Sub-basin Area Research Articles

GIS Application for Creating Potential Flood Map Using AHP: A Case Study in Chaq-Chaq Valley, Sulaymaniyah City, Kurdistan Region, Iraq

This study aims to analyze and classify the hazards of flooding within the Chaq-Chaq sub-basin, the Sharazoor-Piramagroon basin, Sulaymaniyah City, Iraqi Kurdistan Region. The selected area is exposed to flooding from time to time. The study adopted many thematic maps, namely the topographic wetness index (TWI), elevation, slope, precipitation, land use–land cover (LULC), normalized difference vegetation index (NDVI), distance from the river, distance from the road, and drainage density. Modern technologies like remote sensing, GIS, ENVI, and AHP programs are used to obtain a digital map showing the classification of the flooding hazard within the sub-basin area. The results showed that large parts, about 50% of the basin area, are exposed to high and very high classes of flood risk. In comparison, areas of medium risk constituted about 27% of the total area of the sub-basin. Parts with low and very low risk recorded a percentage estimated at 22% of the total area. Large parts of the city of Sulaymaniyah face a high and very high risk of flooding, significantly impacting the tourist areas and economic facilities situated in the valley basin.

Assessment of area at risk of flood and drought in the SeThamok Sub-basin

The problem of floods and drought is a serious problem and has affected many areas in many areas of the world including Lao PDR. SeThaMok sub-basin is a sub-basin that suffers from disasters as mentioned almost every year, especially in Phin district, which has caused enormous damage. Because of such a problem, it is necessary to assess the risk areas for floods and droughts in order to manage floods and droughts that are suitable for the area in order to move forward in planning to deal with floods and droughts in the future. Therefore, this study aims to study flood and drought risk areas as well as create flood maps in (2014, 2018, 2019) and drought maps in (2006, 2012, 2015) using ArcGIS 10.5. This study uses rainfall data from 4 stations using the Thiessen Polygon Method to calculate the average rainfall and using data from the survey, collecting actual data from the field together with the data collected by the Department of Natural Resources and Environment. The results of the study found that: in 2014, there was a flood area covering 11.93% of the total catchment area and the maximum flood level was about 26 meters compared to the lowest level of the catchment area. Among them, the flood event covered 20 villages; In 2018, there is a flood area covering 16.06% of the total catchment area and the maximum flood level is about 32 meters. Among them, the flood event covered 27 villages; In 2019, there is a flood area covering 20.91% and the maximum flood level is about 34 meters. Among them, the flood event covered 39 villages and the results of the evaluation of areas at risk of drought showed that: in 2007, there were areas at risk of drought covering 39.18% of the area of the SeThaMok sub-watershed which covered the number of villages around 32 villages; In 2012, there is a drought-prone area covering 43.29% of the SeThaMok sub-watershed area, which covers about 38 villages; In 2015, there is a drought-prone area covering 36.73% of the SeThaMok sub-basin area, which covers about 30 villages.

Spatial Predictive Modeling of Liver Fluke Opisthorchis viverrine (OV) Infection under the Mathematical Models in Hexagonal Symmetrical Shapes Using Machine Learning-Based Forest Classification Regression

Infection with liver flukes (Opisthorchis viverrini) is partly due to their ability to thrive in habitats in sub-basin areas, causing the intermediate host to remain in the watershed system throughout the year. Spatial modeling is used to predict water source infections, which involves designing appropriate area units with hexagonal grids. This allows for the creation of a set of independent variables, which are then covered using machine learning techniques such as forest-based classification regression methods. The independent variable set was obtained from the local public health agency and used to establish a relationship with a mathematical model. The ordinary least (OLS) model approach was used to screen the variables, and the most consistent set was selected to create a new set of variables using the principal of component analysis (PCA) method. The results showed that the forest classification and regression (FCR) model was able to accurately predict the infection rates, with the PCA factor yielding a reliability value of 0.915. This was followed by values of 0.794, 0.741, and 0.632, respectively. This article provides detailed information on the factors related to water body infection, including the length and density of water flow lines in hexagonal form, and traces the depth of each process.

Spatial and seasonal assessment of surface water quality for domestic use in a semi-arid area of the Upper Kebir Sub-basin, NE Algeria

ABSTRACT The present study was conducted out in the Upper Kebir Sub-basin [North East (NE) Algeria] aiming to evaluate the status and spatial–seasonal variability of water quality for domestic purposes using hydrogeochemical parameters and water quality indices. Surface water samples were collected from selected 27 sites, in the period 2020–2021 during both the wet and dry seasons and were analysed for 22 parameters. The findings were compared with standards and the water quality indices were calculated. The analysis revealed that the basin was mainly polluted and showed significant seasonal and spatial variations in water quality, considerably influenced by climatic conditions (surface runoff) and human activities (urban sewage and agricultural activities). The results reveal significant spatio-temporal fluctuations and highlight areas likely to be affected by anthropogenic activities.

Assessing the current and future trends of climate extremes at Zarima subbasin North Western Ethiopia

Climate extreme events in Ethiopia have increased, impacting the country’s agriculture dependent economy. Localized studies on rainfall extremes provides valuable insights to develop mitigation measures. This study focuses on the analysis of rainfall extremes for the observed (1984–2018) and the future mid time period (2031–2065) and end time period (2066–2100) projected under RCP4.5: moderate emissions reduction scenario aiming to stabilize greenhouse gas concentrations by the mid-21st century and RCP8.5: high emissions scenario with continued increase in greenhouse gas emissions throughout the twenty-first century. Trend analysis was done using R statistical software modified Man Kendell package. The result revealed that the observed total rainfall in wet days (PRCPTOT) showed insignificant declining trend across the subbasin. Under the RCP4.5 scenario, mid time period projections indicated increasing trends in PRCPTOT at Maytsebri, Adiremet and Debarik stations while decreasing trends expected at Ketema Niguse and Zarima stations. In the RCP4.5 end time period, Debarik and Zarima stations showed increasing trends while other stations exhibited decreasing trends. Under the RCP8.5 scenario, PRCPTOT showed insignificant decreasing trend except Ketema Niguse station which showed significant increasing trend during the mid time period. The observed annual maximum 1-day rainfall (RX1day) and annual RX5day rainfall had both positive and negative trends over subbasin. The RCP4.5 scenario projected declining trends in annual RX1day rainfall, while the RCP8.5 scenario projected increasing trends, except the end time projection of Debarik station. Consecutive dry days (CDD) increased and Consecutive wet days (CWD) decreased insignificantly in majority the subbasin. Projections indicated higher CDD and decreased CWD are expected in majority of the subbasin area. These finding implied that further investigation is required on the impact of climate extremes.

Comprehensive Facies Analysis and Depositional Environments of the Kikim Formation, Garba Mountain, South Palembang Subbasin, Indonesia

This study provides an exhaustive facies analysis of the Kikim Formation within the Garba Mountain area of the South Palembang Subbasin, emphasizing the stratigraphic significance and depositional environments during the Paleogene period. Utilizing field data collected from the Bumi Agung and Batu Belang measurement lines, this research categorizes various lithofacies using Miall’s (1978) classification scheme, identifying eight distinct lithofacies and four facies associations indicative of a predominantly fluvial depositional setting. The results depict a detailed sedimentological framework, showing that the Kikim Formation was characterized by a braided river system with significant gravel and sandstone deposits. This analysis not only sheds light on the geological history and processes shaping the South Sumatra Basin but also enhances the understanding of its potential hydrocarbon reservoirs. By detailing the lithological diversity and facies distribution, this paper contributes to the broader geological knowledge required for effective exploration and management of the region's natural resources.

Spatiotemporal Variation in Wind Erosion in Tarim River Basin from 2010 to 2018

The Tarim River Basin, China’s largest inland river basin, is renowned for its ecological fragility characterized by concurrent greening and desertification processes. Soil wind erosion emerges as a critical factor impacting the natural ecosystem of this region. This study employs a soil wind erosion model tailored to cultivated land, grassland, and desert terrains to analyze the multitemporal characteristics of and spatial variations in soil wind erosion across nine subbasins within the Tarim River Basin, utilizing observed data from 2010, 2015, and 2018. Additionally, this study investigates the influence of various factors, particularly wind speed, on the soil wind erosion dynamics. Following established standards of soil erosion classification, the intensity levels of soil erosion are assessed for each calculation grid within the study area alongside an analysis of the environmental factors influencing soil erosion. Findings indicate that approximately 38.79% of the total study area experiences soil wind erosion, with the Qarqan River Basin exhibiting the highest erosion modulus and the Aksu River Basin registering the lowest. Light and moderate erosion predominates in the Tarim River Basin, with an overall decreasing trend observed over the study period. Notably, the Qiemo River Basin, Dina River Basin, and Kaidu Kongque River Basin display relatively higher proportions of eroded area compared to their total subbasin area. Furthermore, this study underscores the substantial influence of the annual average wind speed on soil erosion within the study area, advocating for prioritizing soil and water conservation programs, particularly in the downstream regions of the Tarim River Basin, to mitigate future environmental degradation.

Machine-Learning-Based Forest Classification and Regression (FCR) for Spatial Prediction of Liver Fluke Opisthorchis viverrini (OV) Infection in Small Sub-Watersheds

Infection of liver flukes (Opisthorchis viverrini) is partly due to their suitability for habitats in sub-basin areas, which causes the intermediate host to remain in the watershed system in all seasons. The spatial monitoring of fluke at the small basin scale is important because this can enable analysis at the level of the factors involved that influence infections. A spatial mathematical model was weighted by the nine spatial factors X1 (index of land-use types), X2 (index of soil drainage properties), X3 (distance index from the road network, X4 (distance index from surface water resources), X5 (distance index from the flow accumulation lines), X6 (index of average surface temperature), X7 (average surface moisture index), X8 (average normalized difference vegetation index), and X9 (average soil-adjusted vegetation index) by dividing the analysis into two steps: (1) the sub-basin boundary level was analyzed with an ordinary least square (OLS) model used to select the spatial criteria of liver flukes aimed at analyzing the factors related to human liver fluke infection according to sub-watersheds, and (2) we used the infection risk positional analysis level through machine-learning-based forest classification and regression (FCR) to display the predictive results of infection risk locations along stream lines. The analysis results show four prototype models that import different independent variable factors. The results show that Model 1 and Model 2 gave the most AUC (0.964), and the variables that influenced infection risk the most were the distance to stream lines and the distance to water bodies; the NDMI and NDVI factors rarely affected the accuracy. This FCR machine-learning application approach can be applied to the analysis of infection risk areas at the sub-basin level, but independent variables must be screened with a preliminary mathematical model weighted to the spatial units in order to obtain the most accurate predictions.

Causes of coastal waters pollution with nutrients, chemicals and plastics worldwide

Worldwide, coastal waters contain pollutants such as nutrients, plastics, and chemicals. Rivers export those pollutants, but their sources are not well studied. Our study aims to quantify river exports of nutrients, chemicals, and plastics to coastal waters by source and sub-basin worldwide. We developed a new MARINA-Multi model for 10,226 sub-basins. The global modelled river export to seas is approximately 40,000 kton of nitrogen, 1,800 kton of phosphorous, 45 kton of microplastics, 490 kton of macroplastics, 400 ton of triclosan and 220 ton of diclofenac. Around three-quarters of these pollutants are transported to the Atlantic and Pacific oceans. Diffuse sources contribute by 95–100 % to nitrogen (agriculture) and macroplastics (mismanaged waste) in seas. Point sources (sewage) contribute by 40–95 % to phosphorus and microplastics in seas. Almost 45 % of global sub-basin areas are multi-pollutant hotspots hosting 89 % of the global population. Our findings could support strategies for reducing multiple pollutants in seas.

Effect of Land Use and Land Cover Change on Soil Erosion in Alaba Sub-Watersheds of Central Rift Valley Basin, Ethiopia

The magnitude of soil erosion rates has been accelerating in the Central Rift Valley Area of Ethiopia due to land use and land cover change (LULCC). This study aimed to analyze the trends and changes in land use and land cover dynamics and to analyze the impact of LULC change on soil erosion over the Alaba Sub-Watershed, Central Rift Valley Area of Ethiopia. This study would help to plan and use appropriate land use planning, soil, and water conservation practices, thereby reducing soil erosion in the study area. The soil loss rates were estimated using an empirical prediction model of the Revised Universal Soil Loss Equation (RUSLE) outlined in the ArcGIS environment. During the study period between 1987 and 2018, the rate of change in cultivated land and bare land was raised by 9.09% and 1.08%, respectively. On the contrary, vegetation cover and grasslands had dropped by –2.03%, and -1.42% respectively. From trends of LULC changes, cultivated land revealed an increasing trend increasing from 181.28 hectares to 351.23 hectares for the period 1987 to 2018, respectively. On the other hand, vegetation and grasslands showed a declining trend from -271.92,-22.66 hectares to -305.91, -124.63 hectares, respectively. The findings of the study generally elucidate that the LULCC has a detrimental impact on soil erosion. The estimated total annual actual soil loss in the study landscape was 25707.77 tons in 1987, 29310.71 tons in 2000, and 31769.32 tons in 2018. It was also found that the mean annual soil loss rate of the study catchment was 22.69t/ha/yr., 25.87t/ha/yr. and 28.04t/ha/yr. in 1987, 2000, and 2018 respectively. About 35% and 42% of the Sub-watershed experienced high to very severe soil erosion in 1987 and 2018, respectively. The results indicate that the estimated erosion rate for about 39 % of the sub-basin area exceeds the maximum tolerable soil erosion threshold and this shows that the erosion risk condition is deteriorating in the study landscape. The top three priority levels delineated for urgent SWC measures represent those areas within the large increase in erosion risk levels, with an area of 188 hectares and accounting for 17 % of the sub-watershed area. Therefore, further detailed investigations based on data from primary and secondary sources would be important in identifying driving socioeconomic forces and consequences of LULCCs and suggesting possible alternative options to establish sustainable resource management practices in the study area.

Identification of challenging gas-bearing reservoir based on machine learning (ML) and computed conversion-based AVO analysis: a study from Jaisalmer Sub-basin, India

Amplitude variation with offset (AVO) analysis is an important tool for identifying natural gas-bearing reservoirs. The changes in seismic amplitudes based on the variation of density and velocity of the rock matrix are captured through the AVO analysis. The current work was performed in the Ghotaru region of the Jaisalmer Sub-basin area, where limited and discrete hydrocarbon discoveries were observed from the Lower Goru Formation during the earlier various exploration campaigns. The discrete nature of the reservoir lithofacies developed challenging scenarios for the successful exploratory campaign. The campaign encountered more difficulties because of limited advanced datasets, which affected the study to capture the extension of hydrocarbon-bearing reservoir lithofacies and its characterization towards a successful exploration campaign. This study shows the way to overcome these challenges using an existing conventional dataset. The study shows the possibility of AVO analysis using a post-stack seismic dataset. A unique conversion method from post-stack to pre-stack seismic is introduced in this study based on the uses of the integrated velocity model. An integrated, robust velocity model was developed with consideration of anisotropy factors. Introducing a machine learning-based algorithm in the petrophysical study, including the conventional approach, provides a robust validation of this work. Intercept (A) and gradient (B) are the basic outcome of AVO analysis. The well-based study and AVO analysis based on intercept (A) and gradient (B) complement each other for finding hydrocarbon-bearing reservoir rock. Cross-plots and AVO analysis show the reservoir's lithofacies extension and fluids. The study reveals the potential of natural gas retained in the Lower Goru Formation, which is composed of patchy sandstone. Two AVO classes (Class I and Class III) of gas-bearing sandstone have been identified in this study. This study presents a unique method for identifying natural gas reservoirs with limited old conventional data.

Geospatial Analysis for Tectonic Assessment and Soil Erosion Prioritization: A Case Study of Wadi Al-Lith, Red Sea Coast, Saudi Arabia

An investigation into tectonics and erosion reveals that they play an important role in causing uplifting, valley incision, and soil erosion. The analysis of drainage basins at different scales is irreplaceable in the development of sustainable plans, particularly in arid regions. Morphotectonics and morphometric characterization analyses are very effective methods for defining the evolution of different landforms, current-day tectonic activity, and hydrological and morphological signatures of basins under investigation. The reorganization of critical drainage basins and sub-basin risk priority ranking are essential for effective and accurate sustainable plans for drainage basin management and water resources. In this study, the coupling of geospatial techniques and statistical strategies was used to examine the tectonic activity and priorities in terms of soil erosion for 15 sub-basins of Wadi Al-Lith along the Red Sea coast of Saudi Arabia. Two effective models, namely, the relative tectonic activity model and the weighted sum analysis model, were applied for examining each geomorphological and hydrological characteristic based on an analysis of the morphotectonics and morphometric parameters. Regarding the relative tectonic activity model, the 15 sub-basins were classified into three classes of tectonic activity: low, moderate, and high. Sub-basins 5, 6, 13, and 15 were considered to be in class 1 (high relative tectonic activity). On the other hand, the weighted sum analysis model assigned the sub-basins into three different ranks: low-, moderate-, and high-soil-erosion priorities. The current study’s results suggest that sub-basins 5, 6, 10, 13, and 15 were recorded within the high-soil-erosion zone and highly relative tectonic activity, covering approximately 53.52% of the total sub-basin areas. The relative tectonic activity and weighted sum analysis models proved their validity in the risk studies, which will be very useful for decision makers in various fields, including natural resources and agriculture.

Flood susceptibility modeling using geo-morphometric ranking approach in Jhelum River basin, Pakistan

This study is modeling flood susceptibility in Jhelum River Basin by employing Geo-Morphometric ranking approach. The study area is located in the Monsoon region and exposed to heavy rainfall events. Every year monsoon rainfall and melting of snow and glaciers together generate flash floods in the upper catchment and then riverine flood in the low-lying areas. Watershed modeling approach is used to delineate the Jhelum watershed and its sub-watershed. Advance Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Digital Elevation Model (GDEM) is utilized as input data in ArcMap software environment. Then Geo-Morphometric ranking model is applied to rank the susceptibility of each sub-watershed to flood. The analysis showed that geo-morphometric characteristics vary from basin to basin. There are 44 sub-basins which cover area less than 1000 ​km2. The area of sub-basins ranges from 47.68 ​km2 to 7667.77 ​km2. Based on our results, area of sub-basin directly impacts flood susceptibility. Geo-morphometric parameters such as gradient, relief and geology of basin such as type of bed rock govern the drainage pattern. The results of the study can assist line agencies and concerned government departments to design location specific flood risk reduction strategy.

Spatiotemporal patterns of multiple pesticide residues in central Argentina streams

Pollution of surface waters is a global threat, with particular concern about pesticides due to their severe negative effects on ecosystem functioning and human health. The aims of this study were to identify the spatiotemporal patterns of water and sediment quality, and the key variables related to the variation in pesticide pollution (122 compounds), in headwater streams (surrounding land uses: crop or mixed crop-livestock systems) and floodplain streams (surrounding land uses: urban development or natural wetland) of the Paraná River basin in the central area of Argentina. We found significant differences in water and sediment quality related to local land uses among headwater streams, but not among floodplain streams. These differences were more noticeable during spring than during autumn. Pesticides were widespread in all the streams, independently of the surrounding land use, reflecting the combination of local inputs and the role of floodplain hydrological connectivity in transporting pollutants from upstream sources. The most frequently detected compound was atrazine (75 %), whereas the highest concentration of an individual compound was observed for the glyphosate metabolite aminomethylphosphonic acid (AMPA, up to 4 μg L−1). The significant explanatory variables for pesticide pollution were turbidity, chromophoric dissolved organic matter (CDOM), sub-basin area, side slope of streams (positive relations), wetland cover, and precipitations (negative relations). Our results can be useful for the design of monitoring programs that capture the spatial and temporal variability of pesticide pollution.

Crop Diversification Assessment in Tank Ayacut Areas of Lower Palar Sub-Basin of Chengalpattu District, Tamil Nadu, India Using Geo-Spatial Techniques

For the assessment of crop diversification in the major tank Ayacut area of the Lower Palar sub-basin in Chengalpattu district of Tamil Nadu, research works were carried out using Sentinel 2 optical data by relating with ground truth data, to identify the crops in pixel-based classification and further classified the crops using Random Forest machine learning algorithms. The total area estimated under crop classification was 15767.97 and 28818.17 ha respectively for the summer seasons of 2018 and 2021. Since, the summer season experiences high crop diversification. The water spread area and water volume of tanks estimated were 612.31 and 1177.89 ha and 6,39,248 and 14,06,056 m3 respectively for 2018 and 2021. The accuracy assessment of ground truth points by confusion matrix reveals an overall classification accuracy of 96.8% (2018) and 94.9 % (2021) with kappa scores of 0.96 and 0.94 respectively. The crop diversification assessments were estimated using the Simpson Index of Diversity and values of 0.63 and 0.68 were accounted for in 2018 and 2021 respectively. The diversified pattern of crops is significantly correlated with tank water availability which increased the cropping area in 2021 as confirmed by the Crop Diversification factor.

Hydrogeological Hazards in Open Pit Coal Mines–Investigating Triggering Mechanisms by Validating the European Ground Motion Service Product with Ground Truth Data

This research focuses on the investigation of hydrogeological hazards in open pit coal mines. The study area is the Amyntaio sub-basin area, located in West Macedonia prefecture, Greece. A major part of the SE of this area is occupied by the Amyntaio open pit coal mine. In recent decades, the Amyntaio basin’s aquifer has been overexploited both by dewatering wells of the open pit coal mine and irrigation wells, triggering extensive land subsidence in an area that extends 3 km around the mine. Additionally, one of the biggest mining landslides worldwide occurred on the South-West slopes of the open pit on 10 June 2017. The current study investigates the land subsidence phenomenon and the landslide, highlighting the influence and the interaction of their causal factors which were strongly affected by the groundwater management. To estimate ground surface movement, Earth Observation data from the European Ground Motion Service, of the Copernicus European Union′s Earth observation program, were used for the period 1 January 2016–31 December 2020. The geologic, geotechnical and hydrogeologic data coming from the extensive ground truth survey have been incorporated with the Earth Observation data, highlighting the opposing mechanisms of the interacting geohazards.

Effects of the Time Period Length on the Determination of Long-Term Mean Annual Discharge

Currently, the 40-year-long reference period 1961–2000 is used in Slovakia for systematic assessment of the hydrological regime. The World Meteorological Organization recommends unifying the climatic normal 1991–2020 with a reference period for hydrological characteristics for the purpose of climate change research. We have analyzed changes in the long-term mean annual discharges at 113 water-gauging stations over different time periods. Considering the history of the reference periods used in Slovakia, we have focused on the analysis of the 10, 20, 30, 40, and 50-year-long moving averages of the long-term mean annual discharges in the period 1961–2020 in comparison with the 1961–2000 reference period and the whole selected and analyzed period. The deviations of the annual flow rates for the area of Slovakia and river sub-basins have been analyzed. The results indicate that the new reference period to be used in Slovakia should include the time period after the year 2000. To determine its precise length, a more detailed analysis is needed.

ANALISIS JENIS FLUIDA RESERVOIR BERDASARKAN NILAI SW DAN LOG SUMUR DS-19, CS-21, RS-23 FORMASI AIR BENAKAT CEKUNGAN SUMATERA SELATAN

Hydrocarbon exploration currently has a variety of methods in operation to determine and identify a reservoir according to the required parameters. Well log data plays an important role in the development of hydrocarbon exploration. Hydrocarbon saturation can be known by first calculating the water saturation, so the value of Sw is the key to work to determine the type of reservoir and its fluid content at an interval or reservoir zone accompanied by crossover and separation readings on the density & neutron log curve. The research was conducted in the Jambi Sub-basin area, ANONIM field, South Sumatra, DS-19, CS-21, RS-23 wells with shaly sand lithology which produces three productive zones. Based on the results, wells DS-19, CS-21, RS-23 has a gaseous hydrocarbon fluid with Sw value in the DS-19 well of 10.5%, CS-21 well of 27.1%, and RS-23 well of 22.4%.

Evaluation of Non-Point Source Pollution Load Characteristics and Identifying Management Sub-Basin Area and Best Management Practices Using HSPF Model in Yongdam Dam Watershed

Objectives : To identify and estimate the non-point source (NPS) pollution loads in the Yongdam watershed, and to take an appropriate NPS management plan suitable for the environmental conditions of the sub-basin of Yongdam watershed.Methods : The NPS pollutant loads of the Yongdam watershed was investigated to establish the hydrological simulation program-fortran (HSPF) model for the study area so that the characteristics of non-point runoff were simulated. Furthermore, the detailed catchment area subject to non-point pollution management was selected and the effect of reducing non-point pollution was examined based on the various simulation results.Results and Discussion : The three sub-basins, including specific component of catchments, of Yongdam watershed was selected according to the load intensity and distribution of NPS pollution. The result of analyzing the load flowing into the downstream by rainfall intensity revealed that the pollutant load accounted for 11.8~19.9% in the dry season, and for Jinan-cheon sub-basin the load was high in the range of 10~30 mm while Janggye-cheon sub-basin and downstream of Janggye-cheon junction sub-basin showed a high load in the range 30~60 mm. In addition, the load duration curve (LDC) showed the excess frequency of BOD load was high when the flow rate increased at the end of stream for each sub-basin, whereas the load excess frequency was high in T-P in the entire flow range. LDC analysis led to us that the water quality of stream was affected by point and non-point pollutants in a complex way. When the ground cover in a farm were installed by selecting 10 detailed catchments with high need for NPS pollution management, the reduction of T-P load was estimated to be reduced by 325.256~995.912 g/d in Jinan-cheon sub-basin, 1279.813~3327.513 g/d in Janggye-cheon sub-basin, and 1316.831~3555.443 g/d in downstream of Janggye-cheon junction sub-basin.Conclusion : Through various simulation experiments using the HSPF model, it was feasible to select an catchment subject to NPS pollution control in detail and evaluate the effect of reducing NPS pollution.

Dynamic System Modeling and Sustainability Strategies for Circular Economy-Based Dairy Cow Waste Management

Dairy farming activities produce waste that can have a negative impact on the environment. The processing of livestock waste will reduce pollution and support environmental conservation programs that are currently being intensified by the West Java Provincial Government, Indonesia. An economic approach that can minimize waste and maximize resources is the circular economy (CE) approach. CE can occur at the macro-, meso-, or microlevels. The application of micro-scale CE can be carried out in a business activity. One of the micro business groups that have implemented the CE concept in Bandung Regency, West Java Province, Indonesia, is the Taruna Mukti Farmer Group, which is located in the Citarum River sub-basin area. From 2008 to 2022, this group processed 49,580 tons of cow dung into organic fertilizer. However, there has been a decline in livestock waste processing, where production reduced from 3700 tons in 2018 to 1280 tons in 2021, then to only 500 tons in 2022. Therefore, this study aims to design a sustainable strategy for livestock waste management based on CE in the Taruna Mukti Farmer Group. The method used is in-depth interviews with the Drivers, Pressure, State, Impact, Response (DPSIR) approach. In addition, this study will also describe the CE model in the management of dairy cattle waste. Key Informants come from the Farmer Group and related stakeholders. Based on the results of the study, it is known that the dairy cattle waste management model in the Taruna Mukti Farmer Group is a form of implementing the CE concept with a circular flow of material and involving various stakeholders and an extensive marketing network. With the current conditions, the simulation results of processing livestock waste into organic fertilizer show a decline/unsustainability. To support the sustainability of livestock waste management, a response is needed in the form of strengthening the internal management of the Farmer Group’s organization, regular assistance and supervision from the local government and non-government organizations, and guidance regarding the marketing of organic fertilizers and ease of access to markets.