A review of recent advances and future prospects in calculation of reference evapotranspiration in Bangladesh using soft computing models.

Evapotranspiration (ETo) is a complex and non-linear hydrological process with a significant impact on efficient water resource planning and long-term management. The Penman-Monteith (PM) equation method, developed by the Food and Agriculture Organization of the United Nations (FAO), represents an advancement over earlier approaches for estimating ETo. Eto though reliable, faces limitations due to the requirement for climatological data not always available at specific locations. To address this, researchers have explored soft computing (SC) models as alternatives to conventional methods, known for their exceptional accuracy across disciplines. This critical review aims to enhance understanding of cutting-edge SC frameworks for ETo estimation, highlighting advancements in evolutionary models, hybrid and ensemble approaches, and optimization strategies. Recent applications of SC in various climatic zones in Bangladesh are evaluated, with the order of preference being ANFIS > Bi-LSTM > RT > DENFIS > SVR-PSOGWO > PSO-HFS due to their consistently high accuracy (RMSE and R2). This review introduces a benchmark for incorporating evolutionary computation algorithms (EC) into ETo modeling. Each subsection addresses the strengths and weaknesses of known SC models, offering valuable insights. The review serves as a valuable resource for experienced water resource engineers and hydrologists, both domestically and internationally, providing comprehensive SC modeling studies for ETo forecasting. Furthermore, it provides an improved water resources monitoring and management plans.

Characteristics of surface evapotranspiration and its response to climate and land use and land cover in the Huai River Basin of eastern China.

The Huai River Basin (HRB) has experienced significant climate and land use and land cover changes (LUCC) which have impacted the water cycle in recent times. However, little is understood about the impact of climate change and LUCC affecting evapotranspiration (ET). Thus, we investigate how surface ET response to climate change and LUCC in the HRB for the period from 2001 to 2014. ET and land cover types products (i.e., MOD16 and MCD12Q1, respectively) from MODerate-resolution Imaging Spectroradiometer (MODIS) were employed in this research. Water balance method and D20 pan evaporation data (Epan) as well as eddy covariance (EC) measurements were used to validate the MOD16 product, and the Theil-Sen's slope estimator and Mann-Kendall (M-K) test were adopted to estimate the magnitude and significance of ET trends. Moreover, daily meteorological data of 137 weather stations from 2001 to 2014 were also employed to explore the correlation mechanism between ET and meteorological factors. The results showed that the accuracy of MOD16 product data were convincible and could be used to estimate ET in the HRB. The higher values of ET are mainly distributed in the south and lower values in the north. ET decreased significantly in all seasons except in spring, especially in winter. The results also depicted that the land-use type in the HRB is mainly croplands, followed by forests and grasslands. Croplands area showed a decreasing trend at a rate of -176.2 km2·a-1, grasslands area presents a w-type fluctuation decreasing trend with a rate of -35.8 km2·a-1, urban/built-up area increased at a rate of 138.3 km2·a-1, water bodies area decreased gradually at a rate of -1.38 km2·a-1, wetlands area increased significantly at a rate of 43.6 km2·a-1, and barren area decreased gradually at a rate of -9.5 km2·a-1. The average annual ET is closely related to land-use types and shows a significant downward trend in general. The corresponding ET magnitude is exhibited as follows: forests>grasslands>croplands>wetlands>water bodies>urban/build-up lands>barren. Results of the study also suggest water conditions (precipitation (Pre) and relative humidity (RH) decrease) are major controlling factors in the decline of ET. Overall, the LUCC has a smaller influence on ET than climate change in the HRB. This research will provide a better insight into climate change and LUCC impacts on water resources.

Co-distribution, possible origins, status and potential health risk of trace elements in surface water sources from six major river basins, Bangladesh.

In this study, we appraised the concentrations of 8 major trace elements (TEs) in surface water sources from six river basins, Bangladesh: Meghna, Kartoya, Sitalakha, Teesta, Pashur and Rupsha River basins. Co-distribution, the status of water quality and potential health risks were assessed using statistical analyses, the entropy water quality index (EWQI), sodium adsorption ratio (SAR), spatial autocorrelation index (SAI), hazard index (HI), and Monte-Carlo (MC) simulation. The spatial variations of TEs concentrations differed notably among the studied river basins. The average concentrations of TEs (except Ni, As, and Zn) in six river basins exceeded the drinking water quality guidelines. About 20% of water samples in six basins were categorized as undrinkable to poor qualities for drinking uses, while good water quality for irrigation purposes. The entropy theory identified that Cr, Pb, and As are the key pollutants influencing the water quality. According to the results of non-carcinogenic risk, the hazard index (HI) values for adults and children surpassed the allowable limit (>1), demonstrating detrimental health effects on humans. The carcinogenic risk values of chromium (Cr) were much higher than As and Cd exposures which exceeded the benchmark recommended by US EPA (>10-6 to 10-4), with an elevated risk for adults than children through the oral intake as the primary exposure route. Overall, the results suggest that the local population exposed to surface water may pose an adverse health effect, thus, strict regulation and efficient management should be focused on Cr, Cd and As monitoring and appraisal in these basins.

Dynamic analysis of pan evaporation variations in the Huai River Basin, a climate transition zone in eastern China.

Pan evaporation (Epan), which we examine in this study to better understand atmospheric evaporation demand, represents a pivotal indicator of the terrestrial ecosystem and hydrological cycle, particularly in the Huai River Basin (HRB) in eastern China, where high potential risks of drought and flooding are commonly observed. In this study, we examine the spatiotemporal trend patterns of climatic factors and Epan by using the Mann-Kendall test and the Theil-Sen estimator based on a daily meteorological dataset from 89 weather stations during 1965-2013 in the HRB. Furthermore, the PenPan model is employed to estimate Epan at a monthly time scale, and a differential equation method is applied to quantify contributions from four meteorological variables to Epan trends. The results show that Epan significantly decreased (P<0.001) at an average rate of -8.119mm·a-2 at annual time scale in the whole HRB, with approximately 90% of stations occupied. Meanwhile, the generally higher Epan values were detected in the northern HRB. The values of the aerodynamic components in the PenPan model were much greater than those of the radiative components, which were responsible for the variations in the Epan trend. The significantly decreasing wind speed (u2) was the most dominant factor that controlled the decreasing Epan trend at each time scale, followed by the notable decreasing net radiation (Rn) at the annual time scale also in growing season and summer. However, the second dominant factor shifted to the mean temperature (Ta) during the spring and winter and the vapor pressure deficit (vpd) during the autumn. These phenomena demonstrated a positive link between the significance of climate variables and their control over the Epan trend.

Characterizing groundwater quality ranks for drinking purposes in Sylhet district, Bangladesh, using entropy method, spatial autocorrelation index, and geostatistics.

Drinking water is susceptible to the poor quality of contaminated water affecting the health of humans. Thus, it is an essential study to investigate factors affecting groundwater quality and its suitability for drinking uses. In this paper, the entropy theory, multivariate statistics, spatial autocorrelation index, and geostatistics are applied to characterize groundwater quality and its spatial variability in the Sylhet district of Bangladesh. A total of 91samples have been collected from wells (e.g., shallow, intermediate, and deep tube wells at 15-300-m depth) from the study area. The results show that NO3-, then SO42-, and As are the most contributed parameters influencing the groundwater quality according to the entropy theory. The principal component analysis (PCA) and correlation coefficient also confirm the results of the entropy theory. However, Na+ has the highest spatial autocorrelation and the most entropy, thus affecting the groundwater quality. Based on the entropy-weighted water quality index (EWQI) and groundwater quality index (GWQI) classifications, it is observed that 60.45 and 53.86% of water samples are classified as having an excellent to good qualities, while the remaining samples vary from medium to extremely poor quality domains for drinking purposes. Furthermore, the EWQI classification provides the more reasonable results than GWQIs due to its simplicity, accuracy, and ignoring of artificial weight. A Gaussian semivariogram model has been chosen to the best fit model, and groundwater quality indices have a weak spatial dependence, suggesting that both geogenic and anthropogenic factors play a pivotal role in spatial heterogeneity of groundwater quality oscillations.