Hydrological Analysis Research Articles

Hydraulic model for flood inundation in Diyala River Basin using HEC-RAS, PMP, and neural network

Abstract The Diyala River Basin in Iraq is vital for water supply to residential, agricultural, and the Tigris River (with approximately 4.5 billion cubic meters annually), but it faces frequent floods and droughts due to reliance on rainfall. This study aims to address these issues by simulating flood inundation using the hydrological engineering centre-river analysis system model and predicting high-intensity rainfall with artificial neural networks. ArcGIS and remote sensing tools aid model development with data from official sources and organizations such as national aeronautics and space administration and food and agriculture organization. The hydraulic model is calibrated using satellite imagery to depict a 2019 flood, and artificial intelligence predicts the precipitation patterns for the next 50 years based on historical data from 1981 to 2021. One of the challenges and difficulties encountered in the study is the scarcity of available data, as well as the absence of scientific research pertaining to the region regarding hydraulic modeling. The study identifies flood risks in March and April every year, notably for the Hemrin Dam, which may exceed permissible water levels (reach a level over 110 m where the Hemrin Crest level is 109.5 m). To mitigate this, an artificial canal is proposed to divert water annually, protecting the dam and downstream areas without disrupting operations. The diverted water could also augment the Tigris River in Kut Governorate during summer. The study demonstrates the value of integrating multiple modeling techniques and data sources for accurate hydraulic predictions. It offers insights for decision-makers in flood management and planning. This study contributes to efficient flood management strategies by adopting a multidisciplinary approach.

Optimization of Targeted Differential Interferometric Measurements for Wellpads Detected by Mask Region-Based Convolutional Neural Network in the Tengiz Oilfield of the Caspian Sea Coast

Many previous studies have primarily focused on the use of deep learning for interferometric processing or separate recognition purposes rather than targeted measurements of detected wellpads. The present study centered around the integration of deep learning recognition and interferometric measurements for Tengiz oilfield wellpads. This study proposes the optimization, automation, and acceleration of targeted ground deformation wellpad monitoring. Mask Region-based Convolutional Neural Network (R-CNN)-based deep learning wellpad recognition and consequent Small Baseline Subset Synthetic Aperture Radar Interferometry (SBAS-InSAR) analyses were used for the assessment of ground deformation in the wellpads. The Mask R-CNN technique allowed us to detect 159 wells with a confidence level of more than 95%. The Mask R-CNN model achieved a precision value of 0.71 and a recall value of 0.91. SBAS-InSAR interferometric measurements identified 13 wells for Sentinel-1 (SNT1), 8 wells for COSMO-SkyMed (CSK), and 20 wells for TerraSAR-X (TSX) located within the −54–−40 mm/y class of vertical displacement (VD) velocity. Regression analyses for the annual deformation velocities and cumulative displacements (CD) of wells derived from SNT1, CSK, and TSX satellite missions showed a good agreement with R2 > 95. The predictions for cumulative displacements showed that the vertical subsidence processes will continue and reach −339 mm on 31 December 2023, with increasing spatial coverage and the potential to impact a higher number of wells. The hydrological analyses in the Tengiz oilfield clearly demonstrated that water flow has been moving towards the detected hotspot of subsidence and that its accumulation will increase with increasing subsidence. This detected subsidence hotspot was observed at a crossing with a seismic fault that might always be subject to reactivation. The role of this seismic fault should also be investigated as one of the ground deformation-controlling factors, even though this area is not considered seismically active. The primary practical and scientific values of these studies were identified for the operational risk assessment and maintenance needs of oilfield and gas field operators.

Monitoring Dan Evaluasi Jaringan Drainase Yang Ramah Lingkungan Di Perumahan Villa Delima Mayang Kota Jambi

The rainy season, which has a fairly high frequency over a long period of time, results in the need for drainage so that the amount of rainwater can be channeled into water bodies and some of it can be used for purposes in daily life. This is so as not to cause inundation and flooding problems. This research aims to analyze the condition of the existing drainage network, calculate runoff discharge, plan infiltration wells for utilizing rainwater in the Villa Delima Mayang housing complex, Jambi City. The method used in this planning uses hydrological analysis calculations including mononobe, pearson III and rational log methods. In planning infiltration wells, it refers to the Indonesian National Standard (SNI) No. 03-2453-2002. The result of the 10 year return period design rainfall is 112.17 mm. the results of the analysis of the carrying capacity show that 9 out of 14 channels are unable to accommodate the 10 year return period design discharge. Next, an absorption well with a diameter of 0.8 meters and a depth of 1.5 meters is planned and placed in a drainage channel that cannot accommodate runoff. The absorption capacity of 1 well is 0.7536 m3.

A Review of Empirical Methods for Runoff Estimation and Their GIS Applications

Abstract: Irregularities in rainfall patterns, frequent floods, and droughts in different parts of the world result from the effects of global climate change. In such dynamic climatic conditions, sustainable management of water resources is a challenging task under a river basin's complex process response system. In this perspective, hydrological studies are being carried out to estimate the runoff water yield and understand physico-climatic controls require further development in methodologies. Research criteria have advanced and empirical method's development and applications have advanced significantly. Empirical methods quantify the runoff volume by correlating the amount of rainfall with the number of influencing basin factors. In recent times, empirical runoff estimation has become popular because of its simplicity and correlation assessment capacity with multiple associate factors. This study aims to have an overview of the empirical runoff estimator SCS-CN method and other empirical equations. This study has covered the primary areas in hydrological analysis are runoff estimation, groundwater recharge, and runoff-soil erosion estimation using empirical methods. The authors have suggested the advantages, disadvantages, and possible areas of development of the widely used SCS-CN method and other empirical methods of runoff estimation.

A watershed-scale multi-approach assessment of design flood discharge estimates used in hydrologic risk analyses for forest road stream crossings and culverts

Flood peak magnitudes and frequency estimates are key components of any effective nationwide flood risk management and flood damage abatement program. In this study, we evaluated normalized peak design discharges (Qp) for 1,387 hydrologic unit code 16 to 20 (HUC16-20) watersheds in the White Mountain National Forest (WMNF), New Hampshire and in five Experimental Forest (EF) regions across the United States managed by USDA Forest Service (USDA-FS). Nonstationary regional frequency analysis (RFA) and single site frequency analysis (FA) with long-term high-resolution observed streamflow data along with the deterministic Rational Method (RM) and semi-empirical United States Geological Survey regional regression equation (USGS-RRE) were used. Additionally, a hydrologic vulnerability assessment was performed for 194 road culverts as a result of extreme precipitation-induced flooding on gauged and ungauged watersheds in the Hubbard Brook EF (HBR) within the WMNF. The RM outperformed the USGS-RRE in predicting Qp in the gauged and ungauged HUC16-20 watersheds of WMNF and in three other small, high-relief forest headwater watersheds—Coweeta Hydrologic Lab EF’s watershed-14, and watershed-27 in North Carolina and HJ Andrews EF’s watershed 8 in Oregon. However, the USGS-RRE performed better for larger watersheds, such as the Fraser EF’s St. Louis watershed in Colorado and the Santee EF’s watershed 80 in South Carolina. About 31 %, 26 %, and 56 % of the culverts at the HBR site could not accommodate the 100-yr Qp estimated by RFA, RM and USGS-RRE, respectively. Based on the chosen RIs and techniques, it is determined that except for one culvert with diameter = 0.91 m (36 in.), none of the culverts with diameter of 0.75 m (30 in.) or larger are hydrologically vulnerable. Our results suggest that the observation based RFA works best where multiple gauges are available to extrapolate information for ungauged watersheds, otherwise, RM is best-suited for smaller headwater watersheds and USGS-RRE for larger watersheds. Results from the hydrologic vulnerability analysis revealed that replacing undersized culverts with new culverts of diameter ≥ 0.75-m will improve flood resiliency, provided that the structure is geomorphologically safe (with minimal effects of debris flow, erosion, and sedimentation) and allows for both bank-full discharge and necessary fish passage within that design limit. This study has implications in managing road culverts and crossings at Forest Service and other forested lands for their resiliency to extreme precipitation and flooding hazards induced by climate change.

River Hydrology Analysis For Micro Hydro Power Plant

The Micro Hydro Power Plant (PLTMH) is a generator capable of fulfilling the electrical requirements of isolated regions. PLTMH serves as an alternative means of generating electrical energy for the community. This power facility offers numerous advantages, particularly for remote areas across Indonesia. Water is a crucial energy resource due to its ability to generate electricity, a cost-effective and environmentally friendly kind of energy. The micro-hydro type PLTMH (0.5–100 kilowatts) in Aceh Province is the Lhoong PLTMH, which was built with assistance from PT. Coca-Cola in 2005. This PLTMH is located in Krueng Kala Village, Lhoong District, Aceh Besar Regency. This research aims to determine the availability of the Krueng Kala Lhoong PLTMH's flow rate and the availability of power and energy produced by the Krueng Kala Lhoong PLTMH to meet the electricity needs of Lhoong residents. It is hoped that the benefits of this research will be able to provide development and knowledge, especially in the field of pyrotechnics, and can become reference material for further study, providing information about micro hydropower plants, especially the Krueng Kala Lhoong PLTMH. The research utilizes the Pearson III Log Method to calculate maximum rainfall frequency and Fj Mock for reliable discharge calculation. The research results showed that the full rain discharge with a return period of 25 years was 1152.68 mm/hour. The total potential evapotranspiration (ET0) value occurred in March, reaching 6,649 mm/day. The mainstay discharge with a probability of 85% is Q85% = 0.24 m3/second, obtaining power of 27,914 kW and energy for a year of 20787,644 kWh. The calculation results conclude that the Krueng Kala power plant is still classified as a PLTMH, producing power below 100 kW and generating an annual energy of 20,787,644 kWh. The electricity can be distributed to Meunasah Krueng Kala Village, Baroeh Krueng Kala Village, Tunong Krueng Kala Village, and small enterprises in these three communities.

Integrated Hydrological Modeling for Watershed Analysis, Flood Prediction, and Mitigation Using Meteorological and Morphometric Data, SCS-CN, HEC-HMS/RAS, and QGIS

Flooding is a natural disaster with extensive impacts. Desert regions face altered flooding patterns owing to climate change, water scarcity, regulations, and rising water demands. This study assessed and predicted flash flood hazards by calculating discharge volume, peak flow, flood depth, and velocity using the Hydrologic Engineering Centre-River Analysis System and Hydrologic Modelling System (HEC-HMS and HEC-RAS) software. We employed meteorological and morphological data analyses, incorporating the soil conservation service (SCS) curve number method for precipitation losses and the SCS-Hydrograph for runoff transformation. The model was applied to two drainage basins (An-Nawayah and Al-Rashrash) in southeastern Cairo, Egypt, which recently encountered several destructive floods. The applied model revealed that 25-, 50-, and 100-year storms produced runoff volumes of 2461.8 × 103, 4299.6 × 103, and 5204.5 × 103 m3 for An-Nawayah and 6212 × 103, 8129.4 × 103, and 10,330.6 × 103 m3 for Al-Rashrash, respectively. Flood risk levels, categorised as high (35.6%), extreme (21.9%), and medium (21.12%) were assessed in low- and very-low-hazard areas. The study highlighted that the areas closer to the Nile River mouth faced greater flood impacts from torrential rain. Our findings demonstrate the effectiveness of these methods in assessing and predicting flood risk. As a mitigation measure, this study recommends the construction of five 10 m high dams to create storage lakes. This integrated approach can be applied to flood risk assessment and mitigation in comparable regions.

A Methodology for Water Resource Management and the Planning of the Coastal Reservoir in Indonesia

Metropolitan areas in Indonesia, specifically Jabodetabek, are projected to continue experiencing population growth. This will result in increased water demand, which, if left unchecked, could lead to a water crisis. Additionally, the region faces persistent flooding issues. To mitigate these challenges, the Indonesian government proposes the creation of a coastal reservoir. However, a methodology for the pre-feasibility study of such reservoirs in Indonesia is currently lacking. This study addresses this gap by presenting a methodological framework encompassing hydrology and water allocation analyses as well as numerical modeling related to hydraulic and sedimentation aspects of coastal reservoirs. The methodology was designed to be adaptable based on data availability. Finally, this methodology was applied to a case study located at the Cisadane River estuary. The water allocation simulation showed that the reservoir can release an annual optimum discharge of 80.618 m3/s in wet years and 22.731 m3/s in dry years. Flood modeling demonstrated a modest impact on reducing early-hour floods, with a water level decrease of around 20–50 cm within 5 km of the reservoir. Furthermore, sediment modeling revealed varying sedimentation and erosion depths along the rivers, with approximately 62,300 m3/year settling in the reservoir.

Predicting the peak flow and assessing the hydrologic hazard of the Kessem Dam, Ethiopia using machine learning and risk management centre-reservoir frequency analysis software

Abstract Flooding due to overtopping during peak flow in embankment dams primarily causes dam failure. The Kessem River watershed of the Awash basin in the Rift Valley of the Afar region in Ethiopia was studied intricately to predict the causes of the Kessem Dam safety using machine learning predictive models and risk management centre-reservoir frequency analysis. Recently developed recurrent neural network predictive models with hybrid Soil Conservation Service Curve Number (SCS-CN) were used for simulation of river flow. Peak daily inflow to the reservoir is predicted to be 467.72, 435.88, and 513.55 m3/s in 2035, 2061, and 2090, respectively. The hydrologic hazard analysis results show 2,823.57 m3/s and 935.21 m; 2,126.3 m3/s and 934.18 m; and 11,491.1 m3/s and 942.11 m peak discharge and maximum reservoir water level during the periods of 2022–2050, 2051–2075, and 2076–2100, respectively, for 0.0001 annual exceedance probability. The Kessem Dam may potentially be overtopped by a flood with a return period of about 10,000 years during the period of 2076–2100. Quantitative hydrologic risk assessment of the dam is used for dam safety evaluation to decide whether the existing structure provides an adequate level of safety, and if not, what modifications are necessary to improve the dam's safety.

Unveiling the climate–conflict nexus: Examining the influence of weather extremes on conflict emergence in the Philippine Bangsamoro

Extreme weather events have been closely associated with the escalation of violent conflicts. This article introduces empirical evidence that underscores the vulnerability of conflict emergence to extended deficit rainfall values within Maguindanao, a province situated in the Bangsamoro region of the southern Philippines. Using a combination of satellite data, hydrological analysis and an examination of conflict databases, our study unveils the pivotal role played by protracted droughts and intensified precipitation in fostering human insecurity, consequently elevating the likelihood of violent conflicts. Our research spotlights the climate–conflict nexus within this relatively less-explored geographical area. Our findings underscore a robust association between instances of violent conflicts, protracted deficits or episodes of intense rainfall, and the subsequent surge in food prices. Notably, disruptions in food prices align temporally with heightened participation in violent conflicts by individuals. In essence, the emergence of violent conflicts exacerbates fragility, thereby engendering a vicious cycle that intertwines climate change, conflict dynamics and the pursuit of peace.

Watershed Management for Sustainable Livelihoods: Integrating Local Pond Ecosystems in Malda, West Bengal

This research article explores the intricate relationship between watershed management, local pond ecosystems, and sustainable livelihoods in the Malda district of West Bengal. The study investigates the potential of integrating local pond ecosystems into watershed management strategies as a means to enhance economic prosperity, ecological resilience, and community well-being. Through a multidisciplinary approach, combining ecological assessments, socioeconomic surveys, and participatory engagement, the research aims to provide insights into the synergies that exist between watershed management practices and the sustainable livelihoods of the local villagers. The research methodology involves field studies encompassing hydrological analysis, biodiversity assessments, and community consultations, aimed at understanding the dynamics of local pond ecosystems and their interconnectedness with the broader watershed. Special attention is given to the diverse ecosystem services provided by these ponds, such as water provisioning, nutrient cycling, and supporting aquatic biodiversity, and how they contribute to the overall resilience of the watershed. The findings of this study are expected to contribute valuable information for policymakers, environmental practitioners, and local communities in Malda district, offering a comprehensive understanding of how the integration of local pond ecosystems into watershed management plans can foster sustainable livelihoods. The article discusses potential strategies for optimizing the co-management of these resources, balancing the ecological health of the ponds with the socioeconomic needs of the local population. Ultimately, this research aims to provide a blueprint for sustainable watershed management practices that prioritize the conservation and utilization of local pond ecosystems, fostering a harmonious balance between ecological integrity and the livelihood aspirations of the communities in Malda, West Bengal.

Potential Dam Breach Flood Assessment with the 2D Diffusion and Full Dynamic Wave Equations Using a Hydrologic Engineering Center-River Analysis System

Dam breaches have catastrophic consequences, causing severe property damage, life loss, and environmental impact. The potential dam breach downstream flooding of the Kulekhani reservoir, Nepal, was studied using a 2D Diffusion Wave Equation (DWE) and Full Dynamic Wave Equation (FDWE) through an open-source solver, Hydrologic Engineering Center-River Analysis System (HEC-RAS). The suitable dam breach model was identified based on the dam geometry and sixteen historical dam failure cases. The simulated downstream peak was tested with an empirical relation, considering reservoir volume and duration of failure. Model comparisons through the flood plain mapping of water depth, flow velocity, flood intensity as per guidelines of the American Society of Civil Engineers (ASCE), and arrival time were carried out for flood hazard assessment. FDWE was able to capture the physical flow phenomena in the river bend resulting in higher flow velocity at the outer bend, lower velocity at the inner bend, and formation of eddies due to the application of the turbulence model, considering possible momentum losses, whereas DWE was unable to capture these effects due to a simplified momentum equation. The total area of flood extension was found to be increased by 30% using FDWE than the DWE due to higher water surface elevation. Most of the towns along the Kulekhani River were classified as “Very High” intensity flood regions according to ASCE, due to the V-shape valley. The peak time difference at the Bagmati River confluence was evaluated between the models. This plays an important role in decision-making for the selection of the flood model to make a safe evacuation plan. The application of FDWE was found to be suitable for the rapidly varying unsteady flow in the steep meandering river.

Compound Impact of Storm Surge and Flood Characteristics in Coastal Area Based on Copula

In low-lying coastal areas, the interplay of various factors including precipitation, river flow, and storm surge can lead to greater influence on floods when they occur simultaneously. The copula method was used in this study to investigate the bivariate flood risk of compounding storm surge and river discharge events in the Pearl River Delta (PRD). Our results indicate that while the correlation between storm surge and flood peak (S-Q) was weak, there was a strong dependence between the pairs of storm surge–flood volume (S-V) and storm surge–flood duration (S-D). For these three pairs, the Clayton copula was the optimal function for S-Q, while the Frank copula was the optimal function for S-V and S-D, respectively. When the flood volume exceeds 2.0 × 104 m3/s and the flood duration is more than 10 days, the bivariate hydrologic risk for S-V and S-D is observed to decrease rapidly. Furthermore, the failure probability (FP) would be underestimated when the combined impact of river flow and storm surge is ignored in coastal flood risk assessment. Such bivariate hydrologic risk analysis implies that when determining design values in coastal flood risk assessment, the combined impact of river flow and storm surge should be taken into account.

“Flood inundation mapping of upstream region in the Adyar River basin: Integrating hydrologic engineering centre's river analysis system (HEC-RAS) approach with groundwater considerations”

Chennai, the capital of Tamil Nadu, has grappled with recurrent devastating floods, notably in 2015 and 2021, originating from the upstream of the Adyar River basin. These events have profoundly impacted the city's growth sectors. The regions both upstream and downstream of the Adyar basin, covering Chennai and Chengalpattu districts, face increased vulnerability to severe riverine flooding due to rapid urbanization. The interplay of extensive urban development and river overflow during monsoon seasons has created conditions conducive to substantial flooding, necessitating the development of an effective flood model. This study utilizes digital elevation data and unit hydrograph analysis to estimate flood return probability water levels for various recurrence intervals, including the 10-year and 100-year events. Moreover, it investigates flood inundation, specifically in the Somangalam area, providing insights into the extent of water spread. To comprehensively address the flood dynamics, the study incorporates considerations for groundwater interactions. The overarching objective remains to identify the most vulnerable zones within the Adyar River region prone to flooding. Accurate identification of these vulnerable areas is crucial for policymakers and stakeholders to devise proactive planning and early warning measures, enhancing disaster preparedness and resilience in the face of potential flood disasters. This approach aims to safeguard the well-being of Chennai's residents and promote sustainable development in the region.

Comparative Evaluation of Deep Learning Techniques in Streamflow Monthly Prediction of the Zarrine River Basin

Predicting monthly streamflow is essential for hydrological analysis and water resource management. Recent advancements in deep learning, particularly long short-term memory (LSTM) and recurrent neural networks (RNN), exhibit extraordinary efficacy in streamflow forecasting. This study employs RNN and LSTM to construct data-driven streamflow forecasting models. Sensitivity analysis, utilizing the analysis of variance (ANOVA) method, also is crucial for model refinement and identification of critical variables. This study covers monthly streamflow data from 1979 to 2014, employing five distinct model structures to ascertain the most optimal configuration. Application of the models to the Zarrine River basin in northwest Iran, a major sub-basin of Lake Urmia, demonstrates the superior accuracy of the RNN algorithm over LSTM. At the outlet of the basin, quantitative evaluations demonstrate that the RNN model outperforms the LSTM model across all model structures. The S3 model, characterized by its inclusion of all input variable values and a four-month delay, exhibits notably exceptional performance in this aspect. The accuracy measures applicable in this particular context were RMSE (22.8), R2 (0.84), and NSE (0.8). This study highlights the Zarrine River’s substantial impact on variations in Lake Urmia’s water level. Furthermore, the ANOVA method demonstrates exceptional performance in discerning the relevance of input factors. ANOVA underscores the key role of station streamflow, upstream station streamflow, and maximum temperature in influencing the model’s output. Notably, the RNN model, surpassing LSTM and traditional artificial neural network (ANN) models, excels in accurately mimicking rainfall–runoff processes. This emphasizes the potential of RNN networks to filter redundant information, distinguishing them as valuable tools in monthly streamflow forecasting.

Akurasi Data Curah Hujan Satelit Terhadap Data Pengukuran di Daerah Tangkapan Air (DTA) Waduk Sutami

Sutami Reservoir that located in the Brantas River Basin is a multi-purpose reservoir, it’s used to provide of raw water, irrigation, flood control, and power plants, fish farm, and tourism. Rainfall data information is very important in hydrological analysis as the basis for determining operating patterns, water balances, and calculating sediment rates. Rainfall data that is recorded in a row can show us trends or the nature of rain, but in reality it is very difficult to obtain representative rainfall observation data, both in terms of quality and length of observation data, which is quite in accordance with what is required in several locations, it is very difficult due to the absence of rain stations or broken gauges. Therefore, by taking advantage of technological advances, it is necessary to analyze the accuracy of rainfall data via satellite (GPM V6 and TRMM 3B43 V7) as an alternative to using rainfall data to fill data shortages at certain locations. The results of the analysis of the two satellite rainfall data (GPM V6 and TRMM 3B43 V7) are based on the Nash Sutcliffe Efficiency (NSE) parameters, Root Mean Square Errror (RMSE), Real Error (KR), Correlation Coefficient (R) can be used as an alternative to rainfall data, with satellite rainfall data GPM V6 has better accuracy and performance with average value of NSE 0,8, RMSE 66,46, KR 21,63%, R 0,92.

Hydrological modeling and uncertainty analysis for a snow-covered mountainous river basin

Hydrological modeling and uncertainty analysis for a snow-covered mountainous river basin

Distribution of Groundwater Hydrochemistry and Quality Assessment in Hutuo River Drinking Water Source Area of Shijiazhuang (North China Plain)

The Hutuo River Drinking Water Source Area is an important water source of Shijiazhuang (North China Plain). Knowing the characteristics of groundwater chemistry/quality is essential for the protection and management of water resources. However, there are few studies focused on the groundwater chemistry evolution over the drinking water area. In this study, total of 160 groundwater samples were collected in November 2021, and the spatial distribution of groundwater chemistry and related controlling factors were analyzed using hydrological and multivariate analysis. The entropy-weighted water quality index (EWQI) was introduced to assess the groundwater quality. The results show that the hydrogeochemical types of groundwater are Ca-HCO3 (78.1%), mixed Ca-Mg-Cl (20%), and Ca-Cl (1.9%) in the area. Graphical and binary diagrams indicate that groundwater hydrochemistry is mainly controlled by water–rock interaction (i.e., rock weathering, mineral dissolution, and ion exchange). Five principal components separated from the principal component analysis represent the rock–water interaction and agricultural return, redox environment, geogenic sources, the utilization of agricultural fertilizer, the weathering of aluminum silicates, and dissolution of carbonates, respectively. More than 70% of the samples are not recommended for irrigation due to the presence of high salt content in groundwater. EWQI assessment demonstrates that the quality of the groundwater is good. The outcomes of this study are significant for understanding the geochemical status of the groundwater in the Hutuo River Drinking Water Source Area, and helping policymakers to protect and manage the groundwater.

Hydro-meteorological droughts across the Baltic Region: The role of the accumulation periods

Based on the physical and geographical conditions, the Baltic Region is categorised as a humid climate zone. This means that, there is usually more precipitation than evaporation throughout the year, suggesting that droughts should not occur frequently in this region. Despite the humid climate in the region, the study focused on assessing the spatio-temporal patterns of droughts. The drought events were analysed across the Baltic Region, including Sweden, Finland, Lithuania, Latvia, and Estonia. This analysis included two drought indices, the Standardized Precipitation Index (SPI) and the Streamflow Drought Index (SDI), for different accumulation periods. Daily data series of precipitation and river discharge were used. The spatial and temporal analyses of selected drought indices were carried out for the Baltic Region. In addition, the decadal distribution of drought classes was analysed to disclose the temporal changes and spatial extent of drought patterns. The Pearson correlation between SPI and SDI was applied to investigate the relationship between meteorological and hydrological droughts. The analysis showed that stations with more short-duration SPI or SDI cases had fewer long-duration cases and vice versa. The number of SDI cases (SDI ≤ −1) increased in the Western Baltic States and some WGSs in Sweden and Finland from 1991 to 2020 compared to 1961–1990. The SPI showed no such tendencies except in Central Estonia and Southern Finland. The 6-month accumulation period played a crucial role in both the meteorological and hydrological drought analyses, as it revealed prolonged and widespread drought events. Furthermore, the 9- and 12-month accumulation periods showed similar trends in terms of drought duration and spatial extent. The highest number of correlation links between different months was found between SPI12-SDI9 and SPI12-SDI12. The results obtained have deepened our understanding of drought patterns and their potential impacts in the Baltic Region.

Hydrological Analysis of the Makassar-Pare Corridor Rail Elevated Bridge in Pangkep Regency South Sulawesi Province

Hydrological analysis is an important stage in the development of water resources. Determining hydrological quantities is actually not too difficult if the data for analysis purposes is available in sufficient quantity and quality. The method used for the analysis of the planned flood discharge depends on the amount of discharge data and rainfall data. Based on the analysis of discharge data and rain data. For planning the storage capacity of the river crossing the railway bridge, using the Nakayasu Synthetic Unit Hydrograph (HSS) Method, the river water level to the JEKA 2 structure is 13.38 m and the river water level to the tracks is 16.38 m so that the railroad tracks at Bridge 2 can be said to be safe against the river water level. Hydrological analysis is one part of a whole series in the planning of transportation structures such as roads, bridges and railway bridges including flood barrier embankments and so on.