Hasil untuk "Physical geography"

F. Henselowsky, A. Kadereit, M. Herzog et al.

<p>Linear anomalies of vegetation vitality observed in satellite images motivated in-depth investigations of historical anthropogenic modification and exploitation of the paleo-floodplain of the late-glacial Bergstraßenneckar (BSN) in the Upper Rhine Graben near Mannheim (southwestern Germany). Stratigraphic investigations based on up to 1.7 m deep pits, sediment sampling, and laboratory analyses (grain size distribution; C, N, S; loss on ignition; X-ray fluorescence; morphoscopy of sand grains), as well as electrical resistivity tomography, reveal the presence of long parallel trenches cutting into the organic-rich and fine-grained natural strata which result from silting-up of the abandoned BSN channel during the Holocene. The linear features are interpreted as anthropogenic trenches and were later filled with sand. We identify an aeolian origin of the sand, which points to the use of sand, e.g., from the nearby Bettenberg dune of Last Glacial Maximum (LGM) to late-glacial age. The samples for optically stimulated luminescence dating (OSL) from the fill of the trenches show a wide range of equivalent doses and insufficient bleaching as sand was filled in lumps during shoveling. This results in ages ranging from the LGM to 300 years, depending on the aliquot and age model. This wide range indicates incomplete bleaching and is in agreement with the manual filling process in historical times. Further corroboration is provided by data from the Hesse State Archive at Darmstadt through a license for clay mining and brick burning at the study site dated to 1865 CE, explicitly requiring immediate fill. Local-scale clay pits for mud-brick production have been known about in western Europe since Roman times. However, access to the resources in the BSN channels in 1865 CE was only possible after a significant fall in groundwater tables following the regulation campaign of the Rhine system starting in the first half of the 19th century, which, in a wider context, illustrates the extent to<span id="page34"/> which large-scale anthropogenic changes in the fluvioscape have cascading effects down to the local scale.</p>

Shengjie Yang, Liang Zhong, Jianlong Li et al.

Study region: The Yellow River Basin (YRB), China. Study focus: This study investigates the spatiotemporal trends of water use efficiency (WUE) in the YRB from 2001 to 2020 using ordinary least squares (OLS) regression and Sen's slope estimator. It integrates multi-source spatial data, random forest, and partial least square-structural equation modeling to identify key drivers and quantify the direct and indirect effects of the main driving forces on WUE, including an analysis of the antagonistic or synergistic relationships between these effects. New hydrological insights for the region: Results showed an overall increase in WUE in the YRB, with OLS and Sen's slopes of 0.02 and 0.128 gC·m−2·mm−1·yr−1, respectively. Key drivers included leaf area index, night lights, soil water, elevation, landform relief, temperature, precipitation, and solar radiation. The five-year average effect intensities ranked as: water conditions (0.646) > leaf area index (0.506) > human actvities (0.235) > radiation–temperature (0.115) > geographic environment (0.070). The direct effect of radiation–temperature on WUE was positive; however, negative indirect effects antagonized this contribution, resulting in a net negative total effect. Water conditions and human activities showed synergistic effects that reinforced their positive impacts, whereas the geographic environment exhibited mainly negative direct effects partially offset by positive indirect consequences. These findings demonstrate that strategically leveraging mediating effects can effectively enhance the sustainability of ecosystem WUE in the basin.

Muhammad Khalid Jamil, Wouter Julius Smolenaars, Bashir Ahmad et al.

Nearly 86 % of the 1.4 million agricultural tube wells extracting groundwater for irrigation of crops in Lower Indus Basin (LIB) Pakistan are powered by diesel fuel. Diesel is expensive, needs to be imported and contributes to global warming through CO2 emissions. The increasing global focus on clean energy sources has prompted a shift from diesel fuel to solar photovoltaic (PV) energy for powering irrigation tube wells. The broad availability of inexpensive/free operational energy and abundant solar energy for pumping can cause over-extraction of groundwater. This study investigates the impacts of converting diesel pumps to solar PV pumps on groundwater extraction in LIB Pakistan. We conducted one-to-one comparisons of solar vs diesel pumps in thirty pairs of farmers working in similar circumstances. We estimated annual water extracted by solar and diesel pump farmers in each pair utilizing the data collected through flow measurements and crop wise irrigation times for each pair of farms using a targeted survey questionnaire, followed by a validation process. We utilized validated “Global Solar Atlas” (GSA), an online tool that accounts for daily and seasonal variation in solar pumps flows. Flow rates of diesel-operated pumps were measured, and annual water volumes pumped by both types of pumps were compared. Results show that the introduction of solar pumps significantly increased groundwater pumping compared to diesel fuelled pumps (P = 0.005∗). The average annual water pumped by solar and diesel pumps was found to be 1.6 ∗ 103 and 1.3 ∗ 103 mm respectively. In 77 % of the cases, farms using solar pumps extracted more water than their diesel counterparts under comparable conditions. While acknowledging benefits of solar PV pumping for agriculture in LIB Pakistan, the outcome of the study emphasized the need for a cautious and well-informed upscaling approach to avoid overextraction of groundwater.

Xi Peng, Kim Calders, Louise Terryn et al.

Tree branch angles and their distributions (BADs) are key structural traits influencing light interception, resource allocation, and canopy architecture. However, measuring them accurately remains challenging. We present BASeg, a novel method based on instance segmentation to automatically quantify branch angles and BADs from terrestrial laser scanning (TLS) data. BASeg segments individual branches using Voronoi partitioning, fits branch diameters via non-linear least squares, downsamples branch point clouds of varying diameter to different resolutions, and skeletonizes branches using the Laplacian algorithm. Branch angles are then calculated through a cluster-based nearest neighbor graph. We validated BASeg using leaf-off TLS data from six sycamore trees and using simulated data from nine trees (aspen, birch, and maple), spanning various sizes. Additionally, we evaluated its sensitivity to TLS scanning protocols—scanning angular resolution, scanning distance between different locations, and number of scan positions—using 107 field-measured angles from two large beech trees. BASeg achieved a root mean square error (RMSE) of 9.96° (14.64 %) and a concordance correlation coefficient (CCC) of 0.89 for branch angle estimation. For estimating BADs, BASeg achieved mean absolute error (MAE) ranging from 2.2 to 381.1 (25.2 % to 69.3 %), outperforming TreeQSM, Laplacian, TreeGraph, L1-tree, and WOODSKE. Neither scanning distance (10–20 m) nor the number of scan positions (3–6) affected the accuracy of branch angles or BADs traits, while scanning angular resolution (0.01°–0.04°) did impact these traits. This study offers an effective approach for quantifying BADs and improves the understanding of fine-scale tree architecture within TLS frameworks.

Elnur Baloglanov, Ulviyya Yolchuyeva, Ruslan Akhundov et al.

Problem statement. This study explores unconventional hydrocarbon resources in East Azerbaijan, focusing on oil-bearing rocks in the Cheyildere and Gyrgyshlag-Girdagh areas. It examines the spatial and temporal distribution of minerals and chemical compositions in Miocene formations. Terrigenous quartz types identified in the Maikop (Lower Miocene), Chokrak (Lower Miocene), and Diatom (Middle to Upper Miocene) formations provide insights into sedimentological maturity. Geochemical classification and tectonic discriminant diagrams help interpret the protoliths of these sediments. The study also evaluates how mineralogy and moisture affect oil-bearing potential, offering useful data for future exploration and resource management. Purpose. This study aims to explore the genesis and potential of oil-bearing deposits of the Miocene age in East Azerbaijan by characterizing the geological, mineralogical, and geochemical proxies of samples collected from outcrops across various regions. Methods. The mineralogical composition of samples was analyzed using a MiniFlex 600 diffractometer. Chemical composition was determined using S8 TIGER Series 2 and Agilent 7700 Series ICP-MS spectrometers. Results. The geological characteristics of oil-bearing deposits from the Miocene stratigraphic unit were thoroughly analyzed, providing new insights into the distribution patterns of oil-bearing formations and strata within the studied areas. The mineralogical composition was examined in detail, focusing on the spatial and temporal variations in mineral distribution across different formations of Miocene. The chemical composition reveals significant differences between formations in terms of elemental signatures. The study of the chemical proxies enabled the identification of specific terrigenous quartz types. Additionally, the research assessed the influence of mineralogical composition, moisture and oil content on the oil-bearing capacity. The results demonstrated a clear relationship between the mineralogical characteristics and the oil-bearing potential of the rocks. Conclusions. The Chokrak Formation is of particular interest due to its significant oil-bearing potential, with total thicknesses of up to 40 meters in Miocene outcrops studied in the areas of Cheyildere and Gyrgyshlag-Girdagh. Compared to other areas, the Chokrak Formation is dominated by quartz minerals (>70%), while the oil-bearing rocks of this formation contain fewer clay minerals and no carbonate minerals. The Upper Maikop deposits are characterized by calcite, and the Diatom deposits by dolomite. Most oil-bearing rocks of Maikop and Diatom age correlate with greywacke and litharenite, while Chokrak rocks with higher silicon content show a connection with subarkose and sublitharenites. For Diatom oil-bearing rocks, in addition to quartzitic sedimentary sources, some moderate and acidic magmatic rocks can also be considered. Chokrak horizon deposits, rich in quartz, have a more mature mineralogical nature. These deposits, associated with passive continental margins, are typically linked to the interior of cratons or recycled orogenic regions, suggesting long-distance transport. Relatively moist samples containing clay and carbonate minerals exhibit a significantly higher oil accumulation potential than samples with high quartz content. From this perspective, the marly rocks of the Meotis are of particular interest.

Fang Liu, Hongbo Zhang, Yihang Li et al.

Study region: This study focuses on the Wuding River Basin, located in the middle reaches of the Yellow River Basin in China. Study focus: Event Synchronization (ES) and Event Coincidence Analysis (ECA) were used to investigate the spatiotemporal co-evolution of the multi type of meteorological variable drought (SIMVs) and SSMI in the basin, including the precursor and triggering effect of SIMVs on agricultural drought and the occurrence and development of different levels of agricultural drought events under meteorological variable disturbance. New hydrological insights for the region: In the precursor-and-trigger analysis of ECA, SWI was the main precursor and trigger factor for mild agricultural drought and SPI for moderate and severe drought. The precursor coincidence rate is higher than the trigger coincidence rate, suggesting that not all precursory SIMV events cause agricultural drought. All precursory and triggering effects diminish as the observation time window rises, demonstrating that SIMV has a bigger impact on low-grade agricultural drought. SPI caused 26.86 % of agricultural drought, whereas coupled SIMVs triggered it. The synchronization analysis shows that the lag times for SPI, STI, SWI, and SNR early warnings of drought are 65.7 days, 60.5 days, 52.8 days, and 55.8 days, respectively. The lag times for SIMV triggers are 61.8 days, 53.7 days, 48.4 days, and 53 days.

Minghan Chu, Weicheng Qian

Predicting the evolution of turbulent flows is central across science and engineering. Most studies rely on simulations with turbulence models, whose empirical simplifications introduce epistemic uncertainty. The Eigenspace Perturbation Method (EPM) is a widely used physics-based approach to quantify model-form uncertainty, but being purely physics-based it can overpredict uncertainty bounds. We propose a convolutional neural network (CNN)-based modulation of EPM perturbation magnitudes to improve calibration while preserving physical consistency. Across canonical cases, the hybrid ML-EPM framework yields substantially tighter, better-calibrated uncertainty estimates than baseline EPM alone.

Deaglan J. Bartlett, Harry Desmond, Pedro G. Ferreira et al.

Symbolic regression (SR) has emerged as a powerful method for uncovering interpretable mathematical relationships from data, offering a novel route to both scientific discovery and efficient empirical modelling. This article introduces the Special Issue on Symbolic Regression for the Physical Sciences, motivated by the Royal Society discussion meeting held in April 2025. The contributions collected here span applications from automated equation discovery and emergent-phenomena modelling to the construction of compact emulators for computationally expensive simulations. The introductory review outlines the conceptual foundations of SR, contrasts it with conventional regression approaches, and surveys its main use cases in the physical sciences, including the derivation of effective theories, empirical functional forms and surrogate models. We summarise methodological considerations such as search-space design, operator selection, complexity control, feature selection, and integration with modern AI approaches. We also highlight ongoing challenges, including scalability, robustness to noise, overfitting and computational complexity. Finally we emphasise emerging directions, particularly the incorporation of symmetry constraints, asymptotic behaviour and other theoretical information. Taken together, the papers in this Special Issue illustrate the accelerating progress of SR and its growing relevance across the physical sciences.

J. M. Alarcón, E. Lope-Oter, Y. Cano

There is an increasing interest in the community for the Neutron Stars and what we can learn from them. In this review we show how chiral effective field theory, combined with many-body methods, can provide important results that connect Neutron Star properties at zero temperature to nuclear physics and allows to use these compact objects as laboratories of new physics.

Laura Rodica Giurgiu, Cosmin Damian, Anca Maria Sabău et al.

This study aimed to explore the impact of the first two waves of the COVID-19 pandemic on the mental and physical states of sports students from Romania and also to compare the differences according to gender and the type of sport. Initially, in order to collect demographic data and health reports, a cross-sectional survey was developed to evaluate the emotional needs of sports students during the pandemic. After the second wave, the coping strategies used by the participants to fight negative emotions were assessed using the CERQ questionnaire. The results indicate that depression symptoms are the most reported psychological issues among the participants and that there are differences according to gender concerning the cognitive schemas they use in order to reduce the symptoms. Also, it was found that there are differences, corresponding to the type of sport, in choosing adaptive coping mechanisms. Ultimately, it was confirmed that higher levels of hopelessness among sports students are associated with increased vulnerability to substance use, with the correlation between those two indicators being strong. Delving deeper into this relationship can help identify critical points for intervention to prevent substance abuse. At the same time, the dichotomic analysis of the results found as moderators—the gender and the type of sport in decreasing the severity of depression could be an important aspect of the next counseling interventions.

Chao Xu, Wen Wang, Yanjun Hu et al.

Study region: China. Study focus: Accurate estimation of potential evapotranspiration (PET) is essential for understanding climate change. Using ground-based pan evaporation measurements over continental China, the monthly scale PET data during 2000–2017 of ERA5, ERA5-Land, GLDAS-2.1/Noah, and GLEAM V3.8a are evaluated, from the perspectives of their consistency in spatiotemporal variation, and performance measures. Factors controlling the data quality of the four datasets are investigated from the perspective of their PET calculation models and meteorologically input data. New hydrological insights for the region: PETERA5 performs the best in mainland China among four gridded PET datasets with higher correlation coefficients (r) and smaller biases, which can well capture the temporal variation of Epan. The outstanding performance of PETERA5 in China mainly results from the utilization of the Penman-Monteith (P-M) equation which performs the best among several competing formulas for PET computation, as well as its better meteorological inputs for computing PET than other datasets. Although the PETERA5-Land is a replay of the land component of the ERA5 climate reanalysis, it exhibits substantial overestimation of PET values and temporal trends, particularly in coastal areas of Southern China and the eastern side of Northeastern China, mainly caused by the overestimation of its net radiation. The PETGLDAS shows significant overestimation, partly due to its overestimation of wind speed, but mostly due to its modified P-M equation with its parameterization of land surface conditions for computing PETGLDAS. The PETGLEAM underestimated PET generally mainly due to the joint effect of the use of the Priestley-Taylor equation with small P-T parameter α, and the underestimation of the net radiation input from ERA-Interim, especially in Northwest and Qinghai Tibet.

Calum Buchanan, MacKenzie Carr, Alexander Clifton et al.

We study a two-player game played on undirected graphs called {\sc Trail Trap}, which is a variant of a game known as {\sc Partizan Edge Geography}. One player starts by choosing any edge and moving a token from one endpoint to the other; the other player then chooses a different edge and does the same. Alternating turns, each player moves their token along an unused edge from its current vertex to an adjacent vertex, until one player cannot move and loses. We present an algorithm to determine which player has a winning strategy when the graph is a tree and partially characterize the trees on which a given player wins. Additionally, we show that it is NP-hard to determine if Player~2 has a winning strategy on {\sc Trail Trap} from the starting position, even for connected bipartite planar graphs with maximum degree $4$. We determine which player has a winning strategy for certain subclasses of complete bipartite graphs and grid graphs, and we propose several open problems for further study.

Zhiye Wang, Chuanming Ma, Yan Zhang et al.

Expanding urbanization has led to an increased risk of urban flooding, which poses a hazard to humans. Scientific assessment of urban flooding vulnerability (UFV) is essential to protect human health and reduce losses. In this study, UFV was assessed using the Analytic Hierarchy Process-Press-State-Response (AHP-PSR) model in Jining City, China. The urban flooding index (UFI) was calculated from 13 indicators. Based on the magnitude of UFI, the vulnerability was classified into five classes. Among them, the areas of very high, high, medium, low and very low vulnerability are 897.21 km2 (8.02%), 3192.14 km2 (28.53%), 2063.22 km2 (18.44%), 39773.96 km2 (35.52%) and 1060.47 km2 (9.48%), respectively. Finally, suggestions were proposed for further urban flooding management based on the results. The results of the study can provide an important reference for the government to prevent and mitigate urban flooding. Meanwhile, the modeling framework can be easily transferred to other cities, providing new ideas for UFV assessment.

Zbyněk Engel, Kamil Láska, Jan Kavan et al.

The retreat rates of Triangular Glacier since 1979 and its mass changes during the period 2014/15–2019/20 indicate the sensitive response of small ice masses on the eastern side of the Antarctic Peninsula to air temperature evolution. This cirque glacier in the northern part of James Ross Island receded rapidly during the period of regional warming in the late 20th century, losing 30.8% of its surface area between 1979 and 2006 (−1.7% a−1). The retreat rate then dropped to −0.3% a−1 following the regional cooling trend, but started to accelerate again (−0.8 to −2.3% a−1) with increasing air temperature since the summer 2014/15. Since the glaciological year 2015/16, Triangular Glacier has experienced enhanced snow melt, wind scour and permanent mass loss with annual mass balance ranging from −0.08 ± 0.35 to −0.56 ± 0.25 m w.e. The largest mass loss was observed in the glaciological year 2019/20, which included the warmest summer of the observation period. The cumulative mass balance of −1.66 ± 0.83 m w.e. over the years 2014/15–2019/20 is consistent with the termination of the positive mass-balance period that occurred in the north-eastern Antarctic Peninsula from 2009/10 to 2014/15.

Maxwell X. Cai, Kin Long Kelvin Lee

In physics, density $ρ(\cdot)$ is a fundamentally important scalar function to model, since it describes a scalar field or a probability density function that governs a physical process. Modeling $ρ(\cdot)$ typically scales poorly with parameter space, however, and quickly becomes prohibitively difficult and computationally expensive. One promising avenue to bypass this is to leverage the capabilities of denoising diffusion models often used in high-fidelity image generation to parameterize $ρ(\cdot)$ from existing scientific data, from which new samples can be trivially sampled from. In this paper, we propose $ρ$-Diffusion, an implementation of denoising diffusion probabilistic models for multidimensional density estimation in physics, which is currently in active development and, from our results, performs well on physically motivated 2D and 3D density functions. Moreover, we propose a novel hashing technique that allows $ρ$-Diffusion to be conditioned by arbitrary amounts of physical parameters of interest.

Hongjie He, Hongzhang Xu, Ying Zhang et al.

Fine-scale land disturbances due to mining development modify the land surface cover and have cumulative detrimental impacts on the environment. Understanding the distribution of fine-scale land disturbances related to mining activities, such as oil well sites, in mining regions is of vital importance to sustainable mining development. For efficient mapping, automated identification and extraction of the oil well sites using high-resolution satellite images are required. In this work, we proposed the Oil Well Site extraction (OWS) Mask R-CNN based on the original Mask R-CNN (Region-based Convolutional Neural Networks), to accurately extract well sites using multi-sensor remote sensing images. For improvement of mapping efficiency, two modifications were made to Mask R-CNN: (1) replacing the backbone of Mask R-CNN with D-LinkNet, and (2) adding a semantic segmentation branch to Mask R-CNN to force the whole network to focus on the relationship between line objects and oil well sites. As imagery data were from multiple sensors (RapidEye 2/3 and WorldView 3), a pre-trained Residual Channel Attention Network (RCAN) was applied to super-resolve the images with different resolutions. Several key spatial features, such as nearby roads and area size, have also been used in the oil well site mapping process. The experimental results indicate that our OWS Mask R-CNN considerably improves the average precision (AP) and the F1 score of Mask R-CNN from 51.26% and 25.7% to 60.93% and 61.59%, respectively.

J. Ma, S. Olin, P. Anthoni et al.

<p>Biological nitrogen fixation (BNF) from grain legumes is of significant importance in global agricultural ecosystems. Crops with BNF capability are expected to support the need to increase food production while reducing nitrogen (N) fertilizer input for agricultural sustainability, but quantification of N fixing rates and BNF crop yields remains inadequate on a global scale. Here we incorporate two legume crops (soybean and faba bean) with BNF into a dynamic vegetation model LPJ-GUESS (Lund–Potsdam–Jena General Ecosystem Simulator). The performance of this new implementation is evaluated against observations from a range of water and N management trials. LPJ-GUESS generally captures the observed response to these management practices for legume biomass production, soil N uptake, and N fixation, despite some deviations from observations in some cases. Globally, simulated BNF is dominated by soil moisture and temperature, as well as N fertilizer addition. Annual inputs through BNF are modeled to be <span class="inline-formula">11.6±2.2</span> Tg N for soybean and <span class="inline-formula">5.6±1.0</span> Tg N for all pulses, with a total fixation of <span class="inline-formula">17.2±2.9</span> Tg N yr<span class="inline-formula">⁻¹</span> for all grain legumes during the period 1981–2016 on a global scale. Our estimates show good agreement with some previous statistical estimates but are relatively high compared to some estimates for pulses. This study highlights the importance of accounting for legume N fixation process when modeling C–N interactions in agricultural ecosystems, particularly when it comes to accounting for the combined effects of climate and land-use change on the global terrestrial N cycle.</p>

Nhat M. Nguyen, Hieu T. Tran, Minh V. Duong et al.

We present a differentiable greenhouse simulation model based on physical processes whose parameters can be obtained by training from real data. The physics-based simulation model is fully interpretable and is able to do state prediction for both climate and crop dynamics in the greenhouse over very a long time horizon. The model works by constructing a system of linear differential equations and solving them to obtain the next state. We propose a procedure to solve the differential equations, handle the problem of missing unobservable states in the data, and train the model efficiently. Our experiment shows the procedure is effective. The model improves significantly after training and can simulate a greenhouse that grows cucumbers accurately.

Daniel Kelshaw, Luca Magri

Measurements on dynamical systems, experimental or otherwise, are often subjected to inaccuracies capable of introducing corruption; removal of which is a problem of fundamental importance in the physical sciences. In this work we propose physics-informed convolutional neural networks for stationary corruption removal, providing the means to extract physical solutions from data, given access to partial ground-truth observations at collocation points. We showcase the methodology for 2D incompressible Navier-Stokes equations in the chaotic-turbulent flow regime, demonstrating robustness to modality and magnitude of corruption.

Людмила Горбачова, Борис Христюк

Formulation of the problem. The water flow of the Styr River is using for the needs of industry, agriculture and the population. Thus, forecasting the water flow of this river for the future is an important scientific and practical task. The hydrological forecasts that have a lead time of one year, two years, or a decade are not as reliable as they need to be. Now in the world this problem is not solved. Along with quantitative forecasting methods, the qualitative methods have also been developed. The method of commensurability refers to such methods. It was developed by Chinese geophysicist Weng Wen-Bo in 1984. The commensurability method supports prediction of various natural phenomena, including floods and other dangerous events. The objective of this paper is to use the Weng Wen-Bo method for long-term water flow forecasting of the Styr River at Lutsk city. Methods. The commensurability method uses the dates on which natural phenomena (earthquakes, floods, droughts, etc.) were observed. For this reason, it has been called the information method. It is characterized by simplicity of calculation, graphical visualization, the use of researcher intuition and minimum needs for input information. There are several ways of forecasting using the method of commensurability. This paper is used a method of forecasting by two-dimensional commensurability graphs. Such approach consists in the determining the commensurability values in the dates array of certain phenomena occurrence and creating a two-dimensional graph of commensurability, according to which forecasting occurs. The use of such a method allows determining the years that may be wet and dry in the near future. Results. The data of observations at the hydrological station of the Styr River - Lutsk city for the period 1923-2017 are used in the paper. The results of the study on the commensurability method show that the water flow of the river Styr in 2020-2021 should be more than the norm and in 2023-2024 - less than the norm. Scientific novelty and practical significance. In Ukraine the commensurability method was used for the first time for long-term forecasting of water flow for coming years. The estimating of the effectiveness of forecasting by the commensurability method requires an array of long-term forecasts. Therefore, the next step of the study should be to forecast of water flow on different rivers, but provided that they have the long series of observation. The results of the long-term forecasting will enable the relevant services the negative consequences of a hydrological phenomenon, such as low water flow or floods on rivers will prevent.