Operation of two major reservoirs of Iran under IPCC scenarios during the XXI century

We assess the effects of prospective climate change until 2100 on water management of two major reservoirs of Iran, namely, Dez (3.34 × 10⁹ m³) and Alavian (6 × 10⁷ m³). We tune the Poly‐Hydro model suited for simulation of hydrological cycle in high altitude snow‐fed catchments. We assess optimal operation rules (ORs) for the reservoirs using three algorithms under dynamic and static operation and linear and non‐linear decision rules during control run (1990–2010 for Dez and 2000–2010 for Alavian). We use projected climate scenarios (plus statistical downscaling) from three general circulation models, EC‐Earth, CCSM4, and ECHAM6, and three emission scenarios, or representative concentration pathways (RCPs), RCP2.6, RCP4.5, and RCP8.5, for a grand total of nine scenarios, to mimic evolution of the hydrological cycle under future climate until 2100. We subsequently test the ORs under the future hydrological scenarios (at half century and end of century) and the need for reoptimization. Poly‐Hydro model when benchmarked against historical data well mimics the hydrological budget of both catchments, including the main processes of evapotranspiration and streamflows. Teaching–learning‐based optimization delivers the best performance in both reservoirs according to objective scores and is used for future operation. Our projections in Dez catchment depict decreased precipitation along the XXI century, with ?1% on average (of the nine scenarios) at half century and ?6% at the end of century, with changes in streamflows on average ?7% yearly and ?13% yearly, respectively. In Alavian, precipitation would decrease by ?10% on average at half century and ?13% at the end of century, with streamflows ?14% yearly and ?18% yearly, respectively. Under the projected future hydrology, reservoirs' operation would provide lower performance (i.e., larger lack of water) than now, especially for Alavian dam. Our results provide evidence of potentially decreasing water availability and less effective water management in water stressed areas like Northern Iran here during this century.     

Carbon cycling of alpine tundra ecosystems on Changbai Mountain and its comparison with arctic tundra

The alpine tundra on Changbai Mountain was formed as a left-over ‘island’ in higher elevations after the glacier retrieved from the mid-latitude of Northern Hemisphere to the Arctic during the fourth ice age. The alpine tundra on Changbai Mountain also represents the best-reserved tundra ecosystems and the highest biodiversity in northeast Eurasia. This paper examines the quantity of carbon assimilation, litters, respiration rate of soil, and storage of organic carbon within the alpine tundra ecosystems on Changbai Mountain. The annual net storage of organic carbon was 2092 t/a, the total storage of organic carbon was 33457 t, the annual net storage of organic carbon in soil was 1054 t/a, the total organic carbon storage was 316203 t, and the annual respiration rate of soil was 92.9% and was 0.52 times more than that of the Arctic. The tundra-soil ecosystems in alpine Changbai Mountain had 456081 t of carbon storage, of which, organic carbon accounted for 76.7% whereas the mineral carbon accounted for 23.3%.     

The stereoscopic spatial connectivity of wetland ecosystems: Evaluation method and regulation measures

Currently, the weakened connectivity of wetland ecosystems is the most important factor leading to the destruction, degradation, and disappearance of wetlands. Studying changes in wetland ecosystems connectivity enables the understanding the hydrological processes in wetland ecosystems and provides significant support for the study of ecological water demand. However, recent research on the connectivity of wetland ecosystems has primarily focused on intuitive Heilongjiang River Basin in China (HRBC) connectivity in terms of hydrology and geomorphology, while the impact of wetland ecosystems on habitats has been ignored. The present study applied an innovative method to evaluate and regulate the stereoscopic spatial connectivity (SSC) of the wetland ecosystems in the HRBC. In this method, the water requirements of typical organisms in the region were considered, and the hydrological trends in the wetland ecosystems along with the status of the SSC were analysed using remote sensing images. A regulation mode for improving the stereoscopic spatial connectivity index (SSCI) was proposed. The results revealed that over the past 35 years, the wetland ecosystems in the study area shrank significantly, with the SSCI decreasing from 41.30% in 1980 to 35.08% in 2015. By comparing the correlations among temperature, precipitation, agricultural land, construction land, and the wetland ecosystems during the same period, it was proven that human activity serves as the major driving force behind the observed loss of wetlands in the system. Subsequently, the key protected areas needing protection to maintain the SSC of the wetland ecosystems were clarified, and the key recovery areas were determined based on three scenarios featuring high, medium, and low feasibility, which greatly improved the SSCI and generalization route after regulation. In general, the proposed SSC evaluation and regulation method is widely applicable to all kinds of wetland ecosystems located on animal habitat and migration routes, which can fully reflect the ecological effects of wetland ecosystems, and this method has certain reference significance for the evaluation and regulation of wetland ecosystems in other regions.     

Assessment of the impact of climate change on flow regime at multiple temporal scales and potential ecological implications in an alpine river

The source region of Yellow river is an alpine river sensitive to climate changes, but the potential effects of climate change on hydrological regime characteristics and ecological implications are less understood. This study aims to assess the response of the alterations in the flow regimes over the source region of Yellow river to climate change using Soil and Water Integrated Model driven by different Global Circulation Models (GFDL-ESM2M, IPSL-CM5A-LR and MIROC-ESM-CHEM) under three Representative Concentration Pathway emission scenarios (RCP2.6, RCP4.5 and RCP8.5). Indicators of hydrological alteration and River impact index are employed to evaluate streamflow regime alterations at multiple temporal scales. Results show that the magnitude of monthly and annual streamflow except May, the magnitude and duration of the annual extreme, and the number of reversals are projected to increase in the near future period (2020–2049) and far future period (2070–2099) compared to the baseline period (1971–2000). The timing of annual maximum flows is expected to shift backwards. The source region of Yellow river is expected to undergo low change degree as per the scenarios RCP2.6 for both two future periods and under the scenarios RCP4.5 for the near future period, whereas high change degree under RCP4.5 and RCP8.5 in the far period on the daily scale. On the monthly scale, climate changes mainly have effects on river flow magnitude and timing. The basin would suffer an incipient impact alteration in the far period under RCP4.5 and RCP8.5, while low impact in other scenarios. These changes in flow regimes could have several positive impacts on aquatic ecosystems in the near period but more detrimental effects in the far period.

     

基于CMIP5模式鄱阳湖流域未来参考作物蒸散量预估

预测未来气候情境下鄱阳湖流域参考作物蒸散量(Reference crop Evapotranspiration,ET0)的时空分布可为流域水资源的优化管理,为科学应对气候变化对农业生产的影响提供基础数据支撑.利用鄱阳湖流域14个气象站点1961-2014年逐日气象数据,采用Penman-Monteith公式计算出历史ET0;基于同期美国环境中心(NCEP)再分析数据及2006-2100年CMIP5中CNRM-CM5模式在RCP4. 5和RCP8. 5情景下的预测数据,经统计降尺度模型(statistical downscaling model,SDSM)模拟和偏差校正,预测流域未来ET0;通过Mann-Kendall检验、普通克里金插值和空间自相关法分析了流域1961-2100年ET0的时空演变特征.结果表明:NCEP再分析资料与流域ET0建立的逐步回归降尺度模型模拟效果较好,CNRMCM5模式降尺度模拟结果经偏差校正后,精度明显提高,适宜流域未来ET0的预估.鄱阳湖流域在基准期1961-2010年ET0整体上呈减小趋势,空间分布上呈南北高、中间低的特点,表现出明显的空间差异性.RCP4.5、RCP8.5情景下未来3个时期鄱阳湖流域ET0较基准期均呈不同程度的增加趋势,其空间分布整体表现为东高西低、局地略有突出;无论是在基准期或是未来情景下的3个时期,ET0均具有较强的空间自相关性.在RCP8.5情景下,鄱阳湖1961-2100年干旱指数呈现出较为明显的上升趋势,流域的干旱状况随时间加剧,2011-2100年间流域绝大部分地区由湿润区转为半湿润区,干旱指数自南向北递减,赣江流域将是鄱阳湖流域未来干旱风险的重点防范区.     

The impacts of climate extremes on the terrestrial carbon cycle:A review

The increased frequency of climate extremes in recent years has profoundly affected terrestrial ecosystem functions and the welfare of human society. The carbon cycle is a key process of terrestrial ecosystem changes. Therefore, a better understanding and assessment of the impacts of climate extremes on the terrestrial carbon cycle could provide an important scientific basis to facilitate the mitigation and adaption of our society to climate change. In this paper, we systematically review the impacts of climate extremes(e.g. drought, extreme precipitation, extreme hot and extreme cold) on terrestrial ecosystems and their mechanisms. Existing studies have suggested that drought is one of the most important stressors on the terrestrial carbon sink, and that it can inhibit both ecosystem productivity and respiration. Because ecosystem productivity is usually more sensitive to drought than respiration, drought can significantly reduce the strength of terrestrial ecosystem carbon sinks and even turn them into carbon sources. Large inter-model variations have been found in the simulations of drought-induced changes in the carbon cycle, suggesting the existence of a large gap in current understanding of the mechanisms behind the responses of ecosystem carbon balance to drought, especially for tropical vegetation. The effects of extreme precipitation on the carbon cycle vary across different regions. In general, extreme precipitation enhances carbon accumulation in arid ecosystems, but restrains carbon sequestration in moist ecosystems. However, current knowledge on the indirect effects of extreme precipitation on the carbon cycle through regulating processes such as soil carbon lateral transportation and nutrient loss is still limited. This knowledge gap has caused large uncertainties in assessing the total carbon cycle impact of extreme precipitation. Extreme hot and extreme cold can affect the terrestrial carbon cycle through various ecosystem processes. Note that the severity of such climate extremes depends greatly on their timing, which needs to be investigated thoroughly in future studies. In light of current knowledge and gaps in the understanding of how extreme climates affect the terrestrial carbon cycle, we strongly recommend that future studies should place more attention on the long-term impacts and on the driving mechanisms at different time scales.Studies based on multi-source data, methods and across multiple spatial-temporal scales, are also necessary to better characterize the response of terrestrial ecosystems to climate extremes.     

Shortening the recurrence periods of extreme water levels under future sea-level rise

Sea-level rise, as a result of global warming, may lead to more natural disasters in coastal regions where there are substantial aggregations of population and property. Thus, this paper focuses on the impact of sea-level rise on the recurrence periods of extreme water levels fitted using the Pearson type III (P-III) model. Current extreme water levels are calculated using observational data, including astronomical high tides and storm surges, while future extreme water levels are determined by superposing scenario data of sea-level rise onto current extreme water levels. On the basis of a case study using data from Shandong Province, China, results indicated that sea-level rise would significantly shorten the recurrence periods of extreme water levels, especially under higher representative concentration pathway (RCP) scenarios. Results showed that by the middle of the century, 100-year current extreme water levels for all stations would translate into once in 15–30 years under RCP 2.6, and once in ten to 25 years under RCP 8.5. Most seriously, the currently low probability event of a 1000-year recurrence would become common, occurring nearly every 10 years by 2100, based on projections under RCP 8.5. Therefore, according to this study, corresponding risk to coastlines could well be increase in future, as the recurrence periods of extreme water levels would be shortened with climate change.     

Projected streamflow in the Huaihe River Basin (2010–2100) using artificial neural network

Climate projections for the Huaihe River Basin, China, for the years 2001–2100 are derived from the ECHAM5/MPI-OM model based on observed precipitation and temperature data covering 1964–2007. Streamflow for the Huaihe River under three emission scenarios (SRES-A2, A1B, B1) from 2010 to 2100 is then projected by applying artificial neural networks (ANN). The results show that annual streamflow will change significantly under the three scenarios from 2010 to 2100. The interannual fluctuations cover a significant increasing streamflow trend under the SRES-A2 scenario (2051–2085). The streamflow trend declines gradually under the SRES-A1B scenario (2024–2037), and shows no obvious trend under the SRES-B1 scenario. From 2010 to 2100, the correlation coefficient between the observed and modeled streamflow in SRES-A2 scenario is the best of the three scenarios. Combining SRES-A2 scenario of the ECHAM5 model and ANN might therefore be the best approach for assessing and projecting future water resources in the Huaihe basin and other catchments. Compared to the observed period of streamflows, the projected periodicity of streamflows shows significant changes under different emission scenarios. Under A2 scenario and A1B scenario, the period would delay to about 32–33a and 27–28a, respectively, but under B1 scenario, the period would not change, as it is about 5–6a and the observed period is about 7–8a. All this might affect drought/flood management, water supply and irrigation projects in the Huaihe River basin.     

Uncertainty assessment in river flow projections for Ethiopia’s Upper Awash Basin using multiple GCMs and hydrological models

ABSTRACT

Uncertainty in climate change impacts on river discharge in the Upper Awash Basin, Ethiopia, is assessed using five MIKE SHE hydrological models, six CMIP5 general circulation models (GCMs) and two representative concentration pathways (RCP) scenarios for the period 2071–2100. Hydrological models vary in their spatial distribution and process representations of unsaturated and saturated zones. Very good performance is achieved for 1975–1999 (NSE: 0.65–0.8; r: 0.79–0.93). GCM-related uncertainty dominates variability in projections of high and mean discharges (mean: –34% to +55% for RCP4.5, – 2% to +195% for RCP8.5). Although GCMs dominate uncertainty in projected low flows, inter-hydrological model uncertainty is considerable (RCP4.5: –60% to +228%, RCP8.5: –86% to +337%). Analysis of variance uncertainty attribution reveals that GCM-related uncertainty occupies, on average, 68% of total uncertainty for median and high flows and hydrological models no more than 1%. For low flows, hydrological model uncertainty occupies, on average, 18% of total uncertainty; GCM-related uncertainty remains substantial (average: 28%).     

Projected glacier meltwater and river run‐off changes in the Upper Reach of the Shule River Basin,north‐eastern edge of the Tibetan Plateau

Glacier meltwater change in the north‐eastern edge of the Tibetan Plateau is greatly important for the projection of the impact of future climate change on local water resource management. Although the glaciated area is only approximately 4% of the Upper Reach of the Shule River Basin (URSRB), the average glacier meltwater contribution to river run‐off was approximately 23.6% during the periods 1971/1972 to 2012/2013. A new glacier melting module coupled with the macroscale hydrologic Variable Infiltration Capacity model (VIC‐CAS) was adopted to simulate and project changes in the glacier meltwater and river run‐off of the URSRB forced by downscaled output of the BCC‐CSM1.1(m), CANESM2, GFDL‐CM3, and IPSL‐CM5A‐MR models. Comparisons between the observed and simulated river run‐offs and glacier area changes during the periods 2000/2001, 2004/2006, 2008/2009, and 2012/2013 suggest that the simulation is reasonable. Due to increases in precipitation, the annual total run‐off is projected to increase by approximately 2.58–2.73 × 10⁸ m³ in the 2050s and 0.28–1.87 × 10⁸ m³ in the 2100s compared with run‐off in the 2010s based on the RCP2.6 (low greenhouse gas emission) and RCP4.5 (moderate greenhouse gas emission) scenarios, respectively. The contribution of glacier meltwater to river run‐off will more likely decrease to approximately 10% and less than 5% during the 2050s and 2100s, respectively.     

Potentially modified hydropower production under climate change in the Italian Alps

We present an assessment of the potential impacts of climate change on hydropower production within a paradigmatic, very highly exploited cryospheric area of upper Valtellina valley in the Italian Alps. Based on dependable and unique hydrological measures from our high‐altitude hydrometric network Idrostelvio during 2006–2015, we set up the Poly‐Hydro model to mimic the cryospheric processes driving hydrological flow formation in this high‐altitude area. We then set up an optimization tool, which we call Poly‐Power, to maximize the revenue of the plant manager under given hydrological regimes, namely, by proper operation of the hydroelectric production scheme (reservoirs, pipelines, and power plants) of the area. We then pursue hydrological projections until 2100, feeding Poly‐Hydro with the downscaled outputs of three general circulation models from the Intergovernmental Panel on Climate Change Fifth Assessment Report, under the scenarios Representative Concentration Pathway (RCP) 2.6, RCP 4.5, and RCP 8.5. We assess hydrological flows in two reference decades, that is, at half century (2040–2049), and end of century (2090–2099). We then feed the so obtained hydrological scenarios as inputs to Poly‐Power, and we project future production of hydroelectric power, with and without reoperation of the system. The average annual stream flows for hydropower production decreases along the century under our scenarios (?21 to +7%, on average ? 5% at half century; ?17 to ?2%, average ? 8%, end of century), with ice cover melting unable to offset such decrease. Reduction in snowfall and increase in liquid rainfall are the main factors affecting the modified hydrological regime. Energy production (and revenues) at half century may increase under our scenarios (?9 to +15%, +3% on average). At the end of century in spite of a projected increase on average (?7 to +6%, +1% on average), under the warmest scenario RCP 8.5 decrease of energy production is consistently projected (?4% on average). Our results provide an array of potential scenarios of modified hydropower production under future climate change and may be used for brain storming of adaptation strategies.     

Assess hydrological responses to a warming climate at the Lysina Critical Zone Observatory in Central Europe

Climate warming is having profound effects on the hydrological cycle by increasing atmospheric demand, changing water availability, and snow seasonality. Europe suffered three distinct heat waves in 2019, and 11 of the 12 hottest years ever recorded took place in the past two decades, which will potentially change seasonal streamflow patterns and long-term trends. Central Europe exhibited six dry years in a row since 2014. This study uses data from a well-documented headwater catchment in Central Europe (Lysina) to explore hydrological responses to a warming climate. We applied a lumped parameter hydrologic model Brook90 and a distributed model Penn State Integrated Hydrologic Model (PIHM) to simulate long-term hydrological change under future climate scenarios. Both models performed well on historic streamflow and in agreement with each other according to the catchment water budget. In addition, PIHM was able to simulate lateral groundwater redistribution within the catchment validated by the groundwater table dynamics. The long-term trends in runoff and low flow were captured by PIHM only. We applied different EURO-CORDEX models with two emission scenarios (Representative Concentration Pathways RCP 4.5, 8.5) and found significant impacts on runoff and evapotranspiration (ET) for the period of 2071–2100. Results from both models suggested reduced runoff and increased ET, while the monthly distribution of runoff was different. We used this catchment study to understand the importance of subsurface processes in projection of hydrologic response to a warming climate.     

Detection of trends in hydrological extremes for Canadian watersheds

The potential impacts of climate change can alter the risk to critical infrastructure resulting from changes to the frequency and magnitude of extreme events. As well, the natural environment is affected by the hydrologic regime, and changes in high flows or low flows can have negative impacts on ecosystems. This article examines the detection of trends in extreme hydrological events, both high and low flow events, for streamflow gauging stations in Canada. The trend analysis involves the application of the Mann–Kendall non‐parametric test. A bootstrap resampling process has been used to determine the field significance of the trend results. A total of 68 gauging stations having a nominal record length of at least 50 years are analysed for two analysis periods of 50 and 40 years. The database of Canadian rivers investigated represents a diversity of hydrological conditions encompassing different extreme flow generating processes and reflects a national scale analysis of trends. The results reveal more trends than would be expected to occur by chance for most of the measures of extreme flow characteristics. Annual and spring maximum flows show decreasing trends in flow magnitude and decreasing trends in event timing (earlier events). Low flow magnitudes exhibit both decreasing and increasing trends. Copyright © 2010 John Wiley & Sons, Ltd.     

Hydrologic response to future land use change in the Upper Mississippi River Basin by the end of 21st century

This study demonstrates the spatial variation in hydrologic processes across the Upper Mississippi River Basin (UMRB) by the end of 21st century, by ingesting FOREcasting Scenarios (FORE‐SCE) of Land‐use Change projections into a physics‐based hydrologic model—Soil and Water Assessment Tool. The model is created for UMRB (440,000 km²), using the National Landcover Database of year 2001 and climate data of 1991–2010. Considering 1991–2010 as the baseline reference period, FORE‐SCE projections of year 2091 under three scenarios (A1B, A2, and B1 from the Intergovernmental Panel on Climate Change) are separately assimilated into the calibrated model, whereas climate input is kept the same as in the baseline. Modeling results suggest an increase of 0.5% and 3.5% in the average annual streamflow at the basin outlet (Grafton, Illinois) during 2081–2100, respectively, for A1B and A2, whereas for B1, streamflow would decrease by 1.5%. Under the “worst case” A2 scenario, 6% and 133% increase, respectively, in agricultural and urban areas with 30% depletion of forest and grassland would result into 70% increase in surface runoff, 20% decrease in soil moisture, and 4% decrease in evapotranspiration in certain parts of the basin. Conversion of cropland, forest, or grassland to perennial hay/pasture areas would lower surface runoff by 25% especially in the central region, whereas persistent forest cover in the northern region would cause up to 7% increase in evapotranspiration. The ecosystem in the lower half of UMRB is likely to become adverse, as dictated by a composite water–energy balance indicator. Future land use change extents and resultant hydrologic responses are found significantly different under A2, A1B, and B1 scenarios, which resonates the need for multi‐scenario ensemble assessments towards characterizing a probable future. The spatial variation of hydrologic processes as shown here helps to identify potential “hot spots,” giving ways to adopt more effective policy alternatives at regional level.     

Investigating Impacts of Climate Change on Irrigation Water Demands and Its Resulting Consequences on Groundwater Using CMIP5 Models

In this study, the impacts of climate change on crop water requirements and irrigation water requirements on the regional cropping pattern were evaluated using two climate change scenarios and combinations of 20 GCM models. Different models including CROPWAT, MODFLOW, and statistical models were used to evaluate the climate change impacts. The results showed that in the future period (2017 to 2046) the temperature in all months of the year will increase at all stations. The average annual precipitation decline in Isfahan, Tiran, Flavarjan, and Lenj stations for RCP 4.5 and RCP 8.5 scenarios are 18.6 and 27.6%, 15.2 and 18%, 22.5 and 31.5%, and 10.5 and 12.1%, respectively. The average increase in the evapotranspiration for RCP 4.5 and RCP 8.5 scenarios are about 2.5 and 4.1%, respectively. The irrigation water demands increases considerably and for some crops, on average 18%. Among the existing crops in the cropping pattern, barley, cumin, onion, wheat, and forage crops are more sensitive and their water demand will increase significantly. Results indicate that climate change could have a significant impact on water resources consumption. By considering irrigation efficiency in the region, climate change impacts will result in about 35 to 50 million m³/year, over-extraction from the aquifer. This additional exploitation causes an extra drop of 0.4 to 0.8 m in groundwater table per year in the aquifer. Therefore, with regard to the critical condition of the aquifer, management and preventive measures to deal with climate change in the future is absolutely necessary.     

Multi-scale observation and cross-scale mechanistic modeling on terrestrial ecosystem carbon cycle

To predict global climate change and to implement the Kyoto Protocol for stabilizing atmospheric greenhouse gases concentrations require quantifying spatio-temporal variations in the terrestrial carbon sink accurately. During the past decade multi-scale ecological experiment and observation networks have been established using various new technologies (e.g. controlled environmental facilities, eddy covariance techniques and quantitative remote sensing), and have obtained a large amount of data about terrestrial ecosystem carbon cycle. However, uncertainties in the magnitude and spatio-temporal variations of the terrestrial carbon sink and in understanding the underlying mechanisms have not been reduced significantly. One of the major reasons is that the observations and experiments were conducted at individual scales independently, but it is the interactions of factors and processes at different scales that determine the dynamics of the terrestrial carbon sink. Since experiments and observations are always conducted at specific scales, to understand cross-scale interactions requires mechanistic analysis that is best to be achieved by mechanistic modeling. However, mechanistic ecosystem models are mainly based on data from single-scale experiments and observations and hence have no capacity to simulate mechanistic cross-scale interconnection and interactions of ecosystem processes. New-generation mechanistic ecosystem models based on new ecological theoretical framework are needed to quantify the mechanisms from micro-level fast eco-physiological responses to macro-level slow acclimation in the pattern and structure in disturbed ecosystems. Multi-scale data-model fusion is a recently emerging approach to assimilate multi-scale observational data into mechanistic, dynamic modeling, in which the structure and parameters of mechanistic models for simulating cross-scale interactions are optimized using multi-scale observational data. The models are validated and evaluated at different spatial and temporal scales and real-time observational data are assimilated continuously into dynamic modeling for predicting and forecasting ecosystem changes realistically. in summary, a breakthrough in terrestrial carbon sink research requires using approaches of multi-scale observations and cross-scale modeling to understand and quantify interconnections and interactions among ecosystem processes at different scales and their controls over ecosystem carbon cycle.     

水生态评价方法研究进展及展望

水生态系统是人类赖以生存的基础,近年来气候变化和水资源开发、水体污染、过度捕捞等人类活动导致水生态系统严重受损,水生态系统的保护和修复已成为全球面临的重大挑战。科学合理的水生态评价方法是实现水生态系统稳定、健康和可持续管理的基本保障,也是目前我国各相关管理部门高度重视的关键问题,多个部门围绕水生态评价展开了积极探索与实践。本文系统回顾了水生态评价方法的发展历程并阐释了水生态评价的内涵,梳理了常用的水生态评价方法,明晰了各方法的基本理念和应用场景,分析了各方法的优点和不足,提出了基于生态完整性的水生态健康评价方法,最后对目前我国水生态评价需进一步完善的工作进行了展望。本文以期与相关领域研究者和管理者在水生态评价理论和方法方面进行探讨,为我国水生态考核工作提供理论支持。     

Rapid Expansion of Melica przewalskyi Causes Soil Moisture Deficit and Vegetation Degradation in Subalpine Meadows

Invasive noxious plants have important impacts on community dynamics and ecosystem functions in grasslands. Since the 1960s, the noxious plant Melica przewalskyi has spread rapidly and formed different size of patches in subalpine meadows of the Qilian Mountains, Northwest China. In this study, the species richness, vegetation structure, and soil water content are investigated from the patch edge to the center in four sizes of M. przewalskyi patches (i.e., small patch, <100 cm in canopy diameter; middle patch, 100–200 cm; large patch, 200–300 cm; and the largest patch, >300 cm). The results show that while the patches grow continuously, the dominant species changes from Stipa krylovii to M. przewalskyi with an increasing trend in plant productivity and decreasing trend in species richness and soil water content. Plant height, density, coverage, and above‐ground biomass of M. przewalskyi population increases from the patch edge to the center in small, middle, and large patches, whereas it is precisely the opposite in the largest patch. Interestingly, soil water content exhibits a decreasing trend from the patch edge to the center in all patches. The results indicate that the rapid spread of M. przewalskyi may well alter vegetation pattern and cause a severe soil moisture deficit, which would further drive the degradation of ecosystem functioning in subalpine meadows.     

Advances in carbon flux observation and research in Asia

As an important component of FLUXNET, Asia is increasingly becoming the hotspot in global carbon research for its vast territory, complex climate type and vegetation diversity. The present three regional flux observation networks in Asia (i.e. AsiaFlux, KoFlux and ChinaFLUX)have 54 flux observation sites altogether, covering tropic rainforest, evergreen broad-leaved forest, broad-leaved and coniferous mixed forest, shrubland, grassland, alpine meadow and cropland ecosystems with a latitudinal distribution from 2°N to 63°N. Long-term and continuous fluxes of carbon dioxide, water vapor and energy between the biosphere and atmosphere are mainly measured with eddy covariance technique to (1) quantify and compare the carbon, water and energy budgets across diverse ecosystems; (2) quantify the environmental and biotic controlling mechanism on ecosystem carbon, water and energy fluxes; (3) validate the soil-vegetation-atmosphere model; and (4) serve the integrated study of terrestrial ecosystem carbon and water cycle. Over the last decades, great advancements have been made in the theory and technology of flux measurement, ecosystem flux patterns, simulation and scale conversion by Asian flux community. The establishment of ChinaFLUX has greatly filled the gap of flux observation and research in Eurasia. To further promote the flux measurement and research,accelerate data sharing and improve the data quality, it is necessary to present a methodological system of flux estimation and evaluation over complex terrain and to develop the integrated research that combines the flux measurement, stable isotope measurement, remote sensing observation and GIS technique. It also requires the establishment of the Joint Committee of Asian Flux Network in the Asia-Pacific region in order to promote the cooperation and communication of ideas and data by supporting project scientists, workshops and visiting scientists.     

Projection of future rainfall for the North China Plain using two statistical downscaling models and its hydrological implications

This study projected the future rainfall (2046–2065 and 2081–2100) for the North China Plain (NCP) using two stochastic statistical downscaling models, the non-homogeneous hidden Markov model and the generalized linear model for daily climate time series, conditioned by the large-scale atmospheric predictors from six general circulation models for three emission scenarios (A1B, A2 and B1). The results indicated that the annual total rainfall, the extreme daily rainfall and the maximum length of consecutive wet/dry days would decline, while the number of annual rainfall days would slightly increase (correspondingly rainfall intensity would decrease) in the NCP, in comparison with the base period (1961–2010). Moreover, the summer monsoon rainfall, which accounted for 50–75 % of the total annual rainfalls in NCP, was projected to decrease in the latter half of twenty-first century. The spatial patterns of change showed generally north–south gradients with relatively larger magnitude decrease in the northern NCP and less decrease (or even slightly increase) in the southern NCP. This could result in decline of the annual runoff by ?5.5 % (A1B), ?3.3 % (A2) and ?4.1 % (B1) for 2046–2065 and ?5.3 % (A1B), ?4.6 % (A2) and ?1.9 % (B1) decrease for 2081–2100. These rainfall changes, combined with the warming temperature, could lead to drier catchment soil profiles and further reduce runoff potential, would hence provide valuable references for the water availability and related climate change adaption in the NCP.