Historical and projected response of Southeast Asian lakes surface water temperature to warming climate.

The temperature of surface and epilimnetic waters, closely related to regional air temperatures, responds quickly and directly to climatic changes. As a result, lake surface temperature (LSWT) can be considered an effective indicator of climate change. In this study, we reconstructed and investigated historical and future LSWT across different scenarios for over 80 major lakes in mainland Southeast Asia (SEA), an ecologically diverse region vulnerable to climate impacts. Five different predicting models, incorporating statistical, machine and deep learning approaches, were trained and validated using ERA5 and CHIRPS climatic feature datasets as predictors and 8-day MODIS-derived LSWT from 2000 to 2020 as reference dataset. Best performing model was then applied to predict both historical (1986-2020) and future (2020-2100) LSWT for SEA lakes, utilizing downscaled climatic CORDEX-SEA feature data and multiple Representative Concentration Pathway (RCP). The analysis uncovered historical and future thermal dynamics and long-term trends for both daytime and nighttime LSWT. Among 5 models, XGboost results the most performant (NSE 0.85, RMSE 1.14 °C, MAE 0.69 °C, MBE -0.08 °C) and it has been used for historical reconstruction and future LSWT prediction. The historical analysis revealed a warming trend in SEA lakes, with daytime LSWT increasing at a rate of +0.18 °C/decade and nighttime LSWT at +0.13 °C/decade over the past three decades. These trends appeared of smaller magnitude compared to global estimates of LSWT change rates and less pronounced than concurrent air temperature and LSWT increases in neighbouring regions. Projections under various RCP scenarios indicated continued LSWT warming. Daytime LSWT is projected to increase at varying rates per decade: +0.03 °C under RCP2.6, +0.14 °C under RCP4.5, and +0.29 °C under RCP8.5. Similarly, nighttime LSWT projections under these scenarios are: +0.03 °C, +0.10 °C, and +0.16 °C per decade, respectively. The most optimistic scenario predicted marginal increases of +0.38 °C on average, while the most pessimistic scenario indicated an average LSWT increase of +2.29 °C by end of the century. This study highlights the relevance of LSWT as a climate change indicator in major SEA's freshwater ecosystems. The integration of satellite-derived LSWT, historical and projected climate data into data-driven modelling has enabled new and a more nuanced understanding of LSWT dynamics in relation to climate throughout the entire SEA region.

Integrated assessment of climate change and reservoir operation on flow-regime and fisheries of the Sekong river basin in Lao PDR and Cambodia.

This study assesses the cumulative impact of climate change and reservoir operation on flow regime and fisheries in the Sekong River Basin. Ensemble of five selected Regional Climate Models (RCMs) were used to project the future climate under RCP4.5 and RCP8.5 scenarios. The projected future climate was used to simulate the future hydrology using the SWAT model while HEC-ResSim was utilized for reservoir simulation. Finally fish-flow relationship was developed to estimate the fish catch and productivity in future. Upon investigation we found that, Sekong River Basin is likely grow warmer and drier in future under climate change. The basin is expected to face 1.3-3.6 °C rise in mean annual temperature and receive 0-6% less annual rainfall in future. The wet season in the basin is anticipated to be drier (0% to -6%) while the dry season rainfall shows no particular trend (-3%-10%). Such a change in climate is likely to alter the mean annual flow in future between -3 and 5% at Attapeu, -6 to 2% at Ban Veunkhane, Lao PDR, and -7 to 1% at Siempang, Cambodia (basin outlet). Under climate change, we expect decrement in minimum flow but increment in the maximum flow while opposite is anticipated under reservoir operation. Operation of Xekaman 1 and Sekong 4A are likely to increase the minimum flow at river outlet by 32-59% and 13-18% respectively whereas maximum flow is expected to decrease by 28-5%. In addition, climate change is likely to have crucial impact on fisheries with up to 19% and 12% reduction in fish catches and fish productivity respectively. However, reservoirs tend to have negligible impact on fisheries.

Analysis of potential nature-based solutions for the Mun River Basin, Thailand.

Despite the growth in research and applications of nature-based solutions (NBS) within the literature, there are limited applications in South East Asia, moreover studies which quantitatively assess the impacts of NBS could have on hazard reduction are scarce. This paper addresses this gap by developing and validating MCDA-GIS analysis to map how potential nature strategies could mitigate flood hazard if applied within the Mun River Basin, Thailand. Through a literature review, the top three solutions for flood and drought hazards were found: wetlands, re/afforestation, and changing crop types. These strategies were reviewed and validated with a MCDA-GIS methodology, through land use change (LUC) maps to depict different future scenarios. The results found that flood hazard did decrease when NBS were implemented in the catchment, especially for A/Reforestation, and to a greater extent when a combination of NBS were applied. This article provides specific insights into the current gaps of NBS publications, specifically considering the case of the Mun River Basin, Thailand.

Lapse rate-adjusted bias correction for CMIP6 GCM precipitation data: An application to the Monsoon Asia Region.

Bias correction (BC) of General Circulation Models (GCMs) variables is a common practice when it is being used for climate impact assessment studies at regional scales. The present study proposes a bias correction method (LR-Reg) that first adjusts the original GCM precipitation for local lapse rate corrections and later bias corrects the lapse rate-adjusted GCMs precipitation data with linear regression coefficients. We evaluated LR-Reg BC method in comparison to Linear Scaling (LS) and Quantile Mapping (QMap) BC methods, and NASA's downscaled NEX data for Monsoon Asia region. This study used Coupled Model Intercomparison Project Phase 6 (CMIP6)-based MIROC6 GCM precipitation with historical and projected shared socio-economic pathways (SSP) scenarios (SSP245 and SSP585) datasets. The BC comparison results show that the relative percentage reduction in mean absolute error (MAE) values of LR-Reg over LS-BC was up to 10-30% while this relative reduction in MAE values of LR-Reg was 30-50% over QMap-BC and 75-100% over NASA's NEX-data. The future projected precipitation over Monsoon Asia during dry season shows more decreased precipitation by up to 100% mostly in the south Asia while during wet season shows more increased precipitation by up to 50% mostly in the northeastern China and in the Himalayan belts with respect to the baseline condition (1970-2005). The results on the average precipitation per 0.25 degree increase in latitude analysis shows that the maximums of average monsoon precipitation during baseline period occur at 0 and 25 degree latitudes while the projected monsoon precipitation during both SSP scenarios occurs at 10 and 20 degree latitudes which clearly shows an inward shift in the latitude axis for the projected precipitation in the Monsoon Asia.

Modification and upscaling of S-W model based on vertical distributions of soil moisture and vegetation root biomass.

Soil water is the dominant factor controlling evapotranspiration (ET) in arid and semi-arid regions. However, the widely used ET simulation models, such as the Shuttleworth-Wallace model (S-W model), are insufficient in simulating the direct influence of soil moisture (SM), especially in the root zone. Based on SM and ET field data, we found that the influence of SM on ET increased with soil depth in the grassland. Evaporation in the S-W model was optimized by SM at 0-5 cm as the root mean square error (RMSE) decreased from 1.4 to 0.17, while transpiration was optimized by SM at 10-20 cm as the RMSE decreased from 0.26 to 0.07. The modified S-W model incorporating SM was called the S-W-Ï´ model. To up-scale application and to verify the accuracy of the S-W-Ï´ model under watershed water balance, we replaced the ET simulation module based on the S-W model with our S-W-Ï´ model and the Block-wise TOPMODEL with Muskingum-Cunge routing method (BTOPMC) model that we used as the basis of our simulation. The influence of SM was determined by the proportion of root biomass of different vegetation types at different depths, and each depth interval was assigned a weighting reflecting its degree of influence. The results showed that the S-W-Ï´ model improved accuracy with all the modification schemes tested. The modification scheme determined by the vegetation root distribution pattern had the greatest effect, providing a 4% accuracy improvement. The modified ET and hydrological models have the potential to support water basin management to a greater extent.

Spatiotemporal variations in evapotranspiration and its influencing factors in the semiarid Hailar river basin, Northern China.

Evapotranspiration (ET) is a critical variable in the world's water cycle, and plays a significant role in estimating the impact of environmental change on the regional hydrothermal cycle. Moreover, as an essential of eco-hydrological processes, changes in ET may exceptionally impact the local climate and provide indicative information on the eco-system's functioning. The Hailar River Basin (HRB), located in northern China, is one of the most sensitive areas to climate warming. Under the influence of climate change in recent years, the vegetation dynamics of the basin have been significant and have had profound effects on the regional water cycle conditions and hydrological processes. The HRB is located in a semiarid region and ET is the main mode of water consumption. The ET response to climate change and vegetation dynamics is the focus of research on ecohydrological processes in this basin. In this study, a distributed hydrological model, the BTOPMC model, is used to evaluate the actual ET in the HRB from 1981 to 2020, based on in situ meteorological data as well as LAI data obtained by satellite remote sensing. The seasonal, interannual and spatial dynamics of ET were characterized. The contribution of meteorological factors to ET was calculated by sensitivity analysis and multiple linear regression analysis, and the predominant elements influencing the difference in ET in the HRB were also discussed. The results show that: (1) estimated ET values can clarify over 85% of the seasonal variation in the observed values (R2= 0.79, P < 0.001; R2= 0.84, P < 0.001), which demonstrates that the model has a high precision. (2) Over the past 40 years, the annual ET has shown a clear increasing trend and a large spatial heterogeneity in its spatial distribution, which is consistent with the trend of vegetation. It mainly shows that the eastern forest area is larger than the central forest-grass transition area and the western meadow steppe area. (3) Sensitivity and influential factor contribution analyses show that the main factor driving interannual variability in ET is climate warming, followed by precipitation. At the same time, vegetation dynamics also play a crucial role in ET, especially in areas with different vegetation types and high coverage, while climatic factors also have a strong influence on ET indirectly through vegetation. Due to its special geographic location, the HRB is more sensitive to global climate change and is a typical ecologically fragile area. Therefore, this study has important scientific value and social significance for maintaining ecological security and the sustainable use of water resources.

Evaluating the influence of different environmental water allocation schemes on the water level of a typical shallow lake in semiarid regions: From the perspective of an integrated modeling approach.

Many lakes in semiarid regions around the world rely on environmental water allocation to maintain the health of the lake ecosystem. However, under changing environments, the competition for water resources between human society and natural ecosystems has intensified. How to manage environmental water allocation more reasonably and precisely has become an important issue. The largest lake on the North China Plain, Baiyangdian Lake (BYDL), is a typical lake facing such challenges. To provide feasible strategies for sustainable water allocation to BYDL, with the proper parameterization of hydrological processes, this study developed a 10-day temporal scale lake water level prediction model to quantify how environmental water allocation regulates the BYDL water level under different hydroclimatic conditions. Evaluation of model performance revealed that environmental water allocation rather than natural climatic periodicity dominates the variation in the BYDL water level. The model structure could be further improved with consideration of more detailed observations of both the surface runoff entering BYDL and the water area beneath the canopy of the reeds in BYDL. Analysis of 72 model simulation scenarios indicated that water allocations from multiple sources are indispensable and that the water resources that guarantee maintaining the BYDL water level within the ecologically suitable range vary substantially under different hydroclimatic conditions. More elaborate allocation plans are required both to improve the water quality and health of the aquatic ecosystem of BYDL and to reduce the risk of flooding. The findings from this study are valuable for guiding the implementation of environmental water allocations to lakes in semiarid regions worldwide.

Assessing alterations of water level due to environmental water allocation at multiple temporal scales and its impact on water quality in Baiyangdian Lake, China.

Lakes in arid/semiarid regions face problems of insufficient inflow and degradation of water quality, which threaten the health of the lake ecosystem. Baiyangdian Lake (BYDL), the largest lake in the North China Plain, is confronted with such challenges. The objective of this study was to improve understanding of how changes in water level influence water quality in the BYDL at different temporal scales, especially related to implementations of intermittent environmental water allocation activities in the past two decades, by using data on monthly lake water level, climate factors of precipitation and temperature, and lake water quality. The Mann-Kendall method and continuous wavelet analysis revealed that the lake water level shows a significant decreasing trend after 1967, and the period of 16-year was identified as the principal period for 1950-2018. Based on cross-wavelet transform and wavelet coherence analysis, the periodic agreement and coherence between water level and climatic factors decreased after 1997, when environmental water allocations started, indicating that the influences of climatic factors, i.e., precipitation and temperature, became weak. By utilizing the cross-wavelet transform and wavelet coherence analysis methods, the relationships between lake water level and water quality parameters of chemical oxygen demand, ammonia nitrogen, total nitrogen, and total phosphorus were investigated. We found that the change in source and amount of environmental water allocation is one possible reason for the temporal evolution in joint variability between lake water level and water quality. Meanwhile, a dilution effect of freshwater allocated to BYDL was detected in the time-frequency domain. However, the result also indicates that the driving mechanism of water quality is complex due to the combined impacts of water allocation, nonpoint source pollution in the rainy season, and nutrient release from lake sediment. Our findings improve the general understanding of changes in water level in lakes located in arid and semiarid regions under climate change and intensive human activities, and also provide valuable knowledge for decision making in aquatic ecosystem restoration of BYDL and other similar lakes.

Impacts of climate and land use change on groundwater recharge under shared socioeconomic pathways: A case of Siem Reap, Cambodia.

The rapid pace of urbanization blended with climate change has significantly altered surface and groundwater flows. In the context of tourism-driven economic potential areas, these drivers have greater effects, including threatening groundwater availability. This study assessed the combined impacts of climate and land use changes on the groundwater recharge (GWR) in Siem Reap, Cambodia utilizing Phase Six of the Coupled Model Intercomparison Project (CMIP6) global climate models (GCMs), DynaCLUE land-use model, and Soil Water Assessment Tool (SWAT). Three climate models CanESM5, EC_Earth3, and MIROC6, out of seven, best captured the observed data after performance evaluation through the entropy method, were bias-corrected linearly for two shared socioeconomic pathways (SSPs) - SSP2-4.5 and SSP5-8.5. The results indicate a general increase in precipitation under both SSPs, while the average annual maximum temperature is likely to increase by 0.024 °C/year and 0.049 °C/year under SSP2-4.5 and SSP5-8.5, respectively. A similar trend but relatively higher increase is expected for the minimum temperature. Furthermore, the historical land use change showed the expansion of urban settlement by 373% between 2004 and 2019 at the expense of forest and shrubland. Future land use projections from the DynaCLUE model show that the urban settlements in the study area are likely to expand, from their 2019 condition, by 55% in 2030, 209% in 2060, and 369% in 2090 under SSP2 and at double of these rates under SSP5 scenario. The GWR is expected to rise by 39-53% during the wet season and decrease by 13-29% during the dry season under both scenarios. Meanwhile, under constant land use, the GWR is likely to increase more compared to other scenarios, highlighting the importance of land use planning to policymakers and planners. Additionally, the study shall also be important to practitioners and researchers in understanding, planning, and evaluating the performance of multiple climate models in groundwater assessment.

A novel ecohydrological model by capturing variations in climate change and vegetation coverage in a semi-arid region of China.

Variations in vegetation are influenced by regional climate regimes and, in turn, control the water balance behavior in water-limited regions. Owing to its role in ecohydrological processes, vegetation is an essential link in modeling the relationships among climate conditions, vegetation patterns, and dynamic water balance behavior. However, previous ecohydrological models have been empirical and complex, without physically significant parameters. Here, we propose a novel ecohydrological model (a Budyko model-coupled vegetation model) that combines the impacts of climate change and vegetation variations, featuring simple and deterministic parameters. In addition to accounting for the fundamental water balance model and its factors, mean precipitation, potential evapotranspiration, runoff, and variations in water storage (δS), the model showed better performance when incorporating δS (RMSE = 2.72 mm yr-1) and its parameter ε -, which is mechanically and quantitively subject to the vegetation coverage (R2 = 0.95, p < 0.01). This was estimated as a function of vegetation potential canopy conductance, mean rainstorm depth, mean time between storms, and potential rate of evapotranspiration in a semi-arid watershed with impulsive precipitation in China (R2 = 0.80, p < 0.01). The model also found that vegetation growth was mainly controlled by soil water content and decoupled the impact of the total amount of precipitation on vegetation in the northeastern area of the watershed. Hence, our method presents a new tool for building an ecohydrological model that includes deterministic parameters of mechanical significance.

Assessing the future climate change, land use change, and abstraction impacts on groundwater resources in the Tak Special Economic Zone, Thailand.

Groundwater is an important source of water supply in the Tak Special Economic Zone of Thailand. However, groundwater is under stress from climate change, land use change, and an increase in abstraction, affecting the groundwater level and its sustainability. Therefore, this study analyses the impact of these combined stresses on groundwater resources in the near, mid, and far future. Three Global Climate Models are used to project the future climate under SSP2-4.5 and SSP5-8.5 scenarios. According to the results, both maximum and minimum temperatures are likely to show similar increasing trends for both scenarios, with a rise of approximately 1 (1.5), 2 (3), and 3 (5) °C expected for SSP2-4.5 (SSP5-8.5) in each consecutive period. Annual rainfall is expected to continually increase in the future, with around 1500-1600 mm in rainfall (11ꟷ5.43% higher). Land use change is predicted for two scenarios: business as usual (BU) and rapid urbanisation (RU). The forest area is expected to increase to 30% (35%) coverage in 2090 for BU (RU) while agriculture is likely to reduce to 60% (50%) with the urban area increasing to 2.4% (7%). Water demand is predicted to increase in all future scenarios. The SWAT model is used to project recharge, which is likely to increase by 10-20% over time. The highest increase is predicted in the far future under SSP2 and RU scenarios. MODFLOW was used to project future groundwater resources, but due to the lack of consistent data, the time scale is reduced to yearly simulation. The results reveal that the groundwater level is expected to increase in the central part (urban area) of the study area and decrease along the boundary (agricultural area) of the aquifer. This research can aid policymakers and decision-makers in understanding the impact of multiple stressors and formulating adaptation strategies to manage groundwater resources in special economic zones.

Do Multiple Brain Lesions Always Connote Worse Outcomes? Appraisal Evidence from a Tertiary Care Center in Koshi/Purbanchal Province of Nepal.

Advances in medicine comprising diverse diagnostic and management modalities call for a bundle approach to improve patient care. This study aimed to present diagnostic patterns in patients with multiple intracranial lesions together with connoted survival implications. We retrospectively reviewed medical files of 85 patients with tumor and non-tumor intracranial lesions. Metastatic brain lesions were identified in 23.5% of patients. Neurological pathogenesis underlay 29.4%, infectious 21.2%, and vascular 14.1% of lesions, with the remaining portion comprising less frequent disorders. A favorable prognosis was predicted in 52/85 (61.2%) of the study population despite a variety of pathologies, which speaks for substantial improvements in outcomes of once hardly manageable or mortal brain disorders, comprising both common and rare conditions. The improvements are to the credit of advances in medical radio-imaging enhancing the diagnostic power which enables a precise stratification of brain pathologies. We emphasize the use of an algorithmic evaluation of patients presenting with multiple brain lesions for differential diagnosis and survival prognostication. There seems to be an ongoing transition from imperfect probabilistic prediction models to precision medicine, which determines advantages in disease management and outcome.

Phytoplankton community variation and ecological health assessment for impounded lakes along the eastern route of China's South-to-North Water Diversion Project.

Interbasin water diversion projects have been proven to effectively alleviate water resource shortages in areas along water diversion lines, but few studies have focused on ecological health in impounded lakes compared with research on water quality and pollutants. Herein, monitoring data were collected during the nonwater diversion period (NWDP) and the water diversion period (WDP) from 2018 to 2019, and the index of biological integrity (IBI) method based on phytoplankton communities was used to evaluate the ecological health of the impounded lakes (Nansi Lake and Dongping Lake) along the eastern route of the South-to-North Water Diversion Project. The results demonstrated that water diversion improved the water quality of the impounded lakes during the WDP, especially total nitrogen and ammonia nitrogen. Meanwhile, the water diversion affected the phytoplankton community structure and diversity, and network analysis further revealed water diversion could be beneficial to the ecological health of impounded lakes. Furthermore, the P-IBI showed that the overall ecological health assessment was "good" during the WDP. Water diversion substantially improved the ecological health status and stability of the impounded lakes during the dry season. Finally, the direct correlations between the water quality parameters and the P-IBI were weak, and water quality parameters could indirectly affect the P-IBI by changing the phytoplankton community structure. These findings will enhance our understanding of the ecological health of the impounded lakes of the South-to-North Water Diversion Project. Furthermore, this study will provide a reference to support the ecosystem security of impounded lakes in other large water diversion projects.

Evaluating aquifer stress and resilience with GRACE information at different spatial scales in Cambodia.

Groundwater exploitation for different sectors in Cambodia is expanding. Groundwater levels have already begun to decline in some parts of the country. Monitoring and assessing groundwater storage (GWS) change, aquifer stress and aquifer resilience will support the proper planning and management of the country's groundwater resources; however, information regarding groundwater in Cambodia is currently scarce. Thus, GWS change in Cambodia over the 15 years from April 2002 to March 2017 was assessed using remote-sensing-based Gravity Recovery and Climate Experiment (GRACE) and Global Land Data Assimilation System (GLDAS) datasets, with a comprehensive validation of the GRACE-derived groundwater storage anomaly (GWSA) with respect to in-situ field-based observations. The current study also investigated the impact of surface water storage (SWS) change in Tonle Sap Lake, South-East Asia's largest freshwater lake, on deriving the GWS change in Cambodia. The groundwater aquifer stresses (GAS), and aquifer resilience (AR) were also evaluated. The validation results were promising, with the correlation coefficient between satellite-based estimations and ground-based measurements ranging from 0.82 to 0.88 over four subbasins. The overall decreasing rate of GWS was found to be -0.63 mm/month, with two basins having the highest declining rate of more than 1.4 mm/month. Meanwhile, the aquifer experiencing stress during the dry season had a very low ability to quickly recover from these stresses. These findings emphasise that appropriate management is urgently needed to ensure the sustainability of the groundwater resource system in this country. Supplementary Information: The online version contains supplementary material available at 10.1007/s10040-022-02570-w.

L'exploitation des eaux souterraines s'étend au Cambodge dans différents secteurs. Les niveaux piézométriques ont déjà commencé à baisser sur quelques secteurs du pays. Surveiller et évaluer les changements de stock d'eau souterraine (GWS), la pression sur les aquifères et leur résilience supportera une planification et gestion correctes des ressources en eau dans le pays; toutefois, les informations en relation avec les eaux souterraines sont peu nombreuses aujourd'hui au Cambodge. Ainsi, les changements de GWS au Cambodge sur les 15 dernières années, d'avril 2002 à mars 2017 ont été évalués à l'aide des méthodes de télédétection basées sur le Gravity Recovery and Climate Experiment (GRACE) et les jeux de données du Global Land Data Assimilation System (GLDAS) avec une validation complète des anomalies de stockage d'eau souterraine (GWSA) de GRACE par l'utilisation d'observations de terrain. L'étude a également permis d'étudier l'impact des changements de stocks d'eau de surface (SWS) dans le lac Tonle Sap, le plus grand lac d'eau douce du sud-est asiatique, par dérivation des changements de GWS au Cambodge. Les pressions sur les eaux souterraines (GAS) et la résilience des aquifère (AR) ont également été évaluées. La validation des résultats est prometteuse, avec un coefficient de corrélation entre les estimations basées sur les données satellitaires et les mesures de terrain allant de 0.82 à 0.88 sur quatre sous-bassins. Un taux de baisse globale du GWS de ­0.63 mm/mois a été estimé, avec deux sous-bassins ayant des baisses plus fortes de plus de 1.4 mm/mois. Sur la même période, les aquifère qui subissent un stress durant les basses eaux montrent une faible capacité à récupérer de ce stress. Ces résultats montrent qu'une gestion adéquate est urgemment nécessaire pour assurer la durabilité de la ressource en eau souterraine dans ce pays.

La explotación de las aguas subterráneas para diferentes sectores en Camboya está en expansión. Los niveles de las aguas subterráneas ya han empezado a descender en algunas partes del país. El seguimiento y la evaluación de los cambios en el almacenamiento de las aguas subterráneas (GWS), el estrés del acuífero y la resiliencia del acuífero apoyarán la planificación y la gestión adecuadas de los recursos de aguas subterráneas del país; sin embargo, la información relativa a las aguas subterráneas en Camboya es actualmente escasa. Por lo tanto, se evaluó el cambio de GWS en Camboya durante los últimos 15 años, desde abril de 2002 hasta marzo de 2017, utilizando conjuntos de datos del Gravity Recovery and Climate Experiment (GRACE) y del Global Land Data Assimilation System (GLDAS) basados en la teledetección, con una validación exhaustiva de la anomalía de almacenamiento de aguas subterráneas (GWSA) derivada de GRACE con respecto a las observaciones in situ sobre el terreno. El presente estudio también investigó el impacto del cambio en el almacenamiento de agua superficial (SWS) en el lago Tonle Sap, el mayor lago de agua dulce del sudeste asiático, en la derivación del cambio del GWS en Camboya. También se evaluaron las tensiones de los acuíferos subterráneos (GAS) y la resistencia de los acuíferos (AR). Los resultados de la validación fueron promisorios, ya que el coeficiente de correlación entre las estimaciones basadas en satélites y las mediciones terrestres osciló entre 0.82 y 0.88 en cuatro subcuencas. La tasa global de disminución del GWS fue de ­0.63 mm/mes, con dos cuencas con la tasa de disminución más alta, de más de 1.4 mm/mes. Mientras tanto, el acuífero que experimentaba estrés durante la estación seca tenía una capacidad muy baja para recuperarse rápidamente de estas tensiones. Estos resultados ponen de relieve que se necesita urgentemente una gestión adecuada para garantizar la sostenibilidad del sistema de recursos hídricos subterráneos en este país.

A exploração de águas subterrâneas para diferentes setores no Camboja está se expandindo. Os níveis das águas subterrâneas já começaram a diminuir em algumas partes do país. O monitoramento e avaliação das mudanças no armazenamento de águas subterrâneas (AASub), estresse e resiliência do aquífero apoiarão o planejamento e a gestão adequados dos recursos hídricos subterrâneos do país; no entanto, as informações sobre as águas subterrâneas no Camboja são atualmente escassas. Assim, a mudança de AASub no Camboja nos últimos 15 anos, de abril de 2002 a março de 2017, foi avaliada usando conjuntos de dados Gravity Recovery and Climate Experiment (GRACE) e Global Land Data Assimilation System (GLDAS) baseados em sensoriamento remoto, com uma validação abrangente da anomalia de armazenamento de água subterrânea derivada do GRACE (AAASub) em relação a observações baseadas em campo. O estudo atual também investigou o impacto da mudança de armazenamento de água de superfície (AASup) no Lago Tonle Sap, o maior lago de água doce do Sudeste Asiático, na derivação da mudança de AASub no Camboja. Os estresses das águas subterrâneas no aquífero (SASub) e a resiliência do aquífero (RA) também foram avaliados. Os resultados da validação foram promissores, com o coeficiente de correlação entre as estimativas baseadas em satélite e as medições terrestres variando de 0.82 a 0.88 em quatro sub-bacias. A taxa global decrescente de AAS foi de ­0.63 mm/mês, com duas bacias tendo a maior taxa de declínio de mais de 1.4 mm/mês. Enquanto isso, o aquífero submetido a estresse durante a estação seca teve uma capacidade muito baixa de se recuperar rapidamente desses estresses. Esses achados enfatizam que uma gestão adequada é urgentemente necessária para garantir a sustentabilidade do sistema de recursos hídricos subterrâneos neste país.

Determining suitable machine learning classifier technique for prediction of malaria incidents attributed to climate of Odisha.

This study investigated the influence of climate factors on malaria incidence in the Sundargarh district, Odisha, India. The WEKA machine learning tool was used with two classifier techniques, Multi-Layer Perceptron (MLP) and J48, with three test options, 10-fold cross-validation, percentile split, and supplied test. A comparative analysis was carried out to ascertain the superior model among malaria prediction accuracy techniques in varying climate contexts. The results suggested that J48 had exhibited better skill than MLP with the 10-fold cross-validation method over the percentile split and supplied test options. J48 demonstrated less error (RMSE = 0.6), better kappa = 0.63, and higher accuracy = 0.71), suggesting it as most suitable model. Seasonal variation of temperature and humidity had a better association with malaria incidents than rainfall, and the performance was better during the monsoon and post-monsoon when the incidents are at the peak.

Reconstructing NDVI and land surface temperature for cloud cover pixels of Landsat-8 images for assessing vegetation health index in the Northeast region of Thailand.

Critical applications of satellite data products include monitoring vegetation dynamics and assessing vegetation health conditions. Some indicators like normalized difference vegetation index (NDVI) and land surface temperature (LST) are used to assess the status of vegetation growth and health. But one of the major problems with passive remote sensing satellite data products is cloud and shadow cover that leads to data gaps in the images. The present study proposes temporal aggregation of images over a short time span and developing short span harmonic analysis of time series (SS-HANTS) and pixel-wise multiple linear regression (PMLR) algorithms for retrieving cloud contaminated NDVI and LST information from Landsat-8 (L8) data products, respectively. The developed algorithms were applied in the northeastern part of Thailand to recover the missing NDVI and LST values from time series L8 images acquired in 2018. The predicted NDVI and LST values at artificially clouded locations were compared with the corresponding clear pixel values. Additionally, the model predicted LST and NDVI values were also compared with MODIS LST and NDVI datasets. The calculated root mean square (RMSE) values were ranging from 0.03 to 0.11 and 1.50 to 2.98 °C for NDVI and LST variables, respectively. The validation statistics show that these models can be satisfactorily applied to retrieve NDVI and LST values from cloud-contaminated pixels of L8 images. Furthermore, a vegetation health index (VHI) computed from cloud retrieved continuous NDVI and LST images at province level shows that most of the western provinces have healthy vegetation condition than other provinces in the northeast of Thailand.

Appraisal of Burden of Caregivers to Chronically Rehabilitated Patients with Spinal Cord Injuries in a Tertiary Neurological Center in Nepal.

The care of a patient with a spinal cord injury is part of healthcare systems. It causes a substantial physical and emotional drain on the caretakers who often are in short supply and thus may lack adequate training, preparation, and support. Long hours of assisting a chronically handicapped patient with activities of daily living and exercises decrease the rehabilitator's quality of life and take a psychological toll that increases a risk of burnout syndrome. The present study found a significant caregiving burden among care providers of chronically dependent patients with spinal cord injuries. Additionally, financial drain escalates the issue in this rather neglected health and quality of life aspect concerning caregivers. For the situation to improve, there must be a paradigm shift in care taking toward the motivative patient's participation in the rehabilitative process. Provisions for social support and educational programs focusing on the patients and their families need to be reappraised.

Predicting flood events in Kathmandu Metropolitan City under climate change and urbanisation.

Urbanisation and climate change collectively impose the threat of urban flood. The impervious transformation and changes in local climatic conditions increase the risk of frequent pluvial flooding in Kathmandu. Therefore, this study aims to assess the integrated impact of urbanisation and climate change on pluvial flooding in Kathmandu Metropolitan City, using the Personal Computer Storm Water Management Model. The future daily rainfall from three Regional Climate Models under two Representative Concentration Pathways (RCPs) and the observed daily data has been disaggregated to hourly series using temporal rainfall disaggregation. The result shows that the combined impact on pluvial flood is likely to intensify with relatively more contribution from climate change. The CNRM-CM5-CSIRO-CCAM under the RCP 4.5 scenario projects the maximum increase (60-90%) in flood volume for current (75%) and extreme (90%) imperviousness, under a 2-year and 20-year return period (RP) with the extent of the flood area increasing more than the depth. For a 2-year RP, areas with a depth of 0.10-0.25 m are likely to expand while those from 0.25 to 0.40 m in depth are projected to have more velocity, and these trends are expected to be magnified for higher RPs. The study shows that even though urbanisation contributes less to urban pluvial flood, it can be a catalyst for exaggerating other factors and implementing management measures. For instance, the application of small-scale rainwater harvesting, and overflow storage reduced the runoff, thereby reducing the flood volume by 20-35%. Furthermore, the findings highlight the need for planning management strategies such as evaluation and upgrading of conventional drainage systems with low impact measures (rainwater harvesting and green roofs); technical and financial assistance to urban dwellers in adopting the management measures or a combination of them based on the location, requirements, and availability of information and resources to reduce the effects of pluvial flood in Kathmandu.

Multiple drivers of hydrological alteration in the transboundary Srepok River Basin of the Lower Mekong Region.

Human-induced changes in land and water resources adversely affect global hydrological regimes. Hydrological alteration of the natural flow regime is considered to have a significant damaging and widespread impact on river ecosystems and livelihoods. Therefore, understanding the hydrological alteration of rivers and the potential driving factors affecting such alterations are crucial to effective water resources management. This study analyses the impact of changes in land use, climate, and hydropower development on the hydrological regime of the Srepok River Basin in the Lower Mekong Region. The Lower Mekong Basin (LMB) in Southeast Asia is known for its agriculture, forests, fisheries, wildlife, and diverse natural ecosystems. Historical land use and climate change are quantified (utilising European Space Agency land cover and observed meteorological data) and correlated with the hydrological indicators using the Indicators of Hydrologic Alteration (IHA) software. Moreover, pre and post impacts on the hydrological regime by hydropower development are quantified using the Range of Variability Approach (RAV) in IHA software. The results reveal that land use, rainfall, and temperature affect different aspects of the hydrological regime, with corroborating evidence to support variation among the most correlated IHA and environmental flow component (EFC) parameters with the three drivers. The highest and lowest correlations among the IHA and EFC parameters under each driver are against land use (0.85, -0.83), rainfall (0.78, -0.54), and minimum and max temperatures (0.42, -0.47). Among the parameters, the fall rate has the most significant effect on hydrological alteration of all drivers. Hydropower development in the basin mostly affects the fall rate and reversal. Identifying the connection between these multiple drivers and hydrological alteration could help decision-makers to design more efficient and sustainable water management policies.

PINSPlus: a tool for tumor subtype discovery in integrated genomic data.

SUMMARY: Since cancer is a heterogeneous disease, tumor subtyping is crucial for improved treatment and prognosis. We have developed a subtype discovery tool, called PINSPlus, that is: (i) robust against noise and unstable quantitative assays, (ii) able to integrate multiple types of omics data in a single analysis and (iii) dramatically superior to established approaches in identifying known subtypes and novel subgroups with significant survival differences. Our validation on 12,158 samples from 44 datasets shows that PINSPlus vastly outperforms other approaches. The software is easy-to-use and can partition hundreds of patients in a few minutes on a personal computer. AVAILABILITY AND IMPLEMENTATION: The package is available at https://cran.r-project.org/package=PINSPlus. Data and R script used in this manuscript are available at https://bioinformatics.cse.unr.edu/software/PINSPlus/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.