Spatial characterization of long-term hydrological change in the Arkavathy watershed adjacent to Bangalore, India

Mapping Intimacies ◽

10.5194/hess-2016-562 ◽

2016 ◽

Cited By ~ 3

Author(s):

Gopal Penny ◽

Veena Srinivasan ◽

Iryna Dronova ◽

Sharachchandra Lele ◽

Sally Thompson

Keyword(s):

Surface Water ◽

Surface Area ◽

Water Surface ◽

Water Bodies ◽

Groundwater Depletion ◽

Hydrological Change ◽

Water Surface Area ◽

Hydrologic Change ◽

Surface Water Bodies

Abstract. The complexity and heterogeneity of human water use over large spatial areas and decadal timescales can impede the understanding of hydrologic change, particularly in regions with sparse monitoring of the water cycle. In the Arkavathy watershed in south India, surface water inflows to major reservoirs decreased over a 40 year period during which urbanization, groundwater depletion, modification of the river network, and changes in agricultural practices also occurred. These multiple, co-varying drivers along with limited hydrological monitoring make attribution of the causes of water scarcity in the basin challenging, and limit the effectiveness of policy responses. We develop a novel, spatially distributed dataset to understand hydrologic change by characterizing trends in surface water area in nearly 1700 rainwater harvesting and irrigation structures known as tanks. Using an automated classification approach with subpixel unmixing, we classified water surface area in tanks in Landsat images from 1973 to 2010. The classification results compared well with a reference dataset of water surface area of tanks (R2 = 0.95). We modeled water surface area of 42 clusters of tanks in a multiple regression on simple hydrological covariates and time, and found distinguishable trends in water surface area in different regions of the watershed. Agricultural areas with considerable groundwater irrigation exhibited the strongest drying. Urban land use was associated with intra-urban drying, likely due to tank encroachment, and downstream periurban wetting, likely due to increased urban effluents. Disaggregating the watershed-scale hydrological response via remote sensing of surface water bodies over multiple decades yielded a spatially resolved characterization of hydrological change in an otherwise poorly monitored watershed. This approach presents an opportunity for understanding hydrological change in heavily managed watersheds where surface water bodies integrate upstream runoff and can be delineated using satellite imagery.

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Spatial characterization of long-term hydrological change in the Arkavathy watershed adjacent to Bangalore, India

Hydrology and Earth System Sciences ◽

10.5194/hess-22-595-2018 ◽

2018 ◽

Vol 22 (1) ◽

pp. 595-610 ◽

Cited By ~ 6

Author(s):

Gopal Penny ◽

Veena Srinivasan ◽

Iryna Dronova ◽

Sharachchandra Lele ◽

Sally Thompson

Keyword(s):

Land Use ◽

Surface Water ◽

Temporal Trends ◽

Water Bodies ◽

Irrigated Agriculture ◽

Groundwater Depletion ◽

Groundwater Abstraction ◽

Hydrological Change ◽

Surface Water Bodies

Abstract. The complexity and heterogeneity of human water use over large spatial areas and decadal timescales can impede the understanding of hydrological change, particularly in regions with sparse monitoring of the water cycle. In the Arkavathy watershed in southern India, surface water inflows to major reservoirs decreased over a 40-year period during which urbanization, groundwater depletion, modification of the river network, and changes in agricultural practices also occurred. These multiple, interacting drivers combined with limited hydrological monitoring make attribution of the causes of diminishing water resources in the watershed challenging and impede effective policy responses. To mitigate these challenges, we developed a novel, spatially distributed dataset to understand hydrological change by characterizing the residual trends in surface water extent that remain after controlling for precipitation variations and comparing the trends with historical land use maps to assess human drivers of change. Using an automated classification approach with subpixel unmixing, we classified water extent in nearly 1700 man-made lakes, or tanks, in Landsat images from 1973 to 2010. The classification results compared well with a reference dataset of water extent of tanks (R2 = 0.95). We modeled the water extent of 42 clusters of tanks in a multiple regression on simple hydrological covariates (including precipitation) and time. Inter-annual variability in precipitation accounted for 63 % of the predicted variability in water extent. However, precipitation did not exhibit statistically significant trends in any part of the watershed. After controlling for precipitation variability, we found statistically significant temporal trends in water extent, both positive and negative, in 13 of the clusters. Based on a water balance argument, we inferred that these trends likely reflect a non-stationary relationship between precipitation and watershed runoff. Independently of precipitation, water extent increased in a region downstream of Bangalore, likely due to increased urban effluents, and declined in the northern portion of the Arkavathy. Comparison of the drying trends with land use indicated that they were most strongly associated with irrigated agriculture, sourced almost exclusively by groundwater. This suggests that groundwater abstraction was a major driver of hydrological change in this watershed. Disaggregating the watershed-scale hydrological response via remote sensing of surface water bodies over multiple decades yielded a spatially resolved characterization of hydrological change in an otherwise poorly monitored watershed. This approach presents an opportunity to understand hydrological change in heavily managed watersheds where surface water bodies integrate upstream runoff and can be delineated using satellite imagery.

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Effect of Water Surface Area on the Remotely Sensed Water Quality Parameters of Baysh Dam Lake, Saudi Arabia

10.5194/hess-2019-308 ◽

2019 ◽

Author(s):

Mohamed Elhag ◽

Ioannis Gitas ◽

Anas Othman ◽

Jarbou Bahrawi

Keyword(s):

Water Quality ◽

Surface Water ◽

Surface Area ◽

Water Surface ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Water Quality Monitoring ◽

Quality Parameters ◽

Water Quality Parameters ◽

Water Surface Area

Abstract. Water quality parameters help to decide the further use of water based on its quality. Changes in water surface area in the lake shall affect the water quality. Chlorophyll a, Nitrate concentration and water turbidity were extracted from satellite images to record each variation on these parameters caused by the water amount in the lake changes. Each water quality measures have been recorded with its surface area reading to analyses the effects. Water quality parameters were estimated from Sentinel-2 sensor based on the satellite temporal resolution for the years 2017–2018. Data were pre-processed then processed to estimate the Maximum Chlorophyll Index (MCI), Green Normalized Difference Vegetation Index (GNDVI) and Normalized Difference Turbidity Index (NDTI). The Normalized Difference Water Index (NDWI), was used to calculate and record the changes in the water surface area in Baysh dam lake. Results showed different correlation coefficients between the lake surface area and the water quality parameters estimated Remote Sensing data. The response of the water quality parameters to surface water changes was expressed in four different surface water categories. MCI is more sensitive to surface water changes rather than GNDVI and NDTI. Neural network Analysis showed a resemblance between GNDVI and NDTI expressed in sigmoidal function while MCI showed a different behavior expressed in exponential behavior. Therefore, monitoring of the surface water area of the lack is essential in water quality monitoring.

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Human Activities and Climate Variability Affecting Inland Water Surface Area in a High Latitude River Basin

Water ◽

10.3390/w12020382 ◽

2020 ◽

Vol 12 (2) ◽

pp. 382 ◽

Cited By ~ 1

Author(s):

Liwen Chen ◽

Guangxin Zhang ◽

Y. Jun Xu ◽

Shengbo Chen ◽

Yanfeng Wu ◽

...

Keyword(s):

Surface Area ◽

River Basin ◽

High Latitude ◽

Human Activities ◽

Water Surface ◽

Water Bodies ◽

Total Water ◽

Inland Water ◽

Water Surface Area ◽

Inland Water Bodies

Spatiotemporal changes in the surface area of inland water bodies have important implications in regional water resources, flood control, and drought hazard prediction. Although inland water bodies have been investigated intensively, few studies have looked at the effect of human activities and climate variability on surface area of inland waters at a larger scale over time and space. In this study, we used MODIS (MOD13Q1) images to determine water surface area extent at 250 m spatial resolution. We then applied this algorithm with MOD13Q1 images taken at 16-day intervals from 2000 to 2018 to a large river basin in China’s northeast high latitude region with dense stream network and abundant wetlands to investigate spatiotemporal distribution and dynamics of inland water bodies. The study identified 209 ponds, lakes, and reservoirs with an average total surface area of 2080 km2 in the past 19 years. The total water surface area fluctuated largely from 942 km2 to 5169 km2, corresponding to rainfall intensity and flood. We found that the total water surface area in this high latitude river basin showed an increasing trend during the study period, while the annual precipitation amount in the river basin also had an increasing trend concurrently. Precipitation and irrigation significantly contributed to the monthly change of water surface area, which reached the highest during June and August. The increase of water surface area was significant in the lower basin floodplain region, where agricultural irrigation using groundwater for rice production has progressed. Four nationally important wetland preserves (Zhalong, Xianghai, Momoge, and Chagan Lake) in the river basin made up nearly 50% of the basin’s total water surface area, of which Zhalong, Xianghai, and Momoge are designated by The Ramsar Convention as wetland sites of international importance. Seasonally, these water bodies reached their maximal surface area in August, when both the monsoon weather and agricultural discharge prevailed. This study demonstrates that water surface area in a high latitude river basin is affected by both human activities and climate variation, implying that high latitude regions will likely experience more changes in surface water distribution as global climate change continues and agriculture becomes intensified.

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