Impact of Urbanization on the Natural Groundwater Recharge of Karuvannur Watershed

Transcription

1 Proceedings of International Conference on Materials for the Future - Innovative Materials, Processes, Products and Applications ICMF Impact of Urbanization on the Natural Groundwater Recharge of Karuvannur Watershed Ginu S Malakeel and Prof. K.O.Vargheese Abstract Change in land use is an important issue and concern for water resources management. Groundwater recharge is the portion of infiltrated water that flows beyond the root zone and ultimately reaches the aquifer. The quantity and quality of groundwater recharge can be significantly affected by urbanisation. The main objective of the study is to quantify the natural groundwater recharge from infiltrated precipitation in a watershed under urban development. Water Balance Approach is the simplest way to estimate the change in groundwater recharge due to land use change (urban development) in a watershed. In this study the effect of urbanization on recharge in the Karuvannur river basin is estimated. The FAO (Food and Agriculture Organization under UNESCO) method is used for the estimation of evapotranspiration and the SCS curve number is used for estimating infiltration on a daily time scale. The land use in the years 1967, 1990, 2000 and 2010 were developed from the topographical sheets and satellite imageries. The river basin was divided into soil/land cover combinations or hydrologic response units by overlaying the land use and soil map in the Arc GIS software. The changes in infiltration, evapotranspiration and storage was estimated for various hydrologic response units. The annual recharge was estimated as the weighted average of the recharges of the various hydrologic groups using the model. Impact of urbanization was found out by calculating the difference in ground water recharge for the years 1967 and 2010 using constant meteorological data. Keywords Groundwater Recharge, Soil Water Balance, Evapotranspiration, Infiltration, GIS I. INTRODUCTION ECHARGE is the process by which surface water is added R to groundwater in the hydrological cycle. The process occurs following the addition of water to the land surface by rainfall, melting of snow, or overland flow, and infiltration. The rate of recharge can be much smaller than the rate of infiltration because evaporation from shallow pores in the soil or transpiration by plants can return water to the atmosphere before it makes its way to the water-table. Recharge is one of the most difficult components of the hydrological cycle to quantify. It is often estimated indirectly as a water balance residual by subtracting estimated rates of runoff and Ginu S Malakeel, Department of Civil Engineering, Government Engineering College Thrissur. ginusaji@gmail.com Prof. K.O.Vargheese, Department of Civil Engineering, Government Engineering College Thrissur. evapotranspiration from precipitation. Rainfall is the principal source for replenishment of moisture in the soil water system and recharge to ground water. The amount of recharge depends upon the rate and duration of rainfall, the subsequent conditions at the upper boundary, the antecedent soil moisture conditions, the water table depth and the soil type. Estimating the rate of aquifer replenishment is probably the most difficult of all measures in the evaluation of ground water resources. Estimates are normally and almost inevitably subject to large errors. No single comprehensive estimation technique has yet been identified from the spectrum of those available, which gives reliable results. Recharge estimation can be based on a wide variety of models which are designed to represent the actual physical processes. The methods, commonly in use for estimation of natural ground water recharge, include ground water balance method, soil water balance method, zero flux plane method, onedimensional soil water flow model, inverse modelling technique, and isotope and solute profile techniques. As urban development encroaches on rural and natural areas, groundwater recharge may decrease. The volume of water stored and/or available groundwater may decrease because of reduced infiltration. The construction of roads, buildings, and parking lots will typically increase the amount of impervious areas. More surface runoff, less water infiltration into the soil, and less water recharge to aquifers are often the consequences of urban development. This is an important issue not only for ground water withdrawal to meet society s need, but also for cold-water organisms, such as trout, in groundwater-fed streams. If the groundwater recharge rate is decreased, less groundwater will be available to feed coldwater streams, and more, warmer surface run-off will raise stream temperatures which will affect these organisms. The study uses simple methodology to assess the variability of groundwater recharge at the regional scale using remote sensing and GIS techniques. The FAO-SCS model and FAO- GA model is used to calculate net recharge for different combinations of soil and land use. II. METHODOLOGY A. General Water balance techniques have been extensively used to make quantitative estimates of water resources and the impact of man's activities on the hydrologic cycle. On the basis of the water balance approach, it is possible to make a quantitative evaluation of water resources and its dynamic behaviour under the influence of man's activities. With water balance approach, it is possible to evaluate quantitatively individual contribution

2 Proceedings of International Conference on Materials for the Future - Innovative Materials, Processes, Products and Applications ICMF of sources of water in the system, over different time periods, and to establish the degree of variation in water regime due to changes in components of the system. The basic concept of water balance is: Input to the system - Outflow from the system = change in storage of the system (over a period of time) Groundwater recharge is defined for use in this paper as the amount of water that flows beyond the root zone, i.e. the reach of vegetation, and ultimately reaches an aquifer through vertical percolation or seepage annually or seasonally. The two major sources of groundwater recharge to aquifers are infiltration and percolation from precipitation, and seepage from surface water bodies. The fraction of precipitation that becomes recharge depends on many factors that influence the water s ability to reach the saturated zone (aquifer). A large fraction of precipitation becomes surface runoff that flows overland to streams and lakes. The remaining water infiltrates into the soil and a large portion of this water will be intercepted and discharged back into the atmosphere by plants during evapotranspiration. The amount of water that reaches the aquifer (recharge) depends on various climate parameters including intensity and duration of rainfall events, soil characteristics (such as soil s permeability, moisture content, and thickness) and depth, topography, vegetative land cover, and aquifer depth, that are hard to quantify due to the spatial and temporal variations that exist in natural systems. The various steps followed in this study are Delineation of the study area Preparation of land use map using ERDAS IMAGINE and ArcGIS softwares. Preparation of soil group map for the study area Determination of various soil type - land cover combinations by overlaying land use map and soil map in ArcGIS Determination of soil water budget components for each soil type land cover combination Determination of the ground water recharge for the entire watershed B. Estimation of Evapotranspiration Evapotranspiration (ET) is a major component of the hydrologic cycle. Evapotranspiration is important to groundwater recharge as an abstraction because it accounts for the water that plants extract through their roots from the soil water that has infiltrated from the ground surface. Evapotranspiration depends on plant type, climate, and soil characteristics. A standard method specified by the FAO- 56 for estimating Evapotranspiration is to first estimate a reference evapotranspiration (ETo) that is multiplied by a crop coefficient (kc) to obtain the crop evapotranspiration (ETc) [1]. Crop coefficients depend on plant characteristics and local conditions. The crop evapotranspiration (ETc) is multiplied by a stress coefficient (ks) to represent the water stress on the crop to obtain actual evapotranspiration (ETa). Therefore ETa can be estimated using (1) Where ETa = actual evapotranspiration (mm/day); kc = crop coefficient; ks = water stress coefficient ; ET 0 = reference evapotranspiration (mm/day). Reference Evapo-transpiration is calculated by Penman equation as Where ET 0 = Daily reference evapotranspiration; Rn =net radiation at the crop surface [MJ m -2 day -1 ]; G= soil heat flux density [MJ m -2 day -1 ]; T =mean daily air temperature at 2 m height [ C]; u2= wind speed at 2 m height [m s -1 ]; e s = saturation vapour pressure [kpa],; e a = actual vapour pressure [kpa]; Δ= slope of the vapour pressure curve [kpa C -1 ]; ϒ = psychrometric constant [kpa C -1 ]. The slope of the curve (Δ) at a given temperature is given by, The net radiation (Rn) is the difference between the incoming net shortwave radiation (Rns) and the outgoing net longwave radiation (Rnl): (4) The net shortwave radiation (Rns) is given by: (5) Where, R ns =net solar or shortwave radiation [MJ m -2 day - 1 ];α=albedo or canopy reflection coefficient, which is 0.23 for the hypothetical grass reference crop [dimensionless]; R s = the incoming solar radiation [MJ m -2 day -1 ]. The net longwave radiation (R nl ) is estimated as where R nl = net outgoing longwave radiation [MJ m -2 day -1 ]; σ =Stefan-Boltzmann constant [ 4.903x 10-9 MJ K -4 m -2 day -1 ]; Tmax,K =maximum absolute temperature during the 24-hour period [K= C ];Tmin,K minimum absolute temperature during the 24-hour period [K = C ],e a =actual vapour pressure [kpa]; R s /R so relative shortwave radiation (limited to 1.0);R s measured or calculated solar radiation [MJ m -2 day - 1 ];R so calculated clear-sky radiation [MJ m -2 day -1 ]. While reference crop evapotranspiration accounts for variations in weather and offers a measure of the "evaporative demand" of the atmosphere, crop coefficients account for the difference between the vegetative types of crops. A crop coefficient (kc) is the ratio of evapotranspiration by a particular crop (ET c ) relative to reference evapotranspiration (ET 0 ) for a reference crop such as grass or alfalfa. The water stress component, k s is used to reduce k c under conditions of water stress or salinity stress. Mean water content of the root zone in the FAO-56 procedure is expressed by root zone depletion, Dw ie, water shortage relative to field capacity. Stress is presumed to initiate when Dw exceeds RAW, the depth of readily available water in the root zone. (2) (3) (6)

3 Proceedings of International Conference on Materials for the Future - Innovative Materials, Processes, Products and Applications ICMF For Dw > RAW, k s is given by Where TAW = Total available soil water in root zone (mm); p= fraction of TAW that a crop can extract from the root zone without suffering water stress. Given dr = root zone depth (mm); θ FC = Field capacity ; θ WP =Wilting point TAW = (θ FC - θ WP )dr (8) C. Estimation of Infiltration Infiltration is defined as the process of water penetrating into the soil. The rate of infiltration is influenced by the condition of the soil surface, vegetative cover, and soil properties including porosity, hydraulic conductivity, and moisture content [7]. Soil Conservation Service (SCS) curve number method and the Green Ampt (GA) method is used in this study to determine the infiltration. The U.S. Department of Agriculture Soil Conservation Service (SCS), now the National Resources Conservation Service (NRCS), has developed a rainfall-runoff relationship for watersheds [7]. The SCS method relates infiltration to the total amount of precipitation during a storm event using curve numbers, to account for interception, retention and other processes that relate to run-off and infiltration. Empirical studies by the SCS indicate that the potential maximum retention can be estimated as Where S cn =potential maximum retention in mm and CN=runoff curve number. CN is a function of land use, antecedent soil moisture, and other factors affecting runoff and retention in a watershed. It is assumed that all abstracted water will infiltrate after the rainfall event, although some of the abstracted water will remain in ponds and evaporate. With this assumption rough estimate can be obtained of water remaining in the watershed that can infiltrate. In this method the infiltration is termed as the total abstraction (A) and is calculated as (7) (9) (10) If the precipitation (P) is less than the initial abstractions (Ia), the infiltration is assumed to be equal to precipitation (P). The initial abstraction (Ia) is given by (11) III. RECHARGE ESTIMATION The present study is carried out in the Karuvannur river basin of Thrissur district. The Karuvannur river basin lies between N and N latitudes and E and E longitudes. It is bounded by Thrissur and Chavakkad taluks of Thrissur district in the North, Mukundapuram and Kodungallur taluks of Thrissur district in the South, Alathur and Chittur taluks of Palakkad district in the East and Arabian Sea in the West. The watershed has a total area of sq.km covering 34 villages spread over 32 panchayats, 9 blocks and 2 districts[8]. The major river draining through this watershed is the Karuvannur river which has a length of 48km. The river originates from the Western Ghats and takes a westerly direction and joins the backwaters. The tributaries of the river are Chaurala Ar, Payampara Ar, Maripara Ar, Anaparam Ar, Chimonipuzha, Talikuzhi, Mupilypuzha, Idukuparathodu, Sinikuzhithodu, Kurumalipuzha, Manali Ar, Pullathodu and Karanjirapuzha. Fig. 1. Location map of Karuvannur watershed A. Preparation of Hydrologic Response Groups Soils are classified by the Natural Resource Conservation Service into four Hydrologic Soil Groups based on the soil's runoff potential. The four Hydrologic Soils Groups are A, B, C and D, where A generally have the smallest runoff potential and D the greatest. The soil groups are described as Group A is sand, loamy sand or sandy loam types of soils. It has low runoff potential and high infiltration rates even when thoroughly wetted. They consist chiefly of deep, well to excessively drained sands or gravels and have a high rate of water transmission. Group B is silt loam or loam. It has a moderate infiltration rate when thoroughly wetted and consists chiefly or moderately deep to deep, moderately well to well drained soils with moderately fine to moderately coarse textures. Group C soils are sandy clay loam. They have low infiltration rates when thoroughly wetted and consist chiefly of soils with a layer that impedes downward movement of water and soils with moderately fine to fine structure. Group D soils are clay loam, silty clay loam, sandy clay, silty clay or clay. This HSG has the highest runoff potential. They have very low infiltration rates when thoroughly wetted and consist chiefly of clay soils with a high swelling potential, soils with a permanent high water table, soils with a claypan or

4 Proceedings of International Conference on Materials for the Future - Innovative Materials, Processes, Products and Applications ICMF clay layer at or near the surface and shallow soils over nearly impervious material. Soil map collected from Kerala State Land use board contained five soil types in the study area namely sandy, clay,sandy loam,loam and gravelly clay. These soil types were reclassified into A, B and D to be used for the SCS curve method. The land use map of the basin was prepared by remote sensing technique using ERDAS IMAGINE and ARCGIS 10 software[2]. In this study LANDSAT images for the year 2008 and Survey of India toposheets (1967) have been used for the preparation of land use map. Digital image processing using supervised classification method was used for the creation of land use map from the satellite imagery. The landuse map thus created by the ERDAS IMAGINE which was in raster format was then converted to vector format by using conversion tool in the Arc GIS software. The land use map for the year 1967 was created by digitizing the land uses in the topographical sheet. A vegetation (plant) type was assigned to each land-use type and land-uses with similar plant types were grouped together into land cover groups. Three plant (vegetation) types were assumed to be associated with the different land-use types in the study area. They are 1) row crops were associated with agriculture; 2) turf grass was associated with industrial and institutional developments, multifamily homes, retail/offices, single family homes, and town-homes; 3) trees with grass were associated with parks/preserves and undeveloped/natural land uses. Water bodies were not considered in this study since our main aim is to quantify infiltrated recharge from precipitation only and not the recharge from seepage flow. The hydrological response unit was obtained by overlaying the land use map and the soil map using the intersect operator in Arc GIS. Nine hydrologic response units were obtained for the Karuvannur watershed. Each hydrologic response unit was then assigned a runoff curve number depending on the land use and underlying soil group. The curve number corresponding to the antecedent moisture condition (AMC) was considered. B. Determination of Recharge using soil water balance method The water balance models use equations for physical processes that occur in a soil column to estimate groundwater recharge. The soil column is treated as a hypothetical container that has a depth equal to the root depth of the vegetation that grows on the surface of the container. This depth is also known as the root zone. The water that percolates below the root zone is assumed to be beyond the reach of the roots; it becomes the groundwater recharge. A soil water budget for estimating groundwater recharge is given as (14) Where R i = groundwater recharge for day I (mm);p i = precipitation for day i (mm); RO i = runoff for day i (mm);irr i = net irrigation depth on day i, that infiltrates the soil (mm); CR i = capillary rise depth from groundwater table on day i (mm); ET a,i = crop evapotranspiration depth on day i (mm); ΔS i/t = change in storage in the soil for day i (mm). Precipitation minus runoff (P-RO) is termed as infiltration, I. The change in storage is a function of infiltration, evapotranspiration, soil type, and soil moisture content. Rewriting (14), ignoring irrigation and capillary rise, and inserting infiltration give the relationship (15) Equation (15) gives the water budget assuming a homogeneous soil and vegetative cover. After the recharge for each combination is estimated, a weighted average of the combinations can be taken to estimate a representative groundwater recharge rate for the entire watershed. The FAO-SCS model originally developed by Erickson and Stefan is used to estimate the recharge in this study. The model uses a water budget for a soil container to estimate groundwater recharge by tracking the root zone depletion (i.e. change in storage)[4]. Deep percolation (recharge) is the excess soil water depth following heavy rain, when the soil water content in the root zone exceeds field capacity. Below field capacity, the soil moisture is assumed to be held in the soil and the gravitational effect on the water is assumed to be negligible. If the soil moisture content exceeds the field capacity, it is assumed that the soil water content returns to field capacity (θ fc ) within the day of rainfall event so that the depletion D w,i becomes zero, and all soil water that is above the field capacity will percolate past the root zone under gravity during the same day. Therefore, following heavy rain, deep percolation (groundwater recharge) due to precipitation is given as (16) where I i = daily infiltration depth for day i (mm);et a,i = daily evapotranspiration depth for day i (mm); D w,i-1 = daily soil water depletion for day i-1 (mm). The daily soil water depletion is defined as the depth of soil water depleted by plants that is needed in the soil column to reach field capacity. As long as the soil water content in the root zone is below field capacity (i.e., D w,i > 0), the soil will not drain and DPi = 0. The root zone depletion, Dw, can be estimated by rearranging (16) and using the previous day s estimates (17) Where D w,i = root zone depletion depth for end of day i (mm); D w,i-1 = root zone depletion depth at the end of pervious day i-1 (mm); Ii = infiltration depth for end of day i (mm); ET c,i = crop evapotranspiration depth on day i (mm); DP i = water loss from root zone by deep percolation on day i (mm). This model can be used to estimate annual groundwater recharge on a daily timescale. IV. RESULTS AND DISCUSSION The land uses and the hydrologic response units of the year 1967, 1990, 2000 and 2010 were mapped and their areas were determined. Landuse maps for the above mentioned years have shown below. The change in landuse for various years, based on assigned vegetation types are given in Table II. It shows that uncultivable land and built up area increased while forest and crop land declined continuously from 1967 till Also we can see that about 55% of the agricultural area in 1967 was transformed to plantation in 2010.To further

5 Proceedings of International Conference on Materials for the Future - Innovative Materials, Processes, Products and Applications ICMF evaluate real losses and gains of the different land use classes, matrices of land use changes in sq.km from 1967 to 2010 were shown in Table I. Due to urbanization, the area of turf grass was found to increase and that of row crops and trees was found to decrease from 1967 to Fig. 2. Landuse map of 1967 The infiltration was estimated for the different hydrologic response units using SCS curve number method (7). The values of depletion fraction for no stress, field capacity, wilting point and root zone depth used for the various soil groups are shown in Table III[5]. The soil water balance components which include infiltration, evapotranspiration and change in soil moisture for the years 2010, 2000, 1990 and 1967 were estimated using FAO SCS model and FAO - GA model with the meteorological data of the respective year and also with constant meteorological data. Fig. 5. Landuse map of 2010 This was done in order to make sure that change in recharge is not due to the change in meteorological data. The soil water balance components determined using meteorological data of each year are given in Table IV and V and that using constant meteorological data for all years are given in Table VI and VII. Table I: Landuse Change Transformation Matrix Table II: Change in Landuse for Various Years in Percentage Table III: Parameters Used for FAO-SCS Model Fig. 3. Landuse map of 1990 Fig. 4. Landuse map of 2000

6 Proceedings of International Conference on Materials for the Future - Innovative Materials, Processes, Products and Applications ICMF Table IV: Soil Water Budget Components Using FAO-SCS Model (Using Meteorological Data of Respective Years) Year Precipitation Infiltration Evapotranspiration Recharge The recharge was found to decrease with increase in the built up area from 1967 to It was found to decrease from 45.75% in 1967 to 38.7% in 2010 using FAO-SCS. The lesser variation may be because although the built up area has increased from 1967 to 2010, there is a considerable increase in the area of plantation also. Table V: Soil Water Budget Components Using Fao-Scs Model (Using Constant Meteorological Data) Higher the curve number, less amount of water infiltrates into the soil. V. CONCLUSION The change in landuse was estimated using land uses of the years 1967, 1990, 2000 and 2010.The impact of urbanisation on ground water resources is analyzed in terms of annual recharge of various years using the two soil water balance models. Recharge was found to decrease as a result of the land use change during the years The recharge shows a decreasing trend with increase in built up area. But it has been found that although there is an increase in the built up area, area of plantation has also increased. Infact, about 55% of the agricultural area in 1967 was transformed to plantation in Therefore, only about 7% decrease in the groundwater recharge was calculated using the FAO models. So we can conclude that although there is a change in landuse in this region, groundwater recharge has not decreased tremendously and hence artificial recharge measures are not an immediate necessity for this watershed. ACKNOWLEDGMENT Sincere acknowledgement is given to the firms KFRI Thrissur, Soil Survey of India and Hydology department, Thrissur for providing data. The FAO-SCS model incorporates the effect of urbanisation in terms of curve number which is dependent on the land use, and the root zone depth of the vegetation. As urbanized area increases the turf grass region whose root zone depth is high increases and hence the amount of recharge gets reduced. In case of FAO-SCS model along with the effect of root zone depth, urbanisation increases the curve number also. REFERENCES [1] Allen,R.G.,Pereira,L.S.,Smith,M., Raes,D. and Wright,J.L, FAO-56 Dual Crop Coefficient Method for Estimating evaporation from soil and Application Extensions.Journal of Irrigation and Drainage Engineering, ASCE,Vol-131, pp.2-13,2005. [2] Divya Bhoopesh, M.B. Joisy, Impact of urbanisation on the recharge of Karamana river basin, National Technological Congress, Kerala, [3] Dynamic Groundwater Resources of Kerala, Groundwater Department and Central Groundwater Department,March [4] Erickson,T.O. and Stefan, H.G. Groundwater Recharge on a changing landscape, Saint Anthony Falls Laboratory Project Rep. No. 507, Univ. of Minnesota, [5] Mays, Larry W, Water Resources Engineering, 2005 Edition. John Wiley and Sons,Inc., Hoboken, New Jersey, [6] Szilagyi,J.,Harvey F.E.and Ayers J.F, Regional estimation of base recharge to ground water using water balance and a base flow index,ground Water,Vol.41,No.4, [7] Urban hydrology for Small Watersheds,Technical Release 55, [8] Water Atlas Of Kerala, Centre for Water Resources Development and Management, Kozhikode, 1995.