 25%) performing GWMs over all watersheds. For the high and low flows, average APIextreme is 35% and 26%, respectively, and over six GWMs APISWE is 57%. The Boruta algorithm suggests that using different observation-based climate data sets does not influence the total score of the APIs in all watersheds. Ultimately, only satisfactory to good performing GWMs that effectively represent cold-region hydrological processes (including snow-related processes, permafrost) should be included in multi-model climate change impact assessments in Pan-Arctic watersheds. © 2020, The Author(s)

Global water scarcity including surface water quality and expansions of clean water technologies

Water scarcity threatens people in various regions, and has predominantly been studied from a water quantity perspective only. Here we show that global water scarcity is driven by both water quantity and water quality issues, and quantify expansions in clean water technologies (i.e. desalination and treated wastewater reuse) to ‘reduce the number of people suffering from water scarcity’ as urgently required by UN’s Sustainable Development Goal 6. Including water quality (i.e. water temperature, salinity, organic pollution and nutrients) contributes to an increase in percentage of world’s population currently suffering from severe water scarcity from an annual average of 30% (22%–35% monthly range; water quantity only) to 40% (31%–46%; both water quantity and quality). Water quality impacts are in particular high in severe water scarcity regions, such as in eastern China and India. In these regions, excessive sectoral water withdrawals do not only contribute to water scarcity from a water quantity perspective, but polluted return flows degrade water quality, exacerbating water scarcity. We show that expanding desalination (from 2.9 to 13.6 billion m3 month−1) and treated wastewater uses (from 1.6 to 4.0 billion m3 month−1) can strongly reduce water scarcity levels and the number of people affected, especially in Asia, although the side effects (e.g. brine, energy demand, economic costs) must be considered. The presented results have potential for follow-up integrated analyses accounting for technical and economic constraints of expanding desalination and treated wastewater reuse across the world