Runoff Loss Research Articles

Effectiveness of a 10-year continuous reduction of controlled-release nitrogen fertilizer on production, nitrogen loss and utilization of double-cropping rice

Considerable literature has demonstrated the advantage of controlled-release nitrogen (CRN) fertilizer in improving crop productivity. However, few researches have explored the long-term impacts of using CRN fertilizers as alternative to common urea on production and N utilization in double-cropping paddy. To address this gap, our study utilized a database derived from a 10-year field experiment from 2013 to 2022. During early and late rice seasons, compared to common urea (early rice, 150 kg hm−2; late rice, 180 kg hm−2), CRN fertilizer (150 kg hm−2; 180 kg hm−2) input significantly increased yield by 7.4 %, and 11.7 %, as well as N use efficiency (NUE) from 23.0 % and 24.6 % to 33.0 % and 37.5 %, respectively. CRN application significantly reduced N losses, evidenced by decrease in runoff (23.1 % and 19.4 %), leaching (12.7 % and 12.1 %), ammonia volatilization (28.9 % and 30.2 %), and N2O emissions (10.4 % and 16.1 %). A reduction of 10 % in CRN fertilizer input maintained yield. Compared with normal amount, reducing 10, 20, and 30 % CRN input increased NUE by 7.0–7.6 %, 7.3–7.4 %, and 11.6–12.6 %; reduced runoff loss by 16.1–17.9 %, 27.9–30.7 %, and 35.0–37.2 %; decreased leaching loss by 7.6–12.8 %, 18.1–22.6 %, and 26.5–31.4 %; decreased ammonia volatilization by 9.9–12.3 %, 16.3–22.7 %, and 23.2–29.3 %, and decreased N2O loss by 7.8–13.3 %, 12.8–32.8 %, and 20.3–36.9 %, respectively. Soils with CRN input showed higher total and inorganic N contents than the soils with common urea, and the content increased in parallel with CRN fertilizer input. Soil N content and N runoff loss were significantly related to yield and N uptake, and N runoff and leaching losses were significantly related to NUE. These results support the sustainable use of CRN fertilizers as a viable alternative to common urea, indicating that application rate of 135 and 162 kg N hm−2 of early and late rice, respectively, maintain yield and enhance N utilization in double-season paddy of southern China.

Intensified cropping reduces soil erosion and improves rainfall partitioning and soil properties in the marginal land of the Indian Himalayas

Environmental crises, land degradation, declining factor productivity, and farm profitability questioned the sustainability of linear economy-based existing agricultural production model. Hence, there is a dire need to design and develop circular economy-based production systems to meet the twin objectives of environmental sustainability and food security. Therefore, the productive capacity, natural resource conserving ability, and biomass recycling potential of four intensified maize-based systems viz. maize (Zea mays) + sweet potato (Ipomoea batatas)-wheat, maize + colocasia (Colocasia esculenta)-wheat, maize + turmeric (Curcuma longa), and maize + ginger (Zingiber officinale) were tested consecutively for three years (2020, 2021 and 22) in a fixed plot manner at Dehradun region of the Indian Himalaya against the existing maize-wheat systems. The result showed that the maize + sweet potato-wheat system significantly reduced runoff loss (166.3 mm) over the maize-wheat system. The highest through fall (68.12 %) and the lowest stem flow (23.54 %) were recorded with sole maize. On the contrary, the maize + sweet potato system has the highest stem flow (36.15 %) and the lowest through fall. Similarly, the maize + sweet potato system had 5.6 times lesser soil erosion and 0.77 t ha−1 higher maize productivity over the maize-wheat system. Furthermore, the maize + sweet potato system recorded significantly higher soil moisture (19.3%), infiltration rate (0.95 cm h−1), and organic carbon (0.78%) over the rest of the systems. The maize + sweet potato system also recycled the highest nitrogen (299.2 kg ha−1), phosphorus, (31.0 kg ha−1), and potassium (276.2 kg ha−1) into the soil system. Hence, it can be inferred that concurrent cultivation of sweet potato, with maize, is a soil-supportive, resource-conserving, and productive production model and can be recommended for achieving the circular economy targets in the Indian Himalayas.

Ancient agricultural terrace walls control floods and regulate the distribution of Asphodelus ramosus geophytes in the Israeli arid Negev

Ancient stone terrace walls aimed at harvesting water runoff and facilitating crop production are widespread across the drylands of the Middle East and beyond. In addition to retaining the scarce water resource, the terrace walls also conserve soil and thicken its profile along ephemeral stream channels (wadis) by decreasing fluvial connectivity and mitigating erosional processes. In this study, we created hydrological models for three wadis with ancient stone terrace walls in the arid northern Negev of Israel, where the predominant geophyte species is Asphodelus ramosus L. A two-dimensional (2D) rain-on-grid (RoG) approach with a resolution of 2 m was used to simulate the rain events with return periods of 10, 20, 50, and 99 % (10-y, 5-y, 2-y, and yearly, respectively) based on the Intensity-Duration-Frequency rain curves for the region. To evaluate the effect of stone terrace walls on fluvial hydrology and geomorphology, the ground level was artificially elevated by 20 cm at the wall locations in a digital terrain model (DTM), using the built-in HEC-RAS 2D terrain modification tool. Our results showed that the terraced wadis have a high capacity to mitigate runoff loss, but a lesser capacity to delay the peak flow. Yet, for all rainstorm return periods, peak flow mitigation was positively related to the number of terrace walls along the stream channel. Field surveys in two of the studied wadis demonstrated that the A. ramosus clones were found in proximity to the stone terrace walls, presumably due to the greater soil–water content there. The results thus suggest that the terrace walls provide improved habitat conditions for these geophytes, supporting their growth and regulating their distribution along the wadi beds.

Straw mulching alters the composition and loss of dissolved organic matter in farmland surface runoff by inhibiting the fragmentation of soil small macroaggregates

Straw mulching is a widespread practice for reducing the soil carbon loss caused by erosion. However, the effects of straw mulching on dissolved organic matter (DOM) runoff loss from black soil are not well studied. How straw mulching affects the composition and loss of runoff DOM by changing soil aggregates remains largely unclear. Here, a straw mulching treatment was compared to a no mulching treatment (as a control) on sloping farmland with black soil erosion in Northeast China. We divided the soil into large macroaggregates (>2 mm), small macroaggregates (0.25–2 mm), and microaggregates (<0.25 mm). After five rain events, the effects of straw mulching on the concentration (characterized by dissolved organic carbon (DOC)) and composition (analyzed by fluorescence spectroscopy) of runoff and soil aggregate DOM were studied. The results showed that straw mulching reduced the runoff amount by 54.7%. Therefore, although straw mulching increased the average DOC concentration in runoff, it reduced the total runoff DOM loss by 48.3%. The composition of runoff DOM is similar to that of soil, as both contain humic-like acid and protein-like components. With straw mulching treatment, the protein-like components in small macroaggregates accumulated and the protein-like components in runoff declined with rain events. Fluorescence spectroscopy technology may help in understanding the hydrological paths of rain events by capturing the dynamic changes of runoff and soil DOM characteristics. A variation partitioning analysis (VPA) indicated that the DOM concentration and composition of microaggregates explained 68.2% of the change in runoff DOM from no mulching plots, while the change in runoff DOM from straw mulching plots was dominated by small macroaggregates at a rate of 55.1%. Taken together, our results demonstrated that straw mulching reduces the fragmentation of small macroaggregates and the loss of microaggregates, thus effecting DOM compositions in soil and reducing the DOM loss in runoff. These results provide a theoretical basis for reducing carbon loss in sloping farmland.

An actuarial comparison of loss-ratio-Bornhuetter-Ferguson and classical chain ladder techniques in insurance loss reserving: A computational approach

An insurance firm promises to reimburse benefits to the insured when unforeseen events evolve. When such contingencies arise, the underwriter has a liability to pay the claim through loss reserving techniques. The estimation of such loss reserving should be technically performed so the insurance firm will not run into a loss. This study aims to (i) estimate the Bornheutter-Ferguson reserve and the inverse of its development factor λn under the aegis of the loss ratio framework. (ii) numerically estimate the chain ladder reserve and final losses, (iii) estimate the Ratio of cumulative payments in successive development periods, and (iv) demonstrate to professional insurance firms how to use these techniques in practice. These techniques evaluated through some run-off loss matrix can be employed to estimate technical provisions for the outstanding claims. Computational evidence from our results over the periods analyzed confirms that on the assumption of 0.9 the loss ratio, the Bornheutter- Ferguson technique as an actuarial extension of the chain ladder method numerically presents a lower reserve value than the corresponding chain ladder reserve, and hence CLreserve=249,811.708&gt;BFreserve=86,612.58.

Optimal fertilizer rates towards the improvement of nitrogen use efficiency and reduction of nitrogen export in paddy rice-wheat intensive farming

Introduction: Fertilizer application above plant nitrogen (N) requirements, leading to N use inefficiency, has become the primary source of N surplus, posing nonpoint pollution threats. Chao Lake has received N loadings, primarily from the agroecosystem that surrounds it. Based on 10 years of field monitoring and experiment, this study used optimum fertilizer rates (30% N reduction) to evaluate nitrogen use efficiency (NUE) and N export in the Chao Lake watershed of paddy rice-wheat rotational farming.Methods: Five treatments were tested, namely, the Blank Treatment (CK), Conventional Fertilization Treatment (CFT), High Fertilization Treatment (HFT), Reduced Fertilization Treatment (CFT), Reduced Fertilization Treatment plus Straw addition (RFTS). The parameters employed to measure NUE were 1) by calculating NUE indicators; Agronomic efficiency (kg kg-1), recovery efficiency (%), and partial factor productivity (kg kg-1) 2) using the European Union NUE framework as a comparison tool. N export was measured using N export parameters, namely, nitrogen loading (kg ha-1yr-1), nitrogen runoff loss ratio (%), and net nitrogen runoff loss ratio (%).Results and discussion: Results revealed that optimum N fertilizer input levels maintained high crop and biomass yields. The empirical model of y = y0 + a * exp (−0.5 * (x-x0)/b2) explains the relationships between input N fertilizer and corresponding yield returns. Low yield responses to increased N input beyond certain limits were observed, which may lead to N accumulations. N export was much lower from the reduced fertilization treatments than other treatments. N export increased in 10 years for both paddy rice and wheat seasons. Runoff volume influenced N export more than any other environmental factor studied.Conclusion: Overall, optimal fertilizer levels produced high NUE, maintained high economic yield, and produced lesser N exports; NUE was in the order of reduced &amp;gt; high &amp;gt; conventional fertilization treatments, while it decreased in 10 years (2008–2018) across all treatments. Such strategies that further reduce fertilizer levels by accounting for excess supplies are vital for consolidating effective N control measures.

Nutrient runoff loss from saline-alkali paddy fields in Songnen Plain of Northeast China via different runoff pathways: effects of nitrogen fertilizer types.

The application of nitrogen (N) fertilizer aggravates the nutrient runoff loss from paddy, causing serious agricultural non-point source pollution, and leading to a serious decline in water quality. The global area of saline-alkali paddy has expanded, but the response of nutrient loss via runoff to N-fertilizer applications in saline-alkali paddy is still unclear. This study conducted a 147-day field experiment to evaluate the nutrient runoff loss from saline-alkali paddy with different N-fertilizer application strategies in Songnen Plain of Northeast China. Regardless of N-fertilizer types, the nutrient loss via rainfall runoff in the entire rice-growing season was significantly (p < 0.05) higher than that via artificial drainage. The N and phosphorus (P) concentrations in runoff water were correlated with salinity and alkalinity. Especially, pH had a significant positive correlation with total-P (TP) (r = 0.658, p < 0.01). In the entire rice-growing season, the TN runoff losses in urea (U), microbial fertilizer (MF), and inorganic compound fertilizer (ICF) treatments were significantly (p < 0.05) lower compared with carbon-based slow-release fertilizer (CSF) and organic-inorganic compound fertilizer (OCF), respectively. Meanwhile, the TP runoff losses in OCF and ICF treatments were significantly (p < 0.05) lower than U and MF, respectively. Overall, the application of ICF is a better choice to avoid N and P losses via runoff from saline-alkali paddy fields.

Connecting the dots: Path model to identify key phenotypic traits for screening plants with tolerance to nitrogen deficiency.

Varieties that tolerate low nitrogen (N) application rates can reduce fertilizer costs, minimize nitrate leaching and runoff losses, and lower overall CO2 emissions associated with fertilizer manufacturing. The goal of our research is to show the usefulness of path models to identify key phenotypic traits for screening plants with a tolerance to low N application rates. We grew tolerant and sensitive cultivars of poinsettia (Euphorbia pulcherrima) using a water-soluble fertilizer (15-5-15 Cal Mag) in both optimal (electrical conductivity of 2.5 dS·m-1) and N-deficient (electrical conductivity of 0.75 dS·m-1) treatments and measured 24 different traits at the cellular, leaf, and whole-plant scales in both cultivars and treatments. The experiment was laid out as a split-plot design with N treatments as main plots and cultivars as sub-plots, with five replications. Path analysis was conducted to develop sequential relationships among these traits. Statistical comparisons between tolerant and sensitive cultivars in the N-deficient treatment indicated an increase in shoot biomass (19.9 vs 14.4 g), leaf area (2775 vs 1824 cm2), leaf dry weight (14.7 vs 10.0 g), lateral root dry weight (3.7 vs 2.4 g), light-saturated photosynthesis (14.5 vs 10.1 μmol∙m-2∙s-1), maximum electron transport rate (119 vs 89 μmol∙m-2∙s-1), chlorophyll content (28.1 vs 12.9 g∙100g-1), leaf N content (27.5 vs 19.9 mg∙g-1), and fine root N content (26.1 vs 20.9 mg∙g-1), and a decrease in anthocyanin content (0.07 vs 0.16 ΔOD∙g-1). The path model indicated that an increase in the lateral root growth and fine root N content can lead to an increase in the leaf N content, in the N-deficient treatment. There were three separate paths that connected higher leaf N content to increased shoot biomass. These paths were mediated by the levels of anthocyanin, chlorophylls, and light-saturated photosynthesis rate (or rubisco capacity). The light-saturated photosynthesis model suggested that the increased uptake of N by fine roots in the tolerant cultivar was likely supported by the photosynthates translocated from the shoot to the root. Leaf N content was associated with multiple plant responses in the N-deficient treatment, and can be a useful screening trait for developing new cultivars, especially in marker-assisted molecular breeding.

Controlled-Release Blended Fertilizer Combined with Urea Reduces Nitrogen Losses by Runoff and Improves Nitrogen Use Efficiency and Yield of Wet Direct-Seeded Rice in Central China

Controlled-release fertilizer is one of the best fertilizer management strategies for improving the yield and nitrogen use efficiency of transplanted seedling rice. Wet direct-seeded rice has gradually replaced transplanted seedling rice since it saves labor. In addition, it is conducive to mechanization promotion. However, the effects of controlled-release fertilizers on wet direct-seeded rice remain largely unknown. A two-year field experiment aimed to compare the effects of controlled-release blended fertilizer at two rates (basal N to tiller N ratio = 7:3 (CRBF+U), CRBF alone), urea at two rates (basal–tiller ratio of 4:6 (U40), 6:4 (U60)) and a control (no N fertilizer) on the ammonia volatilization (AV) loss, nitrogen runoff loss, accumulation, transport, utilization and yield of rice. The nitrogen runoff loss in wet direct-seeded rice paddy fields was concentrated from sowing to the three-leaf and one-leaflet stage, and the loss rat was lowest after CRBF+U (11.41–12.94%). AV loss rate was lowest after CRBF (3.41%), followed by CRBF+U (3.55–3.89%). CRBF+U increased nitrogen accumulation by extending the duration of rapid nitrogen growth and accelerating maximum nitrogen growth. CRBF+U also increased the nitrogen transport rate of stems, sheaths and leaves from full heading to maturity, and intensified the increase in nitrogen in panicles, increasing the harvest index, agronomy utilization rate and apparent utilization rate of nitrogen. Finally, the grain number per panicle, seed-setting rate and actual yield of rice were significantly improved. In conclusion, CRBF+U can reduce nitrogen runoff loss and AV loss and can improve the yield and nitrogen use efficiency of wet direct-seeded rice.

Estimation of Cropland Nitrogen Runoff Loss Loads in the Yangtze River Basin Based on the Machine Learning Approaches

A quantitative understanding of cropland nitrogen (N) runoff loss is critical for developing efficient N pollution control strategies. Using correlation analysis, a structural equation model, variance decomposition, and machine learning methods, this study identified the primary influencing factors of total N (TN) runoff loss from uplands (n=570) and paddy (n=434) fields in the Yangtze River Basin (YRB) and then developed a machine learning-based prediction model to quantify cropland N runoff loss load. The results indicated that runoff depth, soil N content, and fertilizer addition rate were the major influencing factors of TN runoff loss from uplands, whereas TN runoff loss rate from paddy fields was mainly regulated by runoff depth and fertilizer addition rate. Among the four used machine learning methods, the prediction models based on the random forest algorithm presented the highest accuracy (R2=0.65-0.94) for predicting upland and paddy field TN runoff loss rates. The random forest algorithm based model estimated a total cropland TN loss load in the YRB of 0.47 Tg·a-1 (upland:0.25 Tg·a-1; paddy field:0.22 Tg·a-1) in 2013, with 58% of TN runoff loss load derived from the midstream and downstream regions. The models predicted that TN runoff loss loads from croplands in YRB would decrease by 2.4%-9.3% for five scenarios, with higher TN load reductions occurring from scenarios with decreased runoff amounts. To mitigate cropland N nonpoint source pollution in YRB, it is essential to integrate efficient water, fertilizer, and soil nutrient managements as well as to consider the midstream and downstream regions as the high priority area. The machine learning-based modeling method developed in this study overcame the difficulty of identifying the functional relationships between cropland TN loss rate and multiple influencing factors in developing relevant prediction models, providing a reliable method for estimating regional and watershed cropland TN loss load.

Effects of microtopography change driven by seepage and slope gradients on hillslope erosion of purple soil

Seepage is the prominent hydrological process on tilled hillslopes covered by purple soil, which can easily exacerbate slope instability and soil loss. Laboratory simulated experiments with a seepage intensity of 4 L min−1 under different slope gradients (5°, 10°, and 15°) were conducted to analyze how seepage induced the erosion impacts the microtopographic change during water erosion process. Three tillage practices, i.e., smooth slope (CK), artificial diffing (AD) and ridge tillage (RT) with different initial microrelief were designed in this study. Results showed that the variation of soil surface roughness (SSR) to seepage erosion showed CK > AD > RT, and the most severe on the midslope and downslope, fluctuating from −4.23% to 12.40%. The sharpness of soil surface microtopography (SSM) on RT and AD decreased as the slope gradient increased. Compared to CK, AD and RT effectively controlled runoff loss. Both AD and RT were unable to reduce soil loss when the seepage duration exceeded 45 min, that was, the sediment yield increased by 815.50% and 730.25%, respectively. The response of surface runoff and sediment yields to microtopography changes was characterized applying multivariate linear equation. The applicability of multifractal parameters was weakened in the terms of the response to soil erosion caused by seepage. In contrast, the contribution rate of RUp to soil erosion was 69.40% and that of RDown was 58.76% in SSR indexes under seepage condition, which were the optimal parameters assessing the changes of surface runoff and sediment yields. This study contributes to elucidating seepage erosion effects in purple soil slope and understanding hydrological processes based on SSM changes.

Influence of concrete material of runoff collection containers on monitoring of nitrogen and phosphorus pollutants.

The accurate monitoring of N and P surface runoff losses from farmland is crucial to control agricultural nonpoint source pollution. A pond constructed with concrete material (CM) is a common collection container used during field experiments in China, but the adsorption characteristics of concrete may cause a considerable underestimation of surface runoff losses from farmland. To characterize any neglected error caused by the collection container material, a laboratory experiment was conducted comparing the N and P contents of runoff samples collected from CM and plastic material (PM) containers. The results indicated that CM containers significantly lowered N and P sample contents compared with PM containers, which was attributed to the adsorption capacity of pollutants by CM containers. This was confirmed by scanning electron microscopy (SEM) images of particles retained in CM containers. In an attempt to alleviate this error, three common water-repellent materials were applied to CM containers that significantly limited the pollutant adsorption of CM containers. Moreover, it was shown that there was no significant difference between the calculated concentration of runoff losses and the total amount of pollutants. To calibrate the observational error from CM containers, stepwise multiple regression models of different forms of N and P pollutants were developed. The results of this study suggest that treating CM containers with water repellent is an effective measure for improving the accuracy of new-built monitor points of agricultural nonpoint source pollutants. In addition, the calibration of observational error from CM containers and delayed sampling is essential to estimate agricultural nonpoint source pollution load via the surface runoff from farmland based on data from monitor points.

Returned straw reduces nitrogen runoff loss by influencing nitrification process through modulating soil C:N of different paddy systems

Nitrogen (N) runoff loss from paddy fields contributes significantly to non-point source pollution. Straw return to soil may affect N runoff loss by changing soil biochemistry. In situ N runoff monitoring combined with an analysis of soil biochemical indicators was implemented to explore the effect of straw return lasting for five or six years on N runoff loss and its potential mechanism in five rice rotation systems. The results showed that straw return reduced total N (TN) runoff losses by 2.29%− 26.10% through physical and biochemical pathways, and the reduction in inorganic N (IN) was the largest (53.56%–82.42%) through biochemistry. This was mainly achieved by the increase in soil C:N due to straw return, thereby increasing the immobilization of microbial N and reducing the soil IN. At the same time, the abundance of functional genes (AOA, AOB, nxrA) participating in the nitrification process was also conducive to the decrease in TN runoff concentration. More importantly, the reduction in IN and functional genes of the nitrification process did not affect N uptake by rice, and the increase in the atmospheric N fixation gene (nifH) was also beneficial to N supplementation in soil. However, the positive effects of straw return under the five rice rotation systems were different, and the TN loss reduction in double-cropping rice was the lowest. With the lower soil C:N in the single-cropping and paddy-upland systems, the increase in soil C:N after straw was more effective, and had greater potential to reduce TN runoff loss. This study provides a new perspective on N cycling in soil biochemistry by straw return, so as to select optimal measures to protect the water environment in different rice rotation systems.

Biochar-amended substrate improves nutrient retention in green roof plots

Green roofs can act as pollutant sources due to the nutrients nitrogen (N) and phosphorus (P) leaching from the engineered soil-like substrate. Designing substrate to reduce this effect, while continuing to provide nutrients for plants, is essential to minimize this ecosystem disservice. Biochar is a water-retaining soil additive with the potential to increase stormwater retention and bind nutrients, thus could reduce loss of nutrients in runoff and simultaneously improve plant performance. Over two growing seasons, our study evaluated plant cover, nutrient retention and water retention in green roof experimental plots after the addition of biochar to the substrate. Replicated plots of green roof substrate amended with different amounts of biochar were established, both vegetated (Sedum mixture) and unvegetated. After initial establishment, plant cover was highest in the intermediate (5% w/w) biochar treatment, and lowest in the high (10% w/w) biochar treatment. Biochar addition did not significantly affect water retention, but improved runoff water quality by decreasing phosphorus, organic carbon and organic nitrogen export, all of which were high in runoff from the standard green roof substrate. Biochar was found to be a minor source of nitrate, but this effect was counteracted by plant presence, with plants greatly reducing N runoff losses. Overall, these results strengthen the case for biochar as a potentially useful amendment for green roofs.

Content Variation and Potential Runoff Loss Risk of Nutrients in Surface Water of Saline-Alkali Paddy in Response to the Application of Different Nitrogen Fertilizer Types

As the saline-alkali paddy area continues to grow, the nutrient (e.g., nitrogen (N) and phosphorus (P)) runoff loss is becoming more serious in the world. The N-fertilizer application affects the nutrient runoff loss risk in paddy. Selecting suitable fertilizer types to reduce nutrient loss is beneficial to agricultural sustainability. However, the effects of N-fertilizer application in saline-alkali paddy are not clear. This study measured the N and P concentration of surface water in saline-alkali paddy, using various N—fertilizer treatments (i.e., urea (U), urea with urease—nitrification inhibitors (UI), organic–inorganic compound fertilizer (OCF), carbon—based slow—release fertilizer (CSF), and no N fertilization (CK)). Based on the structural equation model, both phosphate (PO43−-P) and total−P (TP) concentrations had a positive influence on total-N (TN) concentration regardless of N−fertilizer types applied. Potential risks of ammonia—N (NH4+—N) and nitrate—N (NO3−—N) runoff losses were reduced in UI treatment, but the TN and TP losses were increased. At the panicle-initiation fertilizer stage, the NO3−−N, TN, and TP concentrations in CSF and OCF treatments were lower than U. The CSF application can control the TP runoff loss risk during the rice-growing season. UI should not be suggested for the control of nutrient runoff loss in saline-alkali paddy.

Erosion and weathering in carbonate regions reveal climatic and tectonic drivers of carbonate landscape evolution

Abstract. Carbonate rocks are highly reactive and can have higher ratios of chemical weathering to total denudation relative to most other rock types. Their chemical reactivity affects the first-order morphology of carbonate-dominated landscapes and their climate sensitivity to weathering. However, there have been few efforts to quantify the partitioning of denudation into mechanical erosion and chemical weathering in carbonate landscapes such that their sensitivity to changing climatic and tectonic conditions remains elusive. Here, we compile bedrock and catchment-averaged cosmogenic calcite–36Cl denudation rates and compare them to weathering rates derived from stream water chemistry from the same regions. Local bedrock denudation and weathering rates are comparable, ∼20–40 mm ka−1, whereas catchment-averaged denudation rates are ∼2.7 times higher. The discrepancy between bedrock and catchment-averaged denudation is 5 times lower compared to silicate-rich rocks, illustrating that elevated weathering rates make denudation more spatially uniform in carbonate-dominated landscapes. Catchment-averaged denudation rates correlate well with topographic relief and hillslope gradients, and moderate correlations with runoff can be explained by concurrent increases in weathering rates. Comparing denudation rates with weathering rates shows that mechanical erosion processes contribute ∼50 % of denudation in southern France and ∼70 % in Greece and Israel. Our results indicate that the partitioning between largely slope-independent chemical weathering and slope-dependent mechanical erosion varies based on climate and tectonics and impacts the landscape morphology. This leads us to propose a conceptual model whereby in humid, slowly uplifting regions, carbonates are associated with low-lying, flat topography because slope-independent chemical weathering dominates denudation. In contrast, in arid climates with rapid rock uplift rates, carbonate rocks form steep mountains that facilitate rapid, slope-dependent mechanical erosion required to compensate for inefficient chemical weathering and runoff loss to groundwater systems. This result suggests that carbonates represent an end member for interactions between climate, tectonics, and lithology.

Determining nitrogen fate by hydrological pathways and impact on carbonate weathering in an agricultural karst watershed

Identifying the nitrogen (N) fate is complicated and a great challenge in karst watersheds because of the co-existence of natural pools and anthropogenic sources. The objective of the study was to use stable isotopic composition of dual-isotope (δ15NNitrate and δ18ONitrate) and LOADEST model approaches to trace N sources, pathways in karst watershed. The study was conducted in the Houzhai watershed, which is a typical agricultural karst watershed from July 2016 to August 2018, to reveal the N fate and the coupled carbon(C)–N processes occurring in the riverine-watershed with agricultural activities. We found that the wet deposition of total nitrogen (TN) flux was 33.50 kg hm−2·a−1 and dissolved nitrogen (DN) flux was 21.66 kg hm−2·a−1. The DN runoff loss was 2.10 × 105 kg·a−1 and the loss of DN during the wet season accounted for 95.4% over a year. In the wet season, NO3−-N daily efflux was 977.62 ± 516.66 kg ha−1·day−1and 248.77 ± 57.83 kg ha−1·day−1 in the dry season. The NH4+-N efflux was 29.17 ± 10.50 kg ha−1·day−1 and 4.42 ± 3.07 kg ha−1·day−1 in the wet and dry seasons, respectively. The main form output load of N was NO3−-N which was more than 30 times as much as NH4+-N output loss. The NO3−-N caused by rainfall contributed 11.82%–53.61% to the export load. Nitrate from soil contributed over 94% of the N to Houzhai river caused by N leaching. In addition, manure and farmland soil were the main sources of groundwater in the Houzhai watersheds, the contribution rates were 25.9% and 22.5%. The chemical N fertilizers affected carbonate weathering strongly, and the HCO3− flux caused by nitrification due to N fertilizers application in soil accounted for 23.5% of the entire watershed. This study suggested that carbonate weathering may be influenced by nitrogen nitrification in the karst watershed.

A comprehensive investigation of wetting distribution pattern on sloping lands under drip irrigation: A new gradient boosting multi-filtering-based deep learning approach

Accurate estimation of the wetting distribution pattern (WDP) around the emitters of a drip irrigation system in sloping lands can minimize surface runoff losses by determining the placement status of plants and emitters. In this study, both experimental and computational efforts were made to estimate the WDP in sloping lands with drip irrigation. 486 sets of laboratory experiments were conducted and a series of soil characteristics data were collected. Particularly, the upstream wetting radius (R−), downstream wetting radius (R+), and wetting depth (D) were measured and further used as the target variables of three modeling scenarios. In the modeling effort, a new hybrid framework, consisting of a light gradient boosting machine (LightGBM) and best subset regression (BSR) integrated with bidirectional recurrent neural network (Bi-RNN), was developed for precise simulation of WDP. The main model (i.e., Bi-RNN) was compared with the Elman recurrent neural network (ERNN) and bagging regression tree (BGRT) in the advanced multi-filtering framework for all the scenarios. In the first stage, the LightGBM tree-based feature selection filtered the significant predictors in each scenario. In the second stage, the three best possible input combinations using the N predictors selected in the first stage were extracted among 2N possible combinations via the BSR strategy. The performances of the models were evaluated by using different statistical metrics. It was demonstrated that Bi-RNN achieved the highest accuracy in all the hybrid models for the three scenarios, followed by the ERNN and BGRT models. Also, a resampling bootstrap-based uncertainty analysis proved that the developed multistage-filtering strategy before the deep learning model feeding decreased the uncertainty associated with input combination effects. By determining the placement status of plants and emitters, the proposed framework can effectively reduce surface runoff losses.

Effect and Mechanism of Rice-Pasture Rotation Systems on Yield Increase and Runoff Reduction under Different Fertilizer Treatments

This study investigated the effects of crop rotations and different ratios of dairy manure fertilizer on nitrogen loss and rice yield in the Erhai Lake basin. Two kinds of herbages were set in the rotation: Ryegrass (Lolium multiflorum cv.‘Tetragold’) (R) and Villose Vetch (Vicia villosa var. Glabresens) (V). The experiment involved two-year field tests with nine management treatments. The results showed that the rice-Vicia villosa rotation with 70% chemical and 30% dairy cattle manure fertilization increased rice yield significantly, while reducing nitrogen runoff losses and increasing microbial abundance with nitrification and nitrogen fixation. The microbial abundance varied among tested soils, with Alphaproteobacteria, Rhodopseudomonas, Rhizobiales, Bradyrhizobium, and Azotobacter Vinelandii being the highest in 70% chemical fertilizer + 30% manure rice Villose Vetch (R-V) to ameliorate plant growth and strengthen the efficiency of nutrient uptake, whereas that of Planctomycete was comparatively lower to promote long-term N stabilization in soil. The 70% F—30% M R-V treatment also significantly decreased nitrate reductase and ammonia monooxygenase enzyme activity, potentially improving fertilizer use efficiency, and reducing gaseous losses. The LEfSe analysis results indicated that 70% F—30% M R-V fertilizers significantly enhanced the abundances of metabolic genes related to energy and nitrogen. These findings suggested that appropriate agricultural management using rice-Vicia villosa rotation and 70% chemical + 30% dairy cattle manure fertilization can improve the soil quality and sustainability of agroecosystems.

Biochar amendments combined with organic fertilizer improve maize productivity and mitigate nutrient loss by regulating the C–N–P stoichiometry of soil, microbiome, and enzymes

Coupled amendments of biochar and organic fertilizers may be one of the effective practice to ensure high cropland productivity and resource use efficiency, but there is little field-based evidence for this. Herein, we employed a eight-years (2014–2021) field experiment to explore the effectiveness of biochar and organic fertilizer amendments on crop productivity and nutrient runoff losses, as well as to further explored their relationships with the carbon:nitrogen:phosphorus (C:N:P) stoichiometry of soil, microbiome, and enzymes. Experiment treatments include No fertilizer (CK), chemical-only fertilizer (CF), CF + biochar (CF + B), 20% chemical N was replaced by organic fertilizer (OF), and OF + biochar (OF + B). Compared with the CF, the CF + B, OF, and OF + B treatments increased average yield by 11.5%, 13.2%, and 32%, average N use efficiency by 37.2%, 58.6%, and 81.4%, average P use efficiency by 44.8%, 55.1%, and 118.6%, average plant N uptake by 19.7%, 35.6%, and 44.3%, as well as average plant P uptake by 18.4%, 23.1%, and 44.3%, respectively (p ≤ 0.05). Compared with the CF, the CF + B, OF, and OF + B decreased average average total N losses by 65.2%, 97.4%, and 241.2%, and average total P losses by 52.9%, 77.1%, and 119.7%, respectively (p ≤ 0.05). Organic-amended treatments (CF + B, OF, and OF + B) significantly changed soil total and available C, N, and P content, soil microbial C, N, and P content, as well as the potential activities of soil C-, N-, and P-acquiring enzymes. Plant P uptake and P-acquiring enzyme activity were the main drivers of maize yield, which was influenced by the contents and stoichiometric ratios of soil available C, N, and P. These findings suggest that organic fertilizer applications combined with biochar have the potential to maintain high crop yields while reducing nutrient losses by regulating the stoichiometric balance of soil available C and nutrients.