Reaction Kinetics for Modeling Non-Point Source Pollution of Nitrate with SWAT Model

Transcription

1 Reaction Kinetics for Modeling Non-Point Source Pollution of Nitrate with SWAT Model Narula, K.K., and Gosain, A.K Indian Institute of Technology Delhi 4 th International SWAT Conference 5 th July 27 Delft (The Netherlands)

2 Water resources - vital statistics Rainfall: 4 bcm/yr, translates into water resources (~48), groundwater recharge (~ 11). Water consumers - Agriculture (85); Domestic (4) Availability of water per capita (cu.m/ca/year) World: 67 North America : > 15, India : ~ 12

3 Gross Area Sow n (mha) Net Area 18 Sow n (mha) Area under HYV (mha) Land per capita 195 s:.89 ha 2 s:.33 ha Food grain yields All India cultivated area ( ) Year Foodgrain production Yield (kg ha -1 ) Year Agriculture Meeting requirements of food grains under limited land and water conditions.asks for intensification (HYV, crop intensity) Area cultivated (mha)

4 Fertilizer use and food grain yields Increase in irrigation and fertilizer use Implications of intensification Year Fertilizer consumption (kg ha -1 ) Yield (kg ha -1 ) Total fertilizer consumption Yield of foodgrains Fertilizer use w ith type Year Total fertilizer consumption (MT) Nitrate consumption (MT) Phosphate consumption (MT) Potash consumption (MT) Consumption (MT)

5 Groundwater Impact of excessive use of nitrogenous fertilizers Drinking water quality standard for nitrates: 45 mg l -1 Surface water District State Nitrate (mg l -1 ) Mathura Uttar Pradesh 279 Aligarh Uttar Pradesh 27 Agra Uttar Pradesh 24 Mahendragarh Haryana 131 Gurgaon Haryana 722 Hisar Haryana 419 Ambala Haryana 419 Bhatinda Punjab 567 Ludhiana Punjab 265 Peddavoora Andhra Pradesh 53 Source Kansal et al. (1992); CPCB, MINARS (1997) Data generated from its 48 river quality monitoring stations, mean nitrate values have increased from.4 mg l -1 in 1979 to 2.8 mg l -1 in 2 Nitrate exceedence frequency i.e., stations reporting nitrates exceeding the standard, has increased from 2 in 1979 to 1 in the year 2 (Source: Analysed from datasets published by CPCB, MINARS Series ).

6 HIMACHAL PRADESH Simla Solan Sirmaur HARYANA Yamuna nagar UTTAR PRADESH Dehradun Uttarkashi Tehri Garhwal UTTARANCHAL Study area Upper Yamuna river sub basin HIMACHAL PRADESH Solan Simla Uttarkashi Sirmaur Tehri Garhwal [ Solan [ Simla River Giri [ Kotkhai Chopal [ Jubbal [ River Tons River Yamuna Jamunotri HARYANA Yamuna nagar UTTAR PRADESH UTTARANCHAL Dehradun Chakrata [ District boundary Elevation (m above msl) Hypsometric curve Paonta [ Tajewala [ Koti [ Dakpathar [ Dehradun [ [ Mussoorie Scale: 1 cm = 14 km Catchment boundary Streams catchment area above elevation

7 N Solan Simla Pachchad Kotkhai Chopal Jateon Paonta Jubbal Chakrata Koti Dakpathar Mussoorie Raingage Mussoorie Tajewala Dehradun 2 Kilometers January February March April May June July Precipitation (mm) August September October November December Mussoorie February March April May June July August September October November December January February March April May June July August September Percentage probability () October November Simla w et days w et day after w et day ( of total days) w et day after w et day ( of total w et days) (c) Precipitation (mm) January February March April May June July August September October November December Precipitation distribution in the sub basin Simla (a) w et days w et day after w et day ( of total days) w et day after w et day ( of total w et days) percentage probability () January

8 N 3 1 Kotkhai Jubbal Yashwantnagar # 13 Pachchad Jateon 18 Chopal 17 # 8 Tuini # Damta 1 Paonta 2 19 # Lakhwar 16 # Runoff gages Streams Sub catchments Tons sub catchment Lakhwar sub catchment Giri sub catchment 3 Kilometers

9 Subject area Data basis Source and map scale Basic data Boundaries of the river basin, administrative Survey of India (SoI); 1: 5 boundaries, stream networks Climatic data Soil-physical data Mean monthly and daily precipitation, maximum and minimum temperature, solar radiation, wind speed, potential evaporation Soil characterstics ( silt, sand, clay, rocks), field capacity, wilting point, hydraulic conductivity, depth to water table, properties for different soil layers varying with depth Indian Meteorological Departme (IMD) National Bureau of Soil Survey an Land use planning (NBSS& LUP); 1:25 Landuse data Ground cover SoI, Satellite Imageries, Sta Agricultural Board 1:5 and 1:25 Hydrogeological data and groundwater fluctuation Groundwater-bearing lithologic units, transmissivity, hydraulic conductivity, groundwater levels, fluctuations, hydrochemical data, water use (pumping and extraction) Topography data Elevation contours SoI; 1: 5 Geological Survey of India (GSI National Thematic Ma Organization (NATMO), CGWB SGWB, 1: 25 Gauge data Daily river flows Chander et al. (1984), Central Wat Commission, Ministry of Wat Resources Crop and fertilizer data Water quality data Nitrogenous fertilizers use, crop yields and types of crops; gross and net cropped areas Surface water quality (Nitrate concentrations), ground water quality (nitrate concentrations) Fertilizer Statistics, Fertiliz Association of India (FAI) Central Pollution Control Boa (CPCB); State PCB, Station-wi data

10 8 Daily stream flow (Dam ta upstream station) Flow (cumecs) Results of SWAT Simulated flow s Observed flow s Scatterplot of observed and simulated daily flow s w ith the SWAT model (1976 to 1978, Damta upstream station) 8 Date (mmddyy) Sub-basin Damta upstream station 6 R 2 =.7248 R 2 (daily) Nash and Sutcliffe coefficient (daily) Simulated flow s (cumecs) Observed flow s (cumecs)

11 16 Daily stream flow (Lakhw ar station) Simulated runoff Observed runoff Date Scatterplot of observed and simulated daily flow s w ith the SWAT model (1976 to 1978, Lakhw ar station) R 2 =.7717 Flow (cumecs) Sub-basin Lakhwar station 1:1 R 2 (daily).7717 Nash and Sutcliffe coefficient (daily) Simulated flows (cumecs) Observed flows (cumecs)

12 Nitrate loads in surface w ater (Lakhw ar) Date Daily flow (cumecs) Daily load (kg/ day) Daily flow s (cumecs) Daily nitrate load (kg/day) 6 Nitrate concentration at Lakhw ar Nitrate concentration (mg/l) OB 1976-SIM 1977-OB 1977-SIM 1978-OB 1978-SIM Maximum value for the year Minimum value for the year Mean daily value for the year

13 Nitrate loads in surface water (Giri at Yashwantnagar) Date Daily flow (cumecs) Daily nitrate load (kg/day) Daily flow (cumecs) Daily nitrate load (kg/day) Nitrate concentration at Yashw antnagar OB 1976-SIM 1977-OB 1977-SIM 1978-OB 1978-SIM Nitrate concentration (mg/l) Maximum value for the year Minimum value for the year Mean daily value for the year

14 Summary of the results The study has been successful in calibrating and validating the model consisting of the following components, Streamflow Groundwater levels Nitrates in surface water The simulated nitrate concentrations show a deviation from the observed values The model requires studying nitrate transformation processes in the unsaturated zone of the soil matrix since these have a direct bearing on nitrate transport in surface and groundwater Review of various models shows that Michaelis-Menten kinetics, a mixed-order kinetics, is well suited for simulating microbial action and growth under the influence of various environmental conditions and substrate concentration This aspect has been studied further

15 Field tests for examining the kinetics Parameter Unit Entisol Anthrosol Organic matter g kg Total N g kg NH 4 + mg kg NO 3 - mg kg ph Water holding capacity Density g cm Particle size distribution Sand (2.2 mm) Silt (.2.2 mm) Clay (<.2 mm)

16 N (g/ sqm) Simulation results and comparison of kinetics Simulation of nitrification using published data Simulation of nitrification in Anthrosols N (g/ sqm) Time (days) Time (Days) NH4+: Michaelis NH4+: SWAT NH4+: Observed NO3-: Observed NO3-: Michaelis NO3-: SWAT NO3-: Michaelis menten NO3-: SWAT NO3-: Observed Scatterplot of observed and simulated nitrates due to nitrification 16 Experimental station R 2 Nash and Sutcliffe SWAT (Entisol) Michaelis-Menten (Entisol) SWAT (Anthrosol).85.9 Simulated nitrate (g/sqm) R 2 (SWAT) =.75 R 2 (Michaelis) =.98 Michaelis-Menten (Anthrosol) Observed nitrate (g/sqm) SWAT Proposed Michaelis menten

17 N loss (as of added NO3-) simulation results and comparison of kinetics Simulation results on influence of soil moisture on denitrification Time (days) 75moisture-michaelis 1moisture-SWAT 1moisture-Observed 1moisture-michaelis 75moisture-Observed Experimental station R 2 Nash and Sutcliffe SWAT, Case 1; (Case 2).93; (does not simulate).86; (does not simulate) Michaelis-Menten, Case 1; (Case 2).97; (.97).96; (.96) Simulated N loss () Simulated N loss () Scatterplot of observed and simulated N loss due to denitrification (SW θ <.95 FC) Case 2 R 2 (Michaelis) =.967 SWAT does not model for SW< Observed N loss () Simulated - Michaelis menten Scatterplot of observed and simulated N loss due to denitrification (SW θ >.95 FC) R 2 (SWAT) =.93 Case 1 R 2 (Michaelis) = Observed N loss () Simulated - michaelis menten Simulated - SWAT

18 Conclusions Nitrate transport to surface water and groundwater aquifers takes place under the influence of the runoff components of the land phase of the hydrological cycle. The kinetics of nitrate transformation processes namely, nitrification and denitrification, in the land phase of the hydrological cycle determines the transformation and release of nitrates in surface and groundwater aquifers The transformation of nitrates is governed by bacteriological action, which can be best represented by mixed order kinetics i.e., Michaelis Menten Kinetics The comparison of the existing first-order kinetics with the proposed Michaelis-Menten mixed order kinetics indicates that Michaelis-Menten mixed order kinetics represents the nitrate transformation processes better

19 Limitations of the study A longer length of record would have been desirable for calibration and validation of various components of the integrated model Nitrate concentration data for surface water was limited Fertilizer application data was limited

20 Future scope of research The Michaelis-Menten mixed order kinetics has been successfully tested using published experimental datasets. Incorporating it in the SWAT model itself and simulating nitrate transformations could be done in the future

21 thank you