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The drying of the Arkavathy river: understanding hydrological change in a human-dominated watershed
- Penny, Gopal
- Advisor(s): Thompson, Sally E
Human interventions in the hydrologic cycle have intensified to the extent that water resources cannot be managed and understood in isolation from anthropogenic influences. New approaches are needed to understand the effects of humans on hydrology, especially in regions of the world with limited hydrologic records. This dissertation focuses on a case study of the Arkavathy watershed adjacent to Bangalore, India, which has been transformed by rapid urbanization, intensification of agriculture, and over-exploitation of water resources over the last 50 years. During this time, the disappearance of streamflow in the watershed was largely overlooked as Bangalore shifted from Arkavathy-sourced water supply to imported water and farmers from surface water to groundwater irrigation. With Bangalore continuing to expand its water footprint and local groundwater resources drying up, moving towards sustainable water resources management in the Arkavathy requires overcoming the general absence of local hydrological records to develop an understanding of the changing hydrology of the watershed. To this end, a multifaceted research approach is developed and applied to the Arkavathy watershed to identify the dominant hydrologic dynamics within the watershed and understand the conditions under which hydrologic change occurred. This research reveals a number of important findings. First, humans are the primary drivers of change in this watershed, as neither precipitation variability nor increases in temperature can explain the observed changes in hydrology. Second, hydrologic change within the watershed is spatially heterogeneous, with drying occurring in the northern part of the watershed and increased surface water availability downstream of Bangalore. Third, streamflow decline in the northern Arkavathy has most likely been caused by extensive groundwater depletion driven by groundwater irrigated agriculture. And finally, management strategies designed to reverse groundwater depletion by constructing check dams within the surface water network are unlikely to succeed on the scales pertinent to watershed management. In addition to understanding water resources within the Arkavathy, this work serves as a foundation for understanding the trajectory of water resources in the region. This research also presents an approach for investigating historical hydrologic change in a poorly monitored watershed, understanding human-water interactions, and supporting long-term predictions for sustainable water management.
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Surface water quality assessment of the arkavathi reservoir catchment and command area, india, through multivariate analysis: a study in seasonal and sub-watershed variations.
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1. Introduction
1.1. multivariate analysis of surface water, 1.2. geogenic contamination analysis of groundwater, 1.3. significance of the present study, 2. materials and methods, 2.1. study area, 2.2. geology and geomorphological features, 2.3. land use and landcover of the study area, 2.4. sample collection and testing, 2.5. data suitability, 2.6. multivariate analysis, 2.6.1. factor analysis, 2.6.2. cluster analysis, 2.6.3. two-way and three-way anova and t -tests, 3. results and discussion, 3.1. factor groupings, 3.2. clustering, 3.3. two-way and three-way anova: effects due to years, seasons and locations, 3.4. groundwater quality of the study area—piper trilinear diagrams, 4. conclusions.
- Considering the many townships along the Arkavathi River in SW1, domestic sewage needs to be treated effectively at the border region of SW1 and SW5 and within SW6, especially during the Post-Monsoon season.
- Usage of fertilizers, especially in the agricultural lands in command area SW6, should be closely monitored and controlled.
- Erosion control plans need to be put in place in SW3, SW4 and SW5, as indicated by high TDS in SW6.
- Quarry activities in SW4 and SW3 need to be monitored for potential contamination of smaller streams.
Supplementary Materials
Author contributions, data availability statement, acknowledgments, conflicts of interest.
Click here to enlarge figure
Monsoon | Post-Monsoon | |||||||||
---|---|---|---|---|---|---|---|---|---|---|
D1 | D2 | D3 | D4 | D5 | D1 | D2 | D3 | D4 | D5 | |
pH | −0.015 | 0.225 | −0.031 | −0.134 | −0.011 | −0.212 | −0.030 | −0.089 | ||
DO | 0.008 | −0.428 | 0.157 | −0.383 | −0.267 | −0.103 | −0.003 | 0.017 | ||
BOD | 0.190 | 0.325 | 0.269 | 0.164 | 0.477 | 0.073 | −0.012 | 0.169 | 0.811 | |
COD | 0.057 | 0.052 | −0.410 | −0.003 | 0.509 | 0.063 | −0.006 | 0.182 | 0.783 | |
TSS | 0.046 | −0.044 | 0.032 | 0.105 | 0.333 | −0.379 | 0.105 | 0.291 | ||
Turbidity | −0.039 | −0.117 | 0.084 | 0.161 | 0.258 | −0.043 | 0.186 | −0.070 | ||
TDS | −0.047 | 0.059 | −0.076 | 0.213 | 0.272 | 0.296 | 0.029 | 0.201 | ||
Conductivity | −0.057 | 0.065 | −0.080 | 0.209 | 0.274 | 0.297 | 0.022 | 0.198 | ||
Na | 0.518 | −0.001 | −0.142 | 0.283 | 0.436 | 0.297 | 0.125 | 0.307 | ||
K | 0.164 | −0.219 | −0.054 | −0.080 | −0.088 | −0.144 | 0.411 | 0.349 | ||
Ca | −0.186 | −0.003 | −0.199 | 0.205 | 0.107 | −0.269 | 0.126 | −0.217 | ||
Mg | 0.158 | −0.162 | 0.264 | −0.331 | 0.242 | 0.028 | 0.176 | 0.144 | ||
Total hardness as CaCO | −0.067 | −0.006 | 0.011 | −0.085 | 0.386 | −0.074 | 0.287 | 0.219 | ||
0.446 | −0.093 | 0.076 | 0.237 | 0.322 | 0.042 | 0.092 | 0.055 | |||
0.239 | −0.270 | −0.395 | 0.051 | 0.035 | −0.045 | 0.190 | 0.166 | |||
0.203 | −0.249 | −0.413 | 0.318 | 0.279 | −0.150 | 0.082 | 0.243 | |||
−0.347 | 0.135 | 0.039 | 0.286 | 0.601 | 0.156 | 0.150 | 0.158 | |||
−0.275 | 0.350 | 0.174 | 0.022 | 0.027 | 0.053 | 0.011 | 0.325 | |||
−0.364 | 0.071 | 0.045 | −0.308 | 0.443 | −0.045 | −0.031 | 0.109 | |||
Fe | −0.172 | 0.026 | 0.090 | −0.089 | −0.154 | 0.186 | 0.096 | 0.618 | ||
Zn | 0.120 | 0.097 | 0.340 | −0.157 | 0.277 | −0.329 | 0.109 | 0.310 | ||
Total alkalinity as CaCO | 0.082 | −0.234 | −0.430 | 0.035 | 0.340 | 0.023 | 0.321 | 0.095 | ||
Total coliform/100 mL | −0.113 | −0.180 | 0.172 | −0.014 | −0.133 | 0.033 | 0.172 | 0.378 | ||
Fecal coliform/100 mL | −0.094 | 0.039 | 0.082 | 0.144 | −0.062 | 0.268 | 0.185 | 0.575 | ||
SAR | −0.282 | 0.110 | 0.005 | 0.103 | 0.352 | 0.168 | 0.058 | 0.399 |
Pre-Monsoon | Monsoon | Post-Monsoon | F-Statistic for Seasons | Year 1 | Year 2 | F-Statistic for Years | F-Statistic for Interaction between Seasons and Years | |
---|---|---|---|---|---|---|---|---|
Parameter | Mean concentration level (mg/L) | Mean concentration level (mg/L) | Mean concentration level (mg/L) | (F(2,58) at p < 0.001) | Mean concentration level (mg/L) | Mean concentration level (mg/L) | (F(1,29) at p < 0.001) | (F(2,58) at p < 0.001) |
TDS | 571.27 | 523.72 | 666.15 | 14.58 | 563.48 | 610.61 | 29.22 | 20.59 |
TSS | 5.065 | 4.230 | 7.72 | 36.033 | 5.11 | 6.23 | 101.73 | 24.56 |
2.804 | 1.987 | 9.58 | 52.8 | 4.28 | 5.31 | 79.25 | 22.61 | |
Na | 90.22 | 80.82 | 96.83 | 22.22 | 83.53 | 95.04 | 37.37 | 8.676 (p = 0.001) |
Total Hardness | 242.017 | 201.688 | 347.83 | 47.04 | 249.29 | 278.4 | 53.02 | 31.02 |
Mg | 15.397 | 11.74 | 15.74 | 9.2 (p = 0.01) | 13.32 | 15.26 | 27.01 | 7.437 |
0.112 | 0.038 | 0.105 | 12.21 (p = 0.01) | 0.073 | 0.097 | 22.6 | 13.97 | |
Ca | 61.73 | 62.03 | 69.68 | 4.93 (p = 0.01) | 59.05 | 69.91 | 76.73 | 22.35 |
199.88 | 190.78 | 209.43 | 4.91 (p = 0.01) | 193.156 | 206.91 | 28.34 | 9.48 | |
K | 11.14 | 10.44 | 14.17 | 24.55 (p = 0.01) | 10.52 | 13.31 | 47.17 | 18.16 |
Source | Measure | Type III Sum of Squares | df | Mean Square | F | Sig. | Partial Eta Squared |
---|---|---|---|---|---|---|---|
Location | DO | 13.500 | 5 | 2.700 | 1.348 | 0.279 | 0.219 |
BOD | 465.845 | 5 | 93.169 | 7.239 | 0.000 | 0.601 | |
TDS | 806,893.156 | 5 | 161,378.631 | 1.105 | 0.384 | 0.187 | |
TSS | 92.440 | 5 | 18.488 | 1.680 | 0.178 | 0.259 | |
Na | 54,851.996 | 5 | 10,970.399 | 6.212 | 0.001 | 0.564 | |
Total Hardness | 229,868.853 | 5 | 45,973.771 | 1.436 | 0.247 | 0.230 | |
558.440 | 5 | 111.688 | 9.626 | 0.000 | 0.667 | ||
Fe | 0.796 | 5 | 0.159 | 9.461 | 0.000 | 0.663 | |
196,681.589 | 5 | 39,336.318 | 3.328 | 0.020 | 0.409 | ||
K | 2739.124 | 5 | 547.825 | 6.748 | 0.000 | 0.584 | |
Ca | 17,471.293 | 5 | 3494.259 | 1.581 | 0.203 | 0.248 | |
0.397 | 5 | 0.079 | 5.260 | 0.002 | 0.523 | ||
Mg | 2795.772 | 5 | 559.154 | 2.026 | 0.111 | 0.297 | |
Total Coliform | 95,860.353 | 5 | 19,172.071 | 2.136 | 0.096 | 0.308 | |
SAR | 38.724 | 5 | 7.745 | 6.947 | 0.000 | 0.591 | |
COD | 1677.707 | 5 | 335.541 | 7.483 | 0.000 | 0.609 | |
Error | DO | 48.084 | 24 | 2.003 | |||
BOD | 308.906 | 24 | 12.871 | ||||
TDS | 3,505,192.488 | 24 | 146,049.687 | ||||
TSS | 264.095 | 24 | 11.004 | ||||
Na | 42,387.315 | 24 | 1766.138 | ||||
Total Hardness | 768231.299 | 24 | 32,009.637 | ||||
278.471 | 24 | 11.603 | |||||
Fe | 0.404 | 24 | 0.017 | ||||
283,709.877 | 24 | 11,821.245 | |||||
K+ | 1948.345 | 24 | 81.181 | ||||
Ca | 53,035.943 | 24 | 2209.831 | ||||
0.362 | 24 | 0.015 | |||||
Mg | 6623.993 | 24 | 276.000 | ||||
Total Coliform | 215,430.875 | 24 | 8976.286 | ||||
SAR | 26.758 | 24 | 1.115 | ||||
COD | 1076.217 | 24 | 44.842 |
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Sub-Watershed | Local Name of Sub-Watershed | Area (km ) |
---|---|---|
SW1 | Ramanagara sub-watershed | 348.69 |
SW2 | Suvarnamukhi sub-watershed | 420.25 |
SW3 | Mavathurkere sub-watershed | 369.70 |
SW4 | Kodihalli sub-watershed | 175.06 |
SW5 | Kanakapura sub-watershed | 168.96 |
SW6 | Harobele sub-watershed | 89.39 |
Total | 1572 |
Description | Area (km ) | Percentage of Area |
---|---|---|
Agricultural Plantation | 111.26 | 7.07 |
Barren Rocky/Stony Waste/Sheet-Rock Area | 95.26 | 6.06 |
Degraded Forest | 22.45 | 1.42 |
Fallow Land | 12.53 | 0.79 |
Forest Plantations | 4.72 | 0.3 |
Gully/Ravine Land | 0.73 | 0.04 |
Industrial Area | 6.46 | 0.41 |
Kharif + Rabi (Double Crop) | 264.89 | 16.85 |
Kharif Crop | 547.91 | 34.85 |
Land With Scrub | 139.72 | 8.88 |
Land Without Scrub | 0.82 | 0.05 |
Mining/Industrial Wasteland | 11.03 | 0.7 |
Mixed Vegetation | 10.72 | 0.68 |
Moist and Dry Deciduous Dense Forest | 58.06 | 3.69 |
Moist and Dry Deciduous Open Forest | 20.90 | 1.32 |
Rabi Crop | 0.31 | 0.02 |
Scrub Forest | 169.40 | 10.77 |
Tree Groves | 11.46 | 0.72 |
Town/Cities | 17.81 | 1.13 |
Village | 25.87 | 1.64 |
River/Stream | 11.54 | 0.73 |
Lakes/Tanks | 28.06 | 1.78 |
Total area | 1572 | 100 |
Parameters | Min–Max Range for Year 1 | Min–Max Range for Year 2 | ||||
---|---|---|---|---|---|---|
Pre-Monsoon | Monsoon | Post-Monsoon | Pre-Monsoon | Monsoon | Post-Monsoon | |
pH | 5.7–8.3 | 6.9–8.7 | 7.1–8.5 | 6.1–8.4 | 7.7–9.2 | 7.4–8.5 |
Temp (°C) | 28- 29 | 27 | 24–24 | 27 | 27 | 24–26 |
DO (mg/L) | 3.8–6.4 | 3.4–6.8 | 4–6.3 | 2.2–6.14 | 3–6.6 | 2.7–4.1 |
BOD (mg/L) | 2–15 | 1.6–6 | 3.2–9.1 | 2.1–15 | 2.2–12.8 | 5.5–16 |
COD (mg/L) | 8–36 | 4.8–10.5 | 5.9–16.9 | 6.8–40 | 3.7–22 | 10.2–30 |
Total Suspended Solids (TSS) (mg/L) | 2–13.9 | 1.6–8.2 | 3.5–9.2 | 1.9–15 | 3–11.2 | 6–11.5 |
Turbidity (NTU) | 0.5–1.4 | 0.4–2.2 | 0.5–1.5 | 0.4–2.3 | 0.4–1.3 | 1–1.7 |
Total Dissolved Solids (TDS) (mg/L) | 99–841 | 0.81–791 | 301–799 | 101–860 | 99–850 | 498–879 |
Conductivity EC (µmhos/cm) | 220–1241 | 125–1217 | 465–1230 | 148–1250 | 399–1327 | 766–1353 |
Sodium Na (mg/L) | 25–122 | 28–110 | 35–126 | 28–159 | 51–120 | 71–143 |
Potassium K (mg/L) | 2.1–22.8 | 3–21 | 3.5–25 | 3.9–27 | 3–25 | 4.7–26 |
Calcium Ca (mg/L) | 9–119 | 10–90 | 14–92 | 18–111 | 10–101 | 59–96 |
Magnesium Mg (mg/L) | 3.7–34 | 1.7–33.6 | 1.9–31 | 2–36 | 6–74 | 8–29 |
Total Hardness as CaCO (mg/L) | 81–439 | 42–430 | 209–432 | 89–450 | 55–428 | 275–541 |
Chlorides Cl (mg/L) | 31–205 | 28–182 | 35–210 | 33–305 | 35–221 | 130–275 |
Bicarbonate (mg/L) | 90–275 | 80–281 | 95–276 | 92–305 | 90–285 | 161–281 |
Flouride (mg/L) | 0.01–0.35 | 0.002–0.008 | 0.03–0.2 | 0.012–0.45 | 0.01–0.25 | 0.06–0.3 |
Nitrate (mg/L) | 1.0–3.9 | 0.8–3.2 | 1.4–15.7 | 1.1–8.1 | 0.9–8.6 | 2.7–18.2 |
Phosphate (mg/L) | 0.01–0.31 | 0.02–0.52 | 0.02–0.9 | 0.01–0.48 | 0.05–0.45 | 0.1–0.28 |
Sulphate (mg/L) | 8.5–49 | 6–28 | 13–44 | 6.8–67 | 11–26 | 12–46.7 |
Hexavalent Chromium Cr (mg/L) | Nil | 0–0.008 | 0.003–0.007 | 0.006–0.008 | Nil–0.006 | 0.005–0.09 |
Iron Fe (mg/L) | 0.02–0.22 | 0.01–0.4 | 0.06–0.44 | 0.006–0.45 | 0.03–0.01 | 0.07–0.43 |
Copper Cu (mg/L) | Nil–0.001 | 0–0.005 | 0.003–0.006 | 0.002–0.004 | Nil–0.004 | 0.003–0.008 |
Lead Pb (mg/L) | Nil | 0–0 | 0.03–0.1 | 0.002–0.002 | Nil–0.004 | 0.02–0.1 |
Nickel Ni (mg/L) | Nil–0.001 | 0–0.004 | 0.001–0.004 | 0.001–0.002 | Nil–0.004 | 0.001–0.004 |
Zinc Zn (mg/L) | 0.001–0.1 | 0.01–0.09 | 0.007–0.1 | 0.003–0.12 | 0.02–0.14 | 0.008–0.19 |
Total Alkalinity as CaCO (mg/L) | 87–315 | 80–310 | 225–445 | 98–354 | 90–295 | 228–476 |
Total Coliform/100 mL | 59–301 | 14–156 | 96–190 | 45–298 | 18–214 | 97–199 |
Fecal Coliform/100 mL | 11–81 | 0–12 | 9–45 | 9–84 | 2–33 | 12–56 |
D1 | D2 | D3 | D4 | D5 | |
---|---|---|---|---|---|
23.901 | 21.003 | 13.103 | 8.453 | 8.139 | |
23.901 | 44.904 | 58.007 | 66.460 | 74.599 |
Parameter | Rotated Factor | ||||
---|---|---|---|---|---|
D1 | D2 | D3 | D4 | D5 | |
pH | −0.023 | 0.185 | −0.054 | −0.123 | |
DO | −0.166 | −0.402 | −0.334 | 0.081 | |
BOD | 0.160 | 0.199 | 0.210 | 0.097 | |
COD | 0.326 | 0.149 | −0.022 | 0.065 | |
TSS | 0.082 | −0.155 | −0.092 | −0.193 | |
Turbidity | −0.080 | 0.257 | 0.286 | 0.228 | |
TDS | 0.205 | 0.320 | 0.017 | 0.261 | |
Conductivity | 0.092 | 0.302 | 0.157 | 0.157 | |
Na | 0.558 | 0.393 | 0.049 | 0.105 | |
K | 0.174 | 0.045 | −0.191 | 0.387 | |
Ca | 0.239 | 0.325 | −0.117 | −0.139 | |
Mg | 0.418 | 0.338 | −0.022 | 0.273 | |
Total hardness as CaCO | 0.387 | 0.440 | 0.065 | 0.048 | |
0.364 | 0.379 | 0.018 | 0.427 | ||
0.230 | 0.039 | −0.166 | 0.213 | ||
0.264 | −0.018 | 0.020 | 0.171 | ||
0.355 | 0.152 | 0.352 | 0.038 | ||
0.033 | 0.262 | 0.019 | 0.042 | ||
0.355 | 0.138 | −0.049 | 0.127 | ||
Fe | −0.219 | −0.055 | −0.131 | 0.048 | |
Zn | 0.210 | 0.207 | 0.053 | 0.014 | |
Total alkalinity as CaCO | 0.113 | 0.072 | −0.136 | 0.031 | |
Total coli form/100 mL | −0.056 | 0.403 | 0.221 | 0.255 | |
Fecal coliform/100 mL | 0.098 | 0.460 | 0.330 | 0.365 | |
SAR | 0.037 | 0.182 | −0.247 | 0.251 |
Subdivision of the Diamond | Characteristics of Corresponding Subdivision of Diamond-Shaped Fields | Percentage of Samples in Each Category | |||||
---|---|---|---|---|---|---|---|
Pre- Monsoon (Year 1) | Monsoon (Year 1) | Post-Monsoon (Year 1) | Pre- Monsoon (Year 2) | Monsoon (Year 2) | Post-Monsoon (Year 2) | ||
1 | Alkaline earth (Ca+ Mg) | 100 | 93.93 | 100 | 100 | 96.96 | 100 |
2 | Alkalies exceed alkaline earths | 0 | 6.01 | 0 | 0 | 3.33 | 0 |
3 | Weak acids (CO3 + HCO3) exceed strong acids (SO4 + Cl) | 78.78 | 81.81 | 100 | 81.81 | 75.75 | 100 |
4 | Strong acids exceed weak acids | 21.21 | 18.18 | 0 | 18.18 | 24.24 | 0 |
5 | Magnesium bicarbonate type | 78.78 | 75.75 | 100 | 81.81 | 72.72 | 100 |
6 | Calcium-chloride type | 0 | 0 | 0 | 0 | 0 | 0 |
7 | Sodium-chloride type | 0 | 0 | 0 | 0 | 0 | 0 |
8 | Sodium-bicarbonate type | 0 | 0 | 0 | 0 | 0 | 0 |
9 | Mixed type (No cation–anion exceeds 50%) | 21.21 | 24.24 | 0 | 18.18 | 27.27 | 0 |
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Surendra Kumar, J.R.; Pakka, V.H. Surface Water Quality Assessment of the Arkavathi Reservoir Catchment and Command Area, India, through Multivariate Analysis: A Study in Seasonal and Sub-Watershed Variations. Water 2022 , 14 , 2359. https://doi.org/10.3390/w14152359
Surendra Kumar JR, Pakka VH. Surface Water Quality Assessment of the Arkavathi Reservoir Catchment and Command Area, India, through Multivariate Analysis: A Study in Seasonal and Sub-Watershed Variations. Water . 2022; 14(15):2359. https://doi.org/10.3390/w14152359
Surendra Kumar, Jyothi Roopa, and Vijayanarasimha Hindupur Pakka. 2022. "Surface Water Quality Assessment of the Arkavathi Reservoir Catchment and Command Area, India, through Multivariate Analysis: A Study in Seasonal and Sub-Watershed Variations" Water 14, no. 15: 2359. https://doi.org/10.3390/w14152359
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Water Management in Arkavathy basin: a situation analysis
- S. Lele , V. Srinivasan , +3 authors T. Zuhail
- Published 1 March 2013
- Environmental Science, Geography
30 Citations
Session title: urbanizing watersheds: a basin-level approach to water stress in developing cities, enhancing resilience or furthering vulnerability responses to water stress in an urbanizing basin in southern india 1, proximate and underlying drivers of socio-hydrologic change in the upper arkavathy watershed, india, adapting to climate change in rapidly urbanizing river basins: insights from a multiple-concerns, multiple-stressors, and multi-level approach, why is the arkavathy river drying a multiple-hypothesis approach in a data-scarce region, adapting or chasing water crop choice and farmers' responses to water stress in peri‐urban bangalore, india, water crisis through the analytic of urban transformation: an analysis of bangalore’s hydrosocial regimes.
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Against the current: rewiring rigidity trap dynamics in urban water governance through civic engagement, contribution of sewage treatment to pollution abatement of urban streams, 58 references, an urban water scenario: a case study of the bangalore metropolis, karnataka, india.
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Changes in Public Commons as a Consequence of Urbanization: The Agara Lake in Bangalore, India
Access to water rights, obligations and the bangalore situation, groundwater depletion and coping strategies of farming communities in hard rock areas of southern peninsular india, bacteriological assessment of groundwater in arkavathi and vrishabhavathi basins, bangalore, karnataka, hydrochemical assessment of the pollutants in groundwaters of vrishabhavathi valley basin in bangalore (india)., urban water supply in india: status, reform options and possible lessons, emerging ground water crisis in urban areas - a case study of ward no. 39, bangalore city, toxicity of vrishabhavathy river water and sediment to the growth of phaseolus vulgharis (french beans), norms and standards of municipal basic services in india, related papers.
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Geographical analysis
Department of Geography & GIS
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DOI : 10.53989/bu.ga.v10i1.1
Year : 2021, Volume : 10, Issue : 1, Pages : 1-7
Original Article
Land Use Analysis in Arkavathy Watershed of Karnataka, India Using Remote Sensing and GIS
Shahnin Irfan ✉ 1 , Ashok D Hanjagi 2
Received Date: 02 January 2021, Accepted Date: 12 March 2021
![a case study of pollution in river arkavathy Creative Commons License](https://i.creativecommons.org/l/by/4.0/88x31.png)
According to FAO, World’s 33% of land has been degraded and continue to degrade even in the future. At the same time, world’s population has crossed 8 billion putting more stress on land resources. Rapid urbanization, industrialization, infrastructure development has led to shrink earths land resources. There is huge challenge how the existing land has been used in logistic way. Bangalore which is one of the fastest rising metropolitan hubs in the world is facing major crisis regarding land use. The Arkavathy river that flows through Bangalore Metropolitan is also facing the difficulties in scientific use of land. The watershed lies in the western part of Bangalore Metropolitan Region in Karnataka. Land-Use change has a noteworthy influence on watershed developments such as hydrology, soil loss, carbon confiscation, etc. Hence, the study emphases on the Land use of Arkavathy watershed of Karnataka, India. This study tries to attempt and highlight the change in Land use of the watershed in last three decades. The drastic change in the watershed in last few many years has wider ramification on the environment on regional scale. Multispectral satellite data obtained from Landsat 4 for 2001, IRS P6 LISS IV for and Sentinel-2 for 2018 to classify the watershed. The watershed has been classified into six major classes viz. Agricultural Land, Forest or vegetation cover, Built-up, Wastelands, grazingland and waterbodies. The overall, set-up presented by the study discloses that the land use change is quite visible throughout the study area.
Keywords: Land use, watershed, Change, development
- Rawat JS, MK. Monitoring land use/cover change using remote sensing and GIS techniques: a case study of Hawalbagh block, district Almora, Uttarakhand, India . The Egyptian journal of Remote Sensing and Space Science . 2015;18 (1) : 77 – 84 . Available from: https://doi.org/10.1016/j.ejrs.2015.02.002
- Dinka MO. Analysing decadal land use/cover dynamics of the Lake Basaka catchment (Main Ethiopian Rift) using LANDSAT imagery and GIS . Lakes & Reservoirs Research & Management . 2012;17 (1) . Available from: 10.1111/j.1440-1770.2012.00493.x
- Shah AI, Sen S, MUDD, Kumar V. Land-Use/ Land-Cover Change Detection and Analysis in Aglar Watershed, Uttarakhand . Current Journal of Applied Science and Technology . 2017;24 (1) : 1 – 11 . Available from: https://doi.org/10.9734/CJAST/2017/36019
- Skidmore AK. Expert system classifies eucalypt forest types using thematic mapper data and a digital terrain model . Photogrammetric Engineering and Remote Sensing . 1989;55 (10) : 1149 – 1464 .
© 2021 Irfan & Hanjagi. This is an open-access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Published By Bangalore University , Bengaluru, Karnataka
- 30 May 2022
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How to cite this paper
Irfan S, Hanjagi AD. (2021). Land Use Analysis in Arkavathy Watershed of Karnataka, India Using Remote Sensing and GIS. Geographical Analysis. 10(1): 1-7. https://doi.org/10.53989/bu.ga.v10i1.1
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Abstract. Water planning decisions are only as good as our ability to explain historical trends and make reasonable predictions of future water availability. But predicting water availability can be a challenge in rapidly growing regions, where human modifications of land and waterscapes are changing the hydrologic system. Yet, many regions of the world lack the long-term hydrologic monitoring records needed to understand past changes and predict future trends. We investigated this "predictions under change" problem in the data-scarce Thippagondanahalli (TG Halli) catchment of the Arkavathy sub-basin in southern India. Inflows into TG Halli reservoir have declined sharply since the 1970s. The causes of the drying are poorly understood, resulting in misdirected or counter-productive management responses. Five plausible hypotheses that could explain the decline were tested using data from field surveys and secondary sources: (1) changes in rainfall amount, seasonality and intensity; (2) increases in temperature; (3) groundwater extraction; (4) expansion of eucalyptus plantations; and (5) fragmentation of the river channel. Our results suggest that groundwater pumping, expansion of eucalyptus plantations and, to a lesser extent, channel fragmentation are much more likely to have caused the decline in surface flows in the TG Halli catchment than changing climate. The multiple-hypothesis approach presents a systematic way to quantify the relative contributions of proximate anthropogenic and climate drivers to hydrological change. The approach not only makes a meaningful contribution to the policy debate but also helps prioritize and design future research. The approach is a first step to conducting use-inspired socio-hydrologic research in a watershed.
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Pollution from East Palestine derailment last year spread as far as Wisconsin, study finds
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The National Atmospheric Deposition Program collects rain and snow before it hits the ground at 260 sites across North America, helping researchers determine where pollution is coming from and where it goes. In this case, Gay said, the team was looking for chloride, because train cars containing vinyl chloride had been set on fire to avert a larger explosion.
The concentrations of chloride they found in the rain and snow samples were much higher than normal the week of the accident, as were the pH of the samples and concentrations of sodium and calcium, which are common in fire suppressants. These elevated concentrations ranged as far east as Maine, as far south as Virginia and North Carolina, and as far west as Wisconsin. (Gay said he set Wisconsin as the western boundary of the samples he examined, so it's possible the pollutants actually could have traveled further.)
The researchers also examined the direction of the wind that week to back up their findings. Modeling from the National Oceanic and Atmospheric Administration showed the air flowed both northeast and southeast from the site of the derailment and there was a low-pressure center over Lake Michigan, Gay said. The low-pressure center would have blown air from Ohio north, and then west.
Finally, researchers ruled out other factors that could have caused the higher chloride concentrations, like road salt. The concentrations fell back into normal range a few weeks after the derailment.
Gay said detailed monitoring is critical to tracking how far these pollutants can travel. In 2011, when a tsunami flooded Japan's Fukushima Daichii Nuclear Power Plant and caused radioactive material to leak into the atmosphere, dustings of radionuclides were found in about one-fifth of rain and snow samples across the U.S.
Madeline Heim is a Report for America corps reporter who writes about environmental issues in the Mississippi River watershed and across Wisconsin. Contact her at 920-996-7266 or [email protected] .
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Changes in hydrology and hydrometeorology of the Arkavathy Basin, 1970-2010. (a) Annual inflows into the TG Halli reservoir . The 1938-1975, 1975-2000 and 2000-2010 median and mean annual ...
This dissertation focuses on a case study of the Arkavathy watershed adjacent to Bangalore, India, which has been transformed by rapid urbanization, intensification of agriculture, and over-exploitation of water resources over the last 50 years. ... The drying of the Arkavathy river: understanding hydrological change in a human-dominated ...
affected by nitrate pollution, which is not surprising, given that this tank is situated on the highly polluted Vrishabhavathy River. In another study also, nitrate levels Table 4: Nitrate levels in groundwater in talukas overlapping with the Arkavathy sub-basin Taluka Anekal Bangalore North Bangalore South Doddaballapur Kanakapura Magadi ...
In this study, the water samples are collected from 8 selected sampling stations of Arkavathi River during the study period of post monsoon month in February 2020 for physio-chemical analysis and ...
The Arkavathi River, one of the major tributaries of the Cauvery River in southern India, is a major source of drinking water and agricultural irrigation to villages and townships in the region. Surface water quality distribution and characteristics of the Arkavathi Reservoir catchment and command area were evaluated using multivariate statistical analysis on 29 water quality parameters ...
5 This case study of the data-scarce, upper Arkavathy watershed, near the city of Bengaluru in south- ... and north east (Oct-Dec) monsoons. The main stem of the Arkavathy River has its headwaters in the Nandi Hills north of Bengaluru and is joined by its first major tributary, the Ku-80 mudavathy River at Thippagondanahalli village, where the ...
2.1 Description of Study Area 155 The Arkavathy River is located in Karnataka State in south-ern India (Figure 1). The river's catchment overlaps with the western portion of the rapidly growing metropolis of Ben-galuru (Bangalore). The region is seasonally monsoonal, re-ceiving approximately 830 mm of precipitation annually. The
The paper asks why the Arkavathy River in southern India is drying. The study results indicate that anthropogenic drivers like groundwater pumping, eucalyptus plantations and channel fragmentation are much more likely to have caused the decline than changing climate.
30 The case study shows that direct human interventions play a significant role in altering the hydrology of watersheds. The ... Why is the Arkavathy River drying? 3 ad-hoc decisions. There is an ...
The Arkavathy sub-basin, which is part of the Cauvery basin, is a highly stressed, rapidly urbanising watershed on the outskirts of the city of Bengaluru. The purpose of this situation analysis document is to summarise the current state of knowledge on water management in the Arkavathy sub-basin and identify critical knowledge gaps to inform future researchers in the basin.
It also shows a cluster of villages Two studies (Ramesh et al. 2012; Shashirekha 2009) located downstream of Byramangala tank being monitored the level of pollution in groundwater of the affected by nitrate pollution, which is not surprising, Peenya industrial area in the northern Arkavathy basin. given that this tank is situated on the highly ...
the Arkavathy watershed in southern India. Five possible hy-potheses that link anthropogenic and climatic changes to the water scarcity in the watershed are outlined and investigated. 2 The problem: drying of TG Halli reservoir 2.1 Description of study area The Arkavathy River is located in the state of Karnataka in southern India (Fig.1).
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Five possible hypotheses that link anthropogenic and climatic changes to the water scarcity in the watershed are outlined and investigated. 2 The problem: drying of TG Halli reservoir 2.1 Description of study area The Arkavathy River is located in the state of Karnataka in southern India (Fig. 1).
The Arkavathy River feeds a series of cascading tanks . ... is illustrated by a set of case studies of Tataguni, ... The Central Pollution Control Board of the Government . of India (CPCB) has ...
from here that the Arkavathy River flows as one though the rural district of the Bangalore city. The Arkavathy River flows through a deep gorge here. 3. Study Area and Objective Arkavathi River is one of the peninsular rivers; it is a tributary of the River Cauvery, originated at the foot of Nandi
Arkavathi River. / 13.368689; 77.681335. / 12.287986; 77.432141. The Arkavati is an important mountain river in Karnataka, India, originating at Nandi Hills of Chikkaballapura district. [1] It is a tributary of the Kaveri, which it joins at 34 km south of Kanakapura, Ramanagara District called Sangama in Kannada, after flowing through ...
Figure 1. Map of the upper Arkavathy Watershed, showing regional context within (a) India and (b) KarnatakaBengaluru state, (c) the TG Halli watershed, and (d,e) two intensively-studied milliwatersheds . The Bengaluru (Banga- lore) urban area is shown in red on the eastern boundary of the watershed. 2 Study Area The upper Arkavathy (TG Halli ...
The Arkavathy river that flows through Bangalore Metropolitan is also facing the difficulties in scientific use of land. The watershed lies in the western part of Bangalore Metropolitan Region in Karnataka. Land-Use change has a noteworthy influence on watershed developments such as hydrology, soil loss, carbon confiscation, etc.
So, we focus here on the quality of surface water used for irrigation. Faecal coliforms : Monitoring studies conducted in the Arkavathy sub-basin indicates the presence of FCs in water samples both from Byramangala tank and Arkavathy River downstream of Kanakapura town (CPCB 2012; Prakash and Somashekar 2006; Singh et al. 2009).
The causes of the drying are poorly understood, resulting in misdirected or counter-productive management responses. Five plausible hypotheses that could explain the decline were tested using data from field surveys and secondary sources: (1) changes in rainfall amount, seasonality and intensity; (2) increases in temperature; (3) groundwater ...
Pollution from last year's fiery train derailment in East Palestine, Ohio carried to more than a dozen states — reaching as far as Wisconsin, new research shows.. The Feb. 3, 2023, accident, in ...
Addressing Pollution in Urban Rivers: Lessons from the Vrishabhavathy River in Bengaluru. January 2017. In book: Transcending Boundaries: Reflecting on Twenty Years of Action and Research at ATREE ...