Synthetic Series Research Articles

Hydrological Response to Climate Change: McGAN for Multi-Site Scenario Weather Series Generation and LSTM for Streamflow Modeling

This study focuses on the impacts of climate change on hydrological processes in watersheds and proposes an integrated approach combining a weather generator with a multi-site conditional generative adversarial network (McGAN) model. The weather generator incorporates ensemble GCM predictions to generate regional average synthetic weather series, while McGAN transforms these regional averages into spatially consistent multi-site data. By addressing the spatial consistency problem in generating multi-site synthetic weather series, this approach tackles a key challenge in site-scale climate change impact assessment. Applied to the Jinghe River Basin in west-central China, the approach generated synthetic daily temperature and precipitation data for four stations under different shared socioeconomic pathways (SSP1-26, SSP2-45, SSP3-70, SSP5-85) up to 2100. These data were then used with a long short-term memory (LSTM) network, trained on historical data, to simulate daily river flow from 2021 to 2100. The results show that (1) the approach effectively addresses the spatial correlation problem in multi-site weather data generation; (2) future climate change is likely to increase river flow, particularly under high-emission scenarios; and (3) while the frequency of extreme events may increase, proactive climate policies can mitigate flood and drought risks. This approach offers a new tool for hydrologic–climatic impact assessment in climate change studies.

Surface energy and mass balance of Mera Glacier (Nepal, Central Himalaya) and their sensitivity to temperature and precipitation

Abstract The sensitivity of glacier mass balance to temperature and precipitation variations is crucial for informing models that simulate glaciers’ response to climate change. In this study, we simulate the glacier-wide mass balance of Mera Glacier with a surface energy-balance model, driven by in situ meteorological data, from 2016 to 2020. The analysis of the share of the energy fluxes of the glacier shows the radiative fluxes account for almost all the energy available during the melt season (May–October). However, turbulent fluxes are significant outside the monsoon (June–September). On an annual scale, melt is the dominant mass flux at all elevations, but 44% of the melt refreezes across the glacier. By reshuffling the available observations, we create 180 synthetic series of hourly meteorological forcings to force the model over a wide range of plausible climate conditions. A +1 (−1)°C change in temperature results in a −0.75 ± 0.17 (+0.93 ± 0.18) m w.e. change in glacier-wide mass balance and a +20 (−20)% change in precipitation results in a +0.52 ± 0.10 (−0.60 ± 0.11) m w.e. change. Our study highlights the need for physical-based approaches to produce consistent forcing datasets, and calls for more meteorological and glaciological measurements in High Mountain Asia.

Rainfall Erosivity over Brazil: A Large National Database

Rainfall erosivity (RE) represents the potential of rainfall to cause soil erosion, and understanding its impact is essential for the adoption of soil and water conservation practices. Although several studies have estimated RE for Brazil, currently, no single reliable and easily accessible database exists for the country. To fill this gap, this work aimed to review the research and generate a rainfall erosivity database for Brazil. Data were gathered from studies that determined rainfall erosivity from observed rainfall records and synthetic rainfall series. Monthly and annual rainfall erosivity values were organized on a spreadsheet and in the shapefile format. In total, 54 studies from 1990 to 2023 were analyzed, resulting in the compilation of 5516 erosivity values for Brazil, of which 6.3% were pluviographic, and 93.7% were synthetic. The regions with the highest availability of information were the Northeast (35.6%), Southeast (30.1%), South (19.9%), Central-West (7.7%), and North (6.7%). The database, which can be accessed on the Mendeley Data platform, can aid professionals and researchers in adopting public policies and carrying out studies aimed at environmental conservation and management basin development.

Inflow generation using Thomas- Fiering model for Thaphanseik Reservoir in Myanmar

Thomas-Fiering (T-F) model was applied for generating synthetic streamflow for the Thaphanseik reservoir. The Thomas-Fiering model accommodated the non-stationarity of seasonal data. Time series of streamflow are crucial for the planning, design, and management of various water resource systems. In this study, the model was tested using historical data spanning 39 years (from 1985 to 2023). The model’s performance was evaluated by using statistical measurements such as Coefficient of Determination (R2) and Nash-Sutcliffe Efficiency (NSE). Additionally, this model was utilized to generate synthetic streamflow data for the years 2024 to 2100. The logarithmic transformation method was used in order to avoid the negative flows in the synthetic data. In this study, synthesis flow data were generated using different random sequences. The mean, standard deviation and correlation coefficient of different synthetic series were calculated. The calibration process was performed for the periods 1985 to 2016 and validation process was performed for the years 2017 to 2023. Based on R2 value, most suitable synthetic series were chosen. The generated data showed a high goodness of fit, with R² and NSE values. An analysis of the historical and synthetic discharge statistics revealed that the model successfully captured the features of the historical data and integrated them into the generated sequences.

Flurbiprofen clubbed schiff's base derivatives as potent anticancer agents: In Vitro and In Silico approach towards breast cancer

In this work, we are reporting nineteen hydrazone-Schiff base derivatives (2a-2l and 3a-3g), containing flurbiprofen drug nucleus. The synthesized products were structurally elucidated through 1H, 13C-NMR and HR-ESI-MS spectroscopic techniques and finally tested for in vitro anti-cancer activity. Among the synthetic series, 2f, 2g, 3g, 3b, and 2e attributed the higher inhibitory potential against the breast cancer cell line (MDA-MB-231) having IC50 values of 21.0 ± 0.4, 21.8 ± 0.2, 27.1 ± 0.3, 28.8 ± 0.3, and 29.6 ± 0.3 µM respectively. However, the remaining derivatives attributed good to less active. DFT was used to calculate frontier molecular orbital of (2a-h, j-l, and 3a-d) including HOMO which concentrated on the substituents aromatic ring, and LUMO focused over flurbiprofen and hydrazide fragments, that indicate the charge transfer from molecule to biological media. The reactivity indices suggested the most active 2f (IC50 = 21.0 ± 0.4 µM) and 2g (IC50 = 21.8 ± 0.2 µM) showed higher indices reactivity namely σ, χ, and ω than lowest active 2g; this relation inversely for Eg, η, and IP. 2a-l had more electrophilic character and higher acceptance ability for biological targets than compounds (3a-g). The MEP map indicated the electron density distribution of 2a-l was more dispersed than that of 3a-g, indicating potential biological activities and are chemically reactive zone suitable for drug action. The docking study contributed to the analysis of cytotoxicity for investigated compounds.

A methodology to correlate river inflows in state sampling Monte Carlo simulation

This paper proposes a methodology to sample inflow states of run-of-the-river hydropower plants that are spatially correlated, preserving the statistical dependence among them, in Non-Sequential Monte Carlo Simulation (MCS). The technique used to correlate the inflows of hydro plants in the Brazilian synthetic series generation model, which is based on the correlation matrix and Cholesky Decomposition, is adapted to be used in the sampling stage. Nataf transformation is used for addressing non-normality of the inflow data. The solution method is such that no assumption about the data probability distribution is necessary. Although the methodology is applied to inflows in this paper, it can be applied to any other quantity, such as winds. A case study is proposed to evaluate the correlation of the sampled inflows and the impact on the reliability indices. Besides, it is investigated the effect when inflows states are clustered to reduce the number of states in the system for better computational efficiency. Case study shows that the reliability indices obtained with the proposed methodology are within the confidence interval of the indices calculated by the Sequential MCS with an execution time as fast as the Non-Sequential one, while the non-consideration of correlation causes very significant errors. Simulation with 50 clusters produces equally good results with a reduction of 75 % of the execution time. Sensitivity analysis showed that halving the number of clusters maintains the accuracy of the results, while 10 clusters results in overestimating system reliability. Different degrees of correlation have been simulated, showing that the higher the correlation among the hydro plants, the less reliable the system becomes.

Assessment of Carcinogenic/Mutagenic Potential of Different Series of Synthetic Compounds

The new drug research is usually based on synthesis medicine. The use of these medications has created problems such as tolerance in humans, for a long time and due to legitimate use of anti-infection, microbial defense against branded medication is growing. A mutagensis study by Ames in the early 1970's, used worldwide by drug and chemicals companies to diagnose mutagens carcinogenes, making it possible for them to be detected, and to be added to the mutagenic synthesis portion or radiation source triggering irreversible changes, and to the genetic material transmitted from the parent. deoxyribonucleic acid (DNA). The purpose of this study was to assessment of carcinogenicity of synthetic compounds series by hemolytic, Ames and Damaged DNA protection assay. The cytotoxicity was determined with hemolytic assay and DNA Damage protection assay while mutagenicity was resolute by using S. typhimurium TA100 and TA98 strains. It is concluded that the compounds with less hemolytic compounds are good for uses in drugs. Synthetic compounds were determined to be non- mutagenic in nature. Analysis of variance (ANOVA) was applied to compare the hemolysis percent between different concentrations.

Confrontation between modelled solar integrated observables and direct observations

Context. Stellar variability strongly impacts the search for low-mass exoplanets with radial velocity techniques. Two types of planet-free time series can be used to quantify this impact: models and direct solar observations after a subtraction of the Solar System planetary contribution. Making a comparison among these approaches is necessary to improve the models, which can then be used for blind tests across a broad range of conditions. Aims. Our objective is therefore to validate the amplitude of the convective blueshift in plages used in our previous works, particularly in blind tests, with HARPS-N solar data. Methods. We applied our model to the structures observed at the time of HARPS-N observations and established a direct comparison between the radial velocity time series. To complete our diagnosis, we also studied the observed radial velocities separately for each diffraction order derived from the individual cross-correlation functions, as well as our line-by-line radial velocities. Results. We find that our previous model had been underestimating the amplitude of the convective blueshift inhibition by a factor of about 2. A direct estimation of the convective blueshift in the spectra, which is shown to be correlated with the plage filling factor, allows us to explain the difference with previous estimations obtained with MDI/SOHO Dopplergrams, based on the specific properties of the Ni line used in this mission. In addition, we identified several instrumental systematics, in particular, the presence of a 2 m s−1 peak-to-peak signal with a period of about 200 days in radial velocity and bisector. This signal could be due to periodic detector warmups, a systematic dependence of the long-term trend on wavelength that is possibly related to the variability of the continuum over time, and/or an offset in radial velocity after the interruption of several months in October 2017. Conclusions. A large amplitude in the convective blueshift inhibition of (360 ms−1, namely twice more than in our previous works) must be used when building synthetic times series for blind tests. The presence of instrumental systematics should also be taken into account when using sophisticated methods based on line properties to mitigate stellar activity when searching for very weak signals.

Assessment of synthetic series to design the capacity of flow regulation reservoirs

Freshwater scarcity is perceived as a global systemic risk. Intending to reach water secutiry, flow regulation reservoirs are alternatives to improve streamflow and water storage, especially in places where demand exceeds water availability during periods of drought. However, the unavailability of historical series of flows in watersheds makes the adequate design of reservoirs difficult. To overcome such difficulties, synthetic series of flows are currently being generated for the specific sections of the watercourses where these structures are to be designed. The present study aimed to evaluate two methods of generating synthetic series of flows applied to design the capacity of flow regulation reservoirs in conditions of limited data. A monitored hydrological region (Itapemirim River Basin, Espírito Santo, Brazil) and synthetic flow series generated according to the methodologies of Rodrigues (2017) and Cesconetto (2021) were used. The methodologies were tested by cross-validation, and the results were compared using graphs and statistical indicators to the results obtained with observed data, measured in fluviometric reference stations. After analyzing the statistical indicators, such as the coefficient of determination (R2), the Nash-Sutcliffe efficiency index (NSE), and the reservoir design quality index (IQD), it was concluded that the method proposed by Cesconetto (2021) showed a tendency to under-design the capacities of the reservoirs, mainly for lower flows to be regularized (β < 0.75). The method proposed by Rodrigues (2017) performed better than the method proposed by Cesconetto (2021) for the design of the capacity of flow regulation reservoirs under conditions of limited data in the Itapemirim River Basin.

Time Series Analysis of Nonlinear Head Dynamics Using Synthetic Data Generated with a Variably Saturated Model.

The performance of time series models is assessed using synthetic head series simulated with a numerical model that solves Richards' equation for variably saturated flow. Heads were simulated in a homogeneous unconfined aquifer between two parallel canals; measured daily precipitation and potential evaporation are specified at the land surface and root water uptake is simulated. The head response to a precipitation event is nonlinear and depends on the saturation degree and rainfall before and after the precipitation event while evaporation reduction occurs during summers. Synthetic series were generated for 27 years and three different soil types; the unsaturated zone thickness varies between 0 and >5 m. The synthetic head series were simulated with a linear and nonlinear time series model. Performance of a linear time series model with four parameters, using a scaled Gamma response, gave R2 values ranging from 0.67 to 0.96. The nonlinear time series model with five parameters simulates recharge using a root zone reservoir after which the head response to recharge is simulated with a scaled Gamma response function. The nonlinear time series model was able to simulate all synthetic head series very well with R2 values above 0.9 for almost all models. The head response of the nonlinear model to a single precipitation event compares well to the response of the variably saturated groundwater model. The provided scripts may be used to simulate synthetic head series for other climates or for systems with additional complexity to assess the performance of other data-driven models.

On the Use of Weather Generators for the Estimation of Low-Frequency Floods under a Changing Climate

The present work presents a methodology based on the use of stochastic weather generators (WGs) for the estimation of high-return-period floods under climate change scenarios. Applying the proposed methodology in a case study, Rambla de la Viuda (Spain), satisfactory results were obtained through the regionalization of the bias-corrected EUROCORDEX climate projections and the integration of this information into the parameterization of the WG. The generated synthetic data series fed a fully distributed hydrological model to obtain the future flood quantiles. The results obtained show a clear increase in the precipitation extreme quantiles for the two analyzed projections. Although slightly reducing the annual amount of precipitation, variations between 4.3% for a return period of 5 years in the mid-term projection and 19.7% for a return period of 100 years in the long-term projection have been observed. In terms of temperatures, the results point to clear increases in the maximum and minimum temperatures for both projections (up to 3.6 °C), these increases being greater for the long-term projection, where the heat waves intensify significantly in both magnitude and frequency. Finally, although rivers may present, in general, with lower flows during the year, flood quantiles experience an increase of 53–58% for high return periods, which reach values of up to 145% when we move to smaller catchments. All this combined translates into substantial shifts in the river flow regimes, increasing the frequency and magnitude of extreme flood events.

Application of the SMAP monthly model to the Piauitinga river basin located in the State of Sergipe, Brazil

The generation of flow data allows the assessment of the capacity to meet water demands, predict floods, and estimate the potential for hydraulic exploitation for electrical energy generation. In Brazil, precipitation data series, due to their ease of measurement, are more extensive compared to flow data series, enabling the use of hydrological models called rainfall-runoff models capable of estimating flows from precipitation data. Therefore, utilizing the Brazil Gridded Meteorological Data (BR-DWGD) database, this study aims to generate, calibrate, and validate flow data for the Piauitinga river basin located in the state of Sergipe, Brazil, using the monthly rainfall-runoff SMAP model. The soil parameters considered in the validation for the studied region showed a good fit to the observed data, achieving a Nash-Sutcliffe (NS) of 84% and log-Nash-Sutcliffe (NSLog) of 85% in calibration, and Nash-Sutcliffe (NS) of 70% and a log-Nash-Sutcliffe (NSLog) of 80% in validation. Therefore, since the rainfall-runoff model used exhibited good performance for the studied hydrographic basin, it becomes feasible to use the generated synthetic series to fill possible gaps in the historical series of monthly average flows.

Design, synthesis and characterization of ethyl 3-benzoyl-7-morpholinoindolizine-1-carboxylate as anti-tubercular agents: In silico screening for possible target identification.

A thorough search for the development of innovative drugs to treat tuberculosis, especially considering the urgent need to address developing drug resistance, we report here a synthetic series of ethyl 3-benzoyl-7-morpholinoindolizine-1-carboxylate analogues (5a-o) as potent anti-tubercular agents. These morpholino-indolizines were synthesized by reacting 4-morpholino pyridinium salts, with various electron-deficient acetylenes to afford the ethyl 3-benzoyl-7-morpholinoindolizine-1-carboxylate analogues (5a-o). All synthesized intermediate and final compounds are characterized by spectroscopic methods such as 1H NMR, 13C NMR and HRMS and further examined for their anti-tubercular activity against the M. tuberculosis H37Rv strain (ATCC 27294-American type cell culture). All the compounds screened for anti-tubercular activity in the range of 6.25-50 μM against the H37Rv strain of Mycobacterium tuberculosis. Compound 5g showed prominent activity with MIC99 2.55 μg/mL whereas compounds 5d and 5j showed activity with MIC99 18.91 μg/mL and 25.07 μg/mL, respectively. In silico analysis of these compounds revealed drug-likeness. Additionally, the molecular target identification for Malate synthase (PDB 5CBB) is attained by computational approach. The compound 5g with a MIC99 value of 2.55 μg/mL against M. tuberculosis H37Rv emerged as the most promising anti-TB drug and in silico investigations suggest Malate synthase (5CBB) might be the compound's possible target.

A new method for deriving broad-band polar motion geodetic excitations

While the geodetic excitation χ(t) of polar motion p(t) is essential to improve our understanding of global mass redistributions and relative motions with respect to the terrestrial frame, the widely adopted method to derive χ(t) from p(t) has biases in both amplitude and phase responses. This study has developed a new simple but more accurate method based on the combination of the frequency- and time-domain Liouville's equation (FTLE). The FTLE method has been validated not only with 6-h sampled synthetic excitation series but also with daily and 6-h sampled polar motion measurements as well as χ(t) produced by the interactive webpage tool of the International Earth Rotation and Reference Systems Service (IERS). Numerical comparisons demonstrate that χ(t) derived from the FTLE method has superior performances in both the time and frequency domains with respect to that obtained from the widely adopted method or the IERS webpage tool, provided that the input p(t) series has a length around or more than 25 years, which presents no practical limitations since the necessary polar motion data are readily available. The FTLE code is provided in the form of MatLab function.

Multifaceted bioactivity of thiosemicarbazide derivatives: Synthesis, characterization, and DFT investigations on inhibition of α-amylase, hydroxyl radical scavenging, and iron chelating activities with molecular docking insights

In this study, eight bioactive thiosemicarbazide derivatives (3a-h) were synthesized and characterized through 1HNMR , 13CNMR and Mass spectroscopic techniques. Finally, their inhibition activities against α-amylase and antioxidant activity were investigated. Among the synthetic series, five compounds 3 g (IC50 = 8.61 ± 1.42 µM) 3a (IC50 = 13.41 ± 1.65 µM), 3e (IC50 = 15.23 ± 1.17 µM), 3 h (IC50 = 17.37 ± 0.87 µM) and 3d (IC50 = 17.95 ± 1.99 µM) showed excellent inhibition by comparing with standard (acarbose, IC50 = 21.55 ± 1.31 µM). Similarly, in the case of iron chelating agent activity, product compounds 3a-h presented outstanding activity in the range of IC50 = 18.19 ± 1.81 to 63.42 ± 1.45 µM superior than standard (EDTA, IC50 = 66.43 ± 1.07 µM) while in hydroxyl radical scavenging activity all the synthesized products 3a-h also showed excellent scavenging activity in the range of IC50 values 25.85 ± 1.13 to 58.9 ± 2.95 µM when compared to standard vitamin C (IC50 = 60.51 ± 1.02 µM). We expanded our investigation to molecular interactions via a docking study, where these compounds were docked with the target protein to unveil their binding affinities and key interactions, offering additional insights into their inhibitory mechanisms. The chemical nature of the synthesized compounds was revealed through density functional theory (DFT) calculations at B3LYP/6–311++G(d,p). Intramolecular hydrogen bonding was explored using DFT-d3 and reduced density gradient (RDG) analysis. Additionally, various reactivity parameters were investigated through TD-DFT at the CAM-B3LYP/6–311++G(d,p) method.

Development of intensity – duration – frequency (IDF) curves using combined rain gauge (RG) and remote sense (TRMM) datasets for Weta Traditional Area in Ghana

This research developed IDF curves and derived empirical equations for the Weta Area to estimate design rainfall. Daily rainfall data of Rain Gauge and Tropical Rainfall Measuring Mission (TRMM) 3B42 over 22 years for Weta were obtained from the Ghana Meteorological Services and National Aeronautics and Space Administration, respectively. The Indian Meteorological Department formula was used to disaggregate the daily data into hourly synthetic series to develop the IDF curves. The combined dataset was subjected to frequency analysis to determine the distribution which best characterize the dataset. The results demonstrated that the IDF curves provided higher intensities for shorter durations (0.08-h, 0.17-h, 0.25 h, and 0.5 h) while lower intensities for longer durations (1 h, 2-h, 6-h, 12 h and 24 h). The rainfall intensities and return periods are parallel and high intensities correlated with brief durations for the same return period. TRMM overestimated rainfall compared to Rain Gauge data. The IDF curves and derived empirical equations are useful scientific tools for hydraulic infrastructure design and water resources planning and management.

Indazole derivatives as novel inhibitors of monoamine oxidase and D-amino acid oxidase

The monoamine oxidase (MAO) enzymes metabolize neurotransmitter amines in the peripheral and central tissues, and inhibitors of these enzymes find application in the treatment of neuropsychiatric and neurodegenerative disorders. Based on reports that the neuronal nitric oxide synthase (nNOS) inhibitor, 7-nitroindazole, inhibits the MAO-B isoform, the present study investigated the MAO inhibition potencies of a synthetic series of fifteen C5- and C6-substituted indazole derivatives. While only one derivative (5c) was a submicromolar inhibitor of human MAO-A (IC50 = 0.745 µM), all compounds inhibited human MAO-B with submicromolar IC50 values. Substitution on C5 of indazole yielded particularly potent MAO-B inhibition with IC50 values that ranged from 0.0025–0.024 µM. Further investigation of a selected indazole derivative showed a competitive mode of MAO inhibition. To further explore the pharmacological properties of the indazole derivatives, they were also evaluated as potential inhibitors of porcine D-amino acid oxidase (DAAO). None of the synthetic compounds were noteworthy DAAO inhibitors, however, 1H-indazol-5-ol, a synthetic precursor, was found to be a good potency inhibitor with an IC50 value of 2.03 µM.

Grounded synthetic series lossy inductor simulator circuits employing single current differencing buffered amplifier

SummaryIn this communication, two new positive lossy series inductor simulator circuits using single current differencing buffered amplifier (CDBA), one capacitor, and three resistors are presented. In both the proposed circuits, the inductance value is independently controllable through a grounded resistor, which may be implemented using a voltage‐controlled resistor (VCR), facilitating electronic tuning. Moreover, one of the circuits presented utilizes the intrinsic resistance (internal resistance available at input ports p and n) of the CDBA, thereby enabling electronic control and establishing the inductor simulator as canonical. Both the circuits are analyzed for non‐ideal behavior by taking into account the parasitic elements of CDBA and compared with their ideal counterparts. To demonstrate the efficacy of the proposed series RL simulator circuits, SPICE simulations are performed using CMOS CDBA, and the performance of the proposed circuits is evaluated by designing a lead compensator. The simulation and experimental results of the proposed circuits, along with the application examples employing CDBA realized with the off‐the‐shelf available IC AD844, have also been corroborated.

A generalized visibility graph algorithm for analyzing biological time series having rotation in polar plane

Time series analysis is exploited when temporal measurements about a phenomenon exist. Visibility graphs are a method for representing and analyzing time series. One of the challenges biological time series introduce is rotation in polar plane. Rotation in polar plane is a change in the angle of the time series in polar plane. Rotation in the polar plane exists in any time series that has positive and negative observations together. In this research, a visibility graph algorithm is proposed which could efficiently handle biological time series which have rotation in polar plane. In the proposed algorithm, two observation in the time series are visible to each other in the graph, if the line connecting the points doesn't cross any other point placed between them. The proposed visibility graph algorithm has been evaluated with synthetic and real world time series. The generated visibility graphs are used to evaluate the proposed visibility graph algorithm with different metrics such as pearson autocorrelation and classification accuracy. The synthetic time series are generated by a bipolar feedback process. In one of the synthetic bios series with g = 10, the pearson autocorrelation of the graph is 0.9815 whereas the baseline is 0.9211. In the main experiment with real world time series, the proposed visibility graph algorithm is compared with the state of the art algorithm. The ANOVA test is performed on the results of 60 experiments. The p-value is smaller than 0.05, which states GVG has improved CLPVG significantly.

Understanding hydrologic controls of sloping soil response to precipitation through machine learning analysis applied to synthetic data

Abstract. Soil and underground conditions prior to the initiation of rainfall events control the hydrological processes that occur in slopes, affecting the water exchange through their boundaries. The present study aims at identifying suitable variables to be monitored to predict the response of sloping soil to precipitation. The case of a pyroclastic coarse-grained soil mantle overlaying a karstic bedrock in the southern Apennines (Italy) is described. Field monitoring of stream level recordings, meteorological variables, and soil water content and suction has been carried out for a few years. To enrich the field dataset, a synthetic series of 1000 years has been generated with a physically based model coupled to a stochastic rainfall model. Machine learning techniques have been used to unwrap the non-linear cause–effect relationships linking the variables. The k-means clustering technique has been used for the identification of seasonally recurrent slope conditions in terms of soil moisture and groundwater level, and the random forest technique has been used to assess how the conditions at the onset of rainfall controlled the attitude of the soil mantle to retain much of the infiltrating rainwater. The results show that the response in terms of the fraction of rainwater remaining stored in the soil mantle at the end of rainfall events is controlled by soil moisture and groundwater level prior to the rainfall initiation, giving evidence of the activation of effective drainage processes.