83 shared publications
Department of Geographical Sciences, University of Maryland
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(2010 - 2018)
(2010 - 2018)
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Article 0 Reads 0 Citations Densified multi-mission observations by developed optical water levels show marked increases in lake water storage and o... Published: 15 March 2019
Earth System Science Data Discussions, doi: 10.5194/essd-2019-34
The Tibetan Plateau (TP) known as Asia's water towers is quite sensitive to climate change, reflected by changes in hydrological state variables such as lake water storage. Given the extremely limited ground observations on the TP due to the harsh environment and complex terrain, we exploited multisource remote sensing, i.e., multiple altimetric missions and Landsat archives to create dense time series (monthly and even higher such as 10 days on average) of lake water level and storage changes across 52 large lakes (> 100 km2) on the TP during 2000–2017 (the data set is available online with a DOI: https://doi.org/10.1594/PANGAEA.898411). Field experiments were carried out in two typical lakes to validate the remotely sensed results. With Landsat archives and partial altimetry data, we developed optical water levels that cover most of TP lakes and serve as an ideal reference for merging multisource lake water levels. The optical water levels show an uncertainty of ~ 0.1 m that is comparable with most altimetry data and largely reduce the lack of dense altimetric observations with systematic errors well removed for most of lakes. The densified lake water levels provided critical and accurate information on the long-term and short-term monitoring of lake water level and storage changes on the TP. We found that the total storage of the 52 lakes increased by 97.3 km3 at two stages, i.e., 6.68 km3/yr during 2000–2012 and 2.85 km3/yr during 2012–2017. The total overflow from Lake Kusai to Lake Haidingnuoer and Lake Salt during Nov 9–Dec 31 in 2011 was estimated to be 0.22 km3, providing critical information on lake overflow flood monitoring and prediction as the expansion of some TP lakes becomes a serious threat to surrounding residents and infrastructure.
Article 0 Reads 0 Citations High-resolution global water temperature modelling Published: 12 March 2019
Water Resources Research, doi: 10.1029/2018wr023250
Article 0 Reads 0 Citations Multimodel assessments of human and climate impacts on mean annual streamflow in China Published: 06 March 2019
Hydrology and Earth System Sciences, doi: 10.5194/hess-23-1245-2019
Human activities, as well as climate variability, have had increasing impacts on natural hydrological systems, particularly streamflow. However, quantitative assessments of these impacts are lacking on large scales. In this study, we use the simulations from six global hydrological models driven by three meteorological forcings to investigate direct human impact (DHI) and climate impact on streamflow in China. Results show that, in the sub-periods of 1971–1990 and 1991–2010, one-fifth to one-third of mean annual streamflow (MAF) was reduced due to DHI in northern basins, and much smaller (<4 %) MAF was reduced in southern basins. From 1971–1990 to 1991–2010, total MAF changes range from −13 % to 10 % across basins wherein the relative contributions of DHI change and climate variability show distinct spatial patterns. DHI change caused decreases in MAF in 70 % of river segments, but climate variability dominated the total MAF changes in 88 % of river segments of China. In most northern basins, climate variability results in changes of −9 % to 18 % in MAF, while DHI change results in decreases of 2 % to 8 % in MAF. In contrast with the climate variability that may increase or decrease streamflow, DHI change almost always contributes to decreases in MAF over time, with water withdrawals supposedly being the major impact on streamflow. This quantitative assessment can be a reference for attribution of streamflow changes at large scales, despite remaining uncertainty. We highlight the significant DHI in northern basins and the necessity to modulate DHI through improved water management towards a better adaptation to future climate change.
Article 0 Reads 0 Citations State-of-the-art global models underestimate impacts from climate extremes Published: 01 March 2019
Nature Communications, doi: 10.1038/s41467-019-08745-6
Global impact models represent process-level understanding of how natural and human systems may be affected by climate change. Their projections are used in integrated assessments of climate change. Here we test, for the first time, systematically across many important systems, how well such impact models capture the impacts of extreme climate conditions. Using the 2003 European heat wave and drought as a historical analogue for comparable events in the future, we find that a majority of models underestimate the extremeness of impacts in important sectors such as agriculture, terrestrial ecosystems, and heat-related human mortality, while impacts on water resources and hydropower are overestimated in some river basins; and the spread across models is often large. This has important implications for economic assessments of climate change impacts that rely on these models. It also means that societal risks from future extreme events may be greater than previously thought.
Article 0 Reads 0 Citations Publisher Correction: Recent global decline in endorheic basin water storages Published: 05 February 2019
Nature Geoscience, doi: 10.1038/s41561-019-0316-8
Article 0 Reads 0 Citations Balancing clean water-climate change mitigation trade-offs Published: 11 January 2019
Environmental Research Letters, doi: 10.1088/1748-9326/aaf2a3
Energy systems support technical solutions fulfilling the United Nations' Sustainable Development Goal for clean water and sanitation (SDG6), with implications for future energy demands and greenhouse gas emissions. The energy sector is also a large consumer of water, making water efficiency targets ingrained in SDG6 important constraints for long-term energy planning. Here, we apply a global integrated assessment model to quantify the cost and characteristics of infrastructure pathways balancing SDG6 targets for water access, scarcity, treatment and efficiency with long-term energy transformations limiting climate warming to 1.5 °C. Under a mid-range human development scenario, we find that approximately 1 trillion USD2010 per year is required to close water infrastructure gaps and operate water systems consistent with achieving SDG6 goals by 2030. Adding a 1.5 °C climate policy constraint increases these costs by up to 8 %. In the reverse direction, when the SDG6 targets are added on top of the 1.5 °C policy constraint, the cost to transform and operate energy systems increases 2 to 9 % relative to a baseline 1.5 °C scenario that does not achieve the SDG6 targets by 2030. Cost increases in the SDG6 pathways are due to expanded use of energy-intensive water treatment and costs associated with water conservation measures in power generation, municipal, manufacturing and agricultural sectors. Combined global spending (capital and operational expenditures) in the integrated SDG6-1.5 °C scenarios to 2030 on water and energy systems increases 92 to 125 % relative to a baseline scenario without 1.5 °C and SDG6 constraints. Evaluation of the multi-sectoral policies underscores the importance of water conservation and integrated water-energy planning for avoiding costs from interacting water, energy and climate goals