DSpace at VNU: Application of multimedia methodology for investigation of karst water in highland regions of Ha Giang Province, Vietnam

DSpace at VNU: Application of multimedia methodology for investigation of karst water in highland regions of Ha Giang Pr...

Environ Earth Sci DOI 10.1007/s12665-013-2617-3 SPECIAL ISSUE Application of multimedia methodology for investigation of karst water in highland regions of Ha Giang Province, Vietnam Ngoc Thach Nguyen • Ngoc Hai Pham • Xuan Canh Pham • Thi Thuy Hang Nguyen Van Lam Nguyen • Thi Thanh Thuy Duong • Received: 25 May 2012 / Accepted: 21 June 2013 Ó Springer-Verlag Berlin Heidelberg 2013 Abstract Ha Giang is one of the largest, northern border provinces of Vietnam, consisting of four districts: Yen Minh, Quan Ba, Dong Van and Meo Vac This province features varied karst landscape of Carboniferous–Permian limestone The region has been recognized by UNESCO as one of the 77 geological parks in the world and the second in Southeast Asia on October 2012 In the dry season, little or no rain is recorded; therefore, surface water is very scarce For this reason, proper delineation and exploitation of the groundwater resource is critical for sustainable water supply This has been identified as an important challenge under the scientific project KC-08-10 in the national program KC-08 Remote sensing and GIS were used to decipher the signature of karst water in the highland of Ha Giang Information layers generated were subjected to multi-criteria evaluation using analytic hierarchy process for decision making to identify ideal locations for groundwater prospecting The study resulted in delineation of ten zones for all regions and 18 ideal drilling sites in Tam Son Town of Quan Ba District Drilling and resistivity soundings were performed to assess the success of the interpretation Deep resistivity survey confirmed low resistivity (200–300 Xm) near the identified potential sites in Tam Son Town of Quan Ba District Further, successful drilling at site LKTS1 with a discharge of 7–9 l/s is observed, proving the potential of this methodology for N T Nguyen (&) Á N H Pham Á X C Pham Á T T H Nguyen Faculty of Geography, VNU University of Science, Vietnam National University, Hanoi, Vietnam e-mail: nguyenngocthachhus@gmail.com V L Nguyen Á T T T Duong Faculty of Geology, University of Mining and Geology, Hanoi, Vietnam rapid exploration of groundwater in water-scare karst terrains of Vietnam Keywords Karst water Á Remote sensing Á GIS Á AHP Á Hydrographic geomorphology Á Water resource management Á Groundwater exploration Introduction Geographical information system (GIS) has been rapidly developed and effectively used in various fields of earth science and natural resources management Remote sensing and GIS have been used in exploring groundwater in mountainous areas, particularly in the limestone areas (Granados-Olivas et al 2005) Since the 1950s in many countries, aerial photograph interpretation methods have been applied to groundwater investigation with indirect signs through geomorphologic and tectonic concept Remote sensing has popular applications because of its unique advantages such as synoptic coverage, remote area access, and multi-spectral, multi-resolution and multitemporal properties (Sabins 1991) These properties make satellite remote-sensing data useful for application-specific use, especially for hydrographic geomorphological mapping (Granados-Olivas et al 2005; Walvoord et al 2002) Remote-sensing data have been utilized for decades in hydrogeological investigation work and thematic research Common applications of remote-sensing analysis are stratigraphy mapping, geological structure analysis, fault detection and identification, and geological lineament extraction (Sabins 1991) In many cases, a high density of the extracted geological lineaments is interpreted as a zone of highly fractured rock (Babcock 1974) Hence, these zones receive, in general, first priority for prospection of 123 Environ Earth Sci groundwater resources (Balakrishnan 1986; GranadosOlivas et al 2005; Nag 2005; Srinivasa Rao et al 2000) Systematic methodology in application of remote sensing for groundwater research has been introduced by FAO in the book, ‘‘Groundwater research by remote sensing, a methodological approach’’, by Travaglia and Dainelli (2003) The approach used in this study was a development of the traditional standard sequence of drainage, landforms, cover and lineaments analyses, to which several improvements and additions were made The lineament system is a major indicator of connection between surface and deep groundwater in the karst regions Faults and lineaments system can be extracted automatically or semi-automatically using digital or visual image processing on satellite data These two structural features provide independent information, allowing assessment and analysis of groundwater potentials prior to actual drilling (Balakrishnan 1986) In Vietnam, approaches to hydrographic geomorphology and geology with remote-sensing applications had been introduced in the University of Natural Sciences and University of Mining and Geology since 1972 Currently, satellite digital image scanning and digital image processing techniques are used for assessing underground water potential through automated data classification and separation techniques (Nguyen 1986, 1993) With the availability of high-resolution satellite data, geophysical data and improved positional fidelity due to global positioning system (GPS), the accuracy of mapping groundwater-rich zones and well locations for further groundwater explorations and research has been improved In karst topographic research, the remote-sensing method is applied to determine the landform and tectonic features, which are related to the potential of groundwater concentration Some typical studies can be mentioned as: Hydrogeological characteristics of a karst mountainous catchment in the Northwest of Vietnam (Tam et al 2001); Study on the relationship between lineaments and borehole specific capacity in a fractured and karstified limestone area in Vietnam (Tam et al 2004); Study of cavernous underground conduits in Nam La (Northwest Vietnam) by an integrative approach (Tam et al 2005); Remote sensing and GIS-based analysis of cave development in the Suoi Muoi Catchment (Son La-NW Vietnam) (Hung et al 2002); A multi-analysis remote-sensing approach for mapping groundwater resources in the karstic Meo Vac Valley, Vietnam (Tam and Batelaan 2011) The major focus of these studies is to investigate the relationship between hydrographic geomorphological factors (lineaments and fault systems) with hydrodynamic characteristics of a karstic aquifer The final high-yield locations are based on the maxima of suitable conditions The final location of the borehole is still based on subjective judgment over a smaller zone This study advances 123 the previous one by implementing analytical hierarchy process (AHP) for final suitability, thereby better reporting the subjectivity so that it can be replicable at various scales and with ease Using AHP for decision making has various advantages, including pairwise assessment of multiple factors, weights which are compensatory and choice regarding risk-averse and risk-taking decisions (Saaty 1977) Due to successful quantification of factors and their relative importance, the method established in this study can be applied at various scales of groundwater prospecting in areas with similar topographic and geological setting (Fig 1) Study area Ha Giang, the northernmost province of Vietnam, has a relatively complicated terrain It consists of high mountains and deep valleys, rising from the south to the north, divided into three main regions In the north and northeast of the province, high mountains of limestone with high slopes separated by valleys, rivers and springs mark the area The west of the province includes highland from the Chay River massif These two regions have similar climatic conditions with moderate climate of two seasons: dry and rainy The lower areas in the province include low hills, Lo River Valley and Ha Giang Town In general, the terrain of the province could be characterized by two natural regions, including the upland and the low-lying region (Fig 2a) The upland includes the rocky mountains in the north and northeast, and the highland of mountains in the west Most of this highland forms an arch or semi-arch, with many continuous mountain ranges (Fig 2b, c) The rocky mountains include Quan Ba, Yen Minh, Dong Van and Meo Vac, which are part of the Dong Van Plateau with 80 % of the area covered by limestone, with the notable Lung Cu mountain peak of 1,621 m height The western highland includes Hoang Su Phi, Xin Man partially lying on Bac Ha Plateau with a 2,43 l m elevation and Tay Con Linh mountain peak High mountain ranges alternate with deep valleys through narrow strips of land With 40 locations which have special values in terms of natural resources in karst landforms, the highland karst region of the Ha Giang Province has been recognized by UNESCO as one of the 77 geological parks in the world and the second in Southeast Asia on October 2012 The park covers four districts of Meo Vac, Dong Van, Yen Minh and Quan Ba, totalling over 2,300 km2, with nearly 250,000 residents Up to 80 % of the plateau is covered by limestone The park is home to nearly 20 ethnic groups, with diverse cultures and traditions, which make the plateau an interesting destination for tourists/visitors Environ Earth Sci Fig Flowchart of the study The lower sub-region or lower land includes the remaining area of the province in the southeast, expanding from Bac Me District, Ha Giang Town, Vi Xuyen to Bac Quang close to Tuyen Quang Province The terrain here mostly consists of low hills, with evergreen forests alternating with wet rice fields and alluvial deposits along two river banks Many kinds of crops can be seen in this region Ha Giang is a mountainous province characterized by distinguished tropical monsoon climate from surrounding lower lands and midlands with two main seasons: rainy and dry In 1999, the average temperature in the province was 28.1 °C (Ha Giang Station), 28.3 °C (Bac Quang Station) and 27.35 °C (Bac Me Station) The highest temperature is recorded in June or July, while the lowest is recorded in January at 1.56 °C (Hoang Su Phi Station) The differences between day and night temperatures in valleys are more notable than in the delta region The rain regime in this province is quite diversified The yearly rainfall is 2,860 mm The number of rainy days ranges between 180 and 200 days per year In the dry season, the highland sub- region of Ha Giang is seriously deprived of water, especially in the northeastern part of the province where karst terrain is dominant Supplying water is most difficult in the karst highland areas with elevation from 700 m and above Rivers in Ha Giang are unequal in depth and have high slopes with many waterfalls and rapids Compared to the lowland, the rivers and streams in the upland have low drainage density In other words, the mountain ranges separating the river system in the upland area are very high, e.g., the bed of Nho Que River is 400 m deep from the flat area of human habitation With support from the government, many small lakes have been constructed for various purposes, including storage of rainwater and supplying the same in the dry season However, these lakes are not adequate to meet the increasing water demand, especially in highly populated areas The most critical of these areas are the ones between elevations of 100 and 700 m, where most ethnic minorities live Tam Son Town located in the southeast has similar characteristics (Fig 2) 123 Environ Earth Sci Fig Map of Ha Giang Province (a) and typical land form of the highland area (b, c, d) In consideration of the seriousness of this situation, a subproject under the National Research Program KC-08 ‘‘Pursuing on preventing and mitigating natural disaster’s damages’’ was established This project (No KC 08/06-10) was implemented between the year 2008 and 2010 The main objective of this sub-grant was to rapidly assess potential zones of groundwater for augmenting the water supply in the upland of Ha Giang Province Further objectives were to establish a quantitative method which can be rapidly applied to other areas with similar geological and topographical settings Given the objectives and time frame, remote sensing for rapid identification of hydrographic geomorphological structures and GIS for quantitative decision making were found to be the most suitable techniques The results were further verified by geophysical testing and drilling This study area was spread in four upland districts of Ha Giang Province, namely, Meo Vac, Dong Van, Yen Minh and Quan Ba Field-based validation was conducted at Tam Son Town of Quan Ba District location using several indirect signatures, the following steps were undertaken The scientific approach for studying the karst areas of the Ha Giang is also summarized as a flowchart (Fig 1) Secondary data collection Hydrogeological data which were the product of the mapping project conducted in the region since 1968 to present were collected Major features of the hydrogeology in the highland area of Ha Giang Province can be described as follows: – – Materials and methods Study process – To apply AHP-based decision making to establish a quantitative method to decipher groundwater prospecting 123 Geological formations resulted in aquifers of limestone, dolomite–limestone, interbedded siltstone and shale from Ordovician (O), Ordovician –Silurian (O–S), Silurian (S2), Devon (D1) and Carboniferous–Permian (C3–P1) age The thickness of the aquifer averages about 40–50 m; it is covered by late continental formations Hydrogeological structures are formed and controlled by a major fault in the NW–SE direction (Fig 3) Due to tectonic movement, high densities of lineaments in other directions are formed After a long history of tectonic movement and weathering process, landforms in the area show various shapes such as bell, tower, funnel, cave and Environ Earth Sci Fig Hydogeological map—result of Landsat image interpretation combined with ground truths and comparison with previous data underground cave These features indicate that groundwater is channeled to deeper locations controlled by the predominant structures The secondary information about formations and lineaments were digitized to be amenable to further GIS and remotesensing analysis 123 Environ Earth Sci Remote-sensing data collection Structure Landsat TM image (Landsat 5) with a spatial resolution of 30 m for bands 1–5 and was acquired A cloud-free image of 24 November 2000 (Fig 4) was selected to be used for digital image processing and visual interpretation It must be emphasized that for replicating this model of groundwater prospecting for a larger scale, higher resolution image datasets including SPOT or QUICKBIRD are recommended Using the Landsat TM data, two methods were applied for structure mapping Automated lineament extraction using Laplacian and high-pass filter were faster compared to visual interpretation Secondary information such as digital elevation model (DEM), shaded relief, slope, aspect and curvature maps was found to be useful to enhance automated extraction of linear structures (Elmahdyl and Mohamed 2012) However, between these two approaches, a map created by visual interpretation in combination with secondary geological information was found to be more accurate The automatic extraction of linear features alone was found to be misleading At times, automatic extraction process captured linear features such as roads, while it was not possible to identify overburdened structures Through the combination of primary and secondary dataset and image enhancement, the hydrogeostructural map was generated with 17 major structures, elongated mainly from the northwest to southeast direction Preliminary investigation of the structure map help in locating the general area of good groundwater potential, marked by blue and dark green (Fig 3) The hydrogeostructural map was a key factor in the multi-criteria evaluation process to determine the richest zones of groundwater and drilling sites for augmenting groundwater supply Factors and constraints To select the most suitable location for groundwater prospection, AHP-based decision making was applied Factors and constraints to the analysis were identified based on expert knowledge and past research Hydrographic geomorphological structures, (TWI), lineament density, lineament node density, distance to lineament (NE–SW direction) and topographic wetness index were selected as key factors Constraint to the analysis was identified as the region where the need for augmenting groundwater resource is critical Since this geographic region is marked with a high concentration of ethnic minority population They inhabit the slopes between elevations of 100–700 m The constraint mask was created using DEM of the area Fig FCC Landsat TM image (BRG) of the study area, 24 November 2000 123 Environ Earth Sci Fig Database for the study with nine layers Lineament density and node density Linear features can be interpreted as rift, linear valleys, linear slope breaks or linear ridgelines These features represent pathways for groundwater accumulation and groundwater discharge Many studies have been applied to study and manage groundwater contamination in carbonate aquifers; the role of lineaments in well yield and groundwater contamination is well noted A high positive correlation (r = 0.851) was found between lineament length density and yield, especially where lineaments were cross-cutting (Sener et al 2005; Tam et al 2005) This indicates a strong relationship between fracturing and well production A lineament density map was created using lineament statistic tool in ArcView 3.1 Rose diagrams of three dominant directions, i.e., northwest–southeast, northeast– southwest and north–south were drawn Among these, the oldest direction is northwest–southeast, which plays a major role in forming the major hydrogeological structures The second lineament system divides the major structures into several sub-structures (Fig 3) Further, to integrate information related to cross-cutting lineament, nodes (intersection of lineaments) were extracted and used to calculate a node density map (Fig 5) The study area shows a lineament density ranging from to 4.1 km/km2 (Fig 5) and a node density ranging between and nodes/km2 Distance from lineament NE–SW In the study area, there are three major fault systems (Fig 3) The NW–SE trending system is the oldest Part of this system has been re-activated in the subsequent geological times and determines largely the orientation of the geological structure of the study area (Fig 6) The second system is an NE–SW trending system, while the sub N–S trending system was the latest to be formed Moreover, faults NW–SE play an important role in the groundwater 123 Environ Earth Sci Fig Assessed layers for the model (procedure) created from basic layers by the reclassification tool movement of the study area (Tam et al 2005; Tam and Batelaan 2011) Among four lineament directions, the authors were interested in the NW–SE direction, as this is the main direction for collection and movement of groundwater Water accumulation is highest at the center of the lineament and depletes as we move away from it To adequately represent this in a multi-criteria evaluation model, multiple-buffer of incrementing distances from the center of the lineaments was made with intervals at 50, 100, 150, 200 and [200 m Topographic wetness index The topographic wetness index (TWI) is a function of natural logarithm of ratio of the local upslope contributing area and slope The topographic wetness index (TWI) is frequently used to quantitatively simulate the soil moisture conditions in a watershed and is the most commonly used indicator for static soil moisture content Therefore, it plays an important role in the research of soil erosion and distributed hydrological model in watersheds and is used to approximate the local hydraulic gradient under steady state conditions (Ma et al 2010) The simplicity of input data make TWI a tool of choice for groundwater study especially in areas where direct physical method to understand aquifer is not feasible TWI is extracted using the DEM alone A flow accumulation grid (A) was calculated in ArcGIS This was the input into the equation (Eq 1) for TWI using map algebra 123 TWI ẳ lnA=tanbị 1ị where A is the upslope area contributing water (flow accumulation grid) to the calculation point and b is the local slope gradient Standardization To utilize various factors to get to a decision, it is important to standardize quantities of different type or unit into one scale and one range This is done by the process called standardization All the above-mentioned factors were reclassified into five levels corresponding to their relationship with groundwater potential In the below-mentioned equation, 1–5 is the score for separate units of each layer All the standardized factors were masked with the constraint layer (area of habitation between 100 and 700 m elevation in the four districts) Pairwise weighting and AHP weights Assigning weight to standardized criteria is important to ensure the relative importance to be used as a factor compensation to arrive at final decision This helps in simulating a real-life scenario where adjustments are made to accommodate difficult choices to meet a greater good Environ Earth Sci Fig Groundwater potential map (a, b) for all regions and for the interested areas and maximum GWP points (d) Fig Fixing the potential boring points for karst water exploration in Tam Son Town, Quan Ba District by deep electro-geophysical testing All the factors were compared to each other The comparison was done using expert knowledge and previous researches The comparisons were performed following a nine-point continuous scale (Saaty 1977) The AHP (Saaty 1977) is based on decomposing a complex MCDM problem into a system of hierarchies (Saaty 1977) The final step in the AHP deals with the structure of an M N matrix (where M is the number of 123 Environ Earth Sci alternatives and N is the number of criteria) This matrix is constructed by using the relative importance of the alternatives in terms of each criterion The vector (ai1, ai2, ai3,…, aiN) for each i is the principal eigenvector of an N N reciprocal matrix, which is determined by pairwise comparisons of impact of M alternatives on the ith criterion Some evidence is presented by Saaty (1977), which supports the technique for eliciting numerical evaluations of qualitative phenomena from experts and decision makers Using this method, AHP weights for the criteria were calculated Consistency index of value \0.1 is considered indicative of consistent comparison A consistency index of 0.058 is reported for the final pairwise comparison matrix showing good consistency in assigning comparative degree of preference among factors (Saaty 1977) Weighted linear combination Weighting factors ensure compensation of factor importance while combining them using the linear combination method The factor layers were multiplied with their factor weight These weighted factor layers were summed and averaged (Eq 2) The resultant map was the final groundwater potential map (Figs 7, 8) X M ¼ 1=n ðai à AiÞ ð2Þ Table Pairwise comparison scale (Saaty 1977) Scale Degree of preference Equal importance Moderate importance of one factor over another Strong or essential importance Very strong importance Extreme importance 2,4,6,8 Values for inverse comparison Table Criteria and pairwise comparison C.I = 0.0583207 S TWI ND D L Structure (S) TWI 1/4 1/2 1/3 1/2 Node density (ND) Distance lineament NE–SW (D) 1/2 1/3 Lineament density (L) 1/3 1/4 1/2 SUM 3.08 12.00 3.08 6.83 10.50 Bold values in the cross line indicate equal importance (value = 1), bold values in the bottom line indicate the total value of pairwise comparison of a factor to others Table Pairwise comparison and average weight for each criterion S where M map of groundwater potential, n groundwater potential level, a weight of information layer i, i information layers (from 1….m), m layer order, A assessed for separated layer i Using the weight from Tables 1, 2, 3, the formula is expressed as: M = (structure *0.31 ? TWI *0.08 ? node density *0.33 ? distance lineament NE–SW *0.17 ? lineament density *0.1)/5 TWI ND D L Sum Average Structure 0.32 0.33 0.32 0.29 0.29 1.56 0.31 TWI 0.08 0.08 0.16 0.05 0.05 0.42 0.08 Node density 0.32 0.17 0.32 0.44 0.38 1.64 0.33 Distance lineament NE– SW 0.16 0.25 0.11 0.15 0.19 0.86 0.17 Lineament density 0.11 0.17 0.08 0.07 0.10 0.52 0.10 Bold values indicate average weights for all criteria and these values are used in calculating ground potential map (Eq 2) Results Groundwater potential is depicted by a range of continuous values Due to the application of AHP weights, the final GWP values were in the same range as the range used for standardization of factors The GWP map (Fig 7a) shows the zone of groundwater potential as values ranging from 0.91 to 4.64 Higher values indicated suitable locations for groundwater potential and thus prospection This continuous value map was further classified into potential zones and drilling sites to be a useful and practical tool for the local government to augment groundwater supply This information can be further useful in planning activities, especially new settlement sites in the upland region of Ha Giang Province (Fig 7b, c, d) 123 Validation of the high GWP zones was conducted by detailed geological and hydrogeological field surveys and geophysical measurement (Fig 8) at Tam Son Town of Quang Ba District Geophysical testing with the deepelectronic resistivity measuring technique at 131 sites was conducted in Tam Son Town of Quan Ba District Some potential locations were determined near the maximum GWP point with very low resistivity values ranging from 200 to 300 Xm in comparison to very high resistivity values (up to 4,000 Xm) in neighboring locations (Fig 8) Drilling conducted at site No LKTS1 recorded a good discharge of 7–9 l/s (Nguyen et al 2010) By further classifying the GWP values in Tam Son Town, 18 potential points of maximum GWP were Environ Earth Sci Table Location of the 18 potential points ID Longitude 104o570 49.29900 E o Latitude 00 104 59 10.120 E 23o20 44.86500 N o 00 23 54.634 N 10 Latitude 104o580 47.26800 E o 00 104 59 38.229 E 23o40 7.80600 N 23 41.78900 N 11 104 580 26.56800 E 23o40 17.42600 N 104o590 39.98700 E 23o30 46.66800 N 12 104o580 36.49800 E 23o40 17.32500 N 00 o 00 o 104 59 25.929 E 104 59 17.143 E 00 105 8.103 E o o 00 o 00 o 00 23 51.545 N 23 54.797 N 23 56.424 N o 13 14 15 o 23o40 6.17600 N 105 39.73300 E o o Longitude o ID o 00 23o40 20.81300 N o 00 23o50 3.07300 N o 00 23o50 9.57300 N 104 59 13.626 E 104 57 38.716 E 104 57 24.654 E 104 580 57.81200 E 23 1.29900 N 16 104 570 45.73500 E 23o50 43.72500 N 104o590 31.20000 E 23o40 2.92800 N 17 104o570 17.61000 E 23o50 51.84700 N determined with specific geographic coordinates (Table 4) for easy location of drill sites (Fig 7d) Conclusions AHP showed promising results in decisions making when multiple factors or decision hierarchies were present It provides a balanced approach where risk of decisions can be modulated This study demonstrates the successful application of AHP and GIS multi-criteria evaluation using satellite remote sensing for groundwater potential estimation in karst highlands of Ha Giang Province This study improves upon previous work in the region by way of implementing a better decision-making methodology and enhancing the results by using new factors like node density and TWI The geophysics and drilling conducted on site also validated the results The results of site location and zones had been located on a largescale map after geophysical testing These large-scale maps have been since transferred to the local government for augmenting water supply in the region Finally, use of traditional data along with remote-sensing data under a suitable decisionmaking method is found to be fast and comparatively faster than traditional approaches Therefore, this procedure can be applied at other sites of karst highland in Vietnam for the purpose of groundwater exploitation 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