Despite its complexity and importance in managing water resources in populous deltas, especially in tidal areas, literatures on tidal rivers and their land use linkage in connection to water quality and pollution are rare. Such information is of prior need for Integrated Water Resource Management in water scarce and climate change vulnerable regions, such as the south- western coast of Bangladesh. Using water quality indices and multivariate analysis, we present here the land use signatures of a dying tidal river due to anthropogenic perturbation. Correlation matrix, hierarchical cluster analysis, factor analysis, and bio-geo-chemical fingerprints were used to quantify the hydro-chemical and anthropogenic processes and identify factors influencing the ionic concentrations. The results show remarkable spatial and temporal variations ( p < 0.05) in water quality parameters. The lowest solute concentrations are observed at the mid reach of the stream where the agricultural and urban + + wastewater mix. Agricultural sites show higher concentration of DO, Na and K reflecting the effects of tidal spill-over − − − 3− and shrimp wastewater effluents nearby. Higher level of Salinity, EC, Cl, HCO, NO, PO and TSS characterize the 3 3 4 urban sites indicating a signature of land use dominated by direct discharge of household organic waste into the waters. The spatial variation in overall water quality suggests a periodic enhancement of quality especially for irrigation and non-drinking purposes during monsoon and post-monsoon, indicating significant influence of amount of rainfall in the basin. We recom - mend that, given the recent trend of increasing precipitation and ground water table decrease, such dying tidal river basins may serve as excellent surface water reservoir to supplement quality water supply to the region. Keywords Land use signature · Ephemeral tidal river · Water quality · Hierarchical cluster analysis (HCA) · Bio-geo- chemical fingerprint * Kushal Roy M. Shah Alam Khan Kushal.email@example.com; firstname.lastname@example.org email@example.com Md. Rezaul Karim Environmental Science Discipline, Khulna University, Zitu.firstname.lastname@example.org Khulna 9208, Bangladesh Farjana Akter Department of Agricultural Sciences, Faculty of Agriculture email@example.com and Forestry, University of Helsinki, Helsinki, Finland Md. Safiqul Islam Institute of Water Modelling (IWM), Dhaka, Bangladesh firstname.lastname@example.org Institute of Water and Flood Management, Bangladesh Kousik Ahmed University of Engineering and Technology (BUET), Dhaka, email@example.com Bangladesh Masudur Rahman firstname.lastname@example.org Dilip Kumar Datta email@example.com Vol.:(0123456789) 1 3 78 Page 2 of 16 Applied Water Science (2018) 8:78 landscape. Due to high diversity and biological resources, Introduction such river basins are also exposed to maximum human perturbation resulting in various land use (e.g., Auerbach River water chemistry is controlled by many natural and et al. 2015; Gain et al. 2017; Mutahara et al. 2017). The anthropogenic factors. Anthropogenic factors such as dynamism of tidal rivers, frequent changes in flow and land use is well known as one of the major influences multipurpose use of land resources poses complex impacts on the hydrochemistry of the rivers (e.g., Rothwell et al. of the hydrochemistry and water quality. Therefore, inte- 2010; Pratt and Chang 2012; Huang et al. 2013a, b, etc.). grated water resource management in such regions is quite Anthropogenic activities are increasing day by day leading difficult and requires in-depth research efforts and high- towards conversion of pristine lands, increasing urban resi- resolution monitoring data. dences, surface water runoff, wastewater input and dwin- The southwestern costal region of Bangladesh is one of dling forested lands and wetlands. Literatures suggest the top vulnerable regions in the world due to Climate Change practice of land use changes has an impact spanning from (CC) and Sea Level Rise (SLR) (e.g. Mondal et al. 2013; local to global scale (e.g., Wilson and Weng 2010; Yang Auerbach et al. 2015, Roy et al. 2017). The region is also one et al. 2012; Hur et al. 2014; Roy et al. 2015, etc.), rang- of the examples of massive anthropogenic perturbation and ing from changes in the global carbon cycle (e.g., Pielke degradation in water quality (e.g. Brammer 2010; Auerbach et al. 2002; Kalnay and Cai 2003; Don et al. 2011; Poeplau et al. 2015; Ayers et al. 2016, 2017; Roy et al. 2017). Our et al. 2011, etc.), through changes in surface energy and study area concentrates on the Mayur river basin, a major water balance to widespread effects on water quality (e.g., tributary of the Bhairab river system (Fig. 1). The Bahiarab Foley et al. 2005; Shen et al. 2014, 2015). It has been river system is one of the major systems that flows through observed that, the water chemistry parameters synchro- the southwest delta of Bangladesh. This heavily populated nously vary with the changes of land use pattern (e.g., delta (~ 14 million, calculated from BBS 2011) has evolved Zhou et al. 2012) and hydrological dynamics (e.g., Zhang around this river. Originated from a beel (wetland system) et al. 2014). Runoff is largely affected by physical altera- river Mayur contributes fresh water to the Bhairab system tion of the landscapes (e.g. Tang et al. 2005; Valentin et al. and provides irrigation for ~ 48,000 ha of farmland. Besides 2008; Nunes et al. 2011). The relationship between water the river supports aquaculture and provides base flow for the quality and land use, however, may be concealed by other surrounding groundwater system. Over last 30 years Mayur factors complicating to obtain a distinct hydro-chemical has become an ephemeral tidal river and now-a-days gets signature (e.g., Kang et al. 2010; Huang et al. 2013a, b; disconnected from its source during dry season. However, Bu et al. 2014, etc.). Thus, the study of stream hydro- tidal influence is quite active at the confluence with the chemistry is important in revealing the pattern and linkage river Bhairab. The river, besides irrigation and aquaculture, between evaporation, chemical weathering, precipitation is used as the municipal wastewater drainage along with and anthropogenic impacts (e.g., Gibbs 1970; Meybeck industrial discharges from ~ 1500 industries and factories. 1987; Brennan and Lowenstein 2002; Rothwell et al. 2010; Because of the rivers ephemeral character, its capacity to Tran et al. 2010; Mitchell et al. 2013). Quantifying the assimilate and eliminate pollutants from water is gradually major ion composition of stream waters also has broad reducing. In the context of declining ground water table in implications, i.e., water type, hydrogeology characteris- the city (Fig. 2), salinity intrusion and growing demand for tics, weathering processes and rainfall chemistry. These potable water, search for an alternative water source is now researches featured in scientific literatures over 50 years of utmost importance. The state of current water chemis- (e.g., Gibbs 1970; Brennan and Lowenstein 2002; Nord- try, land use pattern in the drainage basin, rainfall runoff, strom 2011). Understanding how land use and land cover water use conflicts, etc. can be major determinants for the change influence the flow and water quality of rivers is of potentiality of the Mayur as an option. To start with, this utmost importance for river management and restoration river deserves a deeper insight to its chemistry and sources (e.g., Barbosa et al. 2012; Huang et al. 2013a, b). of pollution. However, despite land use and its linkage with hydro- Researchers have employed many statistical applications chemistry being center of attention to many researchers all over the world to investigate the linkage between land in the recent past, tidal rivers in populous deltas have use and water quality. These applications include Correla- attracted little attention. Tidal rivers in coastal deltas are tional Analysis (CA) (e.g., Bu et al. 2014), Multiple Regres- dynamic in terms of variations in settings (e.g. Well 1995); sion Analysis (MRA) (e.g., Kang et al. 2010), Redundancy changes of courses (e.g., Zhang et al. 2010), rate of accre- Analysis (e.g., Shen et al. 2015) and Principal Component tion and erosion (e.g., Rogers et al. 2013) and the amount Analysis (PCA) (e.g., Villegas et al. 2013). In this study, of water discharge/intake over short period. Such charac- major ion composition of the Mayur River has been exam- teristics of tidal rivers lead to dynamic changes to coastal ined and spatio-temporal patterns indicative of their source 1 3 Applied Water Science (2018) 8:78 Page 3 of 16 78 Fig. 1 Distribution of sampling points and major land use pattern in the Mayur River basin are investigated as well as the control mechanisms of ion through drinking and irrigation water quality analysis. It chemistry is explained through various multivariate statistics should be noted that, although use of multivariate techniques and water quality indices. In addition, this dying tidal riv- to identify the linkage between hydrochemistry and land er’s potential as a surface water resource has been inspected use is quite common and popular in scientific community to 1 3 78 Page 4 of 16 Applied Water Science (2018) 8:78 (a) (c) (b) Fig. 2 Measurements of groundwater tables over 1987–2007 in two observation wells in the basin area (a, b). c Exhibits the bathymetric meas- urement of the river basin reveal the management strategy, this is the first attempt to serves irrigation water for the whole basin and plays critical apply such a technique for a tidal river in Bangladesh. role in maintaining the local groundwater table. The river basin is composed of various morphological features such as flood plain, flood basin, swamp, and aban- doned channel (Roy et al. 2005). The elevation of this tidal Study area basin varies between 1.2 and 3.8 m. The region lies on the Ganges deltaic plain in north and Ganges tidal plain in south Our study concentrates on the tidal river basin of Mayur, of Holocene–Recent age (Adhikari et al. 2006). Tectoni- located at the back swamp of the river Bhairab. The river cally, the area lies within the Faridpur Trough of Foredeep is originated from a large wetland system called beel Pabla Bengal Basin. No subsurface fault has been demarcated in and nowadays is ~ 11 km long with 22 canals and one river the region. Lithologically, the area is composed of very fine joining in its course. While its right bank is industrialized sand, silt and silty clay up to a depth of 300 m with peaty and receives municipal and industrial waste, the left bank soil and calcareous as well as non-calcareous soil at the top. characterized with wetlands and agricultural lands being irrigated with its water (Fig. 1). Due to the river’s geographi- cal location, the river shares the basin of river Bhairab’s Materials and methods large tidal basin. Although river Mayur serves fresh water to the river Bhairab during monsoon and post-monsoon, tidal Sampling and analysis impacts are heavy at the confluence of these rivers. Because of wastewater discharge to this river, it is also subject to a Surface samples were collected from the river and its adjoin- massive anthropogenic perturbation (Rahman et al. 2014). ing canals over four seasons: pre-monsoon, monsoon, post- It is embanked on both heads to create land for aquaculture. monsoon and winter. Samples were collected at depths A large 10-vent sluice gate controls the southern end of the 40–50 cm from the water surface approximately at the river (lower reach) to control tidal floodwater from river middle parts of the river. The water samples were filtered Bhairab. The northern end (upper reach) is also embanked (0.45 Millipore filter) in the field and stored in acid washed to reserve beel Pabla’s water. These interventions practically polypropylene bottles. Cleaning of plastic bottles and plas- accelerated the death of the river. However, the river still tic bags was carried out by soaking in 5% (v/v) HNO for 1 3 Applied Water Science (2018) 8:78 Page 5 of 16 78 24 h and then rinsing with milli-Q water. After collection of dataset provided by SRTM v.4.1 and land use characters water samples, the bottles were securely sealed with proper were obtained from Khulna Development Authority (kDa). labeling (sample number, location name and date). Aeration River cross-sections were taken along 12 chains to calcu- during sampling was avoided as far as possible. The water late Mayur’s water retention capacity. Calculation was done samples were carefully transported to the laboratory and pre- using the trapezoidal volume equation. The adjoining 22 served for chemical analysis. Total analysis was carried out canals and one distributary were not considered for cross- within 15 days of collection. The detail sampling and ana- sectional measurements. lytical methods for the water samples have been described elsewhere (APHA 1992; Ramesh and Anbu 1996). Multivariate analysis Physical measures such as pH, electrical conductiv- ity (EC), dissolved oxygen (DO) and total dissolve solids Pearson correlation analysis for Mayur basin was carried out (TDS) were determined by portable water quality multiprobe to evaluate the relationships between various physiochemi- meter (HACH Hydrolab Multiparameter Sonde 4a) in field. cal parameters, with statistical significance set at p < 0.05 + + Na and K were measured by Flame photometric method and p < 0.01. Hierarchical cluster analysis (HCA) and factor 2+ 2+ (Flame photometer—models PEP 7), and Ca and Mg analysis (FA) were performed to reveal the underlying struc- were determined by titrimetric method (Ramesh and Anbu ture of the dataset by means of distance between variables 1996). HCO was analyzed by potentiometric method while in a multi-dimensional space. Ward linkage with Euclidean Cl was quantified by ion electrode method (Cole-Parmer distance was used for HCA. Principal component analysis 3− 2− R 27502-22, -23). PO and SO were determined by (PCA) with Varimax rotation was used for extraction and 4 4 ascorbic acid method and turbidimetric method, respectively deriving factor derivation in FA. The statistical processes (Thermo spectronic UV–visible spectrophotometers, Helios and their applications are stated elsewhere (e.g., Singh et al. 2− 9499230 45811) and dissolve silica (H SiO ) was analyzed 2004). 4 4 by molybdo-silicate method (Thermo spectronic, UV–vis- ible Spectrophotometers, Helios 9499230 45811) (Ramesh and Anbu 1996). Results Basin delineation and bathymetric survey Spatio‑temporal characteristics of hydrochemistry The Mayur River watershed was divided into three zones A summary of the hydrochemistry of the study area is through integrated watershed delineation using DEM presented in Table 1. Hydro chemical parameters show Table 1 Summary Parameter Pre-monsoon Monsoon Post-monsoon Winter hydrochemical composition of the Mayur River basin DO 3.00 ± 1.28 4.44 ± 2.64 6.21 ± 0.70 4.93 ± 2.35 Water temperature 32.02 ± 2.31 33.71 ± 2.46 28.42 ± 0.77 19.96 ± 1.27 pH 6.78 ± 0.42 7.03 ± 0.27 6.87 ± 0.49 7.19 ± 0.17 Salinity 9.88 ± 3.33 1.11 ± 0.87 0.39 ± 0.05 0.60 ± 0.23 EC 987.50 ± 333.31 2352.54 ± 1965.08 721.92 ± 99.18 1290.58 ± 411.29 Na 575.06 ± 336.67 340.00 ± 422.20 240.14 ± 324.20 218.80 ± 90.87 K 164.27 ± 63.69 21.61 ± 12.79 21.23 ± 11.74 14.93 ± 5.56 2+ Ca 41.21 ± 13.64 73.81 ± 7.40 43.50 ± 4.54 50.26 ± 11.77 2+ Mg 74.35 ± 35.02 51.85 ± 44.63 15.85 ± 5.87 24.36 ± 9.04 Cl 330.87 ± 107.65 641.05 ± 683.81 124.69 ± 25.67 240.77 ± 101.13 HCO 350.32 ± 174.58 334.32 ± 101.53 204.04 ± 41.08 346.38 ± 121.50 2− SO 307.12 ± 209.54 143.85 ± 84.44 22.66 ± 7.55 18.79 ± 7.45 NO 7.34 ± 4.63 2.55 ± 1.03 3.24 ± 2.63 4.70 ± 1.86 3− PO 6.43 ± 6.79 0.33 ± 0.14 1.48 ± 0.76 4.45 ± 2.98 SiO 4.55 ± 1.23 8.27 ± 4.24 4.62 ± 1.23 31.98 ± 18.12 TDS 1861.51 ± 438.22 1617.65 ± 1068.51 681.45 ± 344.19 935.92 ± 322.64 TSS 9749.17 ± 4104.80 1781.67 ± 2284.14 118.33 ± 64.91 2267.08 ± 650.09 Values reported as average ± standard deviation in mg/L except for EC (µS/cm), pH, salinity (ppt) and tem- perature (°C) 1 3 78 Page 6 of 16 Applied Water Science (2018) 8:78 remarkable spatio-temporal differences (p < 0.05). DO, over the full cycle of sampling (C.V. > 50) in the order of 3− 2+ + − + 2+ − Salinity, EC and TDS rise about two orders of magnitude PO > SO > K > Cl > Na > Mg > NO . Gener- 4 4 3 from pre-monsoon to post-monsoon. Of the cation budget, ally abundance of major ions decreases from upper reach + − Na shares the major load (69.7%, averaged over four sea- to lower reach. Except HC O all the major ions show + + sons). Second to Na, K shows highest load (21% of total rising trend towards the discharge point. This confirms the 2+ cationic load) in pre-monsoon, while Ca shares the second strong tidal influence in these sampling stations. highest cationic load in every other season (29.63% in mon- soon, 23.16% in post-monsoon and 14.40% in dry season). 2+ Mg has been found as the least abundant cation. The cati- Major ion composition and correlation + + 2+ 2+ − onic order was found as: N a > K > Ca > Mg. Cl domi- nates the anionic load (43.20%, averaged over four seasons) Pearson correlation was examined among the major ions with an average of 334.34 ± 399.02 mg/L followed by and other physical parameters measured (Table 2). Sig- HCO (39.90%, average 308.78 ± 134.16 mg/L). The mean nificant (p < 0.05) and strong (r ≥ 0.80) cor relations have − − − + + values of Cl and HC O load are nearly equal. HC O load been found between salinity and Na, K , TDS and TSS; 3 3 + + + over total anions vary significantly over seasons, showing an Na and K , and TDS and TSS; K , and TDS and TSS; increasing trend from pre-monsoon (33.58%, median value) and TDS and TSS. Significant (p < 0.05) and moderate towards dry season (59.40%, median value). Beside Cl and (r ≥ 0.60 to < 0.80) correlations have been found between − 2− − HCO , the other most abundant anion is SO (avg. DO and HCO (negative); temperature and SiO (nega- 3 4 3 2 2− 2+ − + 123.11 ± 163.10 mg/L) which also shows a marked tempo- tive); salinity and SO and Mg ; EC with Cl; Na with 2+ 2− + 2+ 2− 2+ − ral variation and decreasing trend on total anion load from Mg and SO; K with Mg and SO; Mg and Cl , 4 4 2− − 3− 2+ pre-monsoon (30.93%, median value 287.79 mg/L) towards SO , TDS and TSS; HCO and PO ; and SO and 4 3 4 4 − − dry season (3.04%, median value 20.22 mg/L). NO and TDS and TSS. While Cl shows very weak (0.088) and 3− PO are least abundant anions found (5.97 ± 2.73 and insignificant (p ≫ 0.05) correlation with salinity, strong + + 5.03 ± 0.35 mg/L, respectively). The anionic order was found to moderate correlation between salinity and N a, K , − − 2− − 3− 2+ 2− as Cl > HCO > SO > NO > PO . Mg and SO suggests that it may originate from the 3 4 3 4 4 Significant spatial variations of major ions may indi- urban wastewater released in the head waters of the river. cate the origin of water chemistry at sub-watershed level As Na significantly ( p < 0.05) and moderately (r ≥ 0.60 2+ 2− 2+ (e.g., Chen et al. 2002). The distribution of physico-chem- to < 0.80) correlated with Mg and SO , while Mg − 2− ical parameters over high tide and low tide separated by is further correlated with Cl and SO , it is most likely + 2+ − 2− head waters and tail waters may give better insight while that Na, Mg, Cl and SO may share the same origin. − 3− investigating possible source of the ions. With tempo- The significant association of HCO and PO (p < 0.01, 3 4 − − ral variation, the major ions also show significant spa - r = 0.627), NO and HCO (p < 0.01, r = 0.458) and 3 3 + + 2+ − 3− tial variation (Fig. 3). Of the major ions Na, K, Mg , NO and PO (p < 0.01, r = 0.407) also indicative soil 3 4 − 2− − 3− Cl, SO, NO and PO show high spatial variation leaching and agricultural runoff. 4 3 4 Fig. 3 Distribution of major ions in Mayur River basin: a spatial distribution from north to south; b overall variations in Box–Whisker’s plot. The figure does not include samples from the adjoining canals 1 3 Applied Water Science (2018) 8:78 Page 7 of 16 78 1 3 Table 2 Pearson correlation matrix for major ion chemical composition and physical parameters in the Mayur River, Khulna, Bangladesh (n = 96) DO pH Salinity EC Na K Ca Mg Cl HCO SO NO PO4 H SiO TDS TSS 3 4 3 2 4 DO 1 pH .335** 1 Salinity − .334** − .092 1 EC .028 .351** .014 1 Na − .260* − .028 .936** − .047 1 K − .323** − .145 .920** − .069 .847** 1 2+ Ca .006 .171 − .220* .547** − .210* − .200 1 2+ Mg − .134 .124 .694** .402** .682** .626** .257* 1 Cl .029 .107 .088 .600** .048 .103 .546** .714** 1 HCO − .702** − .341** − .048 − .026 − .153 .000 .095 − .188 − .029 1 2− SO − .239* − .002 .781** .172 .711** .715** .107 .746** .371** − .118 1 NO − .391** − .311** .287** − .229* .278** .389** − .279** − .005 − .159 .458** .053 1 3− PO − .494** − .394** .162 − .191 .057 .166 − .396** − .097 − .110 .627** − .063 .407** 1 H SiO − .154 .224* − .279** .014 − .250* − .287** .065 − .205* − .086 .321** − .289** .100 .175 1 2 4 TDS − .288** − .028 .942** .045 .986** .861** − .114 .778** .202* − .110 .775** .268** .065 − .249* 1 TSS − .310** .021 .942** .077 .911** .861** − .118 .696** .102 − .039 .720** .287** .117 − .135 .917** 1 Data set includes tidal cycles and seasonal variations over 12 stations *Correlation is significant at the 0.05 level (2-tailed) **Correlation is significant at the 0.01 level (2-tailed) 78 Page 8 of 16 Applied Water Science (2018) 8:78 + + 2+ Fig. 4 a Na /(Na + Ca ) versus total dissolved solids (TDS), after Gibbs (1970); b Piper trilinear diagram (Piper 1944) showing ion composi- tion over the sampling period and K . In winter, data points tend to move slightly towards Water types + + − the salinity apex with additional Na, K and HCO input 2+ 2− and further reduction of Ca and SO . Plotting of TDS concentrations against the weight ratios of Na/(Na + Ca) for the upper Mayur river revealed (Gibbs 1970) that the river water is characterized by a very high Discussion ratio of Na/(Na + Ca) and a high TDS concentration (mostly > 1000 mg/L during winter, pre-monsoon and Mechanisms controlling the major ion chemistry monsoon) (Fig. 4a), typical of evaporation–crystallization dominated rivers. To be further in depth, Piper trilinear Cyclic salts diagram (Piper 1944) of major ion compositions was con- structed (Fig. 4b). The plot shows a cyclic pattern of data Rainwater runoff and ground water discharge are the major association. In pre-monsoon the data points cluster around sources of base flow in the Mayur River. Therefore, cyclic the salinity apex with some exceptions, which are clustered sea salts in the dissolved load of the river is expected to towards high-alkali apex. The data points that cluster around carry the signatures of rainfall and groundwater in the the alkali apex are found as headwater samples. This con- region. Generally, the contribution of cyclic salts to riverine firms presence of high alkali in the headwaters during the dissolved salt loads is expected to decrease with increas- season which causes the excessive salinity as inferred from ing distance from the sea. It has been long established that, Pearson correlation (Table 2). In monsoon most of the data Cl in river waters with no terrestrial sources of the element points move towards the upper mid of the diamond plot indi- declines systematically as a function of increasing distance cating a dilution effect and improving water quality. The + + from the sea (Stallard and Edmond 1981). The reverse has cation plot suggests a reduction of Na and K takes while been found in the Mayur River. Although the basin of Mayur calcium enrichment is taking place. The anion plot also sug- 2− − is small (~ 11 km long river with 52 km basin area) increas- gests a marked reduction in SO with HCO enrichment. 4 3 ing amount of Cl towards the upper reaches is noticeable. In post-monsoon the data points further move down to the While Cl was found as 217 mg/L in the lower reaches of mid of the diamond plot with wide distribution with further − 2− the river (average value of four most downstream stations), addition of HCO and further reduction of SO . Although 3 4 upper reaches show 326.8 mg/L of Cl (average value the cations are found widely distributed, it still indicates a 2+ 2+ + of four most upstream stations). This indicates the high slight reduction of both Ca and Mg and addition of N a 1 3 Applied Water Science (2018) 8:78 Page 9 of 16 78 concentration of Cl in the Mayur River likely to be origi- neither evaporate weathering nor the carbonate weathering nated from either weathering of evaporites or anthropogenic is the dominant process in the basin. + − inputs. However, The 22 drains discharging urban effluents High concentration of Na and Cl in natural waters usu- into the river cancels out the possibility of evaporites being ally indicates halite dissolution which may not be case in − + the major contributing source of Cl in the river and indi- this river basin. In majority of the cases (~ 66%) Na has − + cates that the source of water in river Mayur is mostly urban been found comparatively lot higher than Cl as the N a / waste rather than rainfall and groundwater discharge. Cl ratio shows an average of 2.71. This cancels out the dominance of halite dissolution and suggests possible ion- exchange process, if not the presence of silicate weathering, Weathering which in this case has been proved as less dominant earlier. This cation exchange process involves excess N a input by The Piper trilinear plot (Fig. 4b) demonstrates significant the city wastewater lines. variation in water types over the year. From winter towards pre-monsoon data points cluster more towards the salinity Ion exchange + − apex (Na-SO type), while Na and Cl remain more or less 2− + same for the both cases but SO increases in the pre-mon- As depicted in Fig. 6a, the N a concentration of most the soon compared to the winter samples. In the cations trilinear samples (66.66% of total) scattered above the seawater line, plot, data points move more towards the Na apex from winter which suggests excess Na enrichment in the Mayur waters + + − + to pre-monsoon suggesting additional Na discharge to the except in monsoon (N a /Cl = 0.96). This excess N a might dissolved load. In the anion plot, while data points cluster be influenced by cation exchange process. To further inves- − 2− around high HC O and low SO in winter, pre-monsoon tigate the occurrence of cation exchange reactions in the 3 4 2− − is marked with SO enrichment replacing HC O . This studied waters, a Na–Cl versus Ca + Mg – (HCO + SO ) plot 4 3 3 4 exhibits the effect of lack of rainfall in winter followed by was constructed (Fig. 6b). Apart from cation exchange the 2+ 2+ pre-monsoon, consequently increasing the pollution effect, most likely additional sources of Ca and Mg in natural as HCO concentration does not change much (med. value waters are Calcite, dolomite, gypsum and anhydrite weather- 394 mg/L in winter and 312 mg/L in pre-monsoon) but ing. While plotting the diagram, the lithogenic N a available 2− + − SO concentration increases from 20.22 mg/L in winter for exchange is calculated from N a to Cl as it is assumed (median value) to 287.78 mg/L in pre-monsoon (median that the meteoric Na should be balanced by equivalent con- value). In monsoon and post-monsoon, in contrast to that of centration of Cl (Nkotagu 1996). Again, possible contri- 2+ 2+ winter and pre-monsoon, data points float widely in the mid- bution of Ca and Mg from Calcite, dolomite, gypsum 2+ 2+ dle of the diamond plot. However, in monsoon, a reduction and anhydrite dissolution lo lithogenic Ca and Mg are + 2+ of Na and enrichment of Ca is noticed, indicating a dilu- accounted for by subtracting the equivalent concentrations − 2− tion eec ff t. Post-monsoon data points show wide and variant of HCO and S O (Nkotagu 1996). Figure 6b suggests 3 4 + 2+ 2− + combination of N a, Ca and SO suggesting infrequent the excess Na in pre-monsoon and winter season may be + 2+ 2+ freshwater mixing with pollution caused by irregular and due to cation exchange of N a replacing Ca and/or Mg . but intense rainfall. Wide distribution of data points in the trilinear plot indi- Water quality cates the influence of anthropogenic activities in the dis- solved load rather than weathering effects. The concentra- The TDS–TH ratios indicate water quality changes over time tion ratio of HCO :Cl + SO :SiO has been found as 31:36:1 from hard brackish water in pre-monsoon to mostly hard 3 4 2 in the dissolved load and the correlation between SiO and fresh water in all other seasons confirming dilution effect in 2+ + − 2− Ca, K, HCO and SO are negative and very weak wet period. If only TDS is accounted for 58.33% of the sam- 3 4 (< |0.3|) but significant (Table 2). This suggests that silicate ples fall in permissible limit for drinking water, all of which weathering plays a less important role in determining major are found in monsoon and post-monsoon season (Table 3). ions for the whole basin. Again, most of the data point fall According to the irrigation water classification based on below the equiline of HC O /Cl + SO (Fig. 5a) and HC O / the Sodium Absorption Ratio (SAR), most of the samples 3 4 3 Na + K (Fig. 5b) and cluster around the equiline of HCO / (64.58%) fall in poor category indicating poor water quality Ca + Mg (Fig. 5c) indicating that the weathering of carbon- along the river. However, ~ 66% of the samples in monsoon ates and/or evaporites cannot explain the whole composition fall in excellent to good category suggesting improvement in 2+ 2+ of Ca and Mg in the water. While most of the data points water quality in the monsoon. The EC-based classification fall below the isometric line of Ca + Mg/Na + K (Fig. 5d) further show that 93.75% samples fall in good to permis- and Cl + SO /Na + K (Fig. 5e), almost all data points cluster- sible category during monsoon. No sample was found as ing above the Cl + SO = Ca + Mg line (Fig. 5f) indicate that excellent quality. 1 3 78 Page 10 of 16 Applied Water Science (2018) 8:78 (b) (a) 70 0 0 0 10 20 30 40 50 60 70 80 0 10 20 30 40 50 60 70 (c) (d) 0 5 10 15 20 0 10 20 30 40 50 60 70 (e) (f) 70 70 50 50 40 40 10 10 0 10 20 30 40 50 60 70 80 0 10 20 30 40 50 60 70 80 Fig. 5 Proportion of the major ions in the waters of Mayur River. The black blank circles denote pre-monsoon, black filled circles denote mon- soon, green blank circles denote post-monsoon and green filled circles denote winter Fig. 6 Bivariate plots of the studied samples showing relationship between a Cl versus Na and b Na–Cl versus Ca + Mg − (HCO + SO ) 3 4 1 3 Applied Water Science (2018) 8:78 Page 11 of 16 78 Table 3 Drinking water and Category Grade Samples (%) irrigation water quality of Mayur River basin Sodium absorption ratio (SAR) (meq/L) (Richards 1954) Excellent < 10 6.2 Good 10–18 20.8 Fair 19–26 8.4 Poor > 26 64.6 Total dissolved solid (TDS) (mg/L) (Davis and DeWiest 1966) Desirable for drinking < 500 7.2 Permissible for drinking 500–1000 51.1 Useful for irrigation 1000–3000 39.6 Unfit for drinking and irrigation > 3000 2.1 Electrical conductivity (EC) (µS/cm) (Raghunath 1987) Excellent < 250 0 Good 250–750 24 Permissible 750–2000 69.8 Doubtful 2000–3000 1 Unsuitable > 3000 5.2 Table 4. Four factors were extracted using Principal Compo- Land use signatures on water nent Analysis (PCA) based on the condition “eigenvalue > 1” explaining 79.99% of the total variation. Factor 1 explains Multivariate techniques were applied to investigate the 38.10% of the variation and has strong loading (≥ 0.75) major land use sources of ion chemistry in the river. For this + + 2+ 2− on Salinity, TDS, TSS, Na, K, Mg and SO . Since analysis, only river water samples were considered, since weathering effects are not strong in the river basin except the adjoining canals bring area specific discharges to the land runoff and the river is dead at its source, this factor river. The results of Factor Analysis (FA) are presented in Table 4 Varimax rotated factor Factors Communality loading matrix from principal component analysis of physical Factor 1 Factor 2 Factor 3 Factor 4 parameters and major ions DO − .244 − .810 − .094 .014 .725 (n = 96) Water temperature .329 − .055 .317 − .781 .821 pH .074 − .562 .253 .558 .697 Salinity .963 .126 − .061 − .138 .966 EC .051 − .114 .816 .076 .687 Na .960 .019 − .108 − .086 .940 K .898 .179 − .092 − .166 .874 2+ Ca − .170 − .063 .832 − .054 .728 2+ Mg .772 − .082 .528 − .083 .888 Cl .174 − .034 .833 − .082 .732 HCO − .160 .912 .120 .110 .883 2− SO .800 − .009 .272 − .228 .766 NO .263 .606 − .279 .065 .519 3− PO .053 .764 − .231 .107 .651 SiO − .193 .244 .060 .861 .841 TDS .972 .056 .032 − .100 .959 TSS .953 .101 .004 .037 .919 Variance explained (%) 38.109 20.064 12.710 9.103 Total variance explained (%) 79.985 Four components were extracted using Eigenvalue > 1. Bold type face indicates strong loading (≥ 0.75) and italic type face indicate moderate loadings (0.50 ≥ , ≤ 0.75) 1 3 78 Page 12 of 16 Applied Water Science (2018) 8:78 2+ − can be explained as the anthropogenic factor, most likely strong positive loading on EC, Ca and Cl with moderate 2+ the urban influence. Figure 6 presents a spatial distribution positive loading on Mg . This is likely to be the effect of of the factor coefficients along the river. This distribution tidal influence in river during the wet season (Fig. 7). The suggests head waters of the river show high factor 1 coef- fourth factor has a strong negative loading on water tem- ficients which is most populous part of basin. The second perature and strong positive loading on SiO with moderate factor explains 20.06% variation in the data and exhibits positive loading on pH explaining 9.10% of the total varia- − 3− strong positive loading on HCO and PO and strong tion explained. Naturally pH is inversely related with SiO 3 4 2 negative loading on DO and moderate (≥ 0.50 ~ ≤ 0.75) which has been found reverse in this case. Therefore, it can positive loading on N O and moderate negative loading be assumed that, this factor explains the massive construc- on pH. This may represent the agricultural/soil runoff sig- tion works involving the use of silica that is taking place nature. Agricultural activities are known to have a major alongside the river mostly during winter (or dry season). impact on hydrochemistry of streams. The use of N and P The values of SiO found in the river over the seasons sup- fertilizer is common in the Mayur river basin as more than port this theory as in winter SiO in the water samples are 60% of the total basin area falls under agricultural land use. found as 23.55 mg/L (median value) while in pre-monsoon, NO was found as high as 5.97 and 5.05 mg/L (median monsoon and post-monsoon corresponding avg. values are 3− value) in pre-monsoon and winter, respectively. PO was 4.18, 7.3 and 4.32 mg/L, respectively (Fig. 7). found as 5.02 and 4.94 mg/L (median value) in the same The HCA was performed based on the major cations, seasons reported earlier compared to 0.35 and 1.04 mg/L in major anions and the physical parameters, which produced monsoon and post-monsoon, respectively. This indicates the three main clusters (Fig. 8a). Interestingly, the clusters give seasonality of the agricultural practices in the basin, as the a clear indication of changing water quality and dominant winter rice called Boro is cultivated around these seasons. land use types running along the river. First five sampling Figure 7 reveals a peak of factor 2 in the middle reaches of stations fall in cluster 1 which are located in the upstream the river where agricultural activities are concentrated. A and dominated by urban land use. The last three stations at third factor explains 12.70% of the data variation and has a the downstream are clustered together and are dominated Fig. 7 Spatial distribution of the factors extracted from factor analysis C4 winter, HT high tide, and LT low tide. Station 1 represent head (FA). F1–F4 denote the four factors extracted, C1–C4 denote sam- waters while station 12 indicate tail waters with tidal influence pling cycles where C1 pr-monsoon, C2-monsoon, C3 post-monsoon, 1 3 Applied Water Science (2018) 8:78 Page 13 of 16 78 Fig. 8 Land use signature in Mayur river water: a dendrogram pro- land use. Elements that plot above the x-axis have higher concentra- duced from hierarchical cluster analysis (HCA) showing distinct and tions while elements that plot below the x-axis have lower concentra- dominant land use sites; b Spider diagram showing biogeochemical tions in the cluster sites than in the reference sites fingerprints (log normalized to different land uses) of anthropogenic by agriculture. The third cluster represents four sampling agriculture versus mixed cluster shows higher concentra- + + 2+ stations located in the middle reach of the river organized tion (y > 0) of DO, Na, K, Mg and TDS and lower − − 3− among two sub-clusters indicating a mix of the two domi- concentration (y < 0) of salinity, EC, C l, NO, PO , 3 4 nant land use types, urban and agriculture. However, inter- SiO and TSS. estingly, the major two land use dominated clusters (agricul- The spider diagram reveals that mixing of urban waste- ture and urban) are grouped in one mother cluster while the water leads to higher rate of decreasing DO in streams mixed land use show a very different mother cluster. Thus compared to the agricultural environment. Also, it is it illustrates how characteristically distinct an agricultural clear that urban waste water tends to increase salinity runoff and urban wastewater might be, but the mixture of and conductivity in stream water than that of agricultural two can be far different from their original characters. environment. Agricultural runoff is expected to naturally The behavior of the hydrochemical variables of each of produce more N and P products along with lesser amount these clusters is further investigated by developing biogeo- of sodium and potassium compared to the urban streams. chemical fingerprints (Fig. 8b). For each cluster, values of This study shows the other way around. Possible explana- the variables are averaged over sites that fall within the clus- tion for this reverse result can be the influence of shrimp ter and then fingerprints are developed by plotting spider farm end-products in the agricultural sites. There are sev- diagrams with the log of the ratio of the median value for eral shrimp production ponds around the agricultural sites each variable in the cluster of interest to the median value that discharge their waste directly into the river. Shrimp for sites in the reference cluster (Wayland et al. 2003). In this farms are well known for using NaCl and KCl to reduce + + spider diagram, points derived from cluster of interest that crop mortality, thus enriching wastewater with Na, K are plotted on the x-axis (where y = 0) refer to no difference and Cl . In this case, the agriculture dominated sites of the + + − from the reference cluster. The points that plotted over the Mayur River are also rich in Na, K and Cl and show x-axis (y > 0) indicate higher concentration in the ‘interest higher concentration of these ions compared to the mixed cluster’ than that of the ‘reference cluster’ and vice versa. water zone (sampling station 6, 7, 8 and 9). This explana- First, urban cluster was investigated using the agricul- tion is supported by the fact that the average concentra- + + + + tural cluster as reference. DO, N a and K is found as low tion of Na and K at the urban, mixed and agricultural 2+ − − in the urban cluster while Salinity, EC, Ca, Cl, HCO , sites in the river are 278.04 and 18.96, 166.73 and 15.22, − 3− NO, PO, SiO and TSS is found as high in concen- 339.17 and 38.24 mg/L, respectively. The sharp increase 3 4 2 + + tration. These findings are not consistent with available of average N a and K in the agricultural sites indicates previous researches (e.g., Wayland et al. 2003; Fitzpatrick the strong influence of shrimp waste in the river. Increase + + 2+ 2+ − 2− and Long 2007) as they found higher amount of Na, K of Ca, Mg, Cl and SO towards the tail waters of 2− and SO in urban streams compared to the agricultural the river where the agricultural sites are found, also are streams. The log of urban cluster versus mixed cluster sug- indications of the presence of shrimp farm end-products gests, most of parameters have higher concentration in the in water. urban cluster except DO. Again, the log of the ratio of 1 3 78 Page 14 of 16 Applied Water Science (2018) 8:78 Supply and Sewerage Authority (KWASA) is only lim- Conclusions ited to 14 million gallons per day based on groundwater extraction only. A sharp decline of groundwater table in The tidal and ephemeral nature of the Mayur river shows dry season during recent years is contributing a large cut- significant physico-chemical and spatio-temporal varia- off in this water supply. Currently KWASA supplements tions and characterized with excessive amount of TDS, + − 2− supply water from a small open lake after treatment. If Na, Cl and SO during winter and pre-monsoon but river Mayur is properly restored through excavation and shows dilution effect during the rainy season. Major ion implementation of IWRM policies adopted by Bangladesh composition is mainly controlled by two types of anthro- government (see Dewan et al. 2015; Gain et al. 2017; Roy pogenic activities: urban wastewater production and agri- et al. 2017 for a comprehensive review and adoption of cultural activities. Weathering effects are weak in the the current IWRM policies), a 5% withdrawal of the river stream, although effects of soil leaching and runoff are evi- water per day (~ 35–40 million gallons) may contribute dent. Evidences suggest water quality of the river greatly to reduce the current and future gap between supply and improves during monsoon and post-monsoon and become water demand in the region. Although a deeper insight to favorable for irrigation purposes. The piper trilinear dia- the groundwater-surface water recharge and interaction is gram also indicates that with rainfall, pollution effects are required before making such decisions, the recent increase diluted and the river water becomes more usable (e.g., for of annualized precipitation trends in the region (Hos- irrigation purpose). HCA and FA performed on the river sain et al. 2014) presents an opportunity to consider this water samples depicted three distinct water groups based ephemeral embanked river as a water reservoir in future. on major ion composition; urban wastewater, agricultural The Government of Bangladesh (GoB) has recently (year runoff and mixed water. However, compared to the pre- 2017) adopted the Bangladesh Delta Plan 2100 (draft) that vious researches (e.g., Wayland et al. 2003; Fitzpatrick addresses the nation-wide water challenges through a “hot- et al. 2007; Yu et al. 2016), these urban waste water and spot specific’ issues and strategies (Bangladesh Delta Plan agricultural runoffs showed a little difference in ion com- + + 2017). These issues include coastal flooding and salin- position. Unusual high concentration of Na and K and − 3− ity problem and water shortage, drainage and sanitation low concentration of N O and PO in the agricultural 3 4 problem in urban areas. This study is expected to feed stream compared with the urban wastewater reflects the the information channel for the scientific, political and presence of shrimp farm end-products in the agricultural other concerned communities to consider possible oppor- sites. Except this, a decrease of DO and increase in salin- tunities of using the river as source of water supply for ity, EC and TSS is noticed in the urban streams. Drawing the city thus contribute to strategic interventions in the from the analysis and interpretation of major ion chemis- coastal urban regions planned by the Bangladesh Delta try, land use is likely to be the key factor in controlling the Plan (BDP). water quality of the studied river where amount of rainfall on the basin is a determinant of “improvement”. Acknowledgements This study was supported by the project titled Despite some tidal influences at the lower reaches, the “Water Security in Peri-Urban South Asia: Adapting to climate change river is considered dead for last few decades and now and urbanization” funded by IDRC, Canada. We thank Mr. Shankar serves as a major supplement for the city drainage sys- Kumar Das for their laboratory assistance. We also like to acknowledge Mr. Kazi Rifat Ahmed for his assistance in preparing the map used in tem. The southwest region, especially Khulna, the third this paper. largest metropolitan city of Bangladesh, is suffering from a sharp decline in dry season ground water table (Fig. 1) Author contributions KR: Planned and managed the study, made for last couple of decades (Roy et al. 2017). Since the interpretations and authored the manuscript: MRK, FA, MSI and KA: river’s water quality gets usable during the rains, it is Took part in planning process, did field work and laboratory analysis, assisted in writing manuscript; MMR, DKD and MSAK: Involved in possible that through restricting municipal and indus- planning process, reviewed and commented on manuscript. trial wastewater discharge and adapting proper Integrated Water Resource Management (IWRM) system addressing Open Access This article is distributed under the terms of the Crea- land use management system, river Mayur can be used tive Commons Attribution 4.0 International License (http://creat iveco as surface water reservoir for the city. Our bathy survey mmons.or g/licenses/b y/4.0/), which permits unrestricted use, distribu- tion, and reproduction in any medium, provided you give appropriate showed that Mayur can retain ~ 725 million gallon water credit to the original author(s) and the source, provide a link to the with its current capacity, which would extend to least 2.5 Creative Commons license, and indicate if changes were made. times after excavation and restoration. By 2030 with an estimated 1.62 million people residing in Khulna city would demand 112 million gallons of supply water per day. The present water supply capacity of Khulna Water 1 3 Applied Water Science (2018) 8:78 Page 15 of 16 78 Huang J, Li Q, Huang L et al (2013a) Watershed-scale evaluation for References land-based nonpoint source nutrients management in the Bohai Sea Bay, China. Ocean Coast Manag 71:314–325. htt ps ://doi. 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