Severe Rainfall Research Articles

A comparative analysis of deep-learning models for dam discharge forecasting for disaster management

ABSTRACT This paper represents a comprehensive study of dam water discharge prediction using various deep-learning models. The main aim of this paper is to provide a data-driven solution for effective water resource management and thereby controlling the effects of floods and droughts. The Malampuzha dam, which has a spillway, a right bank canal (RBC), and a left bank canal (LBC), is considered for the study. While the spillway helps to control the water level in the reservoir by allowing extra water to flow downstream during times of severe rainfall or high inflow, hence reducing the risk of floods, the LBC and RBC are intended to divert water for agriculture. Altogether, 10 years of consecutive meteorological and dam-related data are utilized for training and testing the models in forecasting water discharge through LBC, RBC, and the spillway. Different deep-learning models, namely, long short-term memory, Bi-directional long-short term memory, recurrent neural network, gated recurrent unit, one-dimensional convolutional neural network (1D-CNN), deep neural network, autoencoder, and residual networks are explored in predicting the accuracy of dam water discharge. After testing eight deep-learning models, it was discovered that 1D-CNN performed well in predicting the discharge of water.

Cost benefit analysis of flood risk in the area of Thrace in Greece

Cost-benefit analysis can significantly aid the decision-making process for flood risk reduction and mitigation. Decision-makers can use it to weigh the expenses of various flood mitigation strategies against their possible upside in terms of lowering the risk of losses and damage. Decisions regarding how to allocate resources for flood risk management can be made more intelligently with the use of this information by policymakers and stakeholders. During severe rainfall or snowfall, these rivers are prone to flooding, which can harm structures such as homes, businesses, and infrastructure, have negative impacts to land uses and as a result they can cause high opportunity costs. Flooding in the Thrace region can have indirect and direct expenses, including property damage and lost commercial activity. These costs can include communication breakdowns and higher insurance rates. The predicted total economic losses from erosion for all of Greece are €356 million and €649 million for a 0.5- and 1-meter sea level increase, respectively.

Spatiotemporal Pattern Detection of Ground Deformations Induced by Extreme Rainfall using InSAR EGMS: The case of Cortina d’Ampezzo after Vaia Storm

Abstract. During October 2018 Vaia Storm occurred in the north of Italy, resulting in a huge amount of rainfall that was recorded. The focus here is given to Cortina d’Ampezzo area in the Veneto Region, due to the high importance of the area from touristic and sport perspectives and the presence of landslides. This study is devoted to investigating the impact of the severe sudden rainfall caused by this extreme atmospheric disturbance on the trends of ground deformations over this area, adopting a risk assessment perspective. The ground deformation Time Series (TS) have been derived from the European Ground Motion Service (EGMS) Ortho products derived from Sentinel-1 InSAR data. Then, according to the daily precipitation records and considering the time of this event as a turning temporal point, the TSs of all data points have been divided into pre-event and post-event phases. After obtaining the displacement rates in each phase, the quantified magnitude of changes in the pre-post rates has been calculated through a proposed simple formulation. The spatial distribution of the deformation parameters (i.e., pre-event displacement velocity and change in the pre-post displacement velocities) is found to be a practical tool for gaining comprehensive knowledge regarding the ground deformation and the effect of the extreme weather conditions on the displacement trends over the area. Furthermore, the positioning of the occurrence of deformation parameters has been compared to the landslide inventory of the area. The results showed that the extreme rainfall caused severe acceleration of displacements, more significant in horizontal East-West direction rather than vertical Up-Down direction. Some slight deceleration has been also detected. No initiation (or reactivation) of the stable zones was witnessed, and the portions with high magnitude of pre-event velocities are the ones whose displacement rates have been remarkably modified due to the severe event.

Comparison of Different Quantitative Precipitation Estimation Methods Based on a Severe Rainfall Event in Tuscany, Italy, November 2023

Accurate quantitative precipitation estimation (QPE) is fundamental for a large number of hydrometeorological applications, especially when addressing extreme rainfall phenomena. This paper presents a comprehensive comparison of various rainfall estimation methods, specifically those relying on weather radar data, rain gauge data, and their fusion. The study evaluates the accuracy and reliability of each method in estimating rainfall for a severe event that occurred in Tuscany, Italy. The results obtained confirm that merging radar and rain gauge data outperforms both individual approaches by reducing errors and improving the overall reliability of precipitation estimates. This study highlights the importance of data fusion in enhancing the accuracy of QPE and also supports its application in operational contexts, providing further evidence for the greater reliability of merging methods.

The assessment of low flow at El Abid river basin for a good management of water resource (High Atlas/Morocco)

Abstract In a scenario where pressures on aquatic ecosystems and the water demands of communities are on the rise, coupled with the impacts of global changes, understanding low water flows becomes a critical concern. Low flow is characterized as a natural and seasonal phenomenon, typically stemming from varying degrees of prolonged and severe rainfall deficits. This phenomenon is prone to temporal and spatial fluctuations, ultimately causing a reduction in streamflow. The El Abid River Basin is located within the big Oum Er Rbia watershed, covering an area of 30.600 km2. El Abid river stands out as the principal tributary of the Oum Er Rbia, boasting an average annual flow of 32 m3/s−1, with a maximum average flow reaching 77 m3/s−1 and a minimum average flow of 10 m3/s−1. The hydrological regime of this river exhibits a pattern of intermittent and extreme floods, as well as periods of low flow sustained by water from the karst hydrosystems of the central High Atlas. The aim of this study is to characterize the low flow rates within the upstream part of El Abid river basin, intending to enhance the management of water resources in this basin. The methodology employed involves extracting the minimum flows, calculating the severity thresholds for low flow, determining the lowest average monthly flow of the year, computing low flow rates based on monthly flow averages, and calculating low flow values for specific return periods. Monthly discharge data from two hydrometric stations within our study area, namely Ait Ouchéne and Tizi Nisly, were utilized. The dataset spans the period from 1976 to 2018.

The Necessity of Updating IDF Curves for the Sharjah Emirate, UAE: A Comparative Analysis of 2020 IDF Values in Light of Recent Urban Flooding (April 2024)

In the arid Arabian Peninsula, particularly within the United Arab Emirates (UAE), the perception of rainfall has shifted from a natural blessing to a significant challenge for infrastructure and community resilience. The unprecedented storm on 17 April 2024, exposed critical vulnerabilities in the UAE’s urban infrastructure and flood management practices, revealing substantial gaps in handling accumulated precipitation. This study addresses the necessity of updating the Intensity–Duration–Frequency (IDF) curves for the Sharjah Emirate by utilizing recent precipitation data from 2021 to April 2024, alongside previously published 2020 data. By recalibrating the IDF curves based on data from three meteorological stations, this study reveals a substantial increase in rainfall intensities across all durations and return periods. Rainfall intensities increased by an average of 36.76% in Sharjah, 26.52% in Al Dhaid, and 17.55% in Mleiha. These increases indicate a trend towards more severe and frequent rainfall events, emphasizing the urgent need to revise hydrological models and infrastructure designs to enhance flood resilience. This study contributes valuable insights for policymakers, urban planners, and disaster management authorities in the UAE and similar regions worldwide.

Investigating the influence of urban morphology on pluvial flooding: Insights from urban catchments in England (UK)

As climate change intensifies, cities globally are experiencing more severe rainfall and frequent pluvial floods. Urban expansion is altering the permeability of the land, thus increasing the risk of flooding. This study investigates the impact of urban morphology on pluvial floodwater distribution in 15 urban catchments across England, UK, to provide an analysis of how urban morphology influences flood magnitude. Using a cellular automata-based model, pluvial flood simulations were conducted for catchments characterized by diverse urban morphologies. Then a series of machine learning models were adopted to reveal the relationships between the morphological characteristics of urban configurations (e.g., building footprints, impervious surfaces, street network, topography) and pluvial flooding. These models were used to identify and quantify the effects of key urban morphological indicators on pluvial flooding. The results indicate that, although the total area of impervious surfaces plays the most significant role in floodwater distribution, the edge density (ED) of building footprints and impervious surfaces also influences this process. Synthetic experiments with an exemplary urban fabric show that decreasing “ED of building footprint” and increasing “ED of impervious surface” can mitigate flood volume by up to 6.3 % at 100 % drainage efficiency and 7.8 % at 50 % efficiency. The results of this study are anticipated to aid urban planners and policymakers in developing strategies for implementing flood-resilient cities.

Temporal soil loss scenarios and erosional dynamics of a slopping landmass in the southwestern India before and after the 2018 severe rainfall and mega flood events

Temporal soil loss scenarios and erosional dynamics of a slopping landmass in the southwestern India before and after the 2018 severe rainfall and mega flood events

Threats of tropical cyclone on cropping systems and crop calendar of rice in India: Issues, policy practice gap and adaptation strategies

The Food and Agriculture Organization (FAO) has calculated that by 2050, we will need to grow 60 % more food to provide for a population of 9.3 billion people worldwide. India must increase its yearly food grain production from the current level of 252–333 million tonnes by 2050 in order to fulfil its expanding population demand. India is one of the nations most at risk from climate change due to its geophysical location and variability. This research explored the impact of cyclonic storm surges on crop calendars (‘Aman’ and ‘Boro’ rice) and also suggested adaption strategies during these conditions. This study showed that alteration of contemporary rice sowing and harvesting dates significantly impacts achieving sustained yields, surpassing all other crop management, soil, and other criteria. The origin and landfall of the cyclone of the Bay of Bengal (BoB) in pre- and post-monsoon season impede the goal of optimal rice production in Eastern and south-eastern India. We have estimated that ‘Rabi’ and ‘Kharif” rice production potential will increase by about 29 % with attainable changes to rice sowing and harvesting dates incorporating the severe cyclonic storm (SCS) landfall and rainfall in the study area. Our results also show that transformational benefits in rice yields are only possible in India if the convectional crop calendar changes with the modern scientific crop calendar. Managing the seasonal cropping calendar more effectively can benefit food security, economic success, and climate adaptability rice seed as a method for adaptation to ongoing climate change.

A proposed methodology to evaluate the influence of climate change on drinking water treatments and costs

Drinking water (DW) production treatments can be affected by climate change, in particular intense rainfall events, having an impact on the availability and quality of the water source. The current study proposes a methodology for the evaluation of the costs of the different treatment steps for surface water (SW) and groundwater (GW), through the analysis and quantification of the main cost items. It provides the details to count for strong variations in the key quality parameters of inlet water following severe rainfalls (namely turbidity, iron, manganese, and E. coli). This methodology is then applied to a large drinking water treatment plant (DWTP) in Italy, which treats both SW, around 70 %, and GW, around 30%. It discusses the overall DW production costs (from 7.60 c€/m3 to 10.43 c€/m3) during the period 2019–2021 and analyzes the contributions of the different treatment steps in water and sludge trains. Then it focuses on the effects on the treatments of significant variations in SW turbidity (up to 1863 NTU) due to intense rainfalls, and on the daily costs of DW with respect to the average (baseline) costs evaluated on the annual basis. It emerges that, when SW has low turbidity levels, the energy-based steps have the biggest contribution on the costs (final pumping 22 % for SW and 10 % for GW, withdrawal 15 % and 14 %, respectively), whereas at very high turbidity levels, sludge greatly increases, and its treatment and disposal costs become significant (up to 14 % and 50 %). Efforts are being made to adopt the best strategies for the management of DWTPs in these adverse conditions, with the aim to guarantee potable water and optimize water production costs. A mitigation measure consists of increasing GW withdrawal up to the authorized flow rate, thus reducing SW withdrawal. In this context, the study is completed by discussing the potential upgrading of the DWTP by only treating GW withdrawn from riverbank filtration. The DW production cost would be 7.76 c€/m3, which is lower than that seen for the same year (2021) with the current plant configuration (8.32 c€/m3).

Paving the complex path to building climate resilient cities through disaster health diplomacy and international public health policy

Disaster resilience defines society’s capabilities to resist/adapt/recover from hazardous events. Priorities for action were outlined at the Sendai Framework for Disaster Risk Reduction to reduce disaster risks by understanding the process, strengthening governance, investing in resilience, improving preparedness/effective response capacities/rehabilitation processes/reconstruction procedures. Disaster diplomacy is a fast growing interdisciplinary field. Natural disasters potentially generate opportunities for diplomatic interaction between rival parties/conflicting states. Climate crisis is growing. By large, Summer 2023 was globally the warmest on record. The 2015 Paris Agreement was a landmark; UNOHCHR proposes a universal decleration of disaster rights. Climate change has widespread impacts on human health. “The greatest health threat of the 21stcentury” affects socio environmental determinants of health, clean air/water/food/shelter. Ninety percent of all disasters are climate/weather related, resulting in >410,000deaths in the last decade, expected to cause 250,000 additional deaths/year from malnutrition/malaria,/diarrhoea/heat stress in 2030 2050. IFRC focuses on strengthening ownership/community leadership/outreach/funding/forecasting/anticipatory action. Climate related flashpoints are the early warnings of impending crises. Turkey Greece have a lot in common from a climate change/disaster resilience viewpoint. Successive earthquakes generated rescue responses/mutual aid/outpouring of sympathy between the two countries within the last decade. Extreme weather events, high temperatures, severe rainfalls continue to batter both countries. Global warming brought intense flooding/wildfires to Southeast Europe/Southwest Asia. Climate change is expected to become the strongest driver of human migration through complex mechanisms in the Mediterranean Basin. The sustainability of Greece’s migration policies may be challenged against the global climate crisis. Environmental change has potential impacts on human health. Health diplomacy in international relations focuses on protecting health/well being. In the past, health interventions as foreign policy were regarded not to be associated with diplomatic disaster efforts. This oral presentation challenges earlier opinions and proposes a “climate change health diplomacy model” for improving capacities in disaster resilience. Around the world, health care professionals speak a unique/universal language of their own. Countries with “otherwise conflicting interests,” stand in solidarity during natural disasters. Through further elaborating on the principles of sustainable collaboration on disaster risks/health diplomacy/climate change, a “first time disaster health diplomacy model” may be developed to serve the world. An outline is hereby presented, 1 to define paths of communication versus the current ad hoc disaster diplomacy efforts, 2 to incorporate risks into the disaster diplomacy plan, 3 to incorporate a well planned disaster health diplomacy agreement. As the Turkish saying goes, “HEALTH COMES FIRST”.

Oral Myiasis: Case Report of a rare entity!

Background: Floods and severe rainfall are major reasons for the increase in infections like Dengue, malaria, and other parasitic infections. There may be an increase in worm infestations in the immediate post-flood period due to moist conditions. Oral myiasis is one of those rare parasitic infestations that may occur during such events and can be life-threatening to the patient due to its destructive nature. The chances become high if the patient has any underlying condition that can act as a reservoir or favourable host for such infestations. Immediate management of the disease increases the chances of a good prognosis and spread of the disease. Oral Myiasis is still a rare condition caused by larvae of flies called maggots. The following case report is an attempt to highlight the timely recognition of the disease which came to a private clinic with a routine complaint of toothache and its early management led to the complete recovery of the lesion and the patient.

Groundwater exhibits spatially opposing trends during the Australian Millennium Drought

The adverse impacts of Australia’s Millennium Drought on both surface and groundwater hydrological systems are extensively documented. During the Millennium Drought, the Murray Basin experienced a severe rainfall deficit. Our study revisited groundwater table trends in 451 wells within the Murray Basin during the drought from 1997 to 2009. These trends varied, 70% showed significant downward shifts, 19% were insignificant, and 11% even displayed upward trends. The results from K-means clustering analysis indicate a markedly slow recuperation of groundwater levels post-drought. We used multiple regression models to link interannual groundwater dynamics with climate variables, revealing climate as the primary driver of declining groundwater levels. This connection is influenced by land cover and thickness of the vadose zone, resulting in hysteresis effects and spatial variations. In cases with a thick vadose zone and minimal evapotranspiration, the influence of the Millennium Drought on the groundwater system is reduced. The increasing trends may also be related to lateral recharge from mountainous areas, human activities in adjacent irrigation districts, and east-west geostress. Our findings reveal the complex interactions between climate, land characteristics, and groundwater behavior during and after the Millennium Drought, holding significant implications for understanding hydrological processes under extreme drought conditions and for the sustainable management of water resources.

The impact of extreme precipitation on water use efficiency along vertical vegetation belts in Hengduan Mountain during 2001 and 2020

In the context of climate change, extreme precipitation events are continuously increasing and impact the water‑carbon coupling of ecosystems. The vertical vegetation zonation, as a characteristic of mountain ecosystems, reflects the differences in vegetation response to climate change at different elevations. In this study, we used the water use efficiency (WUE) as an indicator to evaluate the water‑carbon relationship. By using MODIS data, we analyzed the spatiotemporal patterns of gross primary productivity (GPP), evapotranspiration (ET), and WUE from 2001 to 2020, as well as the responses of WUE to extreme wetness factor Number of precipitation days (R0.1), extreme dryness factor Consecutive dry days (CDD), and meteorological factors under the vertical vegetation zonation. Our results showed that annual GPP and ET displayed a significant increasing trend between 2001 and 2020, whereas WUE showed a weak decreasing trend. Spatially, GPP and WUE decreased with increasing elevation. Analyzing the WUE of mountainous ecosystems as a unified whole may not precisely capture the reactions of vegetation to severe rainfall occurrences. In fact, across different vegetation belts in mountainous areas, there exists a negative correlation between WUE and R0.1, and a positive correlation with CDD. In terms of meteorological factors, the temporal variation of GPP was primarily associated with vapor pressure deficit (VPD) and temperature (Ta), while those of ET was mainly related to soil water content (SWC). WUE was affected by a combination of meteorological factors and had a certain degree of variation between different altitude intervals. These findings contribute to a better understanding and prediction of the relationship between extreme rainfall climate and water‑carbon coupling in mountainous areas.

Trend analysis of extreme rainfall indices from CHIRPS precipitation estimates over the Lake Tana sub-basin, Abbay Basin of Ethiopia.

Ethiopia is among the African nations most susceptible to climate change because of its frequent droughts and heavy rainfall. Therefore, hydrological and water management problems require an investigation of regional variability and extreme rainfall patterns. This study analyzed the spatiotemporal trends of extreme rainfall in the Lake Tana sub-basin (LTSB) of Ethiopia's upper Blue Nile basin (UBNB) between 1981 and 2019. The trend and geographic patterns of ten extreme rainfall indices are evaluated using high-resolution data from Climate Hazards Group InfraRed Precipitation Stations (CHIRPS). The researcher used RClimDex, an R software tool, to analyze the ten severe rainfall indices. The variability of the extreme rain indices was also assessed by applying the standard anomaly index (SAI). The trend analysis shows that the majority of rainfall indices decreased in the majority of station locations. Among the rainfall locations, the decreasing trend was only significant in 40% consecutive wet days (CWD), 13.33% (R95p and R99p), and 6.66% highest rainfall amount in a 1-day period (RX1day). In contrast, significant positive patterns were revealed in the incidence of rainfall events of number of heavy precipitation days (R10mm), annual total wet day rainfall (PRCPTOT), and consecutive dry days (CDD), with significant positive trends of 26.66% (R10mm) and 40% (PRCPTOT). Furthermore, a spatial distribution result of extreme rainfall trends reveals considerable variations between stations location. Thus, these findings point to the necessity of creating adaptation and mitigation plans for climate change variability within the sub-basin.

3D visualization of hurricane storm surge impact on urban infrastructure

As climate change intensifies, resulting in more severe rainfall events, coastal cities globally are witnessing significant life and property losses. A growingly crucial component for flood prevention and relief are urban storm flood simulations, which aid in informed decision-making for emergency management. The vastness of data and the intricacies of 3D computations can make visualizing the urban flood effects on infrastructure daunting. This study offers a 3D visualization of the repercussions of hurricane storm surge flooding on Galveston, TX residences, illustrating the impact on each structure and road across varied storm conditions. We employ target detection to pinpoint house door locations, using door inundation as a metric to gauge potential flood damage. Within a GIS-based framework, we model the damage scope for residences exposed to varying storm intensities. Our research achieves three core goals: 1) Estimating the storm inundation levels on homes across different storm conditions; 2) Assessing first-floor elevations to categorize housing damages into three distinct groups; and 3) Through visualization, showcasing the efficacy of a proposed dike designed to shield Galveston Island from future storm surge and flood events.

The unsuPervised shAllow laNdslide rapiD mApping: PANDA method applied to severe rainfalls in northeastern appenine (Italy)

Shallow landslides, frequently triggered by extreme events such as heavy rainfall, snowmelt, or earthquakes, affect vast areas with remarkable density. In the immediate aftermath of such events, it becomes crucial to rapidly assess landslides distribution and pinpoint the most severely affected areas to prioritize damage assessments and guide field survey operations effectively. Once the emergency phase subsides, the attention can shift to enhancing the accuracy of landslide inventory. In this work, we introduce the two-phase methodology “PANDA”, the unsuPervised shAllow laNdslide rapiD mApping, for the low-cost mapping of the potential landslides, firstly in the emergency phase and then, with an improved version, in the post-emergency one. This approach utilizes variations in NDVI derived from Sentinel-2 satellite imagery and geomorphological filters. We applied PANDA to rainfall events in the northeastern Apennine range, Italy, occurred in May 2023, causing dramatic social and economic consequences for this mountain territory. Within just five days of obtaining Sentinel-2 post-event imagery, we produced a reliable, ready-to-use map covering a vast area (∼4000 km2). The map tested during emergency field mapping shows positive feedback. In the post-emergency phase, accuracy was enhanced using completely cloud-free imagery, a filter to identify false positives associated with land use changes, a higher resolution digital terrain model (DTM), and an iterative approach to optimize NDVI and slope thresholds. Potential landslide density related with rainfall, indicating that the most severely affected region attained a density of approximately 50 landslides/km2. Validation against an independent manual inventory based on high-resolution imagery demonstrated encouraging accuracy results from both inventories, with a noticeable increase in the F1 score for the post-emergency version.

Tree growth and survival are more sensitive to high rainfall than drought in an aseasonal forest in Malaysia

Global change research has largely focused on the effects of drought on forest dynamics while the importance of excessive rainfall that can cause waterlogged soils has largely been assessed in riparian zones or seasonally flooded sites. However, increased rainfall may also cause decreased growth and survival of tree species in lowland aseasonal tropical forests due to increased risk from potentially more extensive and frequent waterlogged soils. We used a Bayesian modelling approach on a tree dynamics dataset from 2004 to 2017 to test the concomitant effects of rainfall excess and deficit and dry period length on tree growth and survival across a network of experimentally planted trees in a primary aseasonal forest in Malaysia. Growth declined in 48% of the species and survival decreased in 92% of the species during periods of high rainfall while as little as 4% of species had decreased growth or survival with drought and long dry periods. Climate change is projected to cause more frequent and severe rainfall deficit and excess, and our results suggest increased rainfall may have stronger negative effects on aseasonal tropical forests than that of severe drought.

Aflatoxins in the nut chains: strategies to reduce their impact on consumer’s health and economic losses

Abstract The presence of Aspergillus section Flavi and aflatoxins (AFs) in nut chains are of great concern due to the toxic effects of AFs on human and animal health as well as the economic losses during commercialisation. Extreme events related to climate change like increased temperature, severe rainfalls and droughts are modulating factors of fungal growth and mycotoxin production. The Expert Working Group (EWG) on nuts that worked under the frame of the Horizon 2020 Mycokey Project prepared this review based on discussions about the situation of contamination with AFs in nuts and the available strategies to reduce the impact of these toxins in the nut chains. The EWG selected as examples peanuts, pistachios and Brazil nuts, and discussed in the review the importance of nut value chains in the production, commercialisation and regulations that establish maximum levels for AFs. Also data on the Rapid Alert System for Food and Feed (RASFF) was considered and showed several notifications for mycotoxins, mainly AFs for nuts and nut products, such as pistachio nuts and dried mix nuts. Under a scenario of climate change, we elaborated strategies to prevent AFs contamination with emphasis on biocontrol and decision support systems. Also, the relevance of strategies to prevent and reduce both fungal infection and AFs accumulation in peanuts, Brazil nuts and pistachio are included as guidelines.

Quantifying Soil Erosion in Drought-Impacted Central Odisha, India, through Geospatial Mapping with RUSLE

Soil degradation in Odisha poses a significant conservation concern for the local environment. The present research focused on a region in central Odisha State, India, affected by drought conditions. Several models have emerged to assess soil loss, with the Revised Universal Soil Loss Equation (RUSLE) standing out as the most suitable option. The erosion computation process entails utilizing the digital elevation model (DEM), Landsat-9 imagery, and soil data from several sources accessible in different forms and scales. The present analysis took into account various elements, namely, crop management factor (C), practice management factor (P), slope length factor (LS), steepness factor of the slope (S), and rainfall factor (R). Multiplying these factors yielded the average rate of soil erosion. Areas with a high slope length factor, such as those in Kandhamal, Kalahandi, and Nuapada, have a high erosion rate. The study reveals that 57% of the land in the study area experiences very low to moderate soil erosion at a rate of 2–10 tons per hectare per year, while 43% faces moderately to very severe erosion at a rate of 10–25 tons per hectare per year. Erosion hotspots, covering 32,205 square kilometers, are mainly identified in agricultural and forested hilly areas where slopes exceed 10°, such as those in Kandhamal, Kalahandi, and Nuapada, which have a high erosion rate. These districts are especially vulnerable to soil loss and resulting climate action (Sustainable Development Goals-13) because of frequent and severe rainfall, shifting agricultural practices, a thin surface soil covering, natural erosion, and barren hills. The research emphasizes the urgent need for implementing conservation and management measures to protect high-risk areas from further degradation. In conclusion, the study underscores the effectiveness of the RUSLE-GIS model in conducting quantitative and spatial assessments of soil erosion on a river watershed scale. The model is deemed crucial in formulating conservation strategies to address the identified erosion issues in the tropical highlands of the area.