Annual Load Research Articles

Optimization scheduling of power system under load winter and summer double-peak scenario

In recent years, due to people’s need for a better life and the impact of extreme weather factors, the annual load curve shows a winter-summer double-peak pattern in summer and winter. In addition, due to the large-scale grid integration of renewable energy sources such as wind power, the uncertainty of its output has further increased the net load during the double-peak scenario, putting the power system under even greater pressure to supply electricity. In this paper, we study the day-ahead hierarchical optimal scheduling model of the power system under the double-peak scenario, considering the pumped-storage flexibility space and the extreme boundary flexibility demand. We simulate and analyze the impacts of different operation modes of the pumped-storage power plant on the scheduling results. The simulation shows that the proposed method can give full play to the effect of pumped storage peak shaving and valley filling and guarantee the reliability of the power supply under the double-peak scenario.

Optimal resource allocation and operation for smart energy hubs considering hydrogen storage systems and electric vehicles

Energy hubs (EHs) have substantially paved the way for the coordinated operation of various energy carriers, converters, and storage. However, the establishment of optimal planning and operation of the EH include several challenges, e.g., the stochastic nature of non-dispatchable generation assets, obtaining a satisfactory performance from the storage assets with reasonable energy and power density costs, and long-term load growth. Accordingly, this paper proposes a two-stage stochastic optimal resource allocation and operation approach for multiple smart energy hubs-based microgrids. The first stage optimizes the location of each EH and different assets' capacities. On the other hand, the second stage optimizes the charging/discharging rates of each asset and parking lot power. These microgrids combine renewable energy sources. Moreover, for research gap and unlike existing research, the cooperative operation of hybrid storage systems (i.e., solar-powered compressed air energy storage, hydrogen storage systems, battery energy storage systems, thermal energy storage systems) along with plug-in electric vehicles (PEV) has been investigated. Furthermore, annual load growth and price-based demand response (PBDR) are employed in this study. The simulation results demonstrate that the controlled charging/discharging of the PEVs reduces the total annualized cost by 5.49%, while the operation and emission costs are reduced by 21.3% and 19.86%, respectively. Furthermore, employing PBDR has led to a reduction of 10.1% in capital and operational costs.

Seasonal Modulation of Crustal Seismicity in Northeastern Japan Driven by Snow Load

AbstractNumerous studies have reported that surface hydrological loading can seasonally modulate seismicity rates at crustal depths. For example, substantial winter snow accumulation occurs across the Japanese Islands, and these snowy regions appear to have seasonally modulated the occurrence of previous large inland earthquakes. Therefore, it is important to investigate the impact of seasonal stress changes on crustal seismicity to deepen our understanding of earthquake generation. Here we constrain seasonal changes in the surface load across northeastern Japan using Global Navigation Satellite System surface displacements and evaluate the potential relationship between temporal trends in inland seismicity and estimated seasonal stress changes. The spatial distribution of the seasonal surface load is consistent with snow depth along the Sea of Japan. The inland seismicity beneath northeastern Japan is modestly modulated by the seasonal stress changes that are induced by the annual snow load. However, this seasonal response is weaker than that in other regions. This weak modulation may be due to the small surface‐load‐induced stress perturbation relative to the long‐term‐averaged stressing rate and/or the limited presence of crustal fluids to trigger seismicity in Japan.

A review of the development and implementation of the critical source area concept: A reflection of Andrew Sharpley's role in improving water quality.

Critical source areas (CSAs) are small areas of a field, farm, or catchment that account for most contaminant loss by having both a high contaminant availability and transport potential. Most work on CSAs has focused on phosphorus (P), largely through the work in the 1990s initiated by Dr. Sharpley and colleagues who recognized the value in targeting mitigation efforts. The CSA concept has been readily grasped by scientists, farmers, and policymakers across the globe. However, experiences and success have been mixed, often caused by the variation in where and how CSAs are defined. For instance, analysis of studies from 1990 to 2023 shows that the proportion of the annual contaminant load coming from a CSA decreases from field to farm to catchment scale. This finding is consistent with increased buffering of CSAs and greater contribution of other sources with scale, or variation in the definition of CSAs. We therefore argue that the best application of CSAs to target mitigation actions should be at small areas that truly account for most contaminant loss. This article sheds light on the development and utilization of CSAs, paying tribute to Dr. Sharpley's remarkable contributions to the improvement of water quality, and reflecting upon where the CSA concept has succeeded or not in reducing contaminant (largely P) loss.

Evaluation of the Characteristics of Pollutant Discharge in Tomato Hydroponic Wastewater (HWW) for Sustainable Water Management in Korea

In South Korea, the use of hydroponic cultivation has been on the rise. However, this system produces a large amount of wastewater. In this study, the amount of wastewater generated by hydroponic tomato cultivation is identified, and a management plan is proposed. Based on the analysis of 103 tomato HWW samples, it was found that the electrical conductivity (EC) was 4.25 ± 1.01 dS/m, the nitrogen (N) content was 411.21 ± 122.64 mg/L, and the phosphorus (P) content was 47.74 mg/L, which caused eutrophication. Therefore, agricultural reuse and HWW treatment were proposed. Regarding the annual HWW load, 1 ha of hydroponics discharges 964.26 kg/ha of N, 111.95 of P, 937.46 of K, 795.14 of Ca, 313.83 of Mg, and 405.40 of S. The trace elements were heavy metals, which were calculated as Fe—4.03, Mn—0.77, Zn—1.08, B—2.25, Cu—0.38, and Mo—0.05 kg/ha. Since wastewater is a national source of drinking water, it needs to be collected and treated. Inter-item correlation analysis showed that most of the fertilizer components were correlated with the EC concentrations. This study can be used to determine the concentrations required for agricultural reuse and to determine the treatment capacity in HWW management.

Historical climate impact attribution of changes in river flow and sediment loads at selected gauging stations in the Nile basin

The Nile basin is the second largest basin in Africa and one of the regions experiencing high climatic diversity with variability of precipitation and deteriorating water resources. As climate change is affecting most of the hydroclimatic variables across the world, this study assesses whether historical changes in river flow and sediment loads at selected gauges in the Nile basin can be attributed to climate change. An impact attribution approach is employed by constraining a process-based model with a set of factual and counterfactual climate forcing data for 69 years (1951–2019), from the impact attribution setup of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP3a). To quantify the role of climate change, we use the non-parametric Mann-Kendall test to identify trends and calculate the differences in long-term mean annual river flow and sediment load simulations between a model setup using factual and counterfactual climate forcing data. Results for selected river stations in the Lake Victoria basin show reasonable evidence of a long-term historical increase in river flows (two stations) and sediment load (one station), largely attributed to changes in climate. In contrast, within the Blue Nile and Main Nile basins, there is a slight decrease of river flows at four selected stations under factual climate, which can be attributed to climate change, but no significant changes in sediment load (one station). These findings show spatial differences in the impacts of climate change on river flows and sediment load in the study area for the historical period.

Aplikasi Kinerja Pembangkit Listrik Tenaga Surya 1200 WP Terhadap Beban Pompa Air Menggunakan Homer Pro Di Desa Pandan Arang

Pandan Arang Village is located in Ogan Komering Ilir District, Kandis District, South Sumatra Province. Solar energy potential in this village is 4.95 kWh/m2/day. Utilization of alternative energy by building a Solar Photovoltaic (PLTS) system. The research aims to analyze the performance of a 1200 WP solar power plant with a water pump load of 2226 kW. The research method consists of 4 stages: 1. Location survey, 2. Data collection, 3. Simulation, 4. Technical analysis. Location data collection includes PLTS components and load data. This data is used for simulations using the HOMER PRO application. The simulation results show that the amount of electrical energy produced is 1605 kWh/year or 4.4 kWh/day. Simulation with 2 water pump loads produces unused electrical power of 3574 kWh/year or 72% of the total annual load. Meanwhile, in the simulation, the unused electricity load for 1 water pump is 1092 kWh/year. Thus, it can be concluded that the 1200 Wp PLTS system cannot meet the daily electricity load requirements for a year.

Detection and Identification of Quarantine and Non-Quarantine Pest Species of Prunus avium Agroecosystem in Kyrgyzstan

Research of agroecosystem is a comprehensive study of one species with in biocenosis taking into account integrated plant protection to increase output. Gardeners in developing countries most often resort to the use of highly toxic universal pesticides, which leads to the Pesticide Syndrome with general decline of these products. The purpose of the research is to identify fauna of the cherry orchard in the south of Kyrgyzstan to apply eco-methods to control pest of stone fruits. Research objectives: 1) identification of organisms in the agrocenosis of the cherry orchard; 2) classification into biological groups; 3) comparison of the experimental and control fields. Our work was carried out in the autumn and spring periods on 2 experimental fields in the South of Kyrgyzstan for 2021-2022. The identified fauna species comprised of 26 species, which are: Coleoptera (26.9%) the largest order; followed by Lepidoptera and Equidoptera (Homoptera) (19.2%); and Hymenoptera (15.4%). The others are less than 10%: Diptera (7.7%); Acariformes; Hemiptera; Neuroptera (3.8%). At the same time, Coleoptera (26.9%) and Lepidoptera pests make up the bulk of the biomass of the agrocenosis of cherry orchard (19.2%) which dominants and most harmful. The research field no. 1 with annual pesticide load has 20% quarantine pest species with no zoophages among identified species. Whereas non-pesticide-treated field no. 2, no quarantine species, there is biocontrol and with richer biodiversity where trophic relationships is preserved.

CAMELS-Chem: augmenting CAMELS (Catchment Attributes and Meteorology for Large-sample Studies) with atmospheric and stream water chemistry data

Abstract. Large sample datasets are transforming the catchment sciences, but there are few off-the-shelf stream water chemistry datasets with complementary atmospheric deposition, streamflow, meteorology, and catchment physiographic attributes. The existing CAMELS (Catchment Attributes and Meteorology for Large-sample Studies) dataset includes data on topography, climate, streamflow, land cover, soil, and geology across the continental US. With CAMELS-Chem, we pair these existing attribute data for 516 catchments with atmospheric deposition data from the National Atmospheric Deposition Program and water chemistry and instantaneous discharge data from the US Geological Survey over the period from 1980 through 2018 in a relational database and corresponding dataset. The data include 18 common stream water chemistry constituents: Al, Ca, Cl, dissolved organic carbon, total organic carbon, HCO3, K, Mg, Na, total dissolved N, total organic N, NO3, dissolved oxygen, pH (field and lab), Si, SO4, and water temperature. Annual deposition loads and concentrations include hydrogen, NH4, NO3, total inorganic N, Cl, SO4, Ca, K, Mg, and Na. We demonstrate that CAMELS-Chem water chemistry data are sampled effectively across climates, seasons, and discharges for trend analysis and highlight the coincident sampling of stream constituents for process-based understanding. To motivate their use by the larger scientific community across a variety of disciplines, we show examples of how these publicly available datasets can be applied to trend detection and attribution, biogeochemical process understanding, and new hypothesis generation via data-driven techniques.

Stochastic optimal allocation for a battery energy storage system in high renewable-penetrated distribution networks

As the penetration of renewable distributed generation (RDG) continues to grow, the stochastic and intermittent nature of its output imposes significant challenges on distribution networks (DNs), such as source–load mismatch and voltage fluctuations, which seriously affects the safety and reliability of the system. Thus, this paper presents a stochastic optimal allocation method for a battery energy storage system (BESS) in the DN, with the consideration of annual load growth, BESS degradation, and DN operation, aiming to minimize the overall cost of DNs and harvest more renewable energy. Based on the rainflow-counting concept, BESS degradation is efficiently modeled and linearized to improve solvability. Additionally, to address the uncertainties of RDG outputs and loads, a stochastic optimization (SO) method is adopted. Furthermore, considering that a large number of integer variables of the BESS allocation model may cause a heavy computational burden, a feasibility pump-based solution algorithm is introduced to accelerate the solving speed. Finally, the effectiveness of the proposed BESS allocation method and the solution algorithm is verified on a 33-bus DN system through comparative analyses, showing high efficiency and performance.

Impact of future climate change on energy consumption in residential buildings: A case study for representative cities in Japan

This study examines the impact of future climate change on energy consumption in residential buildings in Japan, taking into account both the current and future typical meteorological year (TMY) database. TMY data is widely used in the building sector for energy performance assessments, system sizing, and optimization. To investigate the impact of current and future TMY databases on energy consumption of buildings, the study predicts the cooling and heating loads of residential buildings in four cities of Japan under the current (2020 ver.) and future (2086 ver.) TMY databases. Results show that the use of future TMY database leads to significant changes in air-conditioning heat loads of residential buildings in Japan. It finds that the annual cooling load in residential buildings of four cites of Japan increases by approximately 12% for Tokyo, approximately 9% for Toyohashi, approximately 8% for Osaka, and approximately 7% for Nagoya, respectively, however the annual heating load decreases by approximately 8% for Tokyo, approximately 9% for Toyohashi, approximately 6% for Osaka, and approximately 5% for Nagoya, respectively, compared to the current TMY database. This finding suggests that climate change will have a significant impact on future building energy consumption, and proposes energy-efficient building design as a solution to mitigate the impact of climate change on building energy consumption.

Speed optimization for maximizing the ship’s economic benefits considering the Carbon Intensity Indicator (CII)

With the introduction and imposition of the Carbon Intensity Indicator (CII) guidelines, more and more attention is being given to CII compliance of ships. A ship’s normal operation will be affected when it has a CII rating of D or E. However, pursuing lower energy consumption may reduce economic benefits, which is a major concern for stakeholders. This paper proposes a method to maximum a ship’s economic benefits while meeting the CII requirements. An optimization model is established by reallocating the proportions of different speed ranges and adjusting the corresponding average values. A genetic algorithm is adopted to solve the proposed model. The results of a case study based on real ship data demonstrate 5% to 8% improvements in annual full load distance after optimization while maintaining a CII rating of C or better in a given year. The proposed optimization model should be able to provide guidance for operational decision-making under increasingly stringent CII regulations.

Integrating High Levels of Wind in Island Systems: Lessons from Hawaii

such as wind and solar plants presents an operational challenge for grid operators. The economic incentives and technical challenges that accompany large amounts of variable generation in island power systems are often much greater. The Hawaiian Electric Company and its subsidiaries, the Maui Electric Company and the Hawaii Electric Light Company have considerable experience in planning and operating power systems with relatively high levels of wind power. The islands of Hawaii and Maui operate power systems with high levels of wind power (more than 10% by energy) and have experienced and addressed challenges associated with the variability and uncertainty of wind power. The island of Maui is anticipating further wind plant deployments in the near future. Recent analyses of possible near-term deployment of large amounts of wind power on the Oahu power system (500MW of wind power; approximately 1200MW peak and 520MW minimum annual load) has shown the potential for this system to accept almost 25% of its energy from wind and solar power. This paper will identify some of the wind integration challenges and highlight the benefits of a variety of strategies that are expected to improve system economics and operational reliability, including proposed modifications to the baseload thermal fleet (deeper turndown, higher ramp rates, and tuned droop characteristics), advanced wind turbine grid support features, new operating strategies, wind forecasting and refinements to the up and down reserve requirements. This paper will present the key findings in the context of useful insights and lessons learned that are relevant to other island power systems considering very high levels of wind power.

Analysis of the GEFS-Aerosols annual budget to better understand aerosol predictions simulated in the model

Abstract. In September 2020, a global aerosol forecasting model was implemented as an ensemble member of the National Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Prediction (NCEP) Global Ensemble Forecasting System (GEFS) v12.0.1 (hereafter referred to as “GEFS-Aerosols”). In this study, GEFS-Aerosols simulation results from 1 September 2019 to 30 September 2020 were evaluated using an aerosol budget analysis. These results were compared with results from other global models as well as reanalysis data. From this analysis, the global average lifetimes of black carbon (BC), organic carbon (OC), dust, sea salt, and sulfate are 4.06, 4.29, 4.59, 0.34, and 3.3 d, respectively, with the annual average loads of 0.14, 1.29, 4.52, 6.80, and 0.51 Tg. Compared with the National Aeronautics and Space Administration (NASA) Goddard Earth Observing System–Goddard Chemistry Aerosol and Radiation Transport (GEOS4-GOCART) model, the aerosols in GEFS-Aerosols have a relatively short lifetime because of the faster removal processes in GEFS-Aerosols. Meanwhile, in GEFS-Aerosols, aerosol emissions are the determining factor for the mass and composition of aerosols in the atmosphere. The size (bin) distribution of aerosol emissions is as important as its total emissions, especially in simulations of dust and sea salt. Moreover, most importantly, the strong monthly and interannual variations in natural sources of aerosols in GEFS-Aerosols suggest that improving the accuracy of the prognostic concentrations of aerosols is important for applying aerosol feedback to weather and climate predictions.

Morphological Model for Erosion Prediction of India’s Largest Braided River Using MIKE 21C Model

The Brahmaputra River has a dynamic, highly braided channel pattern with frequent river bar formation, making it morphologically very dynamic, especially during the monsoon season with high discharge and sediment load. To understand how the river changes over time, this study focused on two stretches: Palasbari-Gumi and Dibrugarh. Using 2D morphological models (MIKE-21C), the study aimed to predict erosion patterns, plan protective measures, and assess morphological changes over short-term (1 year), medium-term (3 year), and long-term (5 year) periods. Model runs were conducted to predict design variables across these river reaches, encompassing different hydrological scenarios and development-planning scenarios. The coarse sand fraction yielded mean annual sediment load predictions of 257 Mt/year for the 2021 hydrological year and 314 Mt/year under bankfull discharge conditions in the Palasbari-Gumi reach. In the Dibrugarh reach, the corresponding values were 78 Mt/year and 100 Mt/year. Notably, historical records indicate an annual sediment load of 400 Mt/year in the Brahmaputra River. The model results were compared to measurements from Acoustic Doppler Current Profilers (ADCP), showing good accuracy for flow velocities, flood levels, and sediment loads. Discrepancies in peak model velocities compared to ADCP measurements remain consistently below 9% across the majority of recorded data points. The predicted flood levels for the bankfull discharge condition exhibited an outstanding accuracy, reaching nearly 91% at the Palasbari-Gumi site and a notable 95% at the Dibrugarh site. This study has presented a valuable methodology for enhancing the strategic planning and implementation of river training endeavours, particularly within the dynamic and highly braided channels of rivers such as the Brahmaputra River. The approach leverages predictive models to predict morphological changes over a 2–3 years timeframe, contributing to improved river management.

Assessing geomorphic and hydraulic changes related to an unplanned reconnection of the middle Mississippi River and its floodplain near Miller City, Illinois, USA

The 2016 Len Small Levee breach and the decision not to repair this breach provides a unique opportunity to study the geomorphic and hydraulic changes associated with floodplain reconnection along a large (~30 km long) meander of the Mississippi River known as Dogtooth Bend. This study evaluates recent geomorphic, hydraulic, and sediment-transport capacity changes related to the breaching of the Len Small Levee and the development of cutoff channels across the neck of Dogtooth Bend. We also assess actions undertaken to mitigate further development of cutoff channels across Dogtooth Bend. To address these goals, we perform geomorphic change detection (GCD) analysis and hydrodynamic modeling to assess the geomorphic and hydraulic changes within both the Mississippi's river-connected floodplain and channel.GCD analysis using digital elevation models (DEMs) of the floodplain from pre (2011) and post (2020) levee breach showed net deposition of 23 million tons (MT) of sediment across the reconnected portion of Dogtooth Bend floodplain alone and an additional 34 MT within the batture (the land between the channel's low-water elevation and the flood-mitigation levee). Converting these deposition masses to deposition rates indicates ~5.7 MT yr−1 of deposition within the river-connected floodplain, which is equivalent to ~6 % of the average annual suspended load (~89 MT yr−1) showing this floodplain area is currently a substantial sink for river-transported sediments.In 2021, the U.S. Army Corps of Engineers constructed a grade-control structure down gradient of the levee breach to inhibit the development of cutoff channels across the neck of Dogtooth Bend. Our modeling indicates the addition of this grade-control structure could decrease peak discharge by up to ~15 % and annual flow volume by half assuming channel conveyance remains similar to 2020 conditions. However, sediment-transport-capacity modeling revealed the decrease in flow across Dogtooth Bend attributed to the grade-control structure did not translate into an increase in sediment-transport capacity within the main channel. Assessment of critical shear stress of erosion for fine-grained cohesive materials across Dogtooth Bend suggests conditions favorable to scouring along the actively forming cutoff channels even with the grade-control structure in place. These observations taken together suggest the current river management efforts may not be sufficient in preventing a meander cutoff over the long-term.

Medicating the coast in a metropolitan city: Enantiomeric profiles and joint probabilistic risk assessment of antidepressants and antihistamines

Pharmaceuticals are receiving increasing attention as emerging contaminants in the aquatic environment. Herein, we investigated the occurrence of 11 antidepressants, 6 antihistamines and 4 metabolites in treated wastewater effluents, rivers, stormwater, and seawater in Hong Kong, with special focus on chirality. The average levels of ∑pharmaceuticals ranged from 0.525 to 1070 ng/L in all samples and the total annual mass load of target pharmaceuticals in the marine environment of Hong Kong was 756 kg/y. Antihistamines accounted for >80 % of ∑pharmaceuticals, with diphenhydramine and fexofenadine being predominant. The occurrence and enantiomeric profiles of brompheniramine and promethazine sulfoxide were reported in global natural waters for the first time. Among chiral pharmaceuticals, mirtazapine and fexofenadine exhibited R-preference, while others mostly exhibited S-preference, implying that the ecological risks derived from achiral data for chiral pharmaceuticals may be biased. The joint probabilistic risk assessment of fluoxetine revealed that R-fluoxetine and rac-fluoxetine presented different ecological risks from that of S-fluoxetine; Such assessment also revealed that target pharmaceuticals posed only minimal to low risks, except that diphenhydramine posed an intermediate risk. As estimated, 10 % aquatic species will be affected when the environmental level of diphenhydramine exceeds 7.40 ng/L, which was seen in 46.9 % samples. Collectively, this study highlights further investigations on the enantioselectivity of chiral pharmaceuticals, particularly on environmental behavior and ecotoxicity using local aquatic species as target organisms.

Quantifying climate change impacts on future water resources and salinity transport in a high semi-arid watershed

High salinity mobilization and movement from salt-laden deposits in semi-arid landscapes impair soils and water resources worldwide. Semi-arid regions worldwide are expected to experience rising temperatures and lower precipitation, impacting water supply and spatio-temporal patterns of salinity loads and affecting downstream water quality. This study quantifies the impact of future climate on hydrologic fluxes and salt loads in the Gunnison River Watershed (GRW) (14,608 km2), Colorado, using the APEX-MODFLOW-Salt hydro-chemical watershed model and three different CMIP5 climate models projection downscaled by Multivariate Adaptive Constructed Analogs (MACA) for the period 2020–2099. The APEX-MODFLOW-Salt model accounts for the reactive transport of major salt ions (SO42−, Cl−, CO32−, HCO3−, Ca2+, Na+, Mg2+, and K+) to streams via surface runoff, rainfall erosional runoff, soil lateral flow, quick return flow and groundwater-stream exchange. Model results are analyzed for spatial and temporal trends in water yield and salt loading pathways. Although streamflow is primarily derived from surface runoff (65%), the predominant source of salt loads is the aquifer (73%) due to elevated concentrations of groundwater salt. Annual salt loading from the watershed is 582 Mkg, approximately 10% of the salt load in the Colorado River measured at Lee's Ferry, AZ. For future climate scenarios, annual salt loads from the watershed increased between 4.1% and 9.6% from the historical period due to increased salt loading from groundwater and quick return flow. From the results, applying the APEX-MODFLOW-Salt model with downscaled future climate forcings can be a helpful modeling framework for investigating hydrology and salt mobilization, transport, and export in historical and predictive settings for salt-affected watersheds.

Characterisation of storm runoff contamination from a tropical urban residential area in Malaysia

It has been quite a long time since the Malaysian government endorsed the Urban Storm Water Management Manual (USWMM) in 2000. Until now, there is no proper and detailed database on the non-point source contamination characteristics from various land uses in tropical regions of Malaysia. As such this study was conducted to fill part of the information gap pertaining to the nature of runoff quality in the tropical regions. The combined sewer outfall of a 6.14 ha residential area in Malaysia was studied to characterise the urban runoff quality generated due to tropical rain. As the drainage outlet discharges sullage and storm runoff through the same drainage network, hourly flow pattern and contaminant concentrations were determined both for sullage and storm runoff. Basic statistical analysis was conducted to determine the mean, standard deviation and event mean concentration values for the study area, for which such data was not available. It was observed that the runoff generated from the area is polluted due to high total suspended solids (TSS), biochemical oxygen demand (BOD) and chemical oxygen demand (COD). The runoff contained more total organic carbon (TOC) than total inorganic carbon (TIC). The EMC values of BOD, COD, TSS, TOC, total Kjeldhal nitrogen, ammoniacal nitrogen and orthophosphate were 35, 168, 177, 11, 0.32, 0.54, 0.16 mg/L, respectively. The presence of heavy metals in the runoff was low. The EMC values of lead, zinc, nickel, cadmium, chromium and copper were 0.061, 0.358, 0.002, 0.002, 0.025 and 0.022 mg/L, respectively. Due to the high quantity of rainfall, a significant amount of annual contamination loading is generated from the nonpoint sources of the residential area.

Major fluvial erosion and a 500‐Mt sediment pulse triggered by lava‐dam failure, Río Coca, Ecuador

AbstractThe failure of a 144‐m‐high lava‐dam waterfall on the Río Coca, Ecuador, in February 2020 initiated a catastrophic watershed reset—regressive erosion upstream and a massive sediment pulse downstream—as the river evolves towards a new equilibrium grade. The evolution of this river corridor after a sudden base‐level fall embodies the “complex response” concepts long understood through laboratory experiments, numerical modelling and smaller‐scale field studies, but that have not been observed in the field before on this scale. This paper presents geomorphic and geotechnical data to characterize the evolution of the Río Coca since 2020. In the three years after the lava‐dam failure, the erosion front migrated almost 13 km upstream along the mainstem river and triggered secondary headcuts that began migrating up tributaries. Erosion of the mainstem and tributary valleys generated a sediment pulse estimated to be 277 million m3 and ~500 million tonnes (Mt) over three years, depositing sediment tens of meters thick over tens of kilometres downstream from the former waterfall. This sediment pulse is one of the largest in modern times, comparable to the annual sediment load of a major continent‐draining river but with orders‐of‐magnitude greater sediment yield. Geomorphic adjustment of the Río Coca represents a highly unusual natural disaster threatening life, property, water quality, the regional economy, major infrastructure and energy security. However, this event also provides a rare opportunity to learn how a large autogenic watershed disturbance and recovery evolve, with important lessons for interpreting the sedimentary record of volcanic landscapes.