[go: up one dir, main page]

Skip to main content

Advertisement

Log in

Land Use Land Cover (LULC) and Surface Water Quality Assessment in and around Selected Dams of Jharkhand using Water Quality Index (WQI) and Geographic Information System (GIS)

  • Original Article
  • Published:
Journal of the Geological Society of India

Abstract

Surface water quality deterioration is mainly occurring due to anthropogenic activities at an alarming rate in developing countries. Jharkhand has been undergoing exponential urbanisation and mining, causing immense surface water pollution and water stress. The state is heavily dependent on artificial dams for its daily water supply demands. Therefore, an effort is made to monitor and ascertain the surface water quality and the influence of nearby land use pattern on water quality, in the selected five dams, namely, Hatia dam, Kanke dam, Getalsud dam, Galudih barrage, and Chandil dam are done. These dams are built on the Subarnarekha river basin, located in the Jharkhand state on a seasonal basis and associated land use land cover (LULC) changes, changes in vegetation cover using normalised difference vegetation index (NDVI) and water body changes using normalised difference water index (NDWI) that have occurred in a 5-year gap i.e. 2016 and 2021. The secondary data for the year 2016 was obtained from the Jharkhand pollution control board report published by the government of Jharkhand, India. For the year 2021, the samples were collected from sampling sites for pre, post and monsoon seasons. The chemical analysis of collected water samples was done in the laboratory for parameters like pH, dissolved oxygen, biological oxygen demand, total calcium and magnesium, hardness, total dissolved and suspended solids, alkalinity, chlorine etc. and compared with the standard values prescribed by world health organisation (WHO) and Indian standards (IS) 10500:2012. The seasonal water quality status was analysed using the water quality index (WQI) for the pre, post and monsoon seasons of 2016 and 2021. Then, the use of supervised classification method for land use land cover (LULC), normalised difference vegetation index (NDVI) and normalised difference water index (NDWI) was opted to understand the relation between the change in water quality and quantity concerning its land use and land cover, by comparison of results from the year 2016 to 2021. LULC were found using the supervised maximum likelihood classification method in ArcGIS and its accuracy was checked using the kappa accuracy method, which was found to be varying from 87 to 95% for all sites. The results showed that the overall water quality varied from good to poor indicating that it can be used for human activities but may need pre-treatment before drinking. NDWI showed a massive increase in severe drought areas for Hatia, Kanke, Chandil and Galudih barrage, whereas moderate drought regions increased for Hatia, Getalsud, and Kanke. NDVI showed dense and moderate vegetation both decreased massively for all the dam sites indicating an alarming situation and the need to adopt better land management practices.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

Explore related subjects

Find the latest articles, discoveries, and news in related topics.

Abbreviations

BOD:

Biological oxygen demand

COD:

chemical oxygen demand

DO:

Dissolved oxygen

EC:

Electrical conductivity

GIS:

Geographic Information system

MLC:

maximum likelihood classification

ICMR:

Indian council of Medical Research

IS:

Indian Standard

JSPCB:

Jharkhand State Pollution Control Board

LULC:

land use/land cover

NDWI:

Normalized Difference Water Index

NDVI:

Normalised difference vegetation index

NSFWQI:

National Sanitation Foundation water quality Index

TDS:

Total dissolved solids

TSS:

Total suspended solids

WHO:

World Health Organization

WQI:

Water Quality Index

References

  • Abbas, Z. and Jaber, H.S. (2020) Accuracy assessment of supervised classification methods for extraction land use maps using remote sensing and GIS techniques. IOP Conf Ser Mater Sci Eng. v.745(1), doi: https://doi.org/10.1088/1757-899X/745/1/012166

  • Abdel Rahman, M.A.E., Natarajan, A., Hegde, R. and Prakash, S.S. (2019) Assessment of land degradation using comprehensive geostatistical approach and remote sensing data in GIS-model builder. Egypt Jour. Remote Sens. Sp. Sci., v.22(3), pp.323–334. doi: https://doi.org/10.1016/j.ejrs.2018.03.002

    Google Scholar 

  • Abijith, D. and Saravanan, S. (2021) Assessment of land use and land cover change detection and prediction using remote sensing and CA Markov in the northern coastal districts of Tamil Nadu, India. Environ. Sci. Pollut. Res., doi:https://doi.org/10.1007/s11356-021-15782-6

  • Agapiou, A. (2020) Estimating proportion of vegetation cover at the vicinity of archaeological sites using sentinel-1 and-2 data, supplemented by crowdsourced openstreetmap geodata. Appl. Sci., v. 10(14), doi:https://doi.org/10.3390/app10144764

  • Agbeshie, A.A., Abugre, S., Adjei, R., Atta-Darkwa, T. and Anokye, J. (2020) Impact of Land Use Types and Seasonal Variations on Soil Physicochemical Properties and Microbial Biomass Dynamics in a Tropical Climate, Ghana. Adv. Res., v.21(1), pp.34–49. doi:https://doi.org/10.9734/air/2020/v21i130180

    Article  Google Scholar 

  • Ahamad, A., Raju, N.J. and Madhav, S. (2020) Trace elements contamination in groundwater and associated human health risk in the industrial region of southern Sonbhadra, Uttar Pradesh, India. Environ Geochem Health. v.42(10), pp.3373–3391. doi:https://doi.org/10.1007/s10653-020-00582-7

    Article  Google Scholar 

  • Ahmed, K.R. and Akter, S. (2017) Analysis of landcover change in southwest Bengal delta due to floods by NDVI, NDWI and K-means cluster with landsat multi-spectral surface reflectance satellite data. Remote Sens. Appl. Soc. Environ., v.8(August), pp.168–181. doi:https://doi.org/10.1016/j.rsase.2017.08.010

    Google Scholar 

  • ALabdeh, D., Karbassi, A.R., Omidvar, B. and Sarang, A. (2020) Speciation of metals and metalloids in Anzali Wetland, Iran. Internat. Jour. Environ. Sci. Tech. v.17(3), pp.1411–1424. doi:https://doi.org/10.1007/s13762-019-02471-8

    Article  Google Scholar 

  • Amalo, L.F., Ma’Rufah, U. and Permatasari, P.A. (2018) Monitoring 2015 drought in West Java using Normalized Difference Water Index (NDWI) IOP Conf Ser Earth Environ. Sci., v. 149(1), pp.6–13. doi:https://doi.org/10.1088/1755-1315/149/1/012007

    Google Scholar 

  • Anand, A., Pandey, P.C., Petropoulos, G.P., Pavlides, A., Srivastava, P.K., Sharma, J.K. and Malhi, R.K.M. (2020) Use of hyperion for mangrove forest carbon stock assessment in bhitarkanika forest reserve: A contribution towards blue carbon initiative. Remote Sens., v.12(4) doi:https://doi.org/10.3390/rs12040597

  • Anees, M.T., Abdullah, K., Nawawi, M. N. M., Norulaini, N.A.N., Syakir, M.I. and Omar, A.K.M. (2018) Soil erosion analysis by RUSLE and sediment yield models using remote sensing and GIS in Kelantan state, Peninsular Malaysia. Soil Res., v.56(4), pp.356–372. doi:https://doi.org/10.1071/SR17193

    Article  Google Scholar 

  • Aneesha Satya, B., Shashi, M and Deva, P. (2020) Future land use land cover scenario simulation using open source GIS for the city of Warangal, Telangana, India. Appl. Geomatics., v.12(3), pp.281–290. doi:https://doi.org/10.1007/s12518-020-00298-4

    Article  Google Scholar 

  • Anshuman, K.S. and Subodh, K.S. (2020) Fluoride Contamination Studies in Belchampa Pratappur Villages of Garhwa District Jharkhand. Internat. Jour. Res. Eng. Appl. Managmt., v.10, pp.246–253. doi: https://doi.org/10.35291/2454-9150.2020.0047

    Google Scholar 

  • Asia, F.G. (2021) Future Land Use Land Cover Scenario Simulation Using Open-Source GIS. Published online 2021.

  • Aware, D. V., Navgire, M. E. and Aher, H. R. (2013) Assessment of the Water Quality Index of water body at Pravarasangam, Maharashtra. Internat. Jour. Eng. Res. Tech., v.2(11), pp.1363–1366.

    Google Scholar 

  • Barajas-Aceves, M. (2016) Organic Waste as Fertilizer in Semi-Arid Soils and Restoration in Mine Sites. In Organic Fertilizers — From Basic Concepts to Applied Outcomes. InTech. doi:https://doi.org/10.5772/62665

  • Barman, B.C., Saha, A., Dalal, S.S. De and Sinha, B. (2020) Introspect into Reservoir Sedimentation in Some Chotanagpur Plateau Drainage Basin. 2nd International Conference on Sustainable Water Management Organized by Water Resources Department, Govt. of Maharashtra during November 6–8, 2019 at Pune, Maharashtra, India. INTROSPECT, January.

  • Bera, S. (2018) Forest Cover Change Analysis Based on Remote Sensing and GIS of West Singbhum District, Jharkhand. Internat. Jour. Res. Appl. Sci. Eng. Tech., v.6(5), pp.1039–1050. doi:https://doi.org/10.22214/ijraset.2018.5167

    Article  Google Scholar 

  • Bilgin, A. (2018) Evaluation of surface water quality by using Canadian Council of Ministers of the Environment Water Quality Index (CCME WQI) method and discriminant analysis method: a case study Coruh River Basin. Environ. Monit. Assess., v.190(9) doi:https://doi.org/10.1007/s10661-018-6927-5

  • Branch, H. (2020) Analysis of Heavy Metal Contents and Non-carcinogenic Health Risk Assessment through Consumption of Tilapia Fish (Oreochromis niloticus). v.6(1), pp.59–67.

    Google Scholar 

  • Cabral, A.I.R., Silva, S., Silva, P.C., Vanneschi, L. and Vasconcelos, M.J. (2018) Burned area estimations derived from Landsat ETM+ and OLI data: Comparing Genetic Programming with Maximum Likelihood and Classification and Regression Trees. ISPRS Jour. Photogramm. Remote Sens., v.142(August 2017), pp.94–105. doi:https://doi.org/10.1016/j.isprsjprs.2018.05.007

    Article  Google Scholar 

  • Chakrabarti, T. (2019) Assessment of seasonal variations in physico-chemical parameters in Panchet reservoir, Dhanbad district, Jharkhand. Ann. Plant Soil Res., v.21(4), pp.390–394.

    Google Scholar 

  • Chakraborty, S. and Kumar, R.N. (2016) Assessment of groundwater quality at a MSW landfill site using standard and AHP based water quality index: a case study from Ranchi, Jharkhand, India. Environ. Monit. Assess. v.188(6) doi: https://doi.org/10.1007/s10661-016-5336-x

  • Chaturvedi, A., Bhattacharjee, S., Singh, A.K. and Kumar, V. (2018) A new approach for indexing groundwater heavy metal pollution. Ecol. Indic. v.87(June 2017), pp.323–331. doi:https://doi.org/10.1016/j.ecolind.2017.12.052

    Article  Google Scholar 

  • Christopher, S.F., Tank, J.L., Mahl, U.H., Yen, H., Arnold, J.G., Trentman, M.T., Sowa, S.P., Herbert, M.E., Ross, J.A., White, M.J. and Royer, T.V. (2017) Modeling nutrient removal using watershed-scale implementation of the two-stage ditch. Ecol. Eng., v. 108, pp.358–369. doi:https://doi.org/10.1016/j.ecoleng.2017.03.015

    Article  Google Scholar 

  • Costantini, M.L., Agah, H., Fiorentino, F., Irandoost, F., Trujillo, F.J.L., Careddu, G., Calizza, E and Rossi, L. (2021) Nitrogen and metal pollution in the southern Caspian Sea: a multiple approach to bioassessment. Environ. Sci. Pollut. Res. v.28(8), pp.9898–9912. doi: https://doi.org/10.1007/s11356-020-11243-8

    Article  Google Scholar 

  • Das, P.K., Das, B.P. and Dash, P. (2020) Chromite mining pollution, environmental impact, toxicity and phytoremediation: a review Environ. Chem. Lett., doi:https://doi.org/10.1007/s10311-020-01102-w

  • Deb, S. (2019) Drought fear looms large in Jharkhand as 14 districts face 40% rainfall deficit — Hindustan Times. Hindustan Times https://www.hindustantimes.com/ranchi/drought-fear-looms-large-in-jharkhand-as-14-districts-face-40-rainfall-deficit/story-BHb81baR1mfhQ8Ow3oUVMK.html

  • Deep, S and Saklani, A. (2014) Urban sprawl modeling using cellular automata. Egypt Jour. Remote Sens. Sp. Sci., v.17(2), pp.179–187. doi:https://doi.org/10.1016/j.ejrs.2014.07.001

    Google Scholar 

  • Delang, C.O. (2018) Causes and distribution of soil pollution in China. Environ Socio-economic Stud., v.5(4), pp.1–17. doi:https://doi.org/10.1515/environ-2017-0016

    Article  Google Scholar 

  • Devi, S., Srivastava, D.K. and Mohan, C. (2005) Optimal Water Allocation for the Transboundary Subernarekha River, India. Jour. Water Resour Plan Manag. v.131(4), pp.253–269. doi:https://doi.org/10.1061/(asce)0733-9496(2005)131:4(253)

    Article  Google Scholar 

  • Dinesan, V. P., Gopinath, G and Ashitha, M. K. (2015) Application of Geoinformatics for the Delineation of Groundwater Prospects Zones- A Case Study for Melattur Grama Panchayat in Kerala, India. Aquatic Procedia, v.4, pp.1389–1396. doi: https://doi.org/10.1016/j.aqpro.2015.02.180

    Article  Google Scholar 

  • Ding, J., Jiang, Y., Fu, L., Liu, Q., Peng, Q and Kang, M. (2015) Impacts of land use on surface water quality in a subtropical river basin: A case study of the dongjiang river basin, Southeastern China. Water (Switzerland), v.7(8), pp.4427–4445. doi:https://doi.org/10.3390/w7084427

    Google Scholar 

  • Eid, A.N.M., Olatubara, C.O., Ewemoje, T.A., El-Hennawy, M.T. and Farouk, H. (2020) Inland wetland time-series digital change detection based on SAVI and NDWI indecies: Wadi El-Rayan lakes, Egypt. Remote Sens. Appl. Soc. Environ., v. 19, pp.100347. doi: https://doi.org/10.1016/j.rsase.2020.100347

    Google Scholar 

  • El-Feky, M.M.M., Alprol, A.E., Heneash, A.M.M., Abo-Taleb, H.A and Omer, M.Y. (2018) Evaluation of water quality and plankton for mahmoudia canal in Northern west of Egypt. Egypt Jour. Aquat. Biol. Fish. v.22(5), pp.461–474. doi:https://doi.org/10.21608/ejabf.2019.26384

    Google Scholar 

  • Firozjaei, M.K., Sedighi, A., Firozjaei, H.K., Kiavarz, M., Homaee, M., Arsanjani, J.J., Makki, M., Naimi, B. and Alavipanah, S.K. (2021) A historical and future impact assessment of mining activities on surface biophysical characteristics change: A remote sensing-based approach. Ecol Indic., v.122(December 2020), pp.107264. doi:https://doi.org/10.1016/j.ecolind.2020.107264

    Article  Google Scholar 

  • Gautam, S.K., Maharana, C., Sharma, D., Singh, A.K., Tripathi, J.K. and Singh, S.K. (2015) Evaluation of groundwater quality in the Chotanagpur plateau region of the Subarnarekha river basin, Jharkhand State, India. Sustain. Water Qual. Ecol., v.6(013), pp.57–74. doi: https://doi.org/10.1016/j.swaqe.2015.06.001

    Article  Google Scholar 

  • Ghosh, A., Tiwari, A.K. and Das, S. (2015) A GIS based DRASTIC model for assessing groundwater vulnerability of Katri Watershed, Dhanbad, India. Model Earth Syst Environ. v.1(3), pp.1–14. doi: https://doi.org/10.1007/s40808-015-0009-2

    Article  Google Scholar 

  • Giri, S. and Singh, A.K. (2014) Assessment of human health risk for heavy metals in fish and shrimp collected from Subarnarekha river, India. Internat. Jour. Environ Health Res., v.24(5), pp.429–449. doi: https://doi.org/10.1080/09603123.2013.857391

    Article  Google Scholar 

  • Golmohammadi, G., Rudra, R., Prasher, S., Madani, A., Youssef, M., Goel, P and Mohammadi, K. (2017) Impact of tile drainage on water budget and spatial distribution of sediment generating areas in an agricultural watershed. Agric. Water Manag.. v.184, pp.124–134. doi:https://doi.org/10.1016/j.agwat.2017.02.001

    Article  Google Scholar 

  • Gorai, A.K., Hasni, S.A. and Iqbal, J. (2016) Prediction of ground water quality index to assess suitability for drinking purposes using fuzzy rule-based approach. Appl. Water Sci. v.6(4), pp.393–405. doi: https://doi.org/10.1007/s13201-014-0241-3

    Article  Google Scholar 

  • Gorde, S.P. and Jadhav, M.V. (2013) Assessment of Water Quality Parameters: A Review. Int Jour. Eng. Res. Appl., v.3(6), pp.2029–2035.

    Google Scholar 

  • Guha, S., Govil, H. and Besoya, M. (2020) An investigation on seasonal variability between LST and NDWI in an urban environment using Landsat satellite data. Geomatics, Nat. Hazards Risk., v. 11(1), pp.1319–1345. doi:https://doi.org/10.1080/19475705.2020.1789762

    Article  Google Scholar 

  • Gupta, D.B. and Mitra, S. (2004) Sustaining Subernarekha River basin. Int. Jour. Water Resour. Dev., v.20(3), pp.431–444. doi:https://doi.org/10.1080/0790062042000248529

    Article  Google Scholar 

  • Gupta, R. and Sharma, L.K. (2020) Efficacy of Spatial Land Change Modeler as a forecasting indicator for anthropogenic change dynamics over five decades: A case study of Shoolpaneshwar Wildlife Sanctuary, Gujarat, India. Ecol Indic., v.112(August 2019), pp.106171. doi:https://doi.org/10.1016/j.ecolind.2020.106171

    Article  Google Scholar 

  • Gupta, S.K. and Pandey, A.C. (2021) Spectral aspects for monitoring forest health in extreme season using multispectral imagery. Egypt Jour. Remote Sens. Sp. Sci., doi: https://doi.org/10.1016/j.ejrs.2021.07.001

  • Gutiérrez, J.P., van Halem, D., Uijttewaal, W.S.J., del Risco, E. and Rietveld, L.C. (2018) Natural recovery of infiltration capacity in simulated bank filtration of highly turbid waters. Water Res., v.147, pp.299–310. doi:https://doi.org/10.1016/J.WATRES.2018.10.009

    Article  Google Scholar 

  • Hembram, T.K. and Saha, S. (2020) Prioritization of sub-watersheds for soil erosion based on morphometric attributes using fuzzy AHP and compound factor in Jainti River basin, Jharkhand, Eastern India. Environ. Dev. Sustain., v.22(2), pp.1241–1268. doi: https://doi.org/10.1007/s10668-018-0247-3

    Article  Google Scholar 

  • Huang, H., Ouyang, W., Wu, H., Liu, H and Andrea, C. (2017) Long-term diffuse phosphorus pollution dynamics under the combined influence of land use and soil property variations. Sci. Total Environ., v.579, pp.1894–1903. doi: https://doi.org/10.1016/j.scitotenv.2016.11.198

    Article  Google Scholar 

  • Imran, M and Mehmood, A. (2020) Analysis and mapping of present and future drivers of local urban climate using remote sensing: a case of Lahore, Pakistan. Arab. Jour. Geosci., v.13(6) doi: https://doi.org/10.1007/s12517-020-5214-2

  • Islam, S., Tanim, A. H and Mullick, R. A. (2019) Land Use and Land Cover Classification of Coastal Districts of Bangladesh in a 10m Resolution of Sentinel-2 Satellite Image. Proc. Int. Conf. Planning, Archit Civil Eng. 9–11 February 2019, Rajshahi University of Engineering and Technology, Rajshahi, Bangladesh, February, 9–11.

  • Jabbar, F.K. and Grote, K. (2019) Statistical assessment of nonpoint source pollution in agricultural watersheds in the Lower Grand River watershed, MO, USA. Environ. Sci. Pollut. Res., v.26(2), pp.1487–1506. doi:https://doi.org/10.1007/s11356-018-3682-7

    Article  Google Scholar 

  • Jog, S. and Dixit, M. (2016) Supervised classification of satellite images. Conf. Adv. Signal Process. CASP. 2016, X, pp.93–98. doi: https://doi.org/10.1109/CASP.2016.7746144

    Article  Google Scholar 

  • Jothimani, M., Gunalan, J. and Duraisamy, R. (2021) Study the Relationship Between LULC, LST, NDVI, NDWI and NDBI in Greater Arba Minch Area, Rift. v.4, pp.183–193.

    Google Scholar 

  • JRC European Commission. (2011) NDWI (Normalized Difference Water Index) Product Fact Sheet, v.5(July), pp.6–7. http://edo.jrc.ec.europa.eu/documents/factsheets/factsheet_ndwi.pdf

    Google Scholar 

  • JSPCB. (2016) Action Plan for Rejuvenation of Subarnarekha River in Jharkhand. Jharkhand State Pollution Control. pp.1–56.

  • Kafy, A. Al Dey, N. N., Al Rakib, A., Rahaman, Z. A., Nasher, N. M. R. and Bhatt, A. (2021) Modeling the relationship between land use/land cover and land surface temperature in Dhaka, Bangladesh using CA-ANN algorithm. Environ. Challenges., v.4, pp.100190. doi:https://doi.org/10.1016/j.envc.2021.100190

    Article  Google Scholar 

  • Kafy, A. Al, Rahman, M. S., Faisal, A. Al, Hasan, M. M. and Islam, M. (2020) Modelling future land use land cover changes and their impacts on land surface temperatures in Rajshahi, Bangladesh. Remote Sens. Appl. Soc. Environ., v.18, pp.100314. doi:https://doi.org/10.1016/j.rsase.2020.100314

    Google Scholar 

  • Kamaraj, M and Rangarajan, S. (2021) Predicting the Future Land Use and Land Cover Changes for Bhavani Basin, Tamil Nadu, India Using QGIS MOLUSCE Plugin.

  • Kanakoudis, V., Tsitsifli, S., Samaras, P., Zouboulis and Demetriou, G. (2011) Developing appropriate performance indicators for urban distribution systems evaluation at Mediterranean countries. Water Util. Jour. pp.31–40.

  • Kang, L., Di, L., Deng, M., Yu, E and Xu, Y. (2016) Forecasting vegetation index based on vegetation-meteorological factor interactions with artificial neural network. 2016 5th Int Conf Agro-Geoinformatics, Agro-Geoinformatics, 2016, pp.1–6. doi:https://doi.org/10.1109/Agro-Geoinformatics.2016.7577673

  • Koko, A. F., Yue, W., Abubakar, G. A., Hamed, R and Alabsi, A. A. N. (2020) Monitoring and predicting spatio-temporal land use/land cover changes in Zaria City, Nigeria, through an integrated cellular automata and markov chain model (CA-Markov). Sustain. v.12(24), pp.1–21. doi:https://doi.org/10.3390/su122410452

    Google Scholar 

  • Krishna, R., Iqbal, J., Gorai, A. K., Pathak, G., Tuluri, F and Tchounwou, P. B. (2015) Groundwater vulnerability to pollution mapping of Ranchi district using GIS. Appl. Water Sci., v.5(4), pp.345–358. doi:https://doi.org/10.1007/s13201-014-0198-2

    Article  Google Scholar 

  • Kumar, A. and Pandey, A. (2013) Evaluating Impact of Coal Mining Activity on Landuse/Landcover Using Temporal Satellite Images in South Karanpura Coalfields. Int. Jour. Adv. Remote Sens. GIS, v.2(1), pp.183–197.

    Google Scholar 

  • Kumar, A., Rai, A.K. and Pandey, A.C. (2016) Geoinformatics based Site Suitability Modeling for Future Urban Development using MCDM-Analytic Hierarchy Process Techniques. Remote Sens. Natural Resources Management and Monitoring, February 2019, pp.378–399.

  • Kumar, V., Sharma, A., Kumar, R., Bhardwaj, R., Kumar Thukral, A and Rodrigo-Comino, J. (2020) Assessment of heavy-metal pollution in three different Indian water bodies by combination of multivariate analysis and water pollution indices. Hum. Ecol. Risk Assess., v.26(1), pp.1–16. doi:https://doi.org/10.1080/10807039.2018.1497946

    Article  Google Scholar 

  • Kumari, N. and Pandey, S. (2022) Sustainability Assessment of Jumar River in Ranchi District of Jharkhand using River Sustainability Bayesian Network (RSBN) model Approach. Ecol. Significance River Ecosyst. pp.407–428. doi:https://doi.org/10.1016/B978-0-323-85045-2.00021-2

  • Kumari, N and Pathak, G. (2014) A Review of Groundwater Quality Issue in Jharkhand Due to Fluoride. Int. Jour. Eng. Res. Appl., v.4(3), pp.65–77. www.ijera.com

    Google Scholar 

  • Li, C., Zhou, K., Qin, W., Tian, C., Qi, M., Yan, X and Han, W. (2019) A Review on Heavy Metals Contamination in Soil: Effects, Sources and Remediation Techniques. Soil Sediment Contam. v.28(4), pp.380–394. doi:https://doi.org/10.1080/15320383.2019.1592108

    Article  Google Scholar 

  • Liu, J., Shi, S., Shu, J., Li, C., He, H., Xiao, C., Dong, X., He, Y., Liao, J., Liu, N. and Lan, T. (2022). Synthesis and characterization of waste commercially available polyacrylonitrile fiber-based new composites for efficient removal of uranyl from U(VI)-CO3 solutions. Sci. Total Environ., v.822. doi:https://doi.org/10.1016/j.scitotenv.2022.153507

  • Ma, S., Wang, L. J., Zhu, D and Zhang, J. (2021) Spatiotemporal changes in ecosystem services in the conservation priorities of the southern hill and mountain belt, China. Ecol Indic. v.122, pp.107225. doi: https://doi.org/10.1016/j.ecolind.2020.107225

    Article  Google Scholar 

  • Ma, X., Li, Y., Zhang, M., Zheng, F and Du, S. (2011) Assessment and analysis of non-point source nitrogen and phosphorus loads in the Three Gorges Reservoir Area of Hubei Province, China. Sci. Total. Environ., v.412–413, pp.154–161. doi:https://doi.org/10.1016/j.scitotenv.2011.09.034

    Article  Google Scholar 

  • Mansour, S., Al-Belushi, M. and Al-Awadhi, T. (2020) Monitoring land use and land cover changes in the mountainous cities of Oman using GIS and CA-Markov modelling techniques. Land Use Policy, v.91, pp.104414. doi:https://doi.org/10.1016/j.landusepol.2019.104414

    Article  Google Scholar 

  • Matlhodi, B., Kenabatho, P. K., Parida, B. P and Maphanyane, J. G. (2019) Evaluating land use and land cover change in the Gaborone dam catchment, Botswana, from 1984–2015 using GIS and remote sensing. Sustain., v.11(19) doi:https://doi.org/10.3390/su11195174

  • Matta, G, Kumar, A., Nayak, A., Kumar, P., Kumar, A. and Tiwari, A.K. (2020) Determination of water quality of Ganga River System in Himalayan region, referencing indexing techniques. Arab. Jour. Geosci., v. 13(19) doi:https://doi.org/10.1007/s12517-020-05999-z

  • Maurya, C and Sharma, V. N. (2020) Land use/Land cover Change Detection in Auranga River Basin, Jharkhand. Natl. Geogr. Jour. India. v.66(1), pp.51–58. doi:https://doi.org/10.48008/ngji.1729

    Google Scholar 

  • Mehta, A and Singh, D.K. (2014) Modeling Landuse Impact on Runoff and Erosion — A Review. IOSR Jour. Mech. Civ. Eng., v.11(6), pp.54–61. doi:https://doi.org/10.9790/1684-11635461

    Article  Google Scholar 

  • Mendivil-Garcia, K., Amabilis-Sosa, L.E., Rodríguez-Mata, A.E., Rangel-Peraza, J.G., Gonzalez-Huitron, V. and Cedillo-Herrera, C.I. G. (2020) Assessment of intensive agriculture on water quality in the Culiacan River basin, Sinaloa, Mexico. Environ. Sci. Pollut. Res., v.27(23), pp.28636–28648. doi:https://doi.org/10.1007/s11356-020-08653-z

    Article  Google Scholar 

  • Mohamed, A. and Worku, H. (2020) Simulating urban land use and cover dynamics using cellular automata and Markov chain approach in Addis Ababa and the surrounding. Urban Clim. v.31(August 2019), pp.100545. doi:https://doi.org/10.1016/j.uclim.2019.100545

    Article  Google Scholar 

  • Mohan Rajan, S.N. and Loganathan, A. (2021) Modelling Spatial Drivers for LU/LC Change Prediction Using Hybrid Machine Learning Methods in Javadi Hills, Tamil Nadu, India. Jour. Indian Soc. Remote Sens., v.49(4), pp.913–934. doi:: https://doi.org/10.1007/s12524-020-01258-6

    Article  Google Scholar 

  • Mukherjee, Prabir, Singh, C.K. and Mukherjee, S. (2012) Delineation of Groundwater Potential Zones in Arid Region of India-A Remote Sensing and GIS Approach. Water Resour. Manag., v.26(9), pp.2643–2672. doi:https://doi.org/10.1007/s11269-012-0038-9

    Article  Google Scholar 

  • Mukherjee, Prasanjit and Kumar, J. (2019) Studies on the aquatic and semi-aquatic Angiosperms of Kanke Dam, Ranchi, Jharkhand. Phytotaxonomy, v.18.

  • Okeke, C., Abbey, S., Oti, J., Eyo, E., Johnson, A., Ngambi, S., Abam, T. and Ujile, M. (2021) Appropriate use of lime in the study of the physicochemical behaviour of stabilised lateritic soil under continuous water ingress. Sustain. v.13(1), pp.1–26. doi:https://doi.org/10.3390/su13010257

    Google Scholar 

  • Pal, S.C. and Chakrabortty, R. (2019) Simulating the impact of climate change on soil erosion in sub-tropical monsoon dominated watershed based on RUSLE, SCS runoff and MIROC5 climatic model. Adv. Sp. Res., v.64(2), pp.352–377. doi:https://doi.org/10.1016/j.asr.2019.04.033

    Article  Google Scholar 

  • Pal, S. and Debanshi, S. (2018) Influences of soil erosion susceptibility toward overloading vulnerability of the gully head bundhs in Mayurakshi River basin of eastern Chottanagpur Plateau. Environ. Dev. Sustain., v.20(4), pp.1739–1775. doi:https://doi.org/10.1007/s10668-017-9963-3

    Article  Google Scholar 

  • Pandey, S., Kumari, N, and Priya, S. (2021) Soil quality and pollution assessment around Jumar watershed of Jharkhand, India. Arab. Jour Geosci., v.14(24), pp.2748. doi:https://doi.org/10.1007/s12517-021-09091-y

    Google Scholar 

  • Park, E., Loc, H.H., Van Binh, D. and Kantoush, S. (2021) The worst 2020 saline water intrusion disaster of the past century in the Mekong Delta: Impacts, causes and management implications. Ambio. doi: https://doi.org/10.1007/s13280-021-01577-z

  • Pradhan, B., Chaudhari, A., Adinarayana, J. and Buchroithner, M. F. (2012) Soil erosion assessment and its correlation with landslide events using remote sensing data and GIS: A case study at Penang Island, Malaysia. Environ. Monit. Assess., v.184(2), pp.715–727. doi: https://doi.org/10.1007/s10661-011-1996-8

    Article  Google Scholar 

  • Pramanik, A.K., Majumdar, D. and Chatterjee, A. (2020) Factors affecting lean, wet-season water quality of Tilaiya reservoir in Koderma District, India during 2013–2017. Water Sci., v.34(1), pp.85–97. doi: https://doi.org/10.1080/11104929.2020.1765451

    Article  Google Scholar 

  • Rahmani, V., Kastens, J.H., de Noyelles, F., Jakubauskas, M.E., Martinko, E.A., Huggins, D.H., Gnau, C., Liechti, P.M., Campbell, S. W., Callihan, R.A. and Blackwood, A.J. (2018) Examining storage capacity loss and sedimentation rate of large reservoirs in the Central U.S. great plains. Water (Switzerland), v.10(2), pp.1–17. doi: https://doi.org/10.3390/w10020190

    Google Scholar 

  • Rangarajan, S., Thattai, D., Kumar, H., Satish, N. and Rustagi, R. Y.P. (2019) Evaluation of water quality index for River Mahananda West Bengal India. Int. Jour. Innov. Tech. Explor. Eng., v.8(6), pp.1307–1309.

    Google Scholar 

  • Reza, R. and Singh, G. (2010) Heavy metal contamination and its indexing approach for river water. Int. Jour. Environ. Sci. Tech., v.7(4), pp.785–792. doi: https://doi.org/10.1007/BF03326187

    Article  Google Scholar 

  • Rezaei, A. and Hassani, H. (2018) Hydrogeochemistry study and groundwater quality assessment in the north of Isfahan, Iran. Environ. Geochem. Health., v. 40(2), pp.583–608. doi: https://doi.org/10.1007/s10653-017-0003-x

    Article  Google Scholar 

  • Rimal, B., Rijal, S. and Kunwar, R. (2020) Comparing Support Vector Machines and Maximum Likelihood Classifiers for Mapping of Urbanization. Jour. Indian Soc Remote Sens., v.48(1), pp.71–79. doi:https://doi.org/10.1007/s12524-019-01056-9

    Article  Google Scholar 

  • Saha, S., Gayen, A., Pourghasemi, H.R. and Tiefenbacher, J. (2019) Identification of soil erosion-susceptible areas using fuzzy logic and analytical hierarchy process modeling in an agricultural watershed of Burdwan district, India. Environ. Earth Sci., v.78(23), pp.1–18. doi: https://doi.org/10.1007/s12665-019-8658-5

    Article  Google Scholar 

  • Sahay, R.R. (2011) Life forecasting of Getalsud Reservoir in India based on its sedimentation behaviour. Lakes. Reserv. Res. Manag., v.16(4), pp.287–292. doi:https://doi.org/10.1111/j.1440-1770.2011.00488.x

    Article  Google Scholar 

  • Sandeep, P., Reddy, G. P. O., Jegankumar, R. and Arun Kumar, K. C. (2021) Modeling and Assessment of Land Degradation Vulnerability in Semiarid Ecosystem of Southern India Using Temporal Satellite Data, AHP and GIS. Environ. Model. Assess., v.26(2), pp.143–154. doi:https://doi.org/10.1007/s10666-020-09739-1

    Article  Google Scholar 

  • Santy, S., Mujumdar, P. and Bala, G. (2020) Potential Impacts of Climate and Land Use Change on the Water Quality of Ganga River around the Industrialized Kanpur Region. Sci. Rep., v.10(1), pp.1–13. doi:https://doi.org/10.1038/s41598-020-66171-x

    Article  Google Scholar 

  • Sarangi, A. and Bhattacharya, A.K. (2005) Comparison of Artificial Neural Network and regression models for sediment loss prediction from Banha watershed in India. Agric Water Manag., v. 78(3), pp.195–208. doi:https://doi.org/10.1016/j.agwat.2005.02.001

    Article  Google Scholar 

  • Satheeshkumar, S. and Venkateswaran, S. (2022) Impact Assessment of Check Dam in the Pappiredipatti Watershed (South India) U https://doi.org/10.1007/978-3-030-79634-1_12

  • Shafiquzzaman, M., Alqarawi, S.M.A., Haider, H., Rafiquzzaman, M., Almoshaogeh, M., Alharbi, F. and El-Ghoul, Y. (2022) Evaluating Permeable Clay Brick Pavement for Pollutant Removal from Varying Strength Stormwaters in Arid Regions. Water (Switzerland), v.14(3) doi: https://doi.org/10.3390/w14030491

  • Sharma, B., Kumar, M., Denis, D.M. and Singh, S.K. (2019) Appraisal of river water quality using open-access earth observation data set: a study of river Ganga at Allahabad (India). Sustain. Water Resour. Manag., v.5(2), pp.755–765. doi:https://doi.org/10.1007/s40899-018-0251-7

    Article  Google Scholar 

  • Shashikant, V., Mohamed Shariff, A.R., Wayayok, A., Kamal, M.R., Lee, Y.P. and Takeuchi, W. (2021) Utilizing TVDI and NDWI to Classify Severity of Agricultural Drought in Chuping, Malaysia. Agronomy, v. 11(6), pp.1243. doi:https://doi.org/10.3390/agronomy11061243

    Article  Google Scholar 

  • Singh, L. N. and Mandhyan, M. (2017) Seasonal variation in water quality of Kharkai and Subernrekha river of Jamshedpur, Jharkhand. Internat. Jour. Res. Engg., Tech. Sci., v. VII, pp.1–6.

    Google Scholar 

  • Singh, P.K., Rathore, L.S., Athiyaman, B., Singh, K.K., Baxla, A.K., Kumar, A. and Bhargava, A.K. (2009) Frequencies of drought at Ranchi regions, Jharkhand. MAUSAM, v.60(4), pp.455–460. doi: https://doi.org/10.54302/MAUSAM.V60I4.1114

    Article  Google Scholar 

  • Singh, R.K., Villuri, V.G.K and Pasupuleti, S. (2021) Evaluation of water quality and risk assessment by coupled geospatial and statistical approach along lower Damodar river. Int. Jour. Environ. Sci. Tech. doi:https://doi.org/10.1007/s13762-021-03644-0

  • Singh, S., Bhardwaj, A and Verma, V.K. (2020) Remote sensing and GIS based analysis of temporal land use/land cover and water quality changes in Harike wetland ecosystem, Punjab, India. Jour. Environ. Managmt., v.262, pp.110355. doi:https://doi.org/10.1016/j.jenvman.2020.110355

    Article  Google Scholar 

  • Sran, D.S., Kukal, S.S and Singh, M.J. (2012) Run-off and sediment yield in relation to differential gully-plugging schemes in micro-catchments of Shiwaliks in the lower Himalayas. Arch. Agron. Soil Sci., v.58(11), pp.1317–1327. doi:https://doi.org/10.1080/03650340.2011.577422

    Article  Google Scholar 

  • Srivastava, P.K., Gupta, M and Mukherjee, S. (2012) Mapping spatial distribution of pollutants in groundwater of a tropical area of India using remote sensing and GIS. Appl. Geomatics., v. 4(1), pp.21–32. doi:https://doi.org/10.1007/s12518-011-0072-y

    Article  Google Scholar 

  • Surinaidu, L., Nandan, M. J., Sahadevan, D. K., Umamaheswari, A. and Tiwari, V. M. (2021) Source identification and management of perennial contaminated groundwater seepage in the highly industrial watershed, south India. Environ. Pollut., v.269, pp.116–165. doi: https://doi.org/10.1016/j.envpol.2020.116165

    Article  Google Scholar 

  • Tadesse, L., Suryabhagavan, K.V., Sridhar, G. and Legesse, G. (2017) Land use and land cover changes and Soil erosion in Yezat Watershed, North Western Ethiopia. Int. Soil Water Conserv. Res., v.5(2), pp.85–94. doi: https://doi.org/10.1016/j.iswcr.2017.05.004

    Article  Google Scholar 

  • Tamura, T., Nguyen, V. L., Ta, T. K. O., Bateman, M. D., Gugliotta, M., Anthony, E. J., Nakashima, R. and Saito, Y. (2020) Long-term sediment decline causes ongoing shrinkage of the Mekong megadelta, Vietnam. Sci. Rep., v.10(1), pp.4–10. doi: https://doi.org/10.1038/s41598-020-64630-z

    Article  Google Scholar 

  • Thakur, T.K., Patel, D.K., Dutta, J., Kumar, A., Kaushik, S., Bijalwan, A., Fnais, M.S., Abdelrahman, K. and Javed Ansari, M. (2021) Assessment of decadal land use dynamics of upper catchment area of Narmada River, the lifeline of Central India. Jour. King Saud Univ. Sci. v.33(2), pp.101322. doi:https://doi.org/10.1016/j.jksus.2020.101322

    Article  Google Scholar 

  • Tirkey, A.S., Ghosh, M and Pandey, A.C. (2016) Soil erosion assessment for developing suitable sites for artificial recharge of groundwater in drought prone region of Jharkhand state using geospatial techniques. Arab Jour. Geosci., v.9(5) doi: https://doi.org/10.1007/s12517-016-2391-0

  • Tirkey, A.S., Ghosh, M., Pandey, A.C. and Shekhar, S. (2018) Assessment of climate extremes and its long term spatial variability over the Jharkhand state of India. Egypt Jour. Remote Sens. Sp. Sci., v.21(1), pp.49–63. doi:https://doi.org/10.1016/j.ejrs.2016.12.007

    Google Scholar 

  • Tirkey, P., Bhattacharya, T., Chakraborty, S. and Baraik, S. (2017) Assessment of groundwater quality and associated health risks: A case study of Ranchi city, Jharkhand, India. Groundwater Sustain. Dev., v.5, pp.85–100. doi:https://doi.org/10.1016/j.gsd.2017.05.002

    Article  Google Scholar 

  • Tortajada, C. (2015) Dams: An Essential Component of Development. Jour. Hydrol. Eng., v.20(1) doi: https://doi.org/10.1061/(asce)he.1943-5584.0000919

  • Uddin, M.G., Nash, S. and Olbert, A.I. (2021) A review of water quality index models and their use for assessing surface water quality. Ecol. Indic., v.122, pp.107218. doi:https://doi.org/10.1016/j.ecolind.2020.107218

    Article  Google Scholar 

  • Upgupta, S. and Singh, P.K. (2020) Quantifying the Dynamics and Drivers of Landscape Change in an Opencast Coal Mining Area of Central India (East Bokaro, Jharkhand). Proc. Natl. Acad. Sci. India Sect A — Phys. Sci., v.90(3), pp.565–577. doi: https://doi.org/10.1007/s40010-018-0589-0

    Article  Google Scholar 

  • Varol, M. (2020) Use of water quality index and multivariate statistical methods for the evaluation of water quality of a stream affected by multiple stressors: A case study. Environ. Pollut., v.266, pp.115417. doi:https://doi.org/10.1016/j.envpol.2020.115417

    Article  Google Scholar 

  • Verma, P., Raghubanshi, A., Srivastava, P.K. and Raghubanshi, A. S. (2020) Appraisal of kappa-based metrics and disagreement indices of accuracy assessment for parametric and nonparametric techniques used in LULC classification and change detection. Model. Earth Syst. Environ., v.6(2), pp.1045–1059. doi: https://doi.org/10.1007/s40808-020-00740-x

    Article  Google Scholar 

  • Watson, C.S., King, O., Miles, E.S. and Quincey, D.J. (2018) Optimising NDWI supraglacial pond classification on Himalayan debris-covered glaciers. Remote Sens Environ. v.217(September), pp.414–425. doi: https://doi.org/10.1016/j.rse.2018.08.020

    Article  Google Scholar 

  • Yang, X., Zhao, S., Qin, X., Zhao, N. and Liang, L. (2017) Mapping of urban surface water bodies from sentinel-2 MSI imagery at 10 m resolution via NDWI-based image sharpening. Remote Sens., v.9(6), pp.1–19. doi:https://doi.org/10.3390/rs9060596

    Article  Google Scholar 

  • Zeshan, M.T., Mustafa, M.R.U. and Baig, M.F. (2021) Article monitoring land use changes and their future prospects using GIS and ANN-CA for peak river basin, Malaysia. Water (Switzerland), v.13(16), doi:https://doi.org/10.3390/w13162286

  • Zhang, Q. and Wang, C. (2020) Natural and Human Factors Affect the Distribution of Soil Heavy Metal Pollution: a Review. Water Air Soil Pollut., v.231(7), doi:https://doi.org/10.1007/s11270-020-04728-2

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Soumya Pandey.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Pandey, S., Kumari, N. & Al Nawajish, S. Land Use Land Cover (LULC) and Surface Water Quality Assessment in and around Selected Dams of Jharkhand using Water Quality Index (WQI) and Geographic Information System (GIS). J Geol Soc India 99, 205–218 (2023). https://doi.org/10.1007/s12594-023-2288-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12594-023-2288-y

Navigation