Seasonal Time Scales Research Articles

Wetland Water Level Prediction Using Artificial Neural Networks—A Case Study in the Colombo Flood Detention Area, Sri Lanka

Historically, wetlands have not been given much attention in terms of their value due to the general public being unaware. Nevertheless, wetlands are still threatened by many anthropogenic activities, in addition to ongoing climate change. With these recent developments, water level prediction of wetlands has become an important task in order to identify potential environmental damage and for the sustainable management of wetlands. Therefore, this study identified a reliable neural network model by which to predict wetland water levels over the Colombo flood detention area, Sri Lanka. This is the first study conducted using machine learning techniques in wetland water level predictions in Sri Lanka. The model was developed with independent meteorological variables, including rainfall, evaporation, temperature, relative humidity, and wind speed. The water levels measurements of previous years were used as dependent variables, and the analysis was based on a seasonal timescale. Two neural network training algorithms, the Levenberg Marquardt algorithm (LM) and the Scaled Conjugate algorithm (SG), were used to model the nonlinear relationship, while the Mean Squared Error (MSE) and Coefficient of Correlation (CC) were used as the performance indices by which to understand the robustness of the model. In addition, uncertainty analysis was carried out using d-factor simulations. The performance indicators showed that the LM algorithm produced better results by which to model the wetland water level ahead of the SC algorithm, with a mean squared error of 0.0002 and a coefficient of correlation of 0.99. In addition, the computational efficiencies were excellent in the LM algorithm compared to the SC algorithm in terms of the prediction of water levels. LM showcased 3–5 epochs, whereas SC showcased 34–50 epochs of computational efficiencies for all four seasonal predictions. However, the d-factor showcased that the results were not within the cluster of uncertainty. Therefore, the overall results suggest that the Artificial Neural Network can be successfully used to predict the wetland water levels, which is immensely important in the management and conservation of the wetlands.

Evaluating homogeneity and trends in extreme daily precipitation indices in a semiarid region of Brazil

A regional investigation of precipitation extremes could help the local authorities to develop strategies against potential climatic disasters, especially in regions of large climate vulnerability. In this context, this study focused on the homogeneity and trend analysis of eleven extreme precipitation indices from a daily rainfall dataset of rain gauges of the state of Ceará, located in the north of Northeast Brazil, from 1974 to 2018 at annual and seasonal time scales. The data were first submitted to gap-filling and quality control processes. Homogeneity, trend, and correlation coefficient were performed subsequently. Homogeneity results showed that most of the precipitation series were classified as “useful.” Significant break years in the series agreed well with moderate and very strong El Niño and La Niña events, suggesting a further investigation of this possible connection. Wet and dry day precipitation indices mainly indicated a decrease in the rainfall regime and an increase in dry days, mainly in the central-eastern, northwestern, and southern regions of the Ceará, especially during the annual time scale and the rainy season. The Locally Weighted Scatterplot Smoothing (LOWESS) curve showed changes in almost all series during the 1980s and 1990s, coinciding with the homogeneity breaks and years of severe droughts that strongly hit the region. Correlation coefficients were strong and significant between rainfall total index and the other precipitation indices.

Assessment of wind energy resource potential for future human missions to Mars

Energy sustainability and redundancy for surface habitats, life support systems and scientific instrumentation represent one of the highest-priority issues for future crewed missions to Mars. However, power sources utilized for the current class of robotic missions to Mars may be potentially dangerous near human surface habitats (for example, nuclear) or lack stability on diurnal or seasonal timescales (for example, solar) that cannot be easily compensated for by power storage. Here, we evaluate the power potential for wind turbines as an alternative energy resource on the Mars surface. Using a state-of-the-art Mars global climate model, we analyse the total planetary Martian wind potential and calculate its spatial and temporal variability. We find that wind speeds at some proposed landing sites are sufficiently fast to provide a stand-alone or complementary energy source to solar or nuclear power. While several regions show promising wind energy resource potential, other regions of scientific interest can be discarded based on the natural solar and wind energy potential alone. We demonstrate that wind energy compensates for diurnal and seasonal reductions in solar power particularly in regions of scientific merit in the midlatitudes and during regional dust storms. Critically, proposed turbines stabilize power production when combined with solar arrays, increasing the percent time that power exceeds estimated mission requirements from ~40% for solar arrays alone to greater than 60–90% across a broad fraction of the Mars surface. We encourage additional study aimed at advancing wind turbine technology to operate efficiently under Mars conditions and to extract more power from Mars winds.

Hydrologic Control on Arsenic Cycling at the Groundwater-Surface Water Interface of a Tidal Channel.

Historical industrial activities have resulted in soil contamination at sites globally. Many of these sites are located along coastlines, making them vulnerable to hydrologic and biogeochemical alterations due to climate change and sea-level rise. However, the impact of hydrologic dynamics on contaminant mobility in tidal environments has not been well studied. Here, we collected data from pressure transducers in wells, multi-level redox sensors, and porewater samplers at an As-contaminated site adjacent to a freshwater tidal channel. Results indicate that sharp redox gradients exist and that redox conditions vary on tidal to seasonal timescales due to sub-daily water level fluctuations in the channel and seasonal groundwater-surface water interactions. The As and Fe2+ concentrations decreased during seasonal periods of net discharge to the channel. The seasonal changes were greater than tidal variations in both Eh and As concentrations, indicating that impacts of the seasonal mechanism are stronger than those of sub-daily water table fluctuations. A conceptual model describing tidal and seasonal hydro-biogeochemical coupling is presented. These findings have broad implications for understanding the impacts of sea-level rise on the mobility of natural and anthropogenic coastal solutes.

Prediction and projection of heatwaves

Heatwaves constitute a major threat to human health and ecosystems. Projected increases in heatwave frequency and severity thus lead to the need for prediction to enhance preparedness and minimize adverse impacts. In this Review, we document current capabilities for heatwave prediction at daily to decadal timescales and outline projected changes under anthropogenic warming. Various local and remote drivers and feedbacks influence heatwave development. On daily timescales, extratropical atmospheric blocking and global land–atmosphere coupling are most pertinent, and on subseasonal to seasonal timescales, soil moisture and ocean surface anomalies contribute. Knowledge of these drivers allows heatwaves to be skilfully predicted at daily to weekly lead times. Predictions are challenging beyond timescales of a few weeks, but tendencies for above-average temperatures can be estimated. Further into the future, heatwaves are anticipated to become more frequent, persistent and intense in nearly all inhabited regions, with trends amplified by soil drying in some areas, especially the mid-latitudes. There is also an increased occurrence of humid heatwaves, especially in southern Asia. A better understanding of the relevant drivers and their model representation, including atmospheric dynamics, atmospheric and soil moisture, and surface cover should be prioritized to improve heatwave prediction and projection.

Assessing the impact of synoptic weather systems on air quality in Sydney using Radon 222

The state of the atmosphere can affect the degree of dilution of emitted pollutants, and similar local and diurnal meteorological conditions can be grouped according to prevailing synoptic scale weather systems. Traditionally, various methods have been used to classify atmospheric conditions. Here we investigate the use of Radon-222 (radon) for the classification of weather systems and determine the degree of dilution under different synoptic conditions.Air quality data was analyzed in Richmond Australia over a 13-year period. Radon was used to determine 5 nocturnal stability categories numbered 0 to 4, with 0 capturing times of fast-changing fetch influences, and 1–4 representing increasing conditions of nocturnal stability (1: near neutral, to 4: strongly stable). These categories were then related to prevailing synoptic weather systems. It was found that increasing radon-derived stability categories were associated with reducing intensity of frontal systems traversing southern Australia and extending into the Southern Ocean, with stability category 4 associated with blocking high pressure systems located to the east of the site.The median nocturnal wind speeds and mixing layer heights decreased as we moved from stability category 0 to 4, indicating that the mixing volumes for pollutants released into the atmosphere from surface sources was progressively getting smaller. This decreasing dilution from stability category 0 to 4 resulted in strongly increasing median pollutant concentrations. However, on diurnal and seasonal time scales, differences were observed which could be attributed to changes in emission rates.Our results show that when investigating the impact of air quality mitigation strategies, any variations in meteorological conditions during the comparison periods needs to be considered in addition to changes in pollution emission rates, and that near-surface radon observations and the ventilation coefficient are a convenient and effective tool for this purpose.

Historical and projected spatial and temporal rainfall status of Dar es Salaam, Tanzania, from 1982 to 2050

Dar es Salaam, like other cities in Africa, experiences flash floods during the rainfall season that destroy infrastructure due to the overflow of rivers and blocked sewage. This study investigates the historical and future variability and changes in spatial and temporal rainfall over Dar es Salaam. Station data and Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) gridded data crossing 38 years (1982–2019) were used as a baseline and the Coordinated Regional Climate Downscaling Experiment (CORDEX) dataset from 2021 to 2050 was used for projection under Representative Concentration Pathway (RCP 4.5) forcing scenarios. A trend analysis of historical data was conducted at monthly, seasonal, and annual timescales. Mann–Kendall statistical tests and Sen’s slope estimator were applied to identify the current trend direction and magnitude of changes in rainfall patterns over time. A standardized anomaly index (SAI) was also employed to detect the region’s trends in wetness and dryness. The spatial distribution of rainfall in the city was investigated using an inverse distance weighted (IDW) interpolation technique. The statistical results reveal that a non-significant trend in rainfall was observed on monthly, seasonal, and annual timescales. Generally, in the future (2021–2050), the annual cycle of rainfall shows a slight decrease in monthly rainfall, especially from January to August, and an increase from September to December compared to historical (1982–2019) rainfall, for most of studied locations. Spatially, the distribution of projected rainfall shows that the southern part of the city will experience higher rainfall than other parts. The most significant findings were a decrease in annual projected rainfall by 20%, the MAM projected rainfall season increased by 42%, and an increase of 38% of the OND-projected rainfall season. The findings of this study will be useful for the improved management and planning of the city.

What potential for improving sub‐seasonal predictions of the winter NAO?

AbstractThe North Atlantic Oscillation (NAO) is the leading mode of variability across the Atlantic sector and is a key metric of extratropical forecast performance. Skilful predictions of the NAO are possible at medium‐range (1–2 weeks) and seasonal time scales. However, in a leading dynamical prediction system, we find that sub‐seasonal predictions (1 month NAO with a lead time of 20–30 days) are not statistically significant and represent a gap in forecast skill. In this study, we have investigated the potential for improving predictions using a large ensemble of dynamical hindcasts. First, we find that monthly predictions of the NAO are only weakly related to forecast errors at the medium‐range. This implies that improving medium‐range forecast performance is unlikely to drive significant improvements at longer lead times. Second, the Madden‐Julian Oscillation (MJO) is the leading mode of sub‐seasonal variability in the Tropics and projects onto the NAO with a lag of 10–15 days, but its teleconnection is only partially represented in current forecast systems. We, therefore, assess whether improved MJO‐NAO teleconnections are likely to lead to improved monthly NAO predictions. We find that even perfect MJO forecasts and teleconnections lead to only small improvements in NAO prediction skills. This work indicates that monthly timescales may represent a predictability gap for the NAO and hence the Euro‐Atlantic winter climate in which genuine skill improvements are difficult to achieve. Potential progress in this area could stem from currently unknown sources of skill and large initialised climate ensembles will be a vital tool for investigating these.

A Prognostic-Stochastic and Scale-Adaptive Cumulus Convection Closure for Improved Tropical Variability and Convective Gray-Zone Representation in NOAA’s Unified Forecast System (UFS)

Abstract A prognostic closure is introduced to, and evaluated in, NOAA’s Unified Forecast System. The closure addresses aspects that are not commonly represented in traditional cumulus convection parameterizations, and it departs from the previous assumptions of a negligible subgrid area coverage and statistical quasi-equilibrium at steady state, the latter of which becomes invalid at higher resolution. The new parameterization introduces a prognostic evolution of the convective updraft area fraction based on a moisture budget, and, together with the buoyancy-driven updraft vertical velocity, it completes the cloud-base mass flux. In addition, the new closure addresses stochasticity and includes a representation of subgrid convective organization using cellular automata as well as scale-adaptive considerations. The new cumulus convection closure shows potential for improved Madden–Julian oscillation (MJO) prediction. In our simulations we observe better propagation, amplitude, and phase of the MJO in a case study relative to the control simulation. This improvement can be partly attributed to a closer coupling between low-level moisture flux convergence and precipitation as revealed by a space–time coherence spectrum. In addition, we find that enhanced organization feedback representation and stochastic effects, represented using cellular automata, further enhance the amplitude and propagation of the MJO, and they provide realistic uncertainty estimates of convectively coupled equatorial waves at seasonal time scales. The scale-adaptive behavior of the scheme is also studied by running the global model with 25-, 13-, 9-, and 3-km grid spacing. It is found that the convective area fraction and the convective updraft velocity are both scale adaptive, leading to a reduction of subgrid convective precipitation in the higher-resolution simulations.

On the mechanisms controlling near-coast circulation in the southern Colombian Pacific at tidal, seasonal, and interannual time scales

This research analyzed the near-coastal circulation along 300 km in the southern Colombian Pacific, a meso-tidal region formed by Tumaco Bay and the Mira River Delta. The interaction between tidal dynamics and the Mira River plume stratification and dispersion is not well known. Moreover, the combined effects of tide and density gradients on the circulation patterns in Tumaco Bay have rarely been studied. The region was investigated using the Delft3D hydrodynamic model, calibrated and validated using field data. The results show that Tumaco Bay is ebb-dominated, and the tide and bottom shape are the dominant forces in the circulation patterns inside the bay. The weak horizontal density gradient induced by Mira River did not show a substantial effect on the circulation of the bay. Near the mouth of the Mira Delta, the water column was predominantly partially mixed, but stratification changed within the tidal cycle, presenting tidal straining along the minor axis of the plume. This may generate strongly stratified conditions in the water column during flood periods. Although tidal straining is very common along the major axis of tide-dominated estuaries, it is not as common in coastal river plumes. The analyzed system provides additional evidence about this phenomenon in a tropical delta. • Hydrodynamics of Mira River and Tumaco Bay as an integrated system is studied for the first time using 3D modelling. • Tumaco Bay is ebb-dominated, and the bottom shape dominates the circulation patterns. • Tidal straining is observed along the minor axis of the Mira River plume. • Cross-shore tidal straining in the plume of tropical rivers has been barely reported previously.

Destination of New Guinea Coastal Undercurrent in the western tropical Pacific: Variability and linkages

The New Guinea Coastal Undercurrent (NGCUC) is considered a bottleneck in the western tropical Pacific (WTP), carrying upper-to-intermediate waters from the south to the northwestern Pacific, thereby playing a fundamen tal role in the interhemispheric water mass exchange. However, how the NGCUC links to the circulation in the WTP was insufficiently studied. This work explores the destination of NGCUC waters, its spatiotemporal changes, and possible physical processes linked with the downstream NGCUC using ocean reanalysis for 22 years (1994 – 2015). Lagrangian particle tracking discloses eight major destinations of the NGCUC: The Equatorial Undercurrent (EUC, 35.26%), the North Equatorial Countercurrent (NECC, 12.3%), the North (13.33%) and South (8.85%) Subsurface Countercurrents, the Equatorial Deep Jet (11.49%), the Mindanao Undercurrent (13.24%), and the Indonesian (3.47%) and Halmahera (0.86%) Throughflows. The NGCUC waters are distributed mainly to the east (81.65%) and their dissemination varies markedly with depth. These destinations exhibit significant variations on seasonal and interannual time scales. The NGCUC strengthens (weakens) during summer (winter) and more NGCUC waters are distributed westward and northeastward (eastward). Interannually, the distribution of the NGCUC water is influenced by El Niño-Southern Oscillation, in which most of its eastward-distributed waters shift northward (equatorward) in El Niño (La Niña) phase joining the strengthened NECC (EUC). Changes in the NGCUC water destination can transform the water mass properties in the WTP. The findings of this study also emphasize the fundamental role of eddies in trapping and redistributing the NGCUC waters and linking the currents in the WTP.

Long-term variations in water discharge and sediment load of the Pearl River Estuary: Implications for sustainable development of the Greater Bay Area

The water discharge and sediment load have been increasingly altered by climate change and human activities in recent decades. For the Pearl River, however, long-term variations in the sediment regime, especially in the last decade, remain poorly known. Here we updated knowledge of the temporal trends in the sediment regime of the Pearl River at annual, seasonal and monthly time scales from the 1950s to 2020. Results show that the annual sediment load and suspended sediment concentration (SSC) exhibited drastically decreased, regardless of water discharge. Compared with previous studies, we also found that sediment load and SSC reached a conspicuous peak in the 1980s, and showed a significant decline starting in the 2000s and 1990s, respectively. In the last decade, however, water discharge and sediment load showed slightly increasing trends. At the seasonal scale, the wet-season water discharge displays a decreasing trend, while the dry-season water discharge is increasing. At the monthly scale, the flood seasons in the North and East Rivers typically occur one month earlier than that in the West River due to the different precipitation regimes. Precipitation was responsible for the long-term change of discharge, while human activities (e.g. dam construction and land use change) exerted different effects on the variations in sediment load among different periods. Changes in the sediment regime have exerted substantial influences on downstream channel morphology and saltwater intrusion in the Greater Bay Area. Our study proposes a watershed-based solution, and provides scientific guidelines for the sustainable development of the Greater Bay Area.

Variability of Levoglucosan in Precipitation in Lhasa as a Proxy for Tracing Vegetation Fires

Levoglucosan has been extensively used as a biomarker for tracing vegetation fire emissions in atmospheric aerosols, ice cores, and lake sediments. Precipitation can scavenge levoglucosan from the atmosphere to the Earth’s surface. However, almost no previous research has investigated the variability of levoglucosan in precipitation. This research reports levoglucosan records in precipitation samples collected from March 2018 to September 2019 in Lhasa, on the southern Tibetan Plateau. Although the event-based levoglucosan variations seem random, the variability on monthly or seasonal time scales is highly correlated to vegetation fire changes along the Himalayas and surrounding regions. In addition, extreme wildfires in southern Central Asia also affect levoglucosan records in precipitation at Lhasa, especially during the summer. Our results indicate that local vegetation fires are not the major sources of levoglucosan in precipitation in Lhasa. In addition, the annual levoglucosan flux at Lhasa is much higher than that in ice cores on the Tibetan Plateau. This study provides important insights into levoglucosan records in precipitation over the Tibetan Plateau, highlighting how levoglucosan variations could reflect fire changes from a single event to seasonal or annual time scales.

Tracking diurnal to seasonal variations of gross primary productivity using a geostationary satellite, GK-2A advanced meteorological imager

The diurnal sampling capability of geostationary satellites provides unprecedented opportunities for monitoring canopy photosynthesis at multiple temporal scales. At the diurnal scale, only geostationary satellites can currently provide sub-daily data at regular intervals, also it can help to minimize data gaps due to clouds at the seasonal scale. However, the potential of geostationary satellites for monitoring photosynthesis has not been explored in depth. In this study, we tracked diurnal to seasonal variations in gross primary production (GPP) using the product of near-infrared reflectance of vegetation and photosynthetically active radiation (PAR) (NIRvP) over deciduous forests, mixed forests and a rice paddy during the growing season. For this purpose, we generated three levels of reflectance and PAR from Geostationary Korea Multi-Purpose Satellite-2A (GK-2A). We examined how NIRvP derived from GK-2A tracked in-situ GPP data collected from five flux tower sites in South Korea. Bi-directional Reflectance Distribution Function (BRDF) normalized NIRvP agreed well with in-situ GPP over the course of the growing season at hourly (R2 = 0.68–0.77) and daily timesteps (R2 = 0.71–0.83). Atmospheric correction and BRDF normalization improved the performance of NIRvP in tracking GPP at both the diurnal and seasonal time scales. Also, GK-2A showed a much higher percentage of available high-quality BRDF data over the whole growing season for all study sites than the Moderate Resolution Imaging Spectroradiometer (MODIS) (GK-2A: 85%; MODIS: 39%), especially during the cloudy monsoon period. Our findings demonstrated that the unique observation characteristics of geostationary satellites can contribute to large-scale monitoring of diurnal to seasonal GPP dynamics.

Impact of ocean data assimilation on climate predictions with ICON-ESM

We develop a data assimilation scheme with the Icosahedral Non-hydrostatic Earth System Model (ICON-ESM) for operational decadal and seasonal climate predictions at the German weather service. For this purpose, we implement an Ensemble Kalman Filter to the ocean component as a first step towards a weakly coupled data assimilation. We performed an assimilation experiment over the period 1960–2014. This ocean-only assimilation experiment serves to initialize 10-year long retrospective predictions (hindcasts) started each year on 1 November. On multi-annual time scales, we find predictability of sea surface temperature and salinity as well as oceanic heat and salt contents especially in the North Atlantic. The mean Atlantic Meridional Overturning Circulation is realistic and the variability is stable during the assimilation. On seasonal time scales, we find high predictive skill in the tropics with highest values in variables related to the El Niño/Southern Oscillation phenomenon. In the Arctic, the hindcasts correctly represent the decreasing sea ice trend in winter and, to a lesser degree, also in summer, although sea ice concentration is generally much too low in both hemispheres in summer. However, compared to other prediction systems, prediction skill is relatively low in regions apart from the tropical Pacific due to the missing atmospheric assimilation. Further improvements of the simulated mean state of ICON-ESM, e.g. through fine-tuning of the sea ice and the oceanic circulation in the Southern Ocean, are expected to improve the predictive skill. In general, we demonstrate that our data assimilation method is successfully initializing the oceanic component of the climate system.

Offshore wind power potential analysis for different wind turbines in the Mediterranean Region, 1959–2020

We evaluated spatiotemporal characteristics of the wind power density (WPD) in the Mediterranean and the Black Sea. An hourly wind speed data from ERA5 of ECMWF is used covering 62 years between 1959 and 2020. Spatial distributions of WPD at 100 m altitude at monthly, yearly, and seasonal timescales are revealed. The average WPD in the study area is 373 W/m2, where the spatial maximums in the 62-year average map reach up to 1116 W/m2. The spatial distribution of yearly mean WPD considering 13 sub-basins revealed that the two most prominent regions are the Gulf of Lion and the Aegean Sea. The diurnal variation of WPD showed over ± 10 % variability within the considered sub-basins. Five commercial turbines are selected to investigate their performance in the study area. The capacity factors, and operational and rated power time percentages are spatially mapped. The variability in the WPD is investigated using several indicators of yearly variability index, intra-annual variability index, coefficient of variation, robust coefficient of variation, inter-quartile range, and inter-quartile ratio. The long-term trend in the monthly-mean values is investigated and it is revealed that the statistically significant downward trends manifest themselves in the Levantine Basin, Ligurian-Provençal Basin, Balearic Sea, and the Alboran Sea. The capacity factors of five widely used wind turbines are computed in the study area using both yearly and seasonal timescales.

Frequency domain water table fluctuations reveal impacts of intense rainfall and vadose zone thickness on groundwater recharge

Abstract. Groundwater recharge is difficult to estimate, especially in fractured aquifers, because of the spatial variability of the soil properties and because of the lack of data at basin scale. A relevant method, known as the water table fluctuation (WTF) method, consists in inferring recharge directly from the WTFs observed in boreholes. However, the WTF method neglects the impact of lateral groundwater redistribution in the aquifer; i.e., it assumes that all the WTFs are attributable to recharge. In this study, we developed the WTF approach in the frequency domain to better consider groundwater lateral flow, which quickly redistributes the impulse of recharge and mitigates the link between WTFs and recharge. First, we calibrated a 1D analytical groundwater model to estimate hydrodynamic parameters at each borehole. These parameters were defined from the WTFs recorded for several years, independently of prescribed potential recharge. Second, calibrated models are reversed analytically in the frequency domain to estimate recharge fluctuations (RFs) at weekly to monthly scales from the observed WTFs. Models were tested on two twin sites with a similar climate, fractured aquifer and land use but different hydrogeologic settings: one has been operated as a pumping site for the last 25 years (Ploemeur, France), while the second has not been perturbed by pumping (Guidel). Results confirm the important role of rainfall temporal distribution in generating recharge. While all rainfall contributes to recharge, the ratio of recharge to rainfall minus potential evapotranspiration is frequency-dependent, varying between 20 %–30 % at periods <10 d and 30 %–50 % at monthly scale and reaching 75 % at seasonal timescales. We further show that the unsaturated zone thickness controls the intensity and timing of RFs. Overall, this approach contributes to a better assessment of recharge and helps to improve the representation of groundwater systems within hydrological models. In spite of the heterogeneous nature of aquifers, parameters controlling WTFs can be inferred from WTF time series, providing confidence that the method can be deployed in different geological contexts where long-term water table records are available.

Multi-model projections of future evaporation in a sub-tropical lake

Lake evaporation plays an important role in the water budget of lakes. Predicting lake evaporation responses to climate change is thus of paramount importance for the planning of mitigation and adaption strategies. However, most studies that have simulated climate change impacts on lake evaporation have typically utilised a single mechanistic model. Whilst such studies have merit, projected changes in lake evaporation from any single lake model can be considered uncertain. To better understand evaporation responses to climate change, a multi-model approach (i.e., where a range of projections are considered), is desirable. In this study, we present such multi-model analysis, where five lake models forced by four different climate model projections are used to simulate historic and future change (1901–2099) in lake evaporation. Our investigation, which focuses on sub-tropical Lake Kinneret (Israel), suggested considerable differences in simulated evaporation rates among the models, with the annual average evaporation rates varying between 1232 mm year−1 and 2608 mm year−1 during the historic period (1901–2005). We explored these differences by comparing the models with reference evaporation rates estimated using in-situ data (2000–2005) and a bulk aerodynamic algorithm. We found that the model ensemble generally captured the intra-annual variability in reference evaporation rates, and compared well at seasonal timescales (RMSEc = 0.19, R = 0.92). Using the model ensemble, we then projected future change in evaporation rates under three different Representative Concentration Pathway (RCP) scenarios: RCP 2.6, 6.0 and 8.5. Our projections indicated that, by the end of the 21st century (2070–2099), annual average evaporation rates would increase in Lake Kinneret by 9–22 % under RCPs 2.6–8.5. When compared with projected regional declines in precipitation, our projections suggested that the water balance of Lake Kinneret could experience a deficit of 14–40 % this century. We anticipate this substantial projected deficit combined with a considerable growth in population expected for this region could have considerable negative impacts on water availability and would consequently increase regional water stress.

High-resolution surface mass loads in the Amazon Basin combining GRACE and river routing model

SUMMARYUnderstanding water redistribution on Earth's surface is essential to hydrological applications and water management. Variations in water mass loads have been observed by the Gravity Recovery and Climate Experiment (GRACE), but the low spatial resolution of GRACE limits determination of their distribution in detail. Hydrologic models provide higher spatial resolution water mass loads, but may include larger uncertainties. In this study, we develop high-resolution surface mass loads over the Amazon basin using forward modelling by combining GRACE data and a hydrologic model. River routing discharge is also included as a priori information because of the large water volume changes on relatively narrow channels in the Amazon basin. These high-resolution surface mass loads constrained by river routing agree with GRACE observations when spatially smoothed. Vertical deformation estimated from these high-resolution loads agree with Global Navigation Satellite System (GNSS) observations, at both seasonal and inter-annual timescales. In particular the most improved agreement is obtained at the NAUS GNSS station, close to the main channel of the Amazon, relative to predictions made using GRACE data. At two other stations (APSA and MAPA) near the main channel, the estimated vertical deformations apparently differ from observation, but much of the discrepancy is reduced when river path is corrected in river-routing model, indicating the importance of water loads on river channel to understand crustal displacement in the area.

Spatiotemporal Characteristics of Dissolved Oxygen and Control Mechanism of Hypoxia (Low Oxygen) in the Watershed-Coastal System in Fujian Province

Dissolved oxygen is a key parameter to measure water environment quality and ecosystem health. Currently, the problem of hypoxia (low oxygen) is prominent in coastal areas in China, but there is a lack of research on the spatiotemporal characteristics of dissolved oxygen and the control mechanism of hypoxia in the watershed-coastal system. Based on the data of 135 surface water (including estuaries) and 66 coastal water monitoring sites in Fujian Province from 2011 to 2020, this study analyzed the spatiotemporal variation pattern of dissolved oxygen at seasonal and interannual time scales. The data of hypoxia (10% quantile, corresponding to 67% saturation) were selected to study the characteristics and control mechanism of hypoxia in four types of water bodies (i.e., rivers, reservoirs, estuaries, and coastal waters) using mathematical statistics and a random forest model. The results showed that the dissolved oxygen saturation was the highest in the coast[(98.2±10.2)%] and the lowest in the estuary[(79.2±17.9)%]. Compared with that in the 12th Five-Year Plan (2011-2015), the frequency of hypoxia detection in rivers and reservoirs in the 13th Five-Year Plan (2016-2020) was significantly reduced, but the change in estuaries was not significant. Counting the points with hypoxia detection, the multi-year average hypoxia detection frequency of rivers and reservoirs was highest in autumn, and the frequency of estuaries was highest in summer. Hypoxia in reservoirs and estuaries was the most prominent but with different mechanisms. Specifically, hypoxia in reservoir reaches was related to summer runoff carrying large amounts of organic matter input, stratification leading to continuous oxygen depletion in the bottom water, and vertical mixing or discharge through dams in autumn, whereas hypoxia in estuaries was associated with strong pollution inputs and reductive materials. Systematic management and regionalized control mechanisms need to be established to further strengthen watershed-coastal pollution abatement to help mitigate eutrophication and hypoxia problems.