Elevated Risk of Compound Extreme Precipitation Preceded by Extreme Heat Events in the Upper Midwestern United States

Compound extreme events can potentially cause deadlier socio-economic consequences. Although several studies focused on individual extreme climate events, the occurrence of compound extreme events is still not well studied in the upper Midwestern United States. In this study, compound extreme precipitation preceded by extreme hot day events was investigated. Results showed a strong linkage between extreme precipitation events and extreme hot days. A significant increasing trend was noticed mainly in Iowa (10.1%), northern parts of Illinois (5.04%), and Michigan (5.04%). Results also showed a higher intensity of extreme precipitation events preceded by an extremely hot day compared to the intensity of extreme precipitation events not preceded by an extremely hot day, mostly in the central and lower parts of Minnesota, western and upper parts of Iowa, lower and upper parts of Illinois, parts of Ohio, Michigan, and Wisconsin for 1950–2010. In other words, extreme heat contributed to more extreme precipitation events. Our findings would provide important insights related to flood management under future climate change scenarios in the region

ThSSim : A novel tool for simulation of reservoir thermal stratification

AbstractThis study presents a novel tool, ThSSim, for simulation of thermal stratification (ThS) in reservoirs. ThSSim is a simple and flexible reduced-order model-based the basis function (RMBF) that combines CE-QUAL-W2 (W2) and proper orthogonal decomposition (POD). In a case study, it was used to simulate water temperature in the Karkheh Reservoir (KR), Iran, for the period 2019–2035. ThSSim consists of two space- and time-dependent components that add predictive ability to the RMBF, a major refinement that extends its practical applications. Water temperature simulations by the W2 model at three-hour time intervals for the KR were used as input data to the POD model to develop ThSSim. To add predictive ability to ThSSim and considering that space-dependent components are not a function of time, we extrapolated the first three time-dependent components by September 30, 2035. We checked the predictive ability of ThSSim against water temperature profiles measured during eight sampling campaigns. We then applied ThSSim to simulate water temperature in the KR for 2019–2035. Simulated water temperature values matched well those measured and obtained by W2. ThSSim results showed an increasing trend for surface water temperature during the simulation period, with a reverse trend observed for water temperature in the bottom layers for three seasons (spring, summer and autumn). The results also indicated decreasing and increasing trends in onset and breakdown of thermal stability, respectively, so that the duration of ThS increased from 278 days in 2019 to 293 days in 2035. ThSSim is thus useful for reservoir temperature simulations. Moreover, the approach used to develop ThSSim is widely applicable to other fields of science and engineering.Abstract This study presents a novel tool, ThSSim, for simulation of thermal stratification (ThS) in reservoirs. ThSSim is a simple and flexible reduced-order model-based the basis function (RMBF) that combines CE-QUAL-W2 (W2) and proper orthogonal decomposition (POD). In a case study, it was used to simulate water temperature in the Karkheh Reservoir (KR), Iran, for the period 2019–2035. ThSSim consists of two space- and time-dependent components that add predictive ability to the RMBF, a major refinement that extends its practical applications. Water temperature simulations by the W2 model at three-hour time intervals for the KR were used as input data to the POD model to develop ThSSim. To add predictive ability to ThSSim and considering that space-dependent components are not a function of time, we extrapolated the first three time-dependent components by September 30, 2035. We checked the predictive ability of ThSSim against water temperature profiles measured during eight sampling campaigns. We then applied ThSSim to simulate water temperature in the KR for 2019–2035. Simulated water temperature values matched well those measured and obtained by W2. ThSSim results showed an increasing trend for surface water temperature during the simulation period, with a reverse trend observed for water temperature in the bottom layers for three seasons (spring, summer and autumn). The results also indicated decreasing and increasing trends in onset and breakdown of thermal stability, respectively, so that the duration of ThS increased from 278 days in 2019 to 293 days in 2035. ThSSim is thus useful for reservoir temperature simulations. Moreover, the approach used to develop ThSSim is widely applicable to other fields of science and engineering

Metal contamination assessment in water column and surface sediments of a warm monomictic man-made lake : Sabalan Dam Reservoir, Iran

AbstractIn this study, metal concentrations in the water column and surface sediment of the Sabalan Dam Reservoir (SDR) were determined. Moreover, heavy metal pollution index (HPI), contamination index (CI), heavy metal evaluation index (HEI), enrichment factor (EF), geo-accumulation index (Igeo), sediment quality guidelines (SQGs), consensus-based SQGs (C-BSQGs), and mean probable effect concentration quotients (mPECQs) were evaluated for water and sediments of SDR. It was observed that metal concentrations in river entry sediment were lower, but those in river entry water were higher than corresponding values in the vicinity of the dam structure. The HPI values of water samples taken from 10 m depth in the center of SDR exceeded the critical limit, due to high concentrations of arsenic. However, according to CI, the reservoir water was not contaminated. The HEI values indicated contamination of SDR water with metals at 10 m depth. A comparison of water quality indices revealed that HEI was the most reliable index in water quality assessment, while CI and HPI were not sufficiently accurate. For SQGs, As and Cu concentrations in sediments were high, but mPECQ, Igeo, and EF revealed some degree of sediment pollution in SDR. The calculated EF values suggested minor anthropogenic enrichment of sediment with Fe, Co, V, and Ni; moderate anthropogenic enrichment with As and Mn; and moderate to severe anthropogenic enrichment with Cu. A comparison of SQG values revealed that the threshold effect and probable effect levels were the most reliable metrics in the assessment of sediment toxicity. Statistical analysis indicated similarities between metal concentrations in the center of the reservoir and near to the dam structure, as a result of similar sediment deposition behavior at these points, while higher flow velocity at the river entry point limited deposition of fine particles and associated metals.Abstract In this study, metal concentrations in the water column and surface sediment of the Sabalan Dam Reservoir (SDR) were determined. Moreover, heavy metal pollution index (HPI), contamination index (CI), heavy metal evaluation index (HEI), enrichment factor (EF), geo-accumulation index (Igeo), sediment quality guidelines (SQGs), consensus-based SQGs (C-BSQGs), and mean probable effect concentration quotients (mPECQs) were evaluated for water and sediments of SDR. It was observed that metal concentrations in river entry sediment were lower, but those in river entry water were higher than corresponding values in the vicinity of the dam structure. The HPI values of water samples taken from 10 m depth in the center of SDR exceeded the critical limit, due to high concentrations of arsenic. However, according to CI, the reservoir water was not contaminated. The HEI values indicated contamination of SDR water with metals at 10 m depth. A comparison of water quality indices revealed that HEI was the most reliable index in water quality assessment, while CI and HPI were not sufficiently accurate. For SQGs, As and Cu concentrations in sediments were high, but mPECQ, Igeo, and EF revealed some degree of sediment pollution in SDR. The calculated EF values suggested minor anthropogenic enrichment of sediment with Fe, Co, V, and Ni; moderate anthropogenic enrichment with As and Mn; and moderate to severe anthropogenic enrichment with Cu. A comparison of SQG values revealed that the threshold effect and probable effect levels were the most reliable metrics in the assessment of sediment toxicity. Statistical analysis indicated similarities between metal concentrations in the center of the reservoir and near to the dam structure, as a result of similar sediment deposition behavior at these points, while higher flow velocity at the river entry point limited deposition of fine particles and associated metals

Precision Nitrogen Management in Spring Rice (Oryza sativa L.) using Decision Support Tools in Chitwan, Nepal

The blanket prescription of nitrogen (N) fertilizer often results in irrational fertilization. To address this issue and align the application of nitrogen fertilizers with the crop-specific demand, it is imperative to save nitrogen resources, maximize the uptake and net income, and subside environmental pollution. In this context, a field experiment was carried out in Kumroj, Chitwan, Nepal during 2022 to assess the growth, yield, and profitability of rice production by comparing different precision nitrogen management practices. The study was carried out in a randomized complete block design with seven treatments and three replications. The treatments included decision support tools for nitrogen management such as the Green Seeker (GS), the Soil plant analysis development Development (SPAD) meter, and the Leaf Color Chart (LCC) combined with basal application of nitrogen at 30 kg ha–1 and the Urea briquette Deep Placement (UDP), the Polymer Coated Urea (PCU), and the Recommended Dose of Fertilizers (RDF, 120 kg N ha–1). The growth, yield, yield attributes, and financial data were taken. Precision nitrogen management techniques significantly enhanced rice growth and yield parameters. GS–guided application required the highest nitrogen demand (155 kg ha–1), while SPAD (80 kg ha–1) and UDP (78 kg ha–1) resulted in lower usage. PCU and UDP enhanced plant height, leaf area index, and above–ground dry matter. Higher grain yield (6.64 t ha–1) was attained with LCC, SPAD (6.44 t ha–1), and UDP (6.41 t ha–1) treatments. GS application exhibited the highest straw yield (11.17 t ha–1), while LCC demonstrated the highest benefit–cost ratio (1.96). This study concluded that SPAD and UDP demonstrated the potential to save nitrogen resources, while LCC and UDP were found profitable

A Comprehensive Assessment of Apple Production in Jumla District, Nepal: Status, Economics, Marketing and Challenges

Apple production is a vital sector of agriculture in Nepal, significantly impacting local livelihoods and the regional economy. This study, conducted in Jumla District, Nepal, from January to July 2022, aims to comprehensively assess apple production, including its existing conditions, economic implications, marketing and challenges. The research hypothesizes that while apple production in Jumla District contributes significantly to the local economy, it faces challenges related to pest and disease management, marketing, and adoption of modern practices. Using Statistical Package for Social Science (SPSS), descriptive statistics were computed based on data collected from a sample of 80 respondents selected through simple random sampling. The result revealed that agriculture constituted the primary source of income for 73.75% of the population, with an average landholding size of 0.3428 ha and an apple-growing land area of 0.3164 ha. Income from apple production, along with vegetables and fruits, was a major income source. The average annual sales of apple production were 7.291 t/ha. Labor costs accounted for 45.67% of the total cost of apple production, with an average total production cost of NPR 238,097.2 and average gross returns of NPR 485,500. Apple productivity was 9.71 t/ha, demonstrating its economic viability with net returns of NPR 247,402.80 per ha and benefit cost ratio of 2.039. However, the study found that farm produce only sufficed for 6-9 months, with pest and disease incidence and marketing issues as major challenges. Interventions should address pest and disease management, marketing strategies, and modern practices adoption to enhance sustainable and profitable apple production in Jumla. Efforts to extend farm produce sufficiency should also be explored, highlighting apple production's potential and the need for targeted support to overcome challenges and foster sector development

Combining Environmental Monitoring and Remote Sensing Technologies to Evaluate Cropping System Nitrogen Dynamics at the Field-Scale

Nitrogen (N) losses from cropping systems in the U.S. Midwest represent a major environmental and economic concern, negatively impacting water and air quality. While considerable research has investigated processes and controls of N losses in this region, significant knowledge gaps still exist, particularly related to the temporal and spatial variability of crop N uptake and environmental losses at the field-scale. The objectives of this study were (i) to describe the unique application of environmental monitoring and remote sensing technologies to quantify and evaluate relationships between artificial subsurface drainage nitrate (NO3-N) losses, soil nitrous oxide (N2O) emissions, soil N concentrations, corn (Zea mays L.) yield, and remote sensing vegetation indices, and (ii) to discuss the benefits and limitations of using recent developments in technology to monitor cropping system N dynamics at field-scale. Preliminary results showed important insights regarding temporal (when N losses primarily occurred) and spatial (measurement footprint) considerations when trying to link N2O and NO3-N leaching losses within a single study to assess relationship between crop productivity and environmental N losses. Remote sensing vegetation indices were significantly correlated with N2O emissions, indicating that new technologies (e.g., unmanned aerial vehicle platform) could represent an integrative tool for linking sustainability outcomes with improved agronomic efficiencies, with lower vegetation index values associated with poor crop performance and higher N2O emissions. However, the potential for unmanned aerial vehicle to evaluate water quality appears much more limited because NO3-N losses happened prior to early-season crop growth and image collection. Building on this work, we encourage future research to test the usefulness of remote sensing technologies for monitoring environmental quality, with the goal of providing timely and accurate information to enhance the efficiency and sustainability of food production

Innovations in Research and Extension: The DIRECT4AG Project, Part 1; An Introduction

On the dust and winds of Midwestern October, combines roll through an annual rite of passage. In 2024, a hotter and (mostly) drier fall is capping off a strong growing season helping speed the harvest of an expected bumper crop (Thiesse, October 10, 2024; Pope, October 9, 2024; Barnett, September 24, 2024). In the cab, many farmers are also likely planning for next year; like scientists, they use data, observations, and experience to tweak the formulas for optimal outcomes. Farmers rely on the results from their fields and the collective knowledge of agriculture writ large. For researchers, this all can feed the imagining of a digitized repository of field experiments and information on crop performance, coupled with weather and management practices, accessible for critical on-farm decisions, further research, and public policy. To those ends, this article introduces a series discussing innovations in research and extension by the DIRECT4AG project (USDA-REEIS)

The DIRECT4AG Project, Part 3: Technology for Cover Crop Establishment

As combines continue to roll across Midwestern farm fields, the machines serve up reminders about the vast technological advancements in modern farming (see e.g., Castillo, June 3, 2024; Farm Progress, February 15, 2024). There are also reminders that technology for conservation practices and sustainable farming systems has not advanced at the same pace or to a similar degree, presenting opportunities for research and development. The DIRECT4AG project seeks to facilitate the adoption of emerging agricultural advancements that create value for the farmer, while also facilitating productive and sustainable farming practices (farmdoc daily, October 21, 2024; October 14, 2024). This third article in the series reviews collaborative efforts with other research projects to test effective ways to implement cover crops into commercial agricultural systems