Anthropogenic depletion of Iran's aquifers.

Global groundwater assessments rank Iran among countries with the highest groundwater depletion rate using coarse spatial scales that hinder detection of regional imbalances between renewable groundwater supply and human withdrawals. Herein, we use in situ data from 12,230 piezometers, 14,856 observation wells, and groundwater extraction points to provide ground-based evidence about Iran's widespread groundwater depletion and salinity problems. While the number of groundwater extraction points increased by 84.9% from 546,000 in 2002 to over a million in 2015, the annual groundwater withdrawal decreased by 18% (from 74.6 to 61.3 km3/y) primarily due to physical limits to fresh groundwater resources (i.e., depletion and/or salinization). On average, withdrawing 5.4 km3/y of nonrenewable water caused groundwater tables to decline 10 to 100 cm/y in different regions, averaging 49 cm/y across the country. This caused elevated annual average electrical conductivity (EC) of groundwater in vast arid/semiarid areas of central and eastern Iran (16 out of 30 subbasins), indicating "very high salinity hazard" for irrigation water. The annual average EC values were generally lower in the wetter northern and western regions, where groundwater EC improvements were detected in rare cases. Our results based on high-resolution groundwater measurements reveal alarming water security threats associated with declining fresh groundwater quantity and quality due to many years of unsustainable use. Our analysis offers insights into the environmental implications and limitations of water-intensive development plans that other water-scarce countries might adopt.

Water quality effects of peat rewetting and leftover conifer brash, following peatland restoration and tree harvesting.

Harvesting of plantation conifers on peatlands is carried out as part of restoration and forestry operations. In particular, in the UK and Ireland, conifer plantations on drained ombrotrophic blanket and raised bogs are increasingly being removed (by harvesting), along with blocking of drainage ditches to help raise water tables to reinitiate and restore bog vegetation and function. However, both tree harvesting and peatland restoration operations can have significant impacts on water quality at local and catchment scales. Previous research has suggested that leaching from leftover decomposing brash (tree tops and branches, including wood and needles) is the primary cause, while other work has suggested that release from rewetted peat also contributes to water quality changes. This research investigates the relative importance of peat rewetting, needles and branches on water quality using mesocosm experiments, to help elucidate the mechanisms behind water quality changes following restoration and harvesting operations. Peat and brash were collected from a drained afforested blanket bog in the Flow Country, Scotland. Short-term mesocosm experiments were conducted by incubating peat, peat + needles and peat + needles + branches with rainwater in quadruplicate. Brash from Sitka spruce (Picea sitchensis) and lodgepole pine (Pinus contorta) was investigated separately, while we also conducted experiments with fresh and aged (∼18 months) brash. Peat, needles and branches all significantly impacted water quality in the order of branches > needles > peat, while concentrations of DOC, PO43-, NH4+, K and Mn were most impacted. Water quality impacts of spruce brash appeared generally greater than pine, while fresh brash had larger effects than aged brash. In our mesocosms, relative contributions to water quality changes were estimated by elemental yields. On average, peat contributed 25.4% (range 0.6-72.3%), while needles and brash contributed 19.7% (range 3.0-37.0%) and 54.9% (range 22.1-70.2%) to yields, respectively. We further estimate that 267 kg C ha-1 (255.8 kg as DOC, 10.7 kg as DIC), 27.4 kg K ha-1, 5.8 kg P ha-1 (as PO43-) and 0.5 kg N ha-1 (as NH4+) could be released from brash, over nine days.

Deceleration of China's human water use and its key drivers.

Increased human water use combined with climate change have aggravated water scarcity from the regional to global scales. However, the lack of spatially detailed datasets limits our understanding of the historical water use trend and its key drivers. Here, we present a survey-based reconstruction of China's sectoral water use in 341 prefectures during 1965 to 2013. The data indicate that water use has doubled during the entire study period, yet with a widespread slowdown of the growth rates from 10.66 km3⋅y-2 before 1975 to 6.23 km3⋅y-2 in 1975 to 1992, and further down to 3.59 km3⋅y-2 afterward. These decelerations were attributed to reduced water use intensities of irrigation and industry, which partly offset the increase driven by pronounced socioeconomic development (i.e., economic growth, population growth, and structural transitions) by 55% in 1975 to 1992 and 83% after 1992. Adoptions for highly efficient irrigation and industrial water recycling technologies explained most of the observed reduction of water use intensities across China. These findings challenge conventional views about an acceleration in water use in China and highlight the opposing roles of different drivers for water use projections.

Seasonal Risk Assessment of Water-Electricity Nexus Systems under Water Consumption Policy Constraint.

Previous studies have estimated power plant cooling water consumption based on the long-term average cooling water consumption intensity (WI: water consumption per unit of electricity generation) at an annual scale. However, the impacts of the seasonality of WI and streamflow on electricity generation are less well understood. In this study, a risk assessment method is developed to explore the seasonal risk of water-electricity nexus based on the Integrated Environmental Control Model, which can simulate variable WIs in response to daily weather conditions and avoid underestimation in WIs as well as nexus risk during dry seasons. Three indicators, reliability, maximum time to recovery, and total power generation loss, are proposed to quantify the seasonal nexus risk under water consumption policy constraint represented by the allowed maximum percentage of water consumption to streamflow. The applications of the method in two representative watersheds demonstrate that the nexus risk is highly seasonal and is greatly impacted by the seasonal variability of streamflow rather than annual average water resources conditions on which most previous studies are based. The nexus is found more risky in the watershed with almost double mean annual streamflow and greater streamflow variability, compared with the watershed with less streamflow variability.

Global Phosphorus Losses from Croplands under Future Precipitation Scenarios.

Phosphorus (P) losses from fertilized croplands to inland water bodies cause serious environmental problems. During wet years, high precipitation disproportionately contributes to P losses. We combine simulations of a gridded crop model and outputs from a number of hydrological and climate models to assess global impacts of changes in precipitation regimes on P losses during the 21st century. Under the baseline climate during 1991-2010, median P losses are 2.7 ± 0.5 kg P ha-1 year-1 over global croplands of four major crops, while during wet years, P losses are 3.6 ± 0.7 kg P ha-1 year-1. By the end of this century, P losses in wet years would reach 4.2 ± 1.0 (RCP2.6) and 4.7 ± 1.3 (RCP8.5) kg P ha-1 year-1 due to increases in high annual precipitation alone. The increases in P losses are the highest (up to 200%) in the arid regions of Middle East, Central Asia, and northern Africa. Consequently, in three quarters of the world's river basins, representing about 40% of total global runoff and home up to 7 billion people, P dilution capacity of freshwater could be exceeded due to P losses from croplands by the end of this century.

Spatial and Temporal Variation of Drought Based on Satellite Derived Vegetation Condition Index in Nepal from 1982⁻2015.

Identification of drought is essential for many environmental and agricultural applications. To further understand drought, this study presented spatial and temporal variations of drought based on satellite derived Vegetation Condition Index (VCI) on annual (Jan⁻Dec), seasonal monsoon (Jun⁻Nov) and pre-monsoon (Mar⁻May) scales from 1982⁻2015 in Nepal. The Vegetation Condition Index (VCI) obtained from NOAA, AVHRR (National Oceanic and Atmospheric Administration, Advanced Very High Resolution Radiometer) and climate data from meteorological stations were used. VCI was used to grade the drought, and the Mann⁻Kendall test and linear trend analysis were conducted to examine drought trends and the Pearson correlation between VCI and climatic factors (i.e., temperature and precipitation) was also acquired. The results identified that severe drought was identified in 1982, 1984, 1985 and 2000 on all time scales. However, VCI has increased at the rate of 1.14 yr-1 (p = 0.04), 1.31 yr-1 (p = 0.03) and 0.77 yr-1 (p = 0.77) on the annual, seasonal monsoon and pre-monsoon scales, respectively. These increased VCIs indicated decreases in drought. However, spatially, increased trends of drought were also found in some regions in Nepal. For instance, northern areas mainly in the Trans-Himalayan regions identified severe drought. The foothills and the lowlands of Terai (southern Nepal) experienced normal VCI, i.e., no drought. Similarly, the Anomaly Vegetation Condition Index (AVCI) was mostly negative before 2000 which indicated deficient soil moisture. The exceedance probability analysis results on the annual time scale showed that there was a 20% chance of occurring severe drought (VCI ≤ 35%) and a 35% chance of occurring normal drought (35% ≤ VCI ≤ 50%) in Nepal. Drought was also linked with climates in which temperature on the annual and seasonal monsoon scales was significant and positively correlated with VCI. Drought occurrence and trends in Nepal need to be further studied for comprehensive information and understanding.

Constraints and potentials of future irrigation water availability on agricultural production under climate change.

We compare ensembles of water supply and demand projections from 10 global hydrological models and six global gridded crop models. These are produced as part of the Inter-Sectoral Impacts Model Intercomparison Project, with coordination from the Agricultural Model Intercomparison and Improvement Project, and driven by outputs of general circulation models run under representative concentration pathway 8.5 as part of the Fifth Coupled Model Intercomparison Project. Models project that direct climate impacts to maize, soybean, wheat, and rice involve losses of 400-1,400 Pcal (8-24% of present-day total) when CO2 fertilization effects are accounted for or 1,400-2,600 Pcal (24-43%) otherwise. Freshwater limitations in some irrigated regions (western United States; China; and West, South, and Central Asia) could necessitate the reversion of 20-60 Mha of cropland from irrigated to rainfed management by end-of-century, and a further loss of 600-2,900 Pcal of food production. In other regions (northern/eastern United States, parts of South America, much of Europe, and South East Asia) surplus water supply could in principle support a net increase in irrigation, although substantial investments in irrigation infrastructure would be required.

Multimodel assessment of water scarcity under climate change.

Water scarcity severely impairs food security and economic prosperity in many countries today. Expected future population changes will, in many countries as well as globally, increase the pressure on available water resources. On the supply side, renewable water resources will be affected by projected changes in precipitation patterns, temperature, and other climate variables. Here we use a large ensemble of global hydrological models (GHMs) forced by five global climate models and the latest greenhouse-gas concentration scenarios (Representative Concentration Pathways) to synthesize the current knowledge about climate change impacts on water resources. We show that climate change is likely to exacerbate regional and global water scarcity considerably. In particular, the ensemble average projects that a global warming of 2 °C above present (approximately 2.7 °C above preindustrial) will confront an additional approximate 15% of the global population with a severe decrease in water resources and will increase the number of people living under absolute water scarcity (<500 m(3) per capita per year) by another 40% (according to some models, more than 100%) compared with the effect of population growth alone. For some indicators of moderate impacts, the steepest increase is seen between the present day and 2 °C, whereas indicators of very severe impacts increase unabated beyond 2 °C. At the same time, the study highlights large uncertainties associated with these estimates, with both global climate models and GHMs contributing to the spread. GHM uncertainty is particularly dominant in many regions affected by declining water resources, suggesting a high potential for improved water resource projections through hydrological model development.

Multisectoral climate impact hotspots in a warming world.

The impacts of global climate change on different aspects of humanity's diverse life-support systems are complex and often difficult to predict. To facilitate policy decisions on mitigation and adaptation strategies, it is necessary to understand, quantify, and synthesize these climate-change impacts, taking into account their uncertainties. Crucial to these decisions is an understanding of how impacts in different sectors overlap, as overlapping impacts increase exposure, lead to interactions of impacts, and are likely to raise adaptation pressure. As a first step we develop herein a framework to study coinciding impacts and identify regional exposure hotspots. This framework can then be used as a starting point for regional case studies on vulnerability and multifaceted adaptation strategies. We consider impacts related to water, agriculture, ecosystems, and malaria at different levels of global warming. Multisectoral overlap starts to be seen robustly at a mean global warming of 3 °C above the 1980-2010 mean, with 11% of the world population subject to severe impacts in at least two of the four impact sectors at 4 °C. Despite these general conclusions, we find that uncertainty arising from the impact models is considerable, and larger than that from the climate models. In a low probability-high impact worst-case assessment, almost the whole inhabited world is at risk for multisectoral pressures. Hence, there is a pressing need for an increased research effort to develop a more comprehensive understanding of impacts, as well as for the development of policy measures under existing uncertainty.

Spatiotemporal analysis of ground-based woody plant leafing in response to temperature in temperate eastern China.

The analysis of woody plant leafing in response to regional-scale temperature variation using ground-based phenology is usually limited by the sparse coverage and missing data of ground observation. In this study, a station-based multispecies method was proposed to generate spatiotemporal variation of woody plant leafing date using ground observations from the Chinese Phenological Observation Network during 1974-1996. The results show that the leafing date had slightly insignificant advance (-0.56 day decade(-1)), and the Arctic Oscillation (AO) index could explain 36% variance of the spring leafing date anomaly. The leafing date had been substantially delayed (4 days) when AO shifted from an extreme high index state (2) in 1989-1990 to a relatively low state (0.1) in 1991-1996. The canonical correlation analysis (CCA) was used to demonstrate the temporal evolutions and spatial structures of interannual variations of the spring temperature and leafing date anomalies. The three CCA spatial patterns of leafing date anomaly are similar to those of spring temperature anomaly. The first spatial pattern shows ubiquitous warming, which is consistent with the ubiquitous advance in leafing date across the study area. The second and third spatial patterns present the regional differences featured by advanced (delayed) leafing associated with high (low) temperature. The results suggest that the spring leafing date anomaly is spatiotemporally coherent with the regional-scale temperature variations. Although we focus here on woody plant leafing in a historical period in temperate eastern China, our station-based multispecies method may be applicable to analysis of the ground-based phenology in response to regional-scale climatic variation in other regions.

Capturing woody aboveground biomass historical change and potential under climate change using Landsat time-series for afforestation in dryland of China.

Capturing long-term dynamics and the potential under climate change of woody aboveground biomass (AGB) is imperative for calculating and raising carbon sequestration of afforestation in dryland. It is always been a great challenge to accurately capture AGB dynamics of sparse woody vegetation mixed with grassland using only Landsat time-series, resulting in changing trajectory of woody AGB estimates cannot accurately reflect woody vegetation growth regularity in dryland. In this study, surface reflectance (SR) sensitive to woody AGB was firstly selected and interannual time-series of composited SR was smoothed using S-G filter for each pixel, and then optimal machine learning algorithm was selected to estimate woody AGB time-series. Pixels that have reached AGB potential were detected based on the AGB changing trajectory, and the potential was spatial-temporal extended using random forest model combining environmental variables under current climate condition and CMIP6 climate models. Results show that: 1) minimum value composite based on NIRv during Jul.-Sep. is more capable of explaining woody AGB variation in dryland (R = 0.87, p < 0.01), and Random Forest (RF) model has the best performance in estimating woody AGB (R2 = 0.75, RMSE = 4.74 t·ha-1) among sis commonly used machine learning models. 2) Annual woody AGB estimates can be perfectly fitted with a logistic growth curve (R2 = 0.97, p < 0.001) indicating explicit growth regularity of woody vegetation, which provides physiological foundation for determining woody AGB potential. 3) Woody AGB potential can be accurately simulated by RF combining environmental variables (R2 = 0.95, RMSE = 2.89 t·ha-1), and current woody AGB still has a potential of small increase, whereas the overall losses of woody AGB potential were observed in 2030, 2040 and 2050 under CMIP6 SSP-RCP scenarios.

Reservoir operation affects propagation from meteorological to hydrological extremes in the Lancang-Mekong River Basin.

Hydrological extremes intensified by meteorological extremes are threatening water security in the Lancang-Mekong River Basin (LMRB), and reservoir operation may mitigate hydrological extreme through regulating hydrological processes during meteorological extreme. However, the capacity of reservoirs in modulating propagation from meteorological extremes to hydrological extremes has seldom been quantified. This study adopted the VIC-Reservoir hydrological model to assess the impact of reservoir operation on the propagation at multi-timescales in the LMRB. The Standardized Precipitation Index and Standardized Streamflow Index were adopted to characterize meteorological extreme and hydrological extreme, respectively, on a range of timescales. The results indicate that reservoir operation has effectively delayed the propagation from meteorological to hydrological extremes during the period of 2008-2016 with rapid reservoir development in the LMRB, compared with the period of 1984-2007 with natural condition. The transmission process of extreme events with a duration of no more than 6 months has been suppressed during the reservoir impact period. However, the influence of reservoir regulation on long-term extreme events that last more than 12 months is generally low. In the upstream basin where reservoir impact is largest, reservoirs can exert a weak mitigation effect on long-term dry extremes. This study provides quantitative assessment of the role of reservoirs in regulating propagation between meteorological and hydrological extremes in the LMRB, and facilitate decision making for the management of water hazards under changing environment.

Water transfer infrastructure buffers water scarcity risks to supply chains.

Inter-basin water transfer (IBWT) infrastructure has been expanding to deliver water across China to meet water demands in populated and industrial areas. Water scarcity may threaten the ability to produce and distribute goods through supply chains. Yet, it is not clear if IBWTs transmit or buffer water scarcity throughout supply chains. Here we combine a national database of IBWT projects and multi-region input-output analysis to trace water transferred by IBWT and virtual scarce water (scarcity weighted water use) from IBWT sourcing basins to production sites then to end consumers. The results indicate that production and final consumption of sectoral products have been increasingly supported by IBWT infrastructure, with physically transferred water volumes doubling between 2007 and 2017. Virtual scarce water is about half of the virtual water supporting the supply chain of the nation. IBWT effectively reduced virtual scarce water supporting the supply chains of most provinces, with the exposure to water scarcity reduced by a maximum of 56.7% and 15.0% for production and final consumption, respectively. IBWT Infrastructure development can thus buffer water scarcity risk to the supply chain and should be considered in water management and sustainable development policy decisions.

Groundwater recharge estimation using in-situ and GRACE observations in the eastern region of the United Arab Emirates.

The intensive agricultural expansion and rapid urban development in Abu Dhabi Emirate, United Arab Emirates (UAE) have resulted in a major decline in local and regional groundwater levels. By using the latest release (RL06) of Gravity Recovery and Climate Experiment (GRACE) satellite measurements and Global Land Data Assimilation System (GLDAS) products, the groundwater storage change was computed and compared with the time series of in-situ monitoring wells over the period of 2010-2016. The RL06 GRACE products from Jet Propulsion Laboratory (JPL), University of Texas Center for Space Research (CSR), German Research Center for Geosciences (GFZ), and JPL mass concentrations (MASCON) were assessed and have shown satisfactory agreements with the monitoring wells. The JPL MASCON reflected the in-situ groundwater storage change better than the other GRACE products (R = 0.5, lag =1 month, RMSE = 13 mm). The groundwater recharge is estimated for the study area and compared with the in-situ recharge method that considers multi recharge components from the rainfall, irrigation return flow and internal fluxes. The results show that the agreements between in-situ and GRACE-derived recharge estimates are highly agreeable (e.g., R2 = 0.91, RMSE = 1.5 Mm3 to 7.8 Mm3, and Nash-Sutcliff Efficiency = 0.7). Using the Mann-Kendall trend test and Sen's slope, the analyses of policies, number of wells, and farm areal expansion with groundwater time series derived from GRACE helped to validate GRACE and emphasize the importance of regulations for sustainable development of groundwater resources. The impacts of subsidy cuts after 2010 can be captured from the GRACE data in the eastern region of Abu Dhabi Emirate. The linear trend of groundwater storage anomaly obtained from GRACE over the period from 2003 to 2010 is -6.36 ± 0.6 mm/year while it showed a decline trend of -1.2 ± 0.6 mm/year after the subsidy cut. The proposed approach has a potential application for estimating groundwater recharge in other arid regions where in-situ monitoring wells are limited or absent.

A synthesis of hydroclimatic, ecological, and socioeconomic data for transdisciplinary research in the Mekong.

The Mekong River basin (MRB) is a transboundary basin that supports livelihoods of over 70 million inhabitants and diverse terrestrial-aquatic ecosystems. This critical lifeline for people and ecosystems is under transformation due to climatic stressors and human activities (e.g., land use change and dam construction). Thus, there is an urgent need to better understand the changing hydrological and ecological systems in the MRB and develop improved adaptation strategies. This, however, is hampered partly by lack of sufficient, reliable, and accessible observational data across the basin. Here, we fill this long-standing gap for MRB by synthesizing climate, hydrological, ecological, and socioeconomic data from various disparate sources. The data- including groundwater records digitized from the literature-provide crucial insights into surface water systems, groundwater dynamics, land use patterns, and socioeconomic changes. The analyses presented also shed light on uncertainties associated with various datasets and the most appropriate choices. These datasets are expected to advance socio-hydrological research and inform science-based management decisions and policymaking for sustainable food-energy-water, livelihood, and ecological systems in the MRB.

High-quality reconstruction of China's natural streamflow.

Reconstruction of natural streamflow is fundamental to the sustainable management of water resources. In China, previous reconstructions from sparse and poor-quality gauge measurements have led to large biases in simulation of the interannual and seasonal variability of natural flows. Here we use a well-trained and tested land surface model coupled to a routing model with flow direction correction to reconstruct the first high-quality gauge-based natural streamflow dataset for China, covering all its 330 catchments during the period from 1961 to 2018. A stronger positive linear relationship holds between upstream routing cells and drainage areas, after flow direction correction to 330 catchments. We also introduce a parameter-uncertainty analysis framework including sensitivity analysis, optimization, and regionalization, which further minimizes biases between modeled and inferred natural streamflow from natural or near-natural gauges. The resulting behavior of the natural hydrological system is represented properly by the model which achieves high skill metric values of the monthly streamflow, with about 83% of the 330 catchments having Nash-Sutcliffe efficiency coefficient (NSE) > 0.7, and about 56% of the 330 catchments having Kling-Gupta efficiency coefficient (KGE) > 0.7. The proposed construction scheme has important implications for similar simulation studies in other regions, and the developed low bias long-term national datasets by statistical postprocessing should be useful in supporting river management activities in China.

Spatiotemporal variations in damages to cropland from agrometeorological disasters in mainland China during 1978-2018.

Drought, flood, hail, low temperature, and frost (LTF) are the main agrometeorological disasters (AMDs) in China; however, comprehensive and quantitative studies on cropland damage induced by AMDs across the whole country in terms of long-term trends are still lacking and urgently needed. Based on historical statistical data from yearbooks and bulletins, the overall characteristics of cropland damage by AMDs during 1978-2018 were analyzed using a pre-whitening procedure and a Mann-Kendall trend test at yearly and provincial scales in China. The results showed that drought was the most severe, with an average covered area of 22.2 million ha and an affected area of 11.2 million ha every year during 1978-2018, followed by flood, hail, and LTF. A decreasing trend was observed in covered area and affected area by drought, flood, and hail, while only LTF showed an increasing trend. On provincial scale, more than 70% of the covered area by AMDs was induced by drought and flood in most provincial districts. In all provincial districts of northern China, more than 50% of the covered area was induced by drought. In most provincial districts of southern China, more than 40% of the covered area was induced by flood. Hail disasters were prominent in Xinjiang, with significant increasing trends among all parameters. Compared with the other three AMDs, LTF covered and affected the smallest cropland area, but significant increasing trends were observed in the northwest and middle parts of China. The results of this study systematically display the characteristics of damage to cropland by four main AMDs, which are critical and necessary for disaster risk reduction and adaptive strategy development.

Global assessment of future sectoral water scarcity under adaptive inner-basin water allocation measures.

Water scarcity has become a major threat to sustainable development under climate change. To reduce the population exposure to water scarcity and improve universal access to safe drinking water are important targets of the Sustainable Development Goal (SDG) 6 in the near future. This study aims to examine the potential of applying adaptive inner-basin water allocation measures (AIWAM), which were not explicitly considered in previous studies, for mitigating water scarcity in the future period (2020-2050). By incorporating AIWAM in water scarcity assessment, nonagricultural water uses are assumed to have high priority over agricultural water use and thus would receive more water supply. Results show that global water deficit is projected to be ~3241.9 km3/yr in 2050, and severe water scarcity is mainly found in arid and semi-arid regions, e.g. Western US, Northern China, and the Middle East. Future warming climate and socioeconomic development tend to aggravate global water scarcity, particularly in Northern Africa, Central Asia, and the Middle East. The application of AIWAM could significantly mitigate water scarcity for nonagricultural sectors by leading to a decrease of global population subject to water scarcity by 12% in 2050 when compared to that without AIWAM. However, this is at the cost of reducing water availability for agricultural sector in the upstream areas, resulting in an increase of global irrigated cropland exposed to water scarcity by 6%. Nevertheless, AIWAM provides a useful scenario that helps design strategies for reducing future population exposure to water scarcity, particularly in densely populated basins and regions. Our findings highlight increasing water use competition across sectors between upstream and downstream areas, and the results provide useful information to develop adaptation strategies towards sustainable water management.

Complex dynamics of water quality mixing in a warm mono-mictic reservoir.

Cycling of water quality constituents in lakes is affected by thermal stratification and homo-thermal conditions and other factors such as oligotrophication, eutrophication, and microbial activities. In addition, hydrological variability can cause greater differences in water residence time and cycling of constituents in man-made lakes (reservoirs) than in natural lakes. Thus, investigations are needed on vertical mixing of constituents in new impounded reservoirs, especially those constructed to supply domestic water. In this study, sampling campaigns were conducted in the Sabalan reservoir, Iran, to investigate vertical changes in constituent concentrations during the year in periods with thermal stratification and homo-thermal conditions. The results revealed incomplete mixing of constituents, even during cold months when the reservoir was homo-thermal. These conditions interacted to create a bottom-up regulated reservoir with sediment that released settled pollutants, impairing water quality in the Sabalan reservoir during both thermal stratification and homo-thermal conditions. Analysis of total nitrogen and total phosphorus concentrations revealed that the reservoir was eutrophic. External pollution loads, internal cycling of pollutants diffusing out from bottom sediments, reductions in inflow to the reservoir, and reservoir operations regulated vertical mixing and concentrations of constituents in the Sabalan reservoir throughout the year.

Irrigation cooling effect on land surface temperature across China based on satellite observations.

The effect of irrigation on temperature has attracted much attention because its cooling effect may mask the warming due to other factors, such as greenhouse gas forcing. Although many studies have examined the irrigation cooling effect (ICE) based on near-surface air temperature from meteorological observations or climate model simulations, few studies have directly addressed the effect of irrigation on land surface temperature (LST), which is closely linked to the surface energy balance and near-surface air temperature. In this paper, an ICE detection (ICED) method is proposed to assess the effect of irrigation on LST using the Moderate Resolution Imaging Spectroradiometer (MODIS) products across China. The magnitude of the ICE is calculated as the LST difference between irrigated area and adjacent non-irrigated area in the self-adaptive moving window determined by the ICED method. The results show that irrigation cools daytime LST by 1.15 K, and cools nighttime LST by 0.13 K, on average, across irrigated areas in China. The effect of irrigation on LST differs greatly among the climate zones and seasons, characterized by the enhanced ICE in arid regions and the growing season. In the arid climate zone, nearly all the irrigated areas show a lower daytime LST than the adjacent non-irrigated areas, leading to a strong ICE magnitude of >6 K in the growing season. In the humid climate zone, the impact of irrigation on LST is generally negligible, with a magnitude around zero throughout the year. This study provides observational evidence and a comprehensive assessment of the effect of irrigation on LST. The proposed ICED method has the potential to be used to study the spatiotemporal variation of the effect of irrigation on LST over other regions with intensive irrigation.