Prediction of Groundwater Dynamics for Sustainable Water Resource Management in Bogra District, Northwest Bangladesh

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Article Prediction of Groundwater Dynamics for Sustainable Water Resource Management in Bogra District, Northwest Bangladesh

Mohammad Hasanuzzaman 1,2, Xianfang Song 1,2,*, Dongmei Han 1,2, Yinghua Zhang 1 and Shakir Hussain 1

1 Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; [email protected] (M.H.); [email protected] (D.H.); [email protected] (Y.Z.); [email protected] (S.H.) 2 University of Chinese Academy of Sciences, Beijing 100049, China * Correspondence: [email protected]; Tel.: +86-10-6488-9849

Academic Editor: Xiangzheng Deng Received: 20 November 2016; Accepted: 24 March 2017; Published: 28 March 2017

Abstract: The green revolution in the northwest region of Bangladesh over the past three decades has based on groundwater irrigation. For sustainable agricultural accretion, groundwater dynamics play a vital role in this region. In this study, the groundwater level dynamics have been analyzed with a model named “MAKESENS” and with geographical information systems (GIS). The study indicates that, in most of the wells, the water table (WT) depth and the rainfall intensity are declining slowly. The prediction of WT depth during the period of 2020, 2040, and 2060 indicate that, in some cases, the WT depth will approximately double by the year 2060, considering the present declining trend. This result suggests that, for the sustainable management of groundwater, necessary measures should be adopted to avoid or reduce the severe ecological, social, and economic impacts of groundwater mining. Moreover, crop diversiﬁcation, conservation techniques, increasing irrigation efﬁciency, rainwater harvesting, etc. can be adopted to avoid groundwater declination and consequently to enhance the sustainable use of groundwater resources in the area.

Keywords: groundwater dynamics; MAKESENS model; sustainable water use; water table depth; Bangladesh

1. Introduction Groundwater is an important resource serving as a reliable source of water for irrigation, and domestic and industrial purposes in many countries. The growth of population, food insecurity, rising economies, and poor water management are putting unusual pressure on the world’s freshwater resources [1]. Due to the lack of surface water resources, groundwater is the most essential prerequisite for increasing crop production, as well as for the sustainable agricultural development. In many areas of the world, irrigation is critical to food security and groundwater use has increased to become a major source for irrigation water, especially in China and South Asia [2,3]. Bangladesh, though, is blessed with abundant groundwater resources, but not unlimited. A large quantity of groundwater is being pumped each year, mainly for irrigation, and domestic and industrial uses, through different water lifting devices. Availability of groundwater for irrigation has contributed to a manifold increase in crop productivity in Bangladesh. Over the past few decades most of the rivers and canals of the region have dried up during the dry season and the people switched their water supply from surface to groundwater [4–6]. The main supply of groundwater for irrigation is

Water 2017, 9, 238; doi:10.3390/w9040238 www.mdpi.com/journal/water Water 2017, 9, 238 2 of 17 from shallow tube-wells (STW), the numbers of which have grown from around 100,000 in the early 1980s to more than 1.5 million today [7]. Over-extraction of groundwater for irrigation, industrial, and domestic purposes during the dry season, has quickened the groundwater level depletion in such a way that, in some points, it is not fully recharging during the rainy season. The northwest part of Bangladesh, the Barind Tract, located mostly in the greater districts of Rajshahi, Bogra, and Dinajpur, have a gross area of 7727 km2 [8]. Long-term (1981–2013) average annual rainfall of Bogra district is about 1754 mm, while the national average is about 2300 mm. The national water policy of the Bangladesh government inspired groundwater development for irrigation both in the public and the private sectors. Groundwater irrigation has probably been developed in Bangladesh agriculture since the 1980s. The groundwater-based irrigation project in the area, named as the Barind Multipurpose Development Authority (BMDA), has accelerated the use of groundwater, installing deep tube wells (DTWs) in 1986. In addition, STWs are also installed by the private sectors for the exploitation of groundwater for irrigation. Within the crop sector, food production is dominated by irrigated Boro rice. The use of groundwater in this region is much higher compared to other parts of the country due to the lack of surface water resources and major irrigated agricultural sites of the country. In some parts of the country, farmers have been forced to replace their suction mode pumps with submersible pumps because of the continuous decline in groundwater levels. The groundwater level is declining due to overuse of groundwater [9–11]. Overexploitation of groundwater has been reported for some parts of Pakistan [12], India [13], Sri Lanka [14], and China [3]. WT depth is also declining owing to climatic factors, especially rainfall [15]. This decline happens due to insufficient recharge, which is caused by lower rainfall than that of the other regions of the country and its erratic distribution throughout the year. In order to improve and utilize groundwater resources reasonably, and formulate water managing and protecting policies for government, it is important to conduct research on groundwater resource evaluation and groundwater environmental protection. Devlin and Sophocleous [16] mentioned that sustainability of groundwater is a function both of recharge and pumping. Groundwater management practices should be used in a sustainable manner to maintain them for future generations [17]. Alley and Leake [18] defined sustainable groundwater yield as the use of groundwater in a manner that can be maintained for a long time without causing unfavorable environmental, economic, or social consequences. A number of researchers have studied the WT depth dynamics and its long-term trend based on the MAKESENS model for the northeastern Mymensingh district [9], the northwestern Rajshahi district [11], and the Chapai-Nawabganj, Naogaon, and Rajshahi districts [19] of Bangladesh. All of them, except for [11], have not addressed the confidence level of their trend test and residual distribution for the Sen’s slope, nor have any of them even shown a long-term future rainfall projection. For the sustainable use of the resource, the groundwater level dynamics of the region, the present trend and future scenario would be useful in future planning of groundwater use in the region. The objectives of the study are: (i) to analyze the historical dynamics of groundwater level; (ii) to predict the groundwater level for the future using computer software “MAKESENS” and (iii) to realize sustainable groundwater use in the region.

2. Materials and Methods

2.1. Site Description The study area is characterized by two distinct land forms: the undulating Barind tract and the floodplains which are mainly occupied with Pleistocene deposits [20]. Geographically, this region is lying between 88◦200 to 89◦300 E and 24◦200 to 25◦350 N. The Barind area is floored by Madhupur clay. The present study is based on part of a configuration of three greater districts of the Barind tract (Bogra district, which has an area of 2919.9 km2, situated between 89◦220 E and 24◦510 N, comprised of 11 sub-districts called “Upazila”). A location map of the study area is shown in Figure1. Water 2017,, 9,, 238 238 33 of of 17 17

FigureFigure 1. LocationLocation of of the the study area and groundwatergroundwater monitoring wells. The The orange orange dotted dotted line representsrepresents the lithological cross section (Figure 2 2).).

The long-term (33 years) WT depth data, from 1981 to 2013, were collected from the Bangladesh The long-term (33 years) WT depth data, from 1981 to 2013, were collected from the Bangladesh Water Development Board (BWDB). In the area, 27 observation wells have been in use for Water Development Board (BWDB). In the area, 27 observation wells have been in use for groundwater groundwater level monitoring. The number of observation wells with elevation and coordinates level monitoring. The number of observation wells with elevation and coordinates under each Upazila under each Upazila is given in Table 1. For more than 33 years monthly meteorological data were is given in Table1. For more than 33 years monthly meteorological data were collected from the collected from the Bangladesh Meteorological Department (BMD) situated in the study area. The Bangladesh Meteorological Department (BMD) situated in the study area. The long-term data of the long-term data of the irrigated area are mainly covered by STW with a 5–10 cm diameter, extracting irrigated area are mainly covered by STW with a 5–10 cm diameter, extracting water with a centrifugal water with a centrifugal pump, and DTW, with a 15–20 cm diameter, operating with a submersible pump, and DTW, with a 15–20 cm diameter, operating with a submersible turbine pump. Information turbine pump. Information about the irrigated area, as well as the major crop production area, has about the irrigated area, as well as the major crop production area, has been collected from the been collected from the Bangladesh Bureau of Statistics (BBS). Data were analyzed using Bangladesh Bureau of Statistics (BBS). Data were analyzed using MAKESENSE model [21] software, MAKESENSE model [21] software, Origin lab 9.0, and MS Excel. Additionally, Arc GIS 10.1 software Origin lab 9.0, and MS Excel. Additionally, Arc GIS 10.1 software was used for image processing. was used for image processing.

Water 2017, 9, 238 4 of 17

Table 1. Well numbers under different Upazilla of Bogra district used for the study.

No. Upazila (Sub District) Well No. Elevation (m) Longitude (◦) Latitude (◦) GT1006001 17.22 89.08 24.81 1 Adamdighi GT1006002 15.65 89.00 24.81 GT1006003 15.24 89.12 24.77 GT1020004 15.80 89.34 24.89 GT1020005 18.96 89.39 24.93 2 Bogra Sadar GT1020006 16.98 89.36 24.79 GT1020007 17.40 89.41 24.86 3 Dhunot GT1027008 15.21 89.58 24.74 4 Dupchanchia GT1033009 19.06 89.15 24.89 GT1040010 15.87 89.51 24.82 5 Gabtali GT1040011 17.60 89.43 24.96 GT1040012 16.67 89.45 24.87 GT1054013 16.67 89.25 24.86 6 Kahalu GT1054014 17.40 89.26 24.79 7 Nandigram GT1067015 14.26 89.22 24.71 GT1081016 16.55 89.62 24.83 GT1081017 17.04 89.60 24.89 8 Sariakandi GT1081018 15.75 89.64 24.94 GT1081019 17.60 89.57 24.94 GT1081020 17.23 89.63 24.79 GT1088021 17.22 89.39 24.62 9 Sherpur GT1088022 15.91 89.45 24.66 GT1088023 15.77 89.38 24.68 GT1094024 19.91 89.26 24.98 10 Shibganj GT1094025 20.58 89.32 25.06 GT1095026 17.90 89.49 25.01 11 Sonatola GT1095027 18.26 89.54 25.01

2.2. Physiography and Hydrogeological Conditions The topography of the region is characterized by two distinguished landforms: (a) the Barind area, which has irregular topography, and (b) the floodplains. The elevated Barind area is characterized by less infiltration due to clayey and semi- to impermeable Barind clay with excessive surface runoff. Morpho-stratigraphically, the Barind area is subdivided into three geological units: (1) Barind clay residuum overlies and developed on Pleistocene alluvium; (2) Holocene Ganges flood-plain alluvium; and (3) active channel deposits of the Ganges and major Tributaries (modern alluvium). The subsurface lithology covers alluvial sand, alluvial silt, Barind clay residuum, and Marsh clay and peat. Hydrogeological, the area is comprised of semi-impervious recent-Pleistocene clayey silt aquitard (thickness 3.0–47.5 m) which overlays a single- to multiple-layered (2–4) aquifer system of Plio-Pleistocene age (thickness 5.0–42.5 m) [22]. Moreover, for the study region, a recent study [23] identified that the subsurface lithology is composed of mostly clay to silty clay (~10 m) at the upper-most layer and fine to coarse sands, downward (Figure2).

2.3. Climatic Behavior of the Region The annual rainfall from 1981 to 2013 in the study area varies from 1106 to 2601 mm. It also delineates regular positive and negative anomalies over time, as shown in Figure3. The ratio of rainfall from May to September with the total annual rainfall is approximately 84%. The yearly rainfall ﬂuctuates considerably, with mean, standard deviation, and a coefﬁcient of variation of 1754 mm, 399 mm, and 23%, respectively. Long-term monthly average maximum temperature varies from 23 to 35 ◦C and average minimum temperature varies from 10 to 26 ◦C. The long-term average relative humidity varies from 34% to 74%. Water 2017, 9, 238 5 of 17 Water 2017, 9, 238 5 of 17 Water 2017, 9, 238 5 of 17

Figure 2. Lithological cross section of the study area. FigureFigure 2.2. Lithological cross sectionsection ofof thethe studystudy area.area.

Figure 3. (a) Long-term rainfall pattern (b) Mean annual rainfall deviation and (c) Long term seasonal rainfall variation in the study area.

Figure Figure 3.3.( a()a Long-term) Long-term rainfall rainfall pattern pattern (b) Mean(b) Mean annual annual rainfall rainfall deviation deviation and (c) and Long (c term) Long seasonal term rainfallseasonal variation rainfall variation in the study in the area. study area.

Water 2017, 9, 238 6 of 17

2.4. WT Dynamics The long-term patterns of WT depth are presented graphically to explain the dynamic behavior of the groundwater level. Several methods have been applied for analyzing the trend of meteorological and hydrological data, including parametric (linear regression) as well as non-parametric approaches. Widely used has been time-series analysis, such as the Mann–Kendall trend test and Sen’s slope estimator in hydrological analysis [19,24–26]. To detect and estimate the simulated trends of the maximum WT depth, the “MAKESENS” software was used [9], which is based on the non-parametric Mann–Kendall test for trends and the non-parametric Sen’s method for the magnitude of the trend [21]. The Mann–Kendall trend test is a rank-based non-parametric test originally developed for non-correlated data. Not only can it detect any possible trend in temperature or hydrological series, but it can also test whether such trends are statistically signiﬁcant or not. This test checks the null hypothesis of no trend versus the alternative hypothesis of an increasing or decreasing trend. Moreover, this test does not require that the data ﬁt a normal distribution. More generally, nonparametric tests require less restrictive assumptions about the data. Another important reason for these tests is that they allow for the analysis of categorical as well as ranked data. It is important to note that, even with metric data, if assumptions are badly violated, nonparametric tests are likely to be employed. The advantage of non-parametric method is that it is applicable for monotonic trend, and there is no problem with the missing data. The model also exploits both the so-called S statistics and Z statistics (the normal approximation) given by [27]. For time series with fewer than 10 data points, the S test is used; for time series with 10 or more data points, the Z test is used. When the data values xi of a time series can be assumed to obey the following model (Equation (1)), the Mann–Kendall test is valid: xi = f (ti) + εi (1) where f (t) is a continuous monotonic increasing or decreasing function of time and the residuals εi can be assumed to be from the same distribution with a zero mean. In case of data values <10, the number of annual values in the studied data series is denoted by n and the Mann–Kendall test statistic (S) is calculated as

n−1 n S = ∑ ∑ sgn(xj − xk) (2) k−1 j−1 where xj and xk are the annual values in years j and k, respectively, (j > k), and   1 if xj − xk > 0 sgn xj − xk =  0 if xj − xk = 0  (3)   −1 if xj − xk < 0 When the value of n is 9 or less, the absolute value of S is compared with the theoretical distribution of S derived by Mann and Kendall [27]. In MAKESENS the tested signiﬁcance levels α are 0.1, 0.05, 0.01, and 0.001. Further details in relation to the MAKESENS software can be found in [21]. The WT depths were projected [9] as WT depth (m) = B + Q × (Simulation year − Base year) (4) where B is the intercept, and Q is the slope of the trend line, the projections were made for the years 2020, 2040, and 2060. The year 1981 was considered as the base year.

3. Results of the Historical Data Analysis

3.1. Impact of Irrigation Equipment on Crop Area In the Barind area, different irrigation equipment has been introduced significantly in order to fulfill the increasing demand for food production as well as for the deficit of rainfall in during the dry Water 2017, 9, 238 7 of 17 Water 2017, 9, 238 7 of 17 3. Results of the Historical Data Analysis 3.3.1. Results Impact ofof theIrrigation Historical Equipment Data Analysison Crop Area Water3.1.2017 ImpactIn, 9the, 238 ofBarind Irrigation area, Equipment different onirrigation Crop Area equipmen t has been introduced significantly in order7 to of 17 fulfillIn the the increasing Barind area, demand different for irrigationfood production equipmen as twell has asbeen for introducedthe deficit ofsignificantly rainfall in induring order the to fulfilldry season. the increasing This is demand because for of food liberalization production ofas wellgovernment as for the policy deficit (1979) of rainfall on inprocurement, during the season. This is because of liberalization of government policy (1979) on procurement, installation, and dryinstallation, season. andThis managementis because ofof liberalizationirrigation equipment of government [28]. Therefore, policy (1979)after the on 1980s,procurement, farmers management of irrigation equipment [28]. Therefore, after the 1980s, farmers installed a large number installation,installed a largeand managementnumber of STWs of irrigation and DTWs equipment indiscriminately [28]. Therefore, for obtaining after thehigher 1980s, production, farmers of STWs and DTWs indiscriminately for obtaining higher production, owing to achieving the goal of installedowing to aachieving large number the goal of STWsof food and security. DTWs Especially,indiscriminately farmers for grow obtaining Boro ricehigher during production, the dry food security. Especially, farmers grow Boro rice during the dry season, which requires 0.4–1.5 m of owingseason, to which achieving requires the 0.4–1.5goal of mfood of irrigationsecurity. Especially,which is almost farmers completely grow Boro groundwater-fed rice during the [29].dry irrigationseason,Approximately which isrequires 4.2 almost million 0.4–1.5 completely ha of m land of groundwater-fedirrigation is irrigated which by groundwater, is [29 almost]. Approximately completely whereas onlygroundwater-fed 4.2 million 1.03 million ha of ha[29]. land is is irrigatedApproximatelyirrigated by by groundwater, surface 4.2 million water whereas ha [30]. of land onlyContinually is 1.03 irrigated million incr byeasing ha groundwater, is irrigated patterns bywhereasof surfaceirrigated only water area 1.03 [ 30 undermillion]. Continually major ha is increasingirrigatedirrigation patterns byequipment surface of irrigated (STWwater and[30]. area DTW) Continually under during major 1980incr irrigation easingto 2010 equipment patternsis shown of in (STW irrigatedFigure and 4. DTW)Thearea irrigated under during major areas 1980 to 2010irrigationby ismajor shown equipment in Figure (STW4(STW. The andand irrigated DTW) DTW) areasduring are almost by 1980 major to12,000 2010 equipment andis shown 10,000 (STW in haFigure and in DTW)1980 4. The and are irrigated increased almost areas 12,000 to andbyaround 10,000 major 275,000 haequipment in 1980 and 102,000 and (STW increased ha,and respectively, DTW) to around are almost in 275,000 2010. 12,000 and and 102,000 10,000 ha, ha respectively, in 1980 and in 2010.increased to around 275,000 and 102,000 ha, respectively, in 2010.

FigureFigure 4. 4.Changes Changes in in irrigated irrigated areaarea by STW and DTW DTW over over time time in in the the study study area. area. Figure 4. Changes in irrigated area by STW and DTW over time in the study area. 3.2. Impact on the Major Crop Production 3.2. Impact on the Major Crop Production 3.2. ImpactThe increasing on the Major rate Crop of Boro Production rice area was abruptly high between 1981 and 2000 resulting mainly The increasing rate of Boro rice area was abruptly high between 1981 and 2000 resulting mainly fromThe expansion increasing of groundwater-fed rate of Boro rice area irrigation was abruptly facilities high (Figure between 5) be 1981cause and Boro 2000 rice resulting is grown mainly in the from expansion of groundwater-fed irrigation facilities (Figure5) because Boro rice is grown in the fromdry season expansion while of groundwatergroundwater-fed is the irrigation dominant facilities source (Figure of irrigation. 5) because On theBoro other rice hand,is grown Boro in ricethe dry season while groundwater is the dominant source of irrigation. On the other hand, Boro rice dryproduction season whilewas nearly groundwater static during is the the dominant last decade source (2000–2010), of irrigation. while On other the productsother hand, (e.g., Boro Potato rice) production was nearly static during the last decade (2000–2010), while other products (e.g., Potato) productionincreased significantly was nearly (Figurestatic during 5). The the production last decade area (2000–2010), of Boro rice while in Bangladesh other products has increased (e.g., Potato more) increasedincreasedthan three-fold signiﬁcantly significantly in past (Figure few(Figure decades5 ).5). The The [31]. production production The practi areaareace of ofof irrigating Boro rice rice fields, in in Bangladesh Bangladesh thus, opens has has the increased increased water access more more thanthanfacility three-fold three-fold automatically in in past past few forfew Boro decades decades rice [ production,31[31].]. TheThe practicepracti whichce of of restricts irrigating irrigating the fields, ﬁelds,farmers’ thus, thus, options opens opens thefor the waterother water accesscrops. access facilityfacilityNevertheless, automatically automatically with respect for for Boro Boro to ricetherice scope production,production, of the whichmarg whichinal restricts restricts increase the the offarmers’ farmers’ other crops,options options production for for other other crops.stems crops. Nevertheless,Nevertheless,from a gradual with with decrease respect respect in to Boroto the thescope rice scope areas of of the caused the marginal marg by factorsinal increase increase like ofthe otherof cost other crops,of irrigation,crops, production production water stemsscarcity, stems from a gradualfromand/or a gradualpreference decrease decrease in for Boro high-value in rice Boro areas rice crops. caused areas caused by factors by factors like the like cost the of cost irrigation, of irrigation, water water scarcity, scarcity, and/or preferenceand/or preference for high-value for high-value crops. crops.

Figure 5. Cultivated crop production over time in the study area.

FigureFigure 5. 5.Cultivated Cultivated cropcrop production over over time time in in the the study study area. area.

3.3. WT Dynamics The average long-term WT depth fluctuation is very significant for the study area and this depicts that the trend over the years 1981–2013 are declining (Figure6a). Moreover, the long-term rainfall Water 2017, 9, 238 8 of 17 Water 2017, 9, 238 8 of 17 3.3. WT Dynamics 3.3. WT Dynamics Water The2017, 9average, 238 long-term WT depth fluctuation is very significant for the study area and8 ofthis 17 depictsThe that average the trend long-term over the WT years depth 1981–2013 fluctuation are isdeclining very significant (Figure 6a). for Moreover,the study thearea long-term and this rainfalldepicts thatin this the area trend also over shows the years similar 1981–2013 significan arte changesdeclining as (Figure that of 6a). WT Moreover, depth (Figure the long-term 6a). This meansinrainfall this areathat in thiswhen also area shows the also rainfall similar shows is significanthigh, similar then significan changesthe WT tdepth as changes that is of low. WTas thatHowever, depth of (FigureWT the depth WT6a). depth(Figure This means is 6a).partially thatThis whendependentmeans the that rainfall onwhen the isthe temporal high, rainfall then rainfallis thehigh, WT patternthen depth the (Figure isWT low. depth However,6b). isThe low. correlation the However, WT depth factor the is WT partially(i.e., depth r which dependentis partially is the squareondependent the temporalroot on of theR rainfall2) temporalfor these pattern rainfalltwo (Figure parameters pattern6b). The(Figure is correlation0.58 6b(Figur). Thee factor 6b).correlation (i.e.,In addition, r which factor isherein, (i.e., the squarer whichthe seasonal root is the of 2 2 variationRsquare) for theseroot pattern of two R of) parameters for these these two two isevents 0.58 parameters (Figureis also 6cab). isrried In0.58addition, out. (Figur Fore instance, herein,6b). In theaddition, the seasonal maximum herein, variation and the minimum seasonal pattern WTofvariation these depth twopattern of well events ofGT1020005 these is also two carried for events different out. is also Forspecific ca instance,rried ye out.ars, the andFor maximum instance,the rainfall the and for maximum minimumthe respective and WT minimum years depth are of wellpresentedWT depth GT1020005 graphicallyof well for GT1020005 different in Figure for specific 7. different The years,monthly specific and pa the tternyears, rainfall of and the forthehydrograph therainfall respective for shows the yearsrespective that the are WT presented years depth are increasesgraphicallypresented duringgraphically in Figure March–April7 .in The Figure monthly and7. The decreases pattern monthly of or thepa regainsttern hydrograph of itsthe position hydrograph shows during that shows the May–September. WT that depth the WT increases depth The graphduringincreases indicates March–April during a March–Aprillower and decreasesamount and of or decreasesrainfall regains itsduring or position regains the duringdry its seasonposition May–September. (November–April) during May–September. The graph and indicates higher The amountsagraph lower indicates amountduring athe of lower rainfallrainy amount season during (May–September).of the rainfall dry seasonduring (November–April) Accordingly,the dry season WT (November–April) depths and higher are changing amounts and with duringhigher the sametheamounts rainy pattern. during season The the (May–September). differencerainy season between (May–September). Accordingly, the maximum WT Accordingly, depthsand minimum are WT changing depths WT with depthare changing the was same becoming with pattern. the narrower,Thesame difference pattern. implying betweenThe thatdifference the there maximum was between inadequate and the minimum ma rechargeximum WT indepthand the minimumaquifer. was becoming From WT the narrower,depth graph was it implying is becomingclear that rainfalltherenarrower, was plays inadequateimplying an important that recharge there role inwas for the inadequate groundwater aquifer. From recharge re theplenishment, graph in the it aquifer. is clearwith that theFrom rainfallexception the graph plays of itthe an is importantclearrecord that in Junerolerainfall for1990. groundwaterplays an important replenishment, role for groundwater with the exception replenishment, of the record with in the June exception 1990. of the record in June 1990.

Figure 6. Long-term average WT depth and rainfall changes pattern (a); and correlation (b). Figure 6. Long-term average WT depth and rainfall changes pattern (a); and correlation (b). Figure 6. Long-term average WT depth and rainfall changes pattern (a); and correlation (b).

Figure 7. Monthly maximum and minimum WT depth hydrograph and rainfall distribution pattern Figure 7. Monthly maximum and minimum WT depth hydrograph and rainfall distribution pattern inFigure the respective 7. Monthly year maximum for (a) 1981, and minimum(b) 1990, ( WTc) 2000 depth and hydrograph (d) 2010. (Well and No. rainfall GT1020005). distribution pattern in in the respective year for (a) 1981, (b) 1990, (c) 2000 and (d) 2010. (Well No. GT1020005). the respective year for (a) 1981, (b) 1990, (c) 2000 and (d) 2010. (Well No. GT1020005).

Water 2017, 9, 238 9 of 17

Water3.4.2017 Long-Term, 9, 238 Pattern of Yearly Data 9 of 17 The long-term (1981–2013) hydrograph of yearly maximum WT depth under different Upazilas 3.4.are Long-Term shown in PatternFigure 8. of In Yearly this Datafigure, it is observed that the WT depth is beyond the suction limit for 12 wells out of 27 wells in the area. In the rest of the wells, it is also practically impossible to The long-term (1981–2013) hydrograph of yearly maximum WT depth under different Upazilas withdraw water by suction mode pump. This is because, in case of confined/pressurized aquifer are shown in Figure8. In this figure, it is observed that the WT depth is beyond the suction limit (which is the case in this region), when the pumping is started, the cone of depression becomes sharp for(very 12 wells high) out and of the 27 dynamic wells in water the area. level In within the rest the of well the becomes wells, it 3–5 is also m higher practically compared impossible to the to withdrawstatic water water level by [32,33]. suction At mode Adamdighi pump. Upazila, This is the because, WT depths in case are ofdeclining confined/pressurized within the limit from aquifer (which6.06 to is 11.02 the case m in in all this observation region), when wells, the and pumping the decreasing is started, rate the for conewells of GT10006001, depression GT10006002, becomes sharp (veryand high)GT10006003 and the are dynamic 0.084, 0.053, water and level 0.07 withinm/year, the respectively well becomes (Figure 3–5 8). m At higher Bogra comparedSadar Upazila, to the staticthe waterhydrograph level [shows32,33]. a At decreasing Adamdighi trend, Upazila, and varies the WTwithin depths 5.59 to are 9.10 declining m in three within wells, the while limit the from 6.06decreasing to 11.02 mrates in are all observation0.02, 0.09, and wells, 0.04 m/year and the for decreasing locations GT1020005, rate for wells GT1020006, GT10006001, and GT1020007, GT10006002, andrespectively. GT10006003 In contrast, are 0.084, well 0.053, GT1020004 and 0.07 shows m/year, an in respectivelycreasing trend, (Figure with8 a). value At Bogra of 0.02 Sadar m/year. Upazila, At theDhunot, hydrograph Gabtali, shows and aSonatola decreasing all wells trend, run and in varies and remain within within 5.59 to the 9.10 suction m in threelimit wells,(from while3.27 to the decreasing7.99 m). At rates Sariakandi, are 0.02, Nandigram, 0.09, and 0.04 and m/year Shibganj, for nearly locations all of GT1020005, the wells fluctuate GT1020006, within and the GT1020007, suction respectively.limit (8 m). InThis contrast, might be well due GT1020004 to the flowing shows of the an increasingJamuna River trend, through with Sariakandi a value of Upazila, 0.02 m/year. as Atwell Dhunot, as conjunctive Gabtali, anduse of Sonatola surface alland wells groundwater run in and for remainirrigation. within At Dupchanchia the suction limitUpazila, (from the 3.27WT to 7.99depth m). Atvaried Sariakandi, within the Nandigram, suction limit and (8 Shibganj,m) during nearly 1981–1990. all of theA drastic wells fluctuatedecline from within 1991 the to suction1992 limitoccurred, (8 m). Thiswhich might is due be to due the to missing the flowing data from of the July Jamuna to December River through 1991 and Sariakandi low amount Upazila, of rainfall as well as(1382 conjunctive mm) in use 1992. of After surface that, and the groundwater WT depth graduall for irrigation.y declines At up Dupchanchia to 10 m. At Upazila,Kahalu Upazila, the WT two depth variedobservation within thewells suction (GT1054013 limit (8 and m) GT1054014) during 1981–1990. show fluctuations A drastic decline above suction from 1991 limit to between 1992 occurred, the years 1981 and 1987, and then gradually decline to 10 m. At Sherpur Upazila, all observation wells which is due to the missing data from July to December 1991 and low amount of rainfall (1382 mm) in are declining within 4.88 to 13.32 m, while well GT1088023 shows a significant trend of 0.2 m/year. 1992. After that, the WT depth gradually declines up to 10 m. At Kahalu Upazila, two observation Moreover, for the whole study area, result show reasonable spatio-temporal variation of maximum wells (GT1054013 and GT1054014) show fluctuations above suction limit between the years 1981 and WT depth. For example, in 1981 and 2013, it varies from 3.86 to 7.07 m (mean: 5.55 m) and 3.31 to 13.32 m 1987, and then gradually decline to 10 m. At Sherpur Upazila, all observation wells are declining (mean: 7.96 m), respectively (Figures 9). During the observation period from 1981 to 2013 the average withinmaximum 4.88 to WT 13.32 depth m, fluctuation while well is GT10880237.13 m, thus showsindicating a significant a long-term trend declining of 0.2 trend. m/year.

Figure 8. Cont. Water 2017, 9, 238 10 of 17

Water 2017, 9, 238 10 of 17

Figure 8. Long-term maximum WT depth fluctuation scenario for the study area. Figure 8. Long-term maximum WT depth ﬂuctuation scenario for the study area.

Moreover, for the whole study area, result show reasonable spatio-temporal variation of maximum WT depth. For example, in 1981 and 2013, it varies from 3.86 to 7.07 m (mean: 5.55 m) and 3.31 to 13.32 m (mean: 7.96 m), respectively (Figure9). During the observation period from 1981 to 2013 the average maximumFigure WT 8. Long-term depth ﬂuctuation maximum is WT 7.13 depth m, thusfluctu indicatingation scenario a long-term for the study declining area. trend.

Figure 9. WT depth distribution (a) maximum in 1981 and (b) maximum in 2013 (using same legend).

3.5. Future Projections The simulated WT depth fluctuation values from 1981 to 2013 are estimated using the MAKESENSE model. The distribution of simulated WT depth values for 95% and 99% confidence levels, along with the residual distributions, are shown in Figure 10. A negative tendency can be Figure 9. WT depth distribution (a) maximum in 1981 and (b) maximum in 2013 (using same seenFigure in 9.theWT wells depth GT1020004, distribution (aGT1067015,) maximum inGT108 1981 and1016, (b )and maximum GT1081019, in 2013 (usingwhich samereveals legend). more legend). replenishment of the aquifer in this region than the other parts of the study area. The WT depth in other wells is anticipated to increase slowly, except for observation wells at Dupchanchia Upazila 3.5.3.5. FutureFuture ProjectionsProjections (GT1033009) and at Sherpur Upazila (GT1088023). Following the present trend of simulated values, usingTheThe the simulatedsimulated same program, WTWT depth depththe projected ﬂuctuationfluctuation values values for the from fromyears 19812020, 1981 to2040, to 2013 2013 and are are2060 estimatedestimated are also estimated. using using the the MAKESENSEMAKESENSEThe spatial distributions model.model. The of distribution simulated ofmaximum of simulated WT WT WT depth depth depth for values valuesthe years for for 2020,95% 95% and2040, and 99% 99%and confidence conﬁdence2060 are levels,levels,shown along along in Figures with with the the11. residual residualThis shows distributions, distributions, if the present are are shown trend shown in continues; Figure in Figure 10 .the A 10. negativemaximum A negative tendency WT tendency depth can in be can2020, seen be in theseen2040, wells in and GT1020004,the 2060 wells will GT1067015,varyGT1020004, from 2.6 GT1081016, GT1067015,to 13.9 m (mea and GT108n: GT1081019, 8.071016, m), 0.58and which to GT1081019,16.98 reveals m (mean: more which replenishment8.88 m),reveals and −1.44more of the replenishment of the aquifer in this region than the other parts of the study area. The WT depth in other wells is anticipated to increase slowly, except for observation wells at Dupchanchia Upazila (GT1033009) and at Sherpur Upazila (GT1088023). Following the present trend of simulated values, using the same program, the projected values for the years 2020, 2040, and 2060 are also estimated. The spatial distributions of simulated maximum WT depth for the years 2020, 2040, and 2060 are shown in Figures 11. This shows if the present trend continues; the maximum WT depth in 2020, 2040, and 2060 will vary from 2.6 to 13.9 m (mean: 8.07 m), 0.58 to 16.98 m (mean: 8.88 m), and −1.44

Water 2017, 9, 238 11 of 17 aquifer in this region than the other parts of the study area. The WT depth in other wells is anticipated to increase slowly, except for observation wells at Dupchanchia Upazila (GT1033009) and at Sherpur Upazila (GT1088023). Following the present trend of simulated values, using the same program, the projected values for the years 2020, 2040, and 2060 are also estimated. The spatial distributions of simulated maximum WT depth for the years 2020, 2040, and 2060 are shown in Figure 11. This shows if the present trend continues; the maximum WT depth in 2020, 2040, and 2060 will vary from 2.6 to 13.9 m (mean: 8.07 m), 0.58 to 16.98 m (mean: 8.88 m), and −1.44 to 20.07 m (mean: 9.69 m), respectively. If the present trend continues, in many cases (e.g., three wells at Adamdighi, two wells at Bogra Sadar, two wells at Kahalu, three wells at Sherpur, two wells at Shibganj, and one well at Sonatola Upazila), the WT depth in the years 2020, 2040, and 2060 will go down below the suction limit. Consequently, suction-mode pumps will not work and irrigation costs will be increased in such a situation. There are exceptions in some wells, such as well GT1027008 at Dhunot, and wells GT1040010, GT1040011 and GT1040012, at Gabtali. Using the same method, the predicted rainfall values are 1539, 1266, and 992 mm for the years 2020, 2040, and 2060, respectively. The predicted WT depth and rainfall values for 2020, 2040, and 2060 under different observation wells are given in Table2.

Table 2. Position of WT depth and rainfall in the past, at present and in a simulated scenario for the future using MAKESENS software.

WT Depth (m) in Year Predicted WT Depth (m) in Year Signiﬁcance Upazilla Well No. B Q 1981 2013 2020 2040 2060 Level of Trend GT1006001 6.91 10.70 7.07 0.076 10.02 11.53 13.04 *** Adamdighi GT1006002 6.06 10.37 8.31 0.045 10.06 10.95 11.85 *** GT1006003 6.79 11.02 7.70 0.058 9.95 11.10 12.25 *** GT1020004 6.79 6.97 7.88 −0.019 7.13 6.75 6.37 + GT1020005 6.96 9.10 8.06 0.018 8.76 9.12 9.48 + Bogra Sadar GT1020006 5.90 8.99 6.91 0.068 9.56 10.93 12.29 *** GT1020007 5.64 7.98 6.74 0.039 8.25 9.03 9.81 *** Dhunot GT1027008 5.8 6.80 6.13 0.012 6.62 6.86 7.11 + Dupchanchia GT1033009 4.02 9.98 4.43 0.174 11.21 14.69 18.17 *** GT1040010 5.16 6.02 5.54 0.015 6.13 6.43 6.73 + Gabtali GT1040011 3.86 6.01 6.04 0.007 6.32 6.46 6.60 GT1040012 4.27 6.66 5.00 0.042 6.66 7.51 8.36 *** GT1054013 5.08 8.75 7.27 0.043 8.94 9.79 10.65 * Kahalu GT1054014 6.99 9.88 7.23 0.074 10.12 11.60 13.08 *** Nandigram GT1067015 6.78 5.93 7.90 −0.067 5.28 3.94 2.59 *** GT1081016 5.62 3.31 6.55 −0.101 2.60 0.58 −1.44 *** GT1081017 5.34 6.35 5.64 0.060 7.98 9.18 10.38 *** Sariakandi GT1081018 4.25 7.27 4.35 0.102 8.34 10.39 12.44 *** GT1081019 6.05 6.70 7.03 −0.016 6.42 6.11 5.79 + GT1081020 5.16 7.55 5.40 0.046 7.21 8.14 9.07 *** GT1088021 7.07 9.35 8.31 0.030 9.48 10.08 10.68 ** Sherpur GT1088022 5.25 9.42 8.02 0.006 8.25 8.36 8.48 GT1088023 4.88 13.32 7.86 0.155 13.89 16.98 20.07 *** GT1094024 6.34 7.20 6.74 0.037 8.19 8.93 9.67 ** Shibganj GT1094025 4.78 6.78 4.78 0.054 6.90 7.99 9.08 *** GT1095026 4.04 4.87 4.08 0.03 5.11 5.64 6.17 ** Sonatola GT1095027 4.17 7.72 4.07 0.11 8.41 10.64 12.87 ***

Rainfall for Bogra District 1739 1219 2072 −13.67 1539 1266 992 + Notes: B = Intercept of linear regression equation; Q = Slope of linear regression equation; *** trend is significant at α = 0.001; ** trend is significant at α = 0.01; * trend is significant at α = 0.05; + trend is significant at α = 0.1, rainfall unit in mm. Water 2017, 9, 238 12 of 17 Water 2017, 9, 238 12 of 17

Figure 10. Cont.

Water 2017, 9, 238 13 of 17 Water 2017, 9, 238 13 of 17

Figure 10. Trend of maximum fluctuation of WT depth for all of the observation wells. Figure 10. Trend of maximum ﬂuctuation of WT depth for all of the observation wells.

Water 2017, 9, 238 14 of 17 Water 2017, 9, 238 14 of 17

Figure 11. Simulated scenario of WT depth for (a) 2020; (b) 2040; (c) 2060. Figure 11. Simulated scenario of WT depth for (a) 2020; (b) 2040; (c) 2060. 4. Discussion 4. Discussion The stresses on groundwater for irrigation in Bangladesh have increased drastically over the last Thethree stresses decades on and groundwater its contribution for irrigationon irrigation in Bangladeshincreased from have 41% increased in 1982–1983 drastically to 75% over in the last2001–2002 three decades[34]. Moreover, and its the contribution ratio of groundwater on irrigation to surface increased water use from is much 41% in higher 1982–1983 in the Barind to 75% in 2001–2002region compared [34]. Moreover, to other parts the ratio of the of groundwatercountry [19]. The to surface long-term water declining use is much trend higherof WT indepth the Barindin regionthis study compared shows toagreement other parts with of the countryBangladesh [19]. Agricultural The long-term Development declining trendCorporation of WT depth(BADC) in this studyreport. shows However, agreement the long-term with the WT Bangladesh depth fluctuation Agricultural is a Development function of multifold Corporation variables (BADC) (e.g., report. However,annual rainfall, the long-term annual groundwater WT depth ﬂuctuation withdrawal, is aand function local subsurface of multifold conditions). variables (e.g.,In this annual analysis, rainfall, annualmost emphasis groundwater is given withdrawal, to the relation and between local subsurface long-term conditions). WT depth and In thisannual analysis, rainfall most because emphasis the is givenpumping to the data relation is unavailable. between long-termOn the basis WT depthof a sampling and annual duration rainfall (1981–2013), because the the pumping long-term data is unavailable.average maximum On the WT basis depth of asampling is 7.13 m. duration From a (1981–2013), long-term future the long-term projection average perspective, maximum the WT predicted values for the years 2020, 2040, and 2060 are 1.13, 1.24, and 1.36 times higher than that of depth is 7.13 m. From a long-term future projection perspective, the predicted values for the years present trends. However, the WT depth present trend value and projected values for 2020 and 2040 2020, 2040, and 2060 are 1.13, 1.24, and 1.36 times higher than that of present trends. However, the are also dissimilar with that of values estimated by [19]. The yearly variation pattern of the WT WT depth present trend value and projected values for 2020 and 2040 are also dissimilar with that depth reflects a greater depth during October–April and from May–September (rainy season) WT of values estimated by [19]. The yearly variation pattern of the WT depth reﬂects a greater depth depth remains above the suction limit (8 m). Thus, during the dry season (e.g., October–April), WT during October–April and from May–September (rainy season) WT depth remains above the suction depth goes beyond the suction limit as irrigation is given in this period, and this situation limitconsequently (8 m). Thus, limits during the groundwater-fed the dry season irrigation. (e.g., October–April), This variation WT is in depth agreement goes beyondwith the theyearly suction limitrainfall as irrigationvariation ispattern. given inIn thisthis period, analysis, and it thisis found situation that consequently maximum rainfall limits thehappens groundwater-fed during irrigation.May–September This variation and the is least in agreement amount in with February the yearly–April. rainfall The variationcorrelation pattern. value In(0.58) this analysis,between it is foundlong-term that maximumWT depth rainfall and rainfall happens shows during a May–Septembergood dependency and of the groundwater least amount on in February–April.rainfall for Thereplenishment. correlation valueHowever, (0.58) WT between depth long-termabove suction WT depthlimit is and considered rainfall shows for groundwater a good dependency based of groundwaterirrigation because on rainfall in NW for Bang replenishment.ladesh about However,78% irrigated WT land depth is abovecovered suction by groundwater limit is considered and forapproximately groundwater 80% based groundwater irrigation is because lifted by in STW NW using Bangladesh the centrifugal about 78% pump, irrigated which land has isa suction covered by groundwaterlimit of 8 m [35]. and approximatelyAlthough there 80% are groundwatersome exceptions, is lifted the byWT STW depth using continued the centrifugal to decline pump, with whicha hasslight a suction response limit to ofexcess 8 m [35rainfall]. Although in monsoon there areor dry some season exceptions, months. the This WT depthmight continuedbe the cause to declineof withover-extraction a slight response of groundwater to excess for rainfall irrigation in monsoon and the slow or dry rate season of infiltration months. through This might the upper be the clay cause

Water 2017, 9, 238 15 of 17 of over-extraction of groundwater for irrigation and the slow rate of inﬁltration through the upper clay to silty clay layer. Sustainable management of groundwater requires that the extraction from a groundwater reservoir should be in equilibrium with the average recharge in the long-term, and the lowered groundwater levels be environmentally, economically, and socially acceptable. Gradually declining groundwater depths of the study area are an indicator of unsustainable extraction. In some cases, the depth will be approximately double the present value by the year 2060, if the present trend of withdrawal is continued. Consequently, it will increase the irrigation cost and, thus, impact crop production. In addition, a series of ecological and environmental issues (e.g., land subsidence and deterioration of water quality) may develop and become the key factors constraining socioeconomically sustainable development.

5. Conclusions The WT depth of 27 observation wells from 11 Upazilas of the Bogra district for the period of 1981–2013 were analyzed to determine the trends and observe the WT dynamics. The hydrographs exhibit that the WT depth at the beginning and end of the study period vary spatially. However, except for a few cases, the WT depth showed a declining trend, and in many places, the WT depth falls below the lifting capacity (up to 8 m) of suction-mode pumps. Using the MAKESENS software, long-term predictions were projected considering the current rate of the WT depth trend. If the present trend in the dry season is continued, suction-mode pumps may not operate at all due to the exceeding the suction limit. The continuous dropping of the WT is the major principal reason of groundwater level instability. If this instability once appears, it will promote the appearance of many environmental calamities. Moreover, the sustainability of groundwater in Northwest Bangladesh has long been identiﬁed as a matter of concern. Therefore, an urgent measure should be adopted to avoid groundwater over-mining. Minor irrigated crops could be adopted instead of the monopoly of the rice cropping pattern. On-farm management of water, such as growing short-duration drought-tolerant or low water demand crops, applying water saving techniques (such as alternate wetting and drying), soil-water conservation through mulching, rainwater harvesting in farm ponds or surface water bodies, etc., should be adopted to avoid groundwater mining and to promote the sustainable use of groundwater resources. These strategies are expected to lead to the sustainable use of groundwater resources in the area.

Acknowledgments: This work was financially supported by Key Research Program of the Chinese Academy of Sciences (Grant No. KJZD-EW-TZ-G10) and by a fellowship from China Scholarship Council (Grant No. 2014GXYB21) at the Institute of Geographic Sciences and Natural Resources Research, University of Chinese Academy of Sciences. The authors thank the editor and anonymous reviewers for their helpful and constructive comments that greatly contributed to improve the quality of our paper. Author Contributions: Mohammad Hasanuzzaman conceived and designed the study and contributed to the writing of the paper; Yinghua Zhang and Shakir Hussain participated in data processing; Xianfang Song and Dongmei Han reviewed the manuscript. Conflicts of Interest: The authors declare no conflict of interest.

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