Groundwater recharge mapping is essential for sustainable water planning in semi-arid basins where monitoring is limited and groundwater is heavily relied upon. This study mapped potential groundwater recharge zones in the Al-Khazer watershed, northern Iraq, by integrating twelve conditioning factors within a machine-learning framework. A Forest-based Classification and Regression (FBCR) model, implemented in ArcGIS Pro 3.4.2, was trained on groundwater data from 88 wells; model performance was evaluated using error statistics and ROC analysis, and the robustness of the resulting map was then assessed with the Assess Sensitivity to Attribute Uncertainty tool under three input-perturbation scenarios (± 5%, ± 10%, and ± 20%), each with 100 simulations. The model showed consistent performance between training and validation (R² ≈ 0.88, RMSE ≈ 3.4, MAE ≈ 2.75, ~ 90.5% matched features), and ROC analysis confirmed strong discrimination (AUC = 0.912 for training; 0.907 for testing). The predicted suitability pattern was physically coherent, with higher suitability concentrated along the main valley corridors and tributary fans and lower suitability across the steep northern uplands where runoff energy is high. Under increasing perturbation, stability declined systematically but remained dominated by a stable core, 88.80% stable features at ± 5%, 80.27% at ± 10%, and 70.21% at ± 20%, with instability expanding mainly along class boundaries and transition zones. FBCR coupled with simulation-based uncertainty assessment thus provides a transparent basis for identifying high-confidence recharge zones; in the Al-Khazer watershed, the stable high-suitability valley corridors are recommended for groundwater protection and managed-aquifer-recharge screening, while unstable transition zones warrant field verification and enhanced monitoring.

The discharge of pollutant loads from sewage treatment plants (STPs) significantly impacts the quality of tropical rivers. The present study evaluates the impact of projected increases in population equivalent (PE) from STPs on the selected water quality parameters (WQP) of the Kuang River basin (KRB) under the influence of climate stress and advanced treatment. Using the QUAL2K model, discharge was simulated, and scenarios were based on population growth rate (PGR) for the next 10 years, with Low (2.1% PGR), Medium (2.2% PGR) and High (2.5% PGR). The findings indicate that elevated PE affects TSS, NH₃-N, and BOD₅ concentrations with a p-value < 0.05 between the seasons. Under high PGR scenarios in the dry season, concentrations for BOD₅ were 7.82 mg/L, 3.02 mg/L for NH₃-N, and 48 mg/L for TSS. This study suggests reducing pollution loads from STPs by 98.88% (35.59 and 7881.5 kg/day) for BOD₅, 99.44% for NH₃-N (7.16 and 1585.27 kg/day), and 83.93% for TSS (35.25 and 1303.08 kg/day) to meet class II. Additionally, the model's performance was validated with flow calibration results showing R2 = 0.79-0.94 and NSE = 0.80-0.94. Therefore, this study projected the load allocation for WQP for all identified STPs for sustainable KRB management under future urban growth.

Small tropical urban basins are often managed with limited hydrological records despite rapid land-use change and increasing pollution risk. This study provides an exploratory assessment of recent land-use/land-cover (LULC) change and associated simulated hydrological responses in the ungauged Kuang River Basin, Malaysia. LULC maps for 2019 and 2023 were compared using post-classification comparison, and class-level landscape metrics were used to examine sub-basin patterns. ArcSWAT was configured as a scenario-screening tool using global terrain, soil, and climatological inputs. Because continuous discharge records were unavailable, model evaluation was limited to internal water-balance checks and dry- and wet-season spot discharge observations rather than formal calibration and validation. Agriculture remained the dominant class but declined by 21.83% between 2019 and 2023, whereas rangelands and barren land increased by 36.24% and 28.03%, respectively. Across 27 sub-basins, barren land expansion was associated with higher simulated changes in surface runoff (86 mm yr⁻¹), agricultural expansion with reductions in simulated baseflow (up to 4.7 mm yr⁻¹), and agricultural and grassland changes with changes in simulated sediment yield (- 1.89 to + 0.19 t ha⁻¹ yr⁻¹). These findings are hypothesis-generating rather than predictive because the basin is ungauged and climate forcing relied on monthly climatology through the SWAT weather generator.

Emerging contaminants of concern (CECs) are increasingly detected in tropical riverine systems, yet their prioritization remains challenging due to data gaps, complex mixtures, and limited integration of ecological and human health perspectives. This study proposes an integrated framework to identify priority CECs by combining occurrence data, ecological risk quotients (RQ), human health hazard quotients (HQ), and a novel prioritization index (PI). Thirty-four (34) multiclass CECs, including pharmaceuticals, hormones, and plasticizers, were quantified in four rivers in Johor, Malaysia using optimized solid-phase extraction coupled with liquid chromatography-tandem mass spectrometry (LC-MS/MS). Caffeine (1511-6085 ng/L), paracetamol (32-7408 ng/L), and bisphenol A (344-837 ng/L) dominated the contaminant profiles. Most pharmaceuticals posed negligible ecological risk, while bisphenol A showed low ecological risk under worst-case exposure (0.01 < RQ < 0.1). In contrast, human health assessment indicated substantial risks from bisphenol A and bisphenol S, particularly for children (HQ > 1). Integration of ecological thresholds (PNEC) and reference doses (RfD) identified bisphenol analogues as highest-priority contaminants, followed by estrone, lidocaine, dexamethasone, and diphenhydramine. The framework demonstrates that concentration-based assessments may underestimate risk and supports toxicity-weighted prioritization for monitoring and regulation in tropical aquatic systems.

Water scarcity and pollution are escalating challenges in Asia, impacting ecological systems and human livelihoods. This paper reviews the integration of Total Maximum Daily Load (TMDL) and Environmental Flow Assessment (EFA) in water management to address the dual issues of water quality and quantity. TMDL focuses on regulating the number of pollutants entering water bodies to meet quality standards, while EFA ensures that enough water is available to support aquatic ecosystems. Their independent application, however, often leads to gaps—TMDL can overlook ecological needs, while EFA may neglect pollution control. The integration of these two frameworks offers a more holistic solution, especially in water-stressed regions like Southeast Asia, where moderate water availability is exacerbated by urbanization, industrialization, and agricultural runoff. Case studies from Malaysia, Indonesia, and China reveal the limitations of applying TMDL and EFA separately and underscore the necessity of addressing both ecological flow requirements and pollution limits. This paper identifies key pollutants such as biochemical oxygen demand (BOD), chemical oxygen demand (COD), heavy metals, and total suspended solids (TSS), particularly in urban and semi-urban areas, and highlights the importance of tailoring strategies to the specific needs of different regions. By combining TMDL and EFA, policymakers can better manage pollutant loads, secure ecological health, and address Asia’s pressing water management issues. This review emphasizes the need for adaptable, integrated water management strategies that account for seasonal fluctuations, competing water demands, and regional water availability and pollution differences.

Water resources must be preserved because they are vital for agricultural, industrial, and domestic use, especially in tropical forest regions. Given the importance of the Ulu Muda Forest Reserve to the Kedah state in sustaining paddy cultivation for the country, this study aimed to provide reliable forest classification method and produce Normalized Difference Vegetation Index-Maximum Likelihood Classification of forest density map for Ulu Muda Forest Reserve. Here, the study reports measurements of the satellite remote sensing index for the forest based the image date. The forest recorded NDVI index of 0.72 to 0.98 for high density, NDVI index of 0.61 to 0.71 for moderate and NDVI index of 0.26 to 0.60 for low density area. The index showed higher value, which is comparable with reports of other tropical forest elsewhere. The results were influenced using satellite remote sensing pre-processing, processing, and classification. As a result, based on the satellite image indices approach, upper threshold of the higher density, the forest can exhibit higher capability for sustaining its ecological and hydrological functions. Given that most of the tropical forest biome has sustained this threshold, forest management should be sustained at this state, and more measures should be taken for example increase of protection forest classification in Rancangan Pengurusan Hutan (RPH) that is one of yearly planning report in states of Peninsular Malaysia. In the meantime, Geographical Information System (GIS) capacity should be mandate looking forwards for more utilisation in mapping for planning and projection of forest resource management activities.

Pollutant load may be defined as the mass of a substance that passes a particular point of a river in a specified amount of time. Meanwhile, estimation of pollutant loading and identification of their sources is crucial to environmental management and planning. For the first time (in this study), Flow rate measurement was used to estimate daily pollutant loading from Intermittent water quality concentration data, using a 2-dymensional Water Quality Analyser (WQA). Subsequently, Total Maximum Daily Load (TMDL) was determined using the Load duration approach, while Load Reduction Targets were projected for the future, the using regression option of trend analysis available in the WQA. Out of the ten parameters used for the study, BOD, NH3, and TSS have been identified as the most critical pollutants in the area, which require average load reduction of 3898.88 kg-day, 1053.28 kg-day, and 444,716.50 kg-day respectively, to achieve water quality class II, until 2030. Moreover, the study reveals that the load reduction target for BOD and TSS would decrease in the future, while that of NH3 increases (p < 0.001). This is even as significant variability also exists for the projected load reduction target over the months throughout the projected period (p < 0.01). It was concluded that WQA provides a cost and time effective, and a reliable means for estimation of Pollutant load and projection of Load Reduction Target. The study recommends source identification for the critical pollutants into the river and allocation of TMDLs using the dynamic flow approach.

Numerous sudden water pollution (SWP) incidents have occurred frequently in recent years, constituting a potential risk to human, socio-economic, and ecological health. This paper systematically reviews the current literature, with the view to establishing a management framework for SWP incidents. Only 39 of the 327 downloaded articles were selected, and the ROSES protocol was utilized in this review. The results indicated industries, mining sites, and sewage treatment plants as key SWP contributors through accidental leakages, traffic accidents, illegal discharge, natural disasters, and terrorist attacks. These processes also presented five consequences, including the contamination of drinking water sources, disruption of drinking water supply, ecological damage, loss of human life, and agricultural water pollution. Meanwhile, five mitigation strategies included reservoir operation, real-time monitoring, early warning, and chemical and biological treatments. Although an advancement in mitigation strategies against SWP was observed in this review, previous studies reported only a few prevention strategies. Considering that this review provided an SWP-based management framework and a hydrodynamic model selection guideline, which provide a foundation for implementing proactive measures against the SWP. These guidelines and the SWP-based management framework require practical field trials for future studies. PRACTITIONER POINTS: Sudden water pollution increases with industrial growth but decrease with awareness. Human and ecosystem health and social economy are the endpoint receptacles. Mitigation strategies include reservoir dispatch, early warning, and treatments. DPSIR model forms the basis for proving proactive measures against sudden pollution. This review provides a guideline for the selection hydrodynamic models application.

Sedimentation is a natural phenomenon of rivers that is enhanced by modification of the river basin. The presence of dams delays the exchange of sediments, nutrients, and organisms between the terrestrial and aquatic environments. This article assesses the impact of the Selangor dam on the sediment grain size distribution and its association with river velocity and discharge. The fieldwork for sampling is conducted in the normal and rainy seasons. The samples were analyzed through a sieve analysis procedure to determine the particle size of the sediments. After the sieve analysis technique, GRADISTAT analysis was performed on the output. The GRADISTAT analysis classifies the sediments between sandy gravel and sand, and the median grain size (D50) ranges from 4.00 to 0.18 mm. The spatial distribution of the D50 shows that the bed-load sediments of the upper Selangor River are becoming fine-grained downstream. The skewness of the sediments differs from 0.86 to 8.44, which indicates that the sediments are poorly to moderately well sorted. The Spearman's correlation of the D50 and river velocity and discharge determine no association of the D50 with river velocity and discharge. The stations near Selangor Dam have high slopes and receive "sediment hungry" water that washes small-sized sediments; therefore, the upper stations have a more significant amount of gravel and large sand. Doi: 10.28991/CEJ-SP2023-09-02 Full Text: PDF

Abstract An accurate estimation of present and future concentration of pollutant entering the water body provides data support and scientific basis for government decision-making and water resource management. This study conduct trend analysis of pollutant concentration using Water Quality Analyser (WQA), with a view to providing a scientific basis for decision making towards the implementation of the Malaysian Vision Valley (MVV) Development Plan, and other water resource development plans across the world, using river Linggi, Malaysia, as case study. The result indicated that the Water Quality class (WQ-class) of the river for respective pollutants would remain the same beyond the year 2030. Therefore, the proposed project is sustainable under present water management action. Hence, WQA is useful for water quality predictions for water resource planning and management.

The spatial distributed travel time model (SDTTM) with 15-min interval of rainfall event based was rarely used in the humid regions due to the high requirement for data accessibility and complexity level to fulfil the desired objective of hydrological modelling study. The spatial lumped model (SLM) was involved in order to justify the ultimate objective of this study in evaluating the performance of SDTTM and SLM by using selected rainfall events. For this purpose, the effective rainfall was estimated by using National Resources Conservation Services Curve Number (NRCS-CN) method. SDTTM was developed based on a distributed Geographic Information System-based time-area approach by incorporating kinematic wave theory with Manning’s equation to simulate the rainfall-runoff. SLM was developed based on a lumped based approach using Hydrologic Modelling System (HEC-HMS). Nash Sutcliffe Efficiency (NSE), percentage of bias (PBIAS), percentage of error (POE) and correlation coefficient ( r ) were used to evaluate model performance in sensitivity analysis, SDTTM and SLM. Results show that sensitivity analysis, and both observed and simulated hydrographs were highly correlated in mean value during calibration and validation period. Both models have a high applicability in different regions depending on the desired objectives, accessibility of data, time consumption and cost to utilize these models in respective catchments.

Groundwater pollution of the watershed is mainly influenced by the multifaceted interactions of geogenic and anthropogenic processes. In this study, classic chemical and multivariate statistical methods were used to assess the groundwater quality and identify the potential pollution sources affecting the groundwater quality of Galma sub-watershed in a tropical savannah. For this purpose, the dataset of 18 groundwater quality variables covering 57 different sampling boreholes (BH) was used. The order of abundance of the main cations and anions in the samples are Ca2+ > Na+ > Mg2+ > K+ and HCO3− > Cl− > SO4−2 > NO3− respectively. Piper diagram classified the groundwater types of the watershed into mixed Ca–Mg–Cl type of water, which means no cations and anions exceeds 50%. The second dominant water type was Ca–Cl. The Mg–HCO3 water type was found in BH 9, and Na–Cl water type in BH 29 respectively. Hierarchical cluster analysis grouped the sampling boreholes into five statistically significant clusters based on similarities of groundwater quality characteristics. Principal component extracted two principal components that explained around 65% of the total variance, which natural and anthropogenic processes especially agricultural activities as the dominant factors affecting the groundwater quality. The findings of this study are useful to the policy and decision-makers for formulating efficient groundwater utilization and management plans for the groundwater resources.

The river sand mining activity has taken place in a sand-bed river system in Selangor, Malaysia for decades even before the legalisation was initiated in 2008. This study focuses on the determination of optimum sand extraction for low-flow and high-flow seasons. The sand replenishment rate was used as the benchmark in determining the threshold level of the extractable rate in the Langat River, Selangor system. The total sediment load was computed using Yang (1973) equation due to the high percentage of agreement between the predicted sediment load and measured sediment load. Almost 41.6% of the predicted data fall within the allowable discrepancy ratio test between the predicted value and measured value. The comparison of sand replenishment rate in high and low flow seasons proved that the river system has quicker capabilities in sand replenishment rate at the extraction point during the high-flow season compared to the latter by 83%. The quantifiable volume of the extractable sand rate is proposed specifically during low-flow months (May to September) whereby the slower replenishment rate is critical and riskier. The optimal sand mining volume during the low-flow months is calculated by reducing 10% from the total replenishment volume and the recommended optimum extraction load has been delivered by the number of 25 tons lorries for easier observation by the contractor and authority’s body. The monthly optimum extraction in Langat River during low-flow months is calculated at a minimum of 437 trucks to a maximum of 20,114 trucks per month.

Southeast Asia (SEA) is a socio-economically and environmentally dynamic region of the world, with abundant renewable freshwater resources. At the same time, the population of the region is increasing and leading towards unsustainable water use and strict water management. The overall environmental flow status of Southeast Asian Rivers is assessed in this study, which is based on a critical review of the available literature of some important river basins of the study area. The results show that all riparian countries of the Mekong River are trying to utilize the hydropower potential of the river where more than 12,000 dams are constructed, which leads to significant alteration of hydrological regime in all tributaries of MRB. The two influential countries China and India are sharing the Brahmaputra River, where both countries are planning to construct dams. The 400 planned dams on this river will make the area the most concentrated region of the world in terms of big dam construction, while the low lying areas in India and Bangladesh are posing the threat of nutrient pollution due to excessive agricultural activities. The Citarum River in Indonesia is suffering from overburden of pollution, which makes the river heavily polluted while the Muda river in Malaysia is facing a lack of Integrated Water Resources Management (IWRM) and lack of stakeholders' engagement. Moreover, many of river basins in rest of SEA countries i.e. Lao PDR, Cambodia, Viet Nam, Myanmar, Philippines, Brunei Darussalam, and East Timor are lacking attention to research and policy to this field, therefore, the status of Environmental Flow is ranked unsatisfactory in most river basins of SEA. (c) 2021 Elsevier Ltd. All rights reserved.

The authors have requested that this preprint be removed from Research Square.

Freshwater turtles are among the world’s most endangered vertebrates as five out of six species under genus Batagur are already listed as Critically Endangered in IUCN Red List. Since a community’s support for a conservation project depend on their knowledge and attitude towards ecology and local species, this study evaluated the impact of previous awareness campaigns on the community’s knowledge and attitude towards the conservation of freshwater turtle Batagur affinis. The evaluation was based on inputs received from a group of 333 respondents (20.4% of local population) who reside within 10 km of the Kemaman River in Kg Pasir Gajah, Malaysia. Demographical subgroups were given equal representation. The sampling procedure and survey analysis were based on the Stratified Random sampling and Convenience sampling principles. A set of questionnaire comprising 14 statements and 22 questions was used as the instrument of data collection. The general knowledge and attitude of the community towards species conservation was found to be high (58.6% and 61.0% respectively). There was neither a significant difference in knowledge and attitude between the sexes, nor a significant difference among age groups. However, a strong positive relationship was found between knowledge about species conservation and pro-conservation attitude among the respondents. The results may help to identify groups that need more awareness in the follow up conservation campaigns. Moreover, evaluation of other species awareness campaigns can also be initiated using the present study protocol.

Freshwater aquaculture is a prominent activity in Rawang sub-basin of the Selangor River. Despite the importance good water quality in daily life, there is limited study on the impact of aquaculture activities on water quality. This paper discusses water quality parameter status (pH, dissolved oxygen (DO), ammoniacal nitrogen, turbidity, total suspended solids (TSS), chemical oxygen demand (COD) and biochemical oxygen demand (BOD)) based on Water Quality Index (WQI) in the aquaculture-impacted Rawang sub-basin of Selangor River and develops the Inverse Distance Weighted (IDW) maps showing water quality status by using GIS (ArcGIS 10.2.1 software) in order to identify the potential aquaculture impacted sites. Seven river sampling sites were selected including Guntong (SR1), Guntong’s tributaries (SR2/control), Kuang (SR3 and SR7), Gong (SR4), Buaya (SR5), and Serendah (SR6) using random sampling techniques based on accessibility and proximity to aquaculture farms. Seven water quality parameters were recorded and analysed on a bi-monthly basis. Results revealed that Guntong, Kuang, Buaya and Serendah rivers had moderate water quality, whereas Gong River was significantly polluted. The control river recorded clean water quality status. One-way analysis of variance (ANOVA) showed that there were significant differences in all measured water quality parameters among sampling sites (P<0.05).

Tropical rivers and wetlands are recognized as one of the greatest and most abundant ecosystems in terms of ecological and social benefits. However, climate change, damming, overfishing, water pollution, and the introduction of exotic species threaten these ecosystems, which puts about 65% of river flow and aquatic ecosystems under a moderate to high level of threat. This paper aims to assess the environmental flow of the Selangor River based on the hydrological index method using the Global Environmental Flow Calculator (GEFC) and Indicators of Hydrological Alterations (IHA) software. The daily flow data collected by the Department of Irrigation and Drainage (DID), Malaysia, over a 60-year period (1960–2020) was used in this study to assess the Selangor River flow alterations. As per the results, the river flow has had two distinct periods over the last 60 years. In the first period, the river flows without any alteration and has a natural flow with high flood pulses and low flow pulses. While in the second, or post-impact, period, the flow of the river has a steady condition throughout the year with very little fluctuations between the dry and wet seasons of the year. From the overall comparison of the pre- and post-impact periods, it can be concluded that the minimum flow in the dry seasons of the year has increased, while the maximum flow has decreased in the monsoon seasons during the post-impact period. As a result, the Flow Duration Curve (FDC) and Environmental Management Class (EMC) analysis of the river flow recommends that the Selangor River be managed under EMC “C” to provide sufficient water for both human use and ecosystem conservation, which would also help to avoid a water level drop in the reservoirs. However, further holistic studies are suggested for a detailed analysis of the effects of the dams on aquatic biodiversity and ecosystem services in the Selangor River Basin.