Input Rate Research Articles

Microbial nutrient limitations limit carbon sequestration but promote nitrogen and phosphorus cycling: A case study in an agroecosystem with long-term straw return

Soil fertility can be increased by returning crop residues to fields due to the cooperative regulation of microbial metabolism of carbon (C) and nutrients. However, the dose-effect of straw on the soil C and nutrient retention and its underlying coupled microbial metabolic processes of C and nutrients remain poorly understood. Here, we conducted a comprehensive study on soil nutrients and stoichiometry, crop nutrient uptake and production, microbial metabolic characteristics and functional attributes using a long-term straw input field experiment. We estimated the microbial metabolic limitations and efficiency of C and nitrogen (N) use (CUE and NUE) via an enzyme-based vector-TER model, biogeochemical-equilibrium model and mass balance equation, respectively. In addition, the absolute abundances of 20 functional genes involved in the N- and P-cycles were quantified by quantitative PCR-based chip technology. As expected, straw input significantly increased C and N stocks, C: nutrients, crop nutrient uptake and growth. However, the C sequestration efficiency decreased by approximately 6.1 %, and the N2O emission rate increased by 0.5–1.0 times with the increase in straw input rate. Interestingly, the microbial metabolism was more limited by P when straw input was <8 t ha−1 but was reversed when straw input was 12 t ha−1. The enhanced nutrient limitation reduced both the CUE and the NUE of microbes and then upregulated genes associated with the hydrolysis of C, the mineralization of N and P, and denitrification, which consequently influenced C and N losses as well as crop growth. This study highlights that soil C and nutrient cycling are strongly regulated by microbial metabolic limitation, suggesting that adding the appropriate limiting nutrients to reduce nutrient imbalances caused by straw input is conducive to maximizing the ecological benefits of straw return.

Disc-halo gas outflows driven by stellar clusters as seen in multiwavelength tracers

ABSTRACT We consider the dynamics of and emission from growing superbubbles in a stratified interstellar gaseous disc driven by energy release from supernovae explosions in stellar clusters with masses Mcl = 105 − 1.6 × 106 M⊙. Supernovae are spread randomly within a sphere of rc = 60 pc, and inject energy episodically with a specific rate $1/130~\mathrm{M}_\odot ^{-1}$ proportional to the star formation rate (SFR) in the cluster. Models are run for several values of SFR in the range 0.01 to 0.1 M⊙ yr−1, with the corresponding average surface energy input rate ∼0.04–0.4 erg cm−2 s−1. We find that the discrete energy injection by isolated SNe are more efficient in blowing superbubbles: Asymptotically they reach heights of up to 3 to 16 kpc for Mcl = 105 − 1.6 × 105 M⊙, correspondingly, and stay filled with a hot and dilute plasma for at least 30 Myr. During this time, they emit X-ray, Hα and dust infrared emission. X-ray luminosities LX∝SFR3/5 that we derive here are consistent with observations in star-forming galaxies. Even though dust particles of small sizes a ≤ 0.03 μm are sputtered in the interior of bubbles, larger grains still contribute considerably ensuring the bubble luminosity $L_{\rm IR}/{\rm SFR}\sim 5\times 10^7 \, \mathrm{L}_\odot \, \mathrm{M}_\odot ^{-1} ~{\rm yr}$. It is shown that the origin of the North Polar Spur in the Milky Way can be connected with activity of a cluster with the stellar mass of ∼105 M⊙ and the SFR ∼ 0.1 M⊙ yr−1 some 25–30 Myr ago. Extended luminous haloes observed in edge-on galaxies (NGC 891 as an example) can be maintained by disc spread stellar clusters of smaller masses M* ≲ 105 M⊙.

Exact solutions to fractional pharmacokinetic models using multivariate Mittag-Leffler functions

The aim of this paper is to provide a mathematical study of the amount of drug administered as a continuous intravenous infusion or oral dose. For this purpose, we consider fractional-order mammillary-type models describing the anomalous dynamics of exchange of concentrations between compartments at, constant input rates, power-law type, and in the form of oral doses at given (discrete) times. We have developed a general analysis strategy for these models, in which we have found closed-form analytical solutions written in terms of the multivariate Mittag-Leffler function. Numerical simulations have been performed using our formulas, with parameters from the literature.

FAULT DETECTION AND PROTECTION OF POWER TRANSFORMER USING FUZZY LOGIC

Power transformer malfunctions cause significant power outages and, as a result, material damage. This critical issue must be resolved. Power transformers must be protected from various fault conditions and power system failure. Fuzzy logic is used in this study to detect and protect power system transformer faults. In the simulation system that diagnoses transformer faults and monitors its operating conditions, the fuzzy logic (FL) toolbox in MATLAB/ SIMULINK software was used. The input variables, current and rate of change of current with time, have been identified as "Error" and "Error-Dot" in the programme. The study's findings show that when the output response is zero, the current in the transformer is normal. This is obtained by injecting [0] and [0] input values into the system, resulting in a response of "6e(-017)," which is close to zero. If the output response is greater than zero, the transformer current is rising above normal and the protection scheme should be notified. This condition is achieved by giving the system input values of [-1.5] and [5] and expecting a response of "+5". If the response is less than zero, the transformer current is less than normal, and the protection scheme should be notified. The study concluded that electrical faults and mechanical failures in power transformers can be quickly identified using Fuzzy logic. Thus, power transformer damage is avoided by controlling relays more effectively and quickly. This has resulted in significant savings in maintenance and repair costs. It is assumed that the study was a success. Keywords: Fuzzy logic, Transformer, fault, Detection, Current, Protection

Relationship Between Dissolution Rate in Vitro and Absorption Rate in Vivo of Ketamine Prolonged-Release Tablets.

Understanding the processes that determine the time course of drug absorption rates is of great interest. This study aims to answer the questions: (1) How well can the in vitro dissolution rate predict the in vivo input function (absorption rate) of a prolonged-release ketamine dosage form (PR-ketamine)? (2) Is the information obtained from the in vitro dissolution rate profile useful in estimating bioavailability? In vivo plasma concentration data were obtained from 15 healthy volunteers after intravenous and oral dosing of 20 mg PR-ketamine tablets. Both the dissolution and input rates were modeled by a sum of two inverse Gaussian functions. The absorption process was dissolution-limited but the mean input time exceeded the mean dissolution time. When the delayed dissolution rate was used to fit the oral data, the estimated bioavailability was nearly identical to that obtained with the full model. The in vitro dissolution rate profile could be used to develop a one-point sampling strategy for predicting bioavailability. According to their fractional rate profiles, dissolution and input rates belong to different classes of functions. A comparison of the time course of the absorption rate with that of the dissolution rate can reveal more details of the absorption process.

Wave-induced cross-shore distribution of different densities, shapes, and sizes of plastic debris in coastal environments: A laboratory experiment

Plastic debris is a significant threat to marine and coastal ecosystems. Previous research found that waves, wind, as well as density, size, and shape of microplastics, drive their transport and dispersion. In this paper, a set of laboratory experiments on the effect of waves and wave-induced currents on the input rate and cross-shore transport and dispersion of different types of plastic debris, including the macro and mesosizes, in addition to microplastics is presented. 15 plastic-debris types characterized by different sizes, shapes, and densities, including facemasks, were analyzed under regular and irregular wave conditions. The results show that input and transport rates of plastics depend on their terminal velocities and wave steepness. Plastics with higher settling velocities under less-steep wave conditions are likely to escape coastal entrapment and end up in the breaking zone. However, plastics with greater buoyancy rates under steeper waves show a predominant accumulation closer to the shoreline.

Efficient Nitrogen Management Technologies for Sustainable Rice Production

The use of nitrogen (N) fertilizers in rice fields as a source of nutrition is the major source of emission of nitrous oxide (N2O). Two key factors which control the flux of N2O at the field level are the amount of N supplied and the efficiency at which it is absorbed by plants. To reduce the N2O emissions, optimum N fertilizer application (in terms of input rate and time of application) and ideal fertilizer selection are crucial. Optimizing N use efficiency (NUE) is crucial to sustain productivity and profitability. Depending on edaphic and climatic conditions, improved N management can dramatically cut greenhouse gases (GHGs) emissions. Producers must ensure that the kind, rate, and time of N application do not result in substantial losses owing to volatilization, leaching, or denitrification. Adoption of best nitrogen management practices like deep placement of urea, use of nitrification inhibitors, urease inhibitors, and slow-release nitrogen fertilizers will reduce the N loss and increase NUE. The goal of this review is to discuss in detail the various technologies that have been developed and refined to improve NUE and protect the environment.

Discrete-time adaptive predictive sliding mode trajectory tracking control for dynamic positioning ship with input magnitude and rate saturations

This paper investigates the discrete-time adaptive predictive sliding mode trajectory tracking control problem based on a reference sliding mode trajectory for the dynamic positioning ship with model uncertainty, environmental disturbances and input magnitude and rate saturations. Initially, a two-step delay discrete-time disturbance observer is designed to estimate the model uncertainty and environmental disturbances, and the input constraints are processed by quadratic programming. Then, an adaptive expected heading is proposed to ensure faster trajectory tracking and more stable heading changes simultaneously. Furthermore, using a double closed-loop control strategy, a new discrete-time virtual velocity controller is designed in the outer loop based on Euler discretization to convert trajectory tracking into velocity tracking. In the inner loop, a discrete-time adaptive predictive sliding mode velocity controller is designed based on a new adaptive reference sliding mode trajectory and an integral terminal sliding mode surface with disturbance estimation error. The proposed strategy can adaptively adjust the sliding mode bandwidth and convergence speed, which not only ensures the system’s rapid convergence but also reduces the tracking error and weakens the chattering. Finally, the stability analysis proves that the closed-loop system is uniformly bounded stable. Comparative simulation results verify the effectiveness of the proposed control scheme.

Influence of innovative human capital on economic development of China through the STI model

Abstract With the continuous progress of the times, innovation is the first driving force of development, and human capital is the carrier of innovation ability. Innovative human capital plays an important role in China’s economic development and enhancing its competitiveness. By selecting physical capital, labor input and innovative human capital input, and establishing an RBM-STI function model, the impact of innovative human capital on China’s economic development is calculated. The results show that innovative human capital has a significant role in promoting the contribution rate of economic development. And in the 2021-2022 stage, the growth rate of innovative human capital input and output is the largest, at 81.9%, while the growth rate of physical capital input and output is only 26.3%. It shows that although the role of physical capital in promoting economic development is not as obvious as that of innovative human capital, it is still the backbone of promoting economic development. The lowest contribution rate to economic growth in China’s provinces and cities is the labor input, which accounts for only 9.6% in the 2021-2022 period.

A deep neural network-based smart error measurement method for fiscal accounting data.

The error measurement of fiscal accounting data can effectively slow down the change of financial assets. Based on deep neural network theory, we constructed an error measurement model for fiscal and tax accounting data, and we analyzed the relevant theories of fiscal and tax performance evaluation. By establishing a batch evaluation index of finance and tax accounting, the model can monitor the changing trend of the error of urban finance and tax benchmark data scientifically and accurately, as well as solve the problem of high cost and delay in predicting the error of finance and tax benchmark data. In the simulation process, based on the panel data of credit unions, the entropy method and a deep neural network were used to measure the fiscal and tax performance of regional credit unions. In the example application, the model, combined with MATLAB programming, calculated the contribution rate of regional higher fiscal and tax accounting input to economic growth. The data show that the contribution rates of some fiscal and tax accounting input, commodity and service expenditure, other capital expenditure and capital construction expenditure to regional economic growth are 0.0060, 0.0924, 0.1696 and -0.0822, respectively. The results show that the proposed method can effectively map the relationships between variables.

Soil erosion control from trash residues at varying land slopes under simulated rainfall conditions.

Trash mulches are remarkably effective in preventing soil erosion, reducing runoff-sediment transport-erosion, and increasing infiltration. The study was carried out to observe the sediment outflow from sugar cane leaf (trash) mulch treatments at selected land slopes under simulated rainfall conditions using a rainfall simulator of size 10 m × 1.2 m × 0.5 m with the locally available soil material collected from Pantnagar. In the present study, trash mulches with different quantities were selected to observe the effect of mulching on soil loss reduction. The number of mulches was taken as 6, 8 and 10 t/ha, three rainfall intensities viz. 11, 13 and 14.65 cm/h at 0, 2 and 4% land slopes were selected. The rainfall duration was fixed (10 minutes) for every mulch treatment. The total runoff volume varied with mulch rates for constant rainfall input and land slope. The average sediment concentration (SC) and sediment outflow rate (SOR) increased with the increasing land slope. However, SC and outflow decreased with the increasing mulch rate for a fixed land slope and rainfall intensity. The SOR for no mulch-treated land was higher than trash mulch-treated lands. Mathematical relationships were developed for relating SOR, SC, land slope, and rainfall intensity for a particular mulch treatment. It was observed that SOR and average SC values correlated with rainfall intensity and land slope for each mulch treatment. The developed models' correlation coefficients were more than 90%.

Revendo o processamento da matéria orgânica pelas áreas úmidas

Abstract Aim Cycling processes in wetlands are highly dynamic and involve complex interactions between hydrological processes, biogeochemical transformations, and microbial communities. This review attempts to assess the interactions between elements within biogeochemical cycles and the possible routes in which organic matter is processed in waterlogged soils. Methods The input and cycling of organic matter in flooded soils were approached in this review. We used a non-systematic literature survey to indicate the possible biogeochemical routes of organic matter processing in waterlogged soils. Results We explore hydrological processes, oxygen availability, biogeochemical routes of the organic matter process, and the inputs and exports of organic matter in flooded soils from wetlands. Conclusions The anaerobic degradation of organic resources predominantly occurs within submerged soils. Under conditions of maintenance of natural rates of primary production and allochthonous detritus input, storing organic detritus in flooded soils prevails over mineralization. The importance of hydrology for the export of organic carbon is evident. In wetlands, the export of organic matter is predominantly associated with dissolved organic matter and methane production.

Robust Adaptive Prescribed Performance Control for Unknown Nonlinear Systems With Input Amplitude and Rate Constraints

A novel approximation-free prescribed performance control scheme for unknown nonlinear systems with amplitude and rate saturation on the control input signal is designed in this letter. The proposed control strategy employs nested smooth saturation functions and introduces a reconciling relaxation of the performance constraints based on the actuator limitations. The straightforward gain selection along with the low complexity of the control scheme, simplifies the practical implementation of our algorithm. The adoption of the adaptive prescribed performance control technique ensures the desired trade-off between input and output constraints for any input-to-state stable (ISS) system. Inevitably, for generic systems, the boundedness properties are guaranteed only locally; thus, we provide a sufficient boundedness condition for all closed-loop signals. Finally, an illustrative simulation study is conducted to demonstrate the efficacy of the proposed approach.

Sensors Scheduling for Remote State Estimation Over an Unslotted CSMA/CA Channel

This article investigates the sensor selection problem for remote state estimation. A set of sensors measures a process's state and sends the measurements to a remote estimator over an unslotted carrier sense multiple access/collision avoidance (CSMA/CA) channel in IEEE 802.15.4-based wireless body area networks. This article aims to answer which sensors should be selected according to probability so that the state estimation error covariance and the energy consumption of sensors can be optimized. A common assumption in most existing methods about sensor scheduling is that the packet loss process is unrelated to the channel input. This article analyzes the relationship between channel input and packet loss rate by modeling the communication process. A scheduling scheme is proposed to increase channel utilization from the perspective of sensor information fusion. Then the constraint on the performance metrics is presented. By transforming the sensor selection problem into a constrained optimization problem, the solution to the optimization problem is obtained by a numerical algorithm. Finally, the validity of the model and the feasibility of the sensor scheduling are demonstrated by a numerical simulation.

Understanding response of yield-scaled N2O emissions to nitrogen input: Data synthesis and introducing new concepts of background yield-scaled N2O emissions and N2O emission-yield curve

Yield-scaled nitrous oxide (N 2 O) emission ( YSNE ) has been recognized as a means for developing appropriate nitrogen (N) management strategies to balance food security and mitigating N 2 O emissions. To better understand and use the concept of YSNE, it is essential to be assessed under various field conditions. The main objectives of this study were to assess the relationship between N inputs and YSNE with published results and identify response patterns of YSNE to N inputs. We assessed the relationship between N inputs and YSNE using published results encompassing 1800 observations (published from 1980 to 2020) from maize, rice, and wheat crops worldwide. Background yield-scaled N 2 O emission ( BYSNE; a YSNE in the condition of zero N input) was significantly different by crop type. Rice (90.8 ± 12.9 g N 2 O−N Mg −1 ) had lower BYSNE compared to maize (174.2 ± 30.1 g N 2 O−N Mg −1 ) and wheat (325.4 ± 41.8 g N 2 O−N Mg −1 ). BYSNE was positively correlated with annual mean temperature in maize, rice, and wheat fields. BYSNE was negatively correlated with soil total nitrogen contents in rice fields. Over 60% data set showed a positive relationship between N inputs and YSNE in all three crops studied. A small proportion of the dataset had an optimum N rate that minimized YSNE . The results suggest that in general, lower N input rates result in lower YSNE in crop production. YSNE can be reduced in three ways: increasing yields (Type 1), reducing N 2 O emissions (Type 2), and both increasing yields and reducing N 2 O emissions (Type 3). To identify appropriate measures, we suggest a N 2 O emission-yield curve combining responses of yields and N 2 O emissions to N inputs. In type 1, 2, and 3 measures, an N 2 O emission-yield curve is shifted to the right, down, and both right and down, respectively. Through identifying direction and magnitude of the shifting, the effects of applied measures on yields and N 2 O emission in N input levels can be easily compared and recognized. This study provided insights into the nature of YSNE and how YSNE responds to N inputs. It also suggested an N 2 O emission-yield curve, which can be useful to identify how certain measures affect both N 2 O emissions and crop yields. The information can be useful for scientific community and policymakers developing appropriate N management strategies to balance food security and the mitigation of N 2 O emissions. Type 1 measures: increasing yields without changing N 2 O emissions. Type 2 measures: reducing N 2 O emissions without changing yields. Type 3 measures: both increasing yields and reducing N 2 O emissions. • Background yield-scaled N 2 O emission ( BYSNE ) varied by crop type. • BYSNE was positively correlated with annual mean temperature. • Over 60% data sets showed consistently lower yield-scaled N 2 O emission as N input decreased. • N 2 O emission yield curve showed the effects of mitigation measures on both yields and N 2 O emission.

Study on the simplified model of vertical double U-pipe ground heat exchanger

A simplified semi-analytical model of vertical double U-pipe ground heat exchanger was established. The validity of the established model is examined by contrasting the figured outcomes with experiment data, emulation results of 3-D numerical model and calculation results of infinite line-source model for different inlet boundary conditions and configurations. After one hour, the semi-analytical model?s relative error is less than 0.32% under the boundary condition of given inlet fluid temperature. Under the boundary condition of given total heat input rate, the semi-analytical model?s relative error after ten hours is less than 0.11%, while the infinite line-source model?s relative error is less than 0.60%. The semi-analytical model is in good agreement with experiment and numerical model, and has higher calculation accuracy than infinite line-source model.

Popularization of Pearlmillet Production Technology through Front Line Demonstrations in the Transitional plain Zone of Luni Basin of Rajasthan

Front line demonstrations on pearlmillet were carried out by College of Agriculture Sumerpur, Pali (Rajasthan) to study the yield gaps between improved packages of practices (IP) verses farmer’s practice (FP) during Kharif seasons 2019-20 to 2021-22 at Rohit block of Pali district of Rajasthan. The improved technologies consisted use of high yielding hybrids, application of micro nutrients, integrated weed, pest and disease management. Yield attributes of improved practice (IP) and farmers’ practice (FP) were recorded, and percent yield increase, technology gap, extension gap, technology index, and FLD economics were examined. The results revealed that the highest seed yield was obtained in demonstrated plot with an average of 1481 kg ha-1 as compared to 1119 kg ha-1 and recorded an increase in the tune of 32.4 per cent. Higher net return (` 18642 ha -1) in the demonstration plots compared to farmers’ practice plot (` 13719 ha-1) was also net worth with an extension and technology gaps of 362 kg ha-1 and 1319 kg ha-1, respectively on mean basis. The demonstrations also recorded an additional return of ` 4922 ha-1 with additional investments of ` 2062 ha -1. It was attributed to scientific management and monitoring of demonstrations and use of low cost monitory inputs. The MSP of pearl millet during different years influenced the economic returns resulted into an incremental benefit: cost ratio of 2.6 under demonstrations on an average basis besides fluctuating rates of various inputs. By conducting front line demonstration of proven technologies, yield potential of pearl millet crop could be enhanced to a great extent with increase in the income level of the farming community.

Influence of land use and different plant residues on isotopic carbon distribution of total and water extractable organic matter in an incubation experiment with weathered tropical soil

AbstractIn weathered tropical soils, the inherent pedoclimatic characteristics strengthen the role of soil organic matter (SOM) pools within the carbon cycle for both forest and agricultural ecosystems. The fast SOM turnover and the humid climate hasten the impact of land use and emphasize the importance of water extractable organic matter (WEOM) on soil organic carbon (SOC) dynamics. The goal of this study was to determine the short‐term dynamics of bulk SOM and WEOM pool in weathered Brazilian soil, as conditioned by both land use and type of plant inputs. To this aim we used the appraisal of the natural δ13C‐OC signature to follow the variation of SOC pools and to overcome the analytical issues related to low OC concentration of WEOM fractions. In a one‐year laboratory incubation, soil samples from a natural forest and an adjacent site under sugarcane monoculture were amended with either forest litter or sugarcane straw to evaluate SOM and WEOM dynamics. The bulk SOM was mainly affected by inherited conditions rather than on the organic amendments. The incorporation of sugarcane residues in the forest site produced a partial replacement of the original SOC, while the amendments to the cultivated soil promoted a stable increase in SOC. The analysis of WEOM highlighted its influence as a reactive pool in the short‐term SOM dynamics. The δ13C variation of WEOM from cultivated soil corroborated the significant ponderal rate of OC input from forest litter that accounted for 22% of total dissolved carbon. Unexpected evidence on the shift of isotopic dilution between SOC pools indicates that the evaluation of δ13C to determine the origin of the SOC fraction should be conservatively adopted. The results outline that the steady state of SOM in forest systems may undergo a rapid decline with limited counteracting effects of exogenous OM inputs. Conversely, OC depleted agricultural soils may benefit from organic amendments, thus acting as an effective sink for SOC accumulation.

Genetic variation in the dopamine system is associated with mixed-strategy decision-making in patients with Parkinson's disease.

Decision-making during mixed-strategy games requires flexibly adapting choice strategies in response to others' actions and dynamically tracking outcomes. Such decisions involve diverse cognitive processes, including reinforcement learning, which are affected by disruptions to the striatal dopamine system. We therefore investigated how genetic variation in dopamine function affected mixed-strategy decision-making in Parkinson's disease (PD), which involves striatal dopamine pathology. Sixty-six PD patients (ages 49-85, Hoehn and Yahr Stages 1-3) and 22 healthy controls (ages 54-75) competed in a mixed-strategy game where successful performance depended on minimizing choice biases (i.e., flexibly adapting choices trial by trial). Participants also completed a fixed-strategy task that was matched for sensory input, motor outputs and overall reward rate. Factor analyses were used to disentangle cognitive from motor aspects within both tasks. Using a within-subject, multi-centre design, patients were examined on and off dopaminergic therapy, and genetic variation was examined via a multilocus genetic profile score representing the additive effects of three single nucleotide polymorphisms (SNPs) that influence dopamine transmission: rs4680 (COMT Val158 Met), rs6277 (C957T) and rs907094 (encoding DARPP-32). PD and control participants displayed comparable mixed-strategy choice behaviour (overall); however, PD patients with genetic profile scores indicating higher dopamine transmission showed improved performance relative to those with low scores. Exploratory follow-up tests across individual SNPs revealed better performance in individuals with the C957T polymorphism, reflecting higher striatal D2/D3 receptor density. Importantly, genetic variation modulated cognitive aspects of performance, above and beyond motor function, suggesting that genetic variation in dopamine signalling may underlie individual differences in cognitive function in PD.

Methodological Contribution to the Assessment of Generation and Sediment Transport in Tropical Hydrographic Systems

The efficiency and useful life of reservoirs are directly related to the production and input rates of sediments resulting from erosive processes at the edges and those resulting from the action of surface runoff in contribution areas and transported via tributary channels. Knowledge of the intensity, as well as the relationship between generation and input, allows more precise identification of critical environments, helping in the decision-making process and allowing the definition of mitigating measures. This work aims to relate the spatial variability of soil loss with the respective sediment transfer potential in two sub-basins tributary to the HPP Batalha reservoir in the Midwest region of Brazil. The methodology comprised the bivariate analysis between estimates of soil loss in areas of contribution and the Declivity-Extent Relationship along the channels. The results point to the configuration of four spatial patterns, indicating different levels of criticality in terms of sediment generation potential and transport capacity. In addition, they highlight basins with high potential and greater proximity to the reservoir, which constitute priority areas for monitoring, especially the conditions of soil cover and management, to contribute to the reduction of sediment inputs and prolong the efficiency of these structures.