On the difficulties in estimating water balance components from remote sensing in an anthropogenically modified catchment in southern India

Author(s):  
Tejas Kulkarni ◽  
Mathias Gassmann ◽  
Sanaz Vajedian

<p>The Arkavathy river was once a major water supply source to the city of Bangalore, India, till 1970s but has completely dried up post the 1990s. The study re-invigorates on the socio-hydro dynamics in the Upper Arkavathy Catchment (UAC), covering 1432 km<sup>2</sup>, through the combination of latest remote sensing products (namely Gravity Recovery and Climate Experiment (GRACE), Global Land Data Assimilation System (GLDAS), Landsat derived NDVI). The parameters of remotely sensed long-term precipitation and temperature from corresponded well with in-situ data. Seasonal trend analysis helped re-instate no evidence of climatic driven drought to explain the decline of flows in the river. To investigate the anthropogenic proximate drivers of change - mainly groundwater exploitation and increase in water intensive cropping in the catchment - a spatio-temporal assimilation of GRACE TWS, GLDAS state variables and LandSAT-NDVI with in-situ well observations is incorporated into the water balance equation. While, studies have shown high correlation in quantifying groundwater storage changes (GWSC) and attempted downscaling with this GRACE-GLDAS-GWL-NDVI assimilation in natural catchments, this did not seem to be very skilful in human-altered fractured rock aquifers of south India for the following reasons. Firstly, the GRACE-TWS (RL-06) for the grid showed a meagre declining trend of -.033mm/year (2002-2018) and did not seem to capture the deeper groundwater extraction as compared to the social narrative in shift of hundreds of metres decline in static water levels. Secondly, the disaggregation through the GLDAS-NOAH soil moisture which corresponded well with rainfall patterns, assigns inclusion of only the shallow storage fluxes in the sub-surficial aquifer showing -5.3mm/year, which explains no overland flows in the river, but neglects the modelling of the GW aquifer and showed a faulty +47.4mm/year (2002-2018). Thirdly, the simple addition of groundwater observation well trends showed a decrease of -106.6mm/year in GWSC (2001-2017) as compared to the -656.6mm/year (1970-2000) of field scale models by Srinivasan et.al (2015). This is attributed to the fact that data used in such studies from the governmental groundwater authority boards are generally of shallower wells (up to 70m below surface) and cannot be representative of the on-ground reality of shift to deeper exploitation of GW (up to 350m) by privatised borewells. Finally, cloud-cover and scan line error corrected NDVI pixels showed an increase of irrigated area in the UAC by 31% (1972-2018). However, we observed long term data gaps (1998-2003) in images and higher uncertainties during the crucial cropping season due to monsoonal cloud cover (JJASO months) in the images to effectively understand the agricultural dynamics. Hence, it is concluded that this  procedure coupled with this period receiving higher rainfall with an average of1000mm/year (2001-2019) as compared to 800mm/year (1901-2000) makes it an unreliable method to disassociate the human interventions in modifying hydro-geologic fluxes or patterns accurately in the UAC.</p>

2016 ◽  
Vol 20 (7) ◽  
pp. 2877-2898 ◽  
Author(s):  
Hannes Müller Schmied ◽  
Linda Adam ◽  
Stephanie Eisner ◽  
Gabriel Fink ◽  
Martina Flörke ◽  
...  

Abstract. When assessing global water resources with hydrological models, it is essential to know about methodological uncertainties. The values of simulated water balance components may vary due to different spatial and temporal aggregations, reference periods, and applied climate forcings, as well as due to the consideration of human water use, or the lack thereof. We analyzed these variations over the period 1901–2010 by forcing the global hydrological model WaterGAP 2.2 (ISIMIP2a) with five state-of-the-art climate data sets, including a homogenized version of the concatenated WFD/WFDEI data set. Absolute values and temporal variations of global water balance components are strongly affected by the uncertainty in the climate forcing, and no temporal trends of the global water balance components are detected for the four homogeneous climate forcings considered (except for human water abstractions). The calibration of WaterGAP against observed long-term average river discharge Q significantly reduces the impact of climate forcing uncertainty on estimated Q and renewable water resources. For the homogeneous forcings, Q of the calibrated and non-calibrated regions of the globe varies by 1.6 and 18.5 %, respectively, for 1971–2000. On the continental scale, most differences for long-term average precipitation P and Q estimates occur in Africa and, due to snow undercatch of rain gauges, also in the data-rich continents Europe and North America. Variations of Q at the grid-cell scale are large, except in a few grid cells upstream and downstream of calibration stations, with an average variation of 37 and 74 % among the four homogeneous forcings in calibrated and non-calibrated regions, respectively. Considering only the forcings GSWP3 and WFDEI_hom, i.e., excluding the forcing without undercatch correction (PGFv2.1) and the one with a much lower shortwave downward radiation SWD than the others (WFD), Q variations are reduced to 16 and 31 % in calibrated and non-calibrated regions, respectively. These simulation results support the need for extended Q measurements and data sharing for better constraining global water balance assessments. Over the 20th century, the human footprint on natural water resources has become larger. For 11–18% of the global land area, the change of Q between 1941–1970 and 1971–2000 was driven more strongly by change of human water use including dam construction than by change in precipitation, while this was true for only 9–13 % of the land area from 1911–1940 to 1941–1970.


Author(s):  
Vadim Yapiyev ◽  
Kanat Samarkhanov ◽  
Dauren Zhumabayev ◽  
Nazym Tulegenova ◽  
Saltanat Jumassultanova ◽  
...  

Both climate change and anthropogenic activities contribute to the deterioration of terrestrial water resources and ecosystems worldwide. Central Asian endorheic basins are among the most affected regions through both climate and human impacts. Here, we used a digital elevation model, digitized bathymetry maps and Landsat images to estimate the areal water cover extent and volumetric storage changes in small terminal lakes in Burabay National Nature Park (BNNP), located in Northern Central Asia (CA), for the period of 1986 to 2016. Based on the analysis of long-term climatic data from meteorological stations, short-term hydrometeorological network observations, gridded climate datasets (CRU) and global atmospheric reanalysis (ERA Interim), we have evaluated the impacts of historical climatic conditions on the water balance of BNNP lake catchments. We also discuss the future based on regional climate model projections. We attribute the overall decline of BNNP lakes to long-term deficit of water balance with lake evaporation loss exceeding precipitation inputs. Direct anthropogenic water abstraction has a minor importance in water balance. However, the changes in watersheds caused by the expansion of human settlements and roads disrupting water drainage may play a more significant role in lake water storage decline. More precise water resources assessment at the local scale will be facilitated by further development of freely available higher spatial resolution remote sensing products. In addition, the results of this work can be used for the development of lake/reservoir evaporation models driven by remote sensing and atmospheric reanalysis data without the direct use of ground observations.


2013 ◽  
Vol 13 (5) ◽  
pp. 1402-1409
Author(s):  
Adam Trescott ◽  
Elizabeth Isenstein ◽  
Mi-Hyun Park

The objective of this study was to develop cyanobacteria remote sensing models using Landsat 7 Enhanced Thematic Mapper Plus (ETM+) as an alternative to shipboard monitoring efforts in Lake Champlain. The approach allowed for estimation of cyanobacteria directly from satellite images, calibrated and validated with 4 years of in situ monitoring data from Lake Champlain's Long-Term Water Quality and Biological Monitoring Program (LTMP). The resulting stepwise regression model was applied to entire satellite images to provide distribution of cyanobacteria throughout the surface waters of Lake Champlain. The results demonstrate the utility of remote sensing for estimating the distribution of cyanobacteria in inland waters, which can be further used for presenting the initiation and propagation of cyanobacterial blooms in Lake Champlain.


2014 ◽  
Vol 11 (13) ◽  
pp. 3547-3602 ◽  
Author(s):  
P. Ciais ◽  
A. J. Dolman ◽  
A. Bombelli ◽  
R. Duren ◽  
A. Peregon ◽  
...  

Abstract. A globally integrated carbon observation and analysis system is needed to improve the fundamental understanding of the global carbon cycle, to improve our ability to project future changes, and to verify the effectiveness of policies aiming to reduce greenhouse gas emissions and increase carbon sequestration. Building an integrated carbon observation system requires transformational advances from the existing sparse, exploratory framework towards a dense, robust, and sustained system in all components: anthropogenic emissions, the atmosphere, the ocean, and the terrestrial biosphere. The paper is addressed to scientists, policymakers, and funding agencies who need to have a global picture of the current state of the (diverse) carbon observations. We identify the current state of carbon observations, and the needs and notional requirements for a global integrated carbon observation system that can be built in the next decade. A key conclusion is the substantial expansion of the ground-based observation networks required to reach the high spatial resolution for CO2 and CH4 fluxes, and for carbon stocks for addressing policy-relevant objectives, and attributing flux changes to underlying processes in each region. In order to establish flux and stock diagnostics over areas such as the southern oceans, tropical forests, and the Arctic, in situ observations will have to be complemented with remote-sensing measurements. Remote sensing offers the advantage of dense spatial coverage and frequent revisit. A key challenge is to bring remote-sensing measurements to a level of long-term consistency and accuracy so that they can be efficiently combined in models to reduce uncertainties, in synergy with ground-based data. Bringing tight observational constraints on fossil fuel and land use change emissions will be the biggest challenge for deployment of a policy-relevant integrated carbon observation system. This will require in situ and remotely sensed data at much higher resolution and density than currently achieved for natural fluxes, although over a small land area (cities, industrial sites, power plants), as well as the inclusion of fossil fuel CO2 proxy measurements such as radiocarbon in CO2 and carbon-fuel combustion tracers. Additionally, a policy-relevant carbon monitoring system should also provide mechanisms for reconciling regional top-down (atmosphere-based) and bottom-up (surface-based) flux estimates across the range of spatial and temporal scales relevant to mitigation policies. In addition, uncertainties for each observation data-stream should be assessed. The success of the system will rely on long-term commitments to monitoring, on improved international collaboration to fill gaps in the current observations, on sustained efforts to improve access to the different data streams and make databases interoperable, and on the calibration of each component of the system to agreed-upon international scales.


Water ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 2333 ◽  
Author(s):  
Dario Ruggiu ◽  
Francesco Viola

The prediction of long term water balance components is not a trivial issue, even when empirical Budyko’s type approaches are used, because parameter estimation is often hampered by missing or poor hydrological data. In order to overcome this issue, we provided regression equations that link climate, morphological, and vegetation parameters to Fu’s parameter. Climate is here defined as a specific seasonal pattern of potential evapotranspiration and rain: five climatic scenarios have been considered to mimic different conditions worldwide. A weather generator has been used to create stochastic time series for the related climatic scenario, which in turn has been used as an input to a conceptual hydrological model to obtain long-term water balance components with low computational effort, while preserving fundamental process descriptions. The morphology and vegetation’s role in determining water partitioning process has been epitomized in four parameters of the conceptual model. Numerical simulations explored a large set of basins in the five climates. Results show that climate superimposes partitioning rules for a given basin; morphological and vegetation watershed properties, as conceptualized by model parameters, determine the Fu’s parameter within a given climate. A sensitive analysis confirmed that vegetation has the most influencing role in determining water partitioning rules, followed by soil permeability. Finally, linear regressions relating basin characteristics to Fu’s parameter have been obtained in the five climates and tested in a basin for each case, obtaining encouraging results. The small amount of data required and the very low computational effort of the method make this approach ideal for practitioners and hydrologists involved in annual runoff assessment.


2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Yabin Sun ◽  
Dadiyorto Wendi ◽  
Dong Eon Kim ◽  
Shie-Yui Liong

AbstractThe rainfall intensity–duration–frequency (IDF) curves play an important role in water resources engineering and management. The applications of IDF curves range from assessing rainfall events, classifying climatic regimes, to deriving design storms and assisting in designing urban drainage systems, etc. The deriving procedure of IDF curves, however, requires long-term historical rainfall observations, whereas lack of fine-timescale rainfall records (e.g. sub-daily) often results in less reliable IDF curves. This paper presents the utilization of remote sensing sub-daily rainfall, i.e. Global Satellite Mapping of Precipitation (GSMaP), integrated with the Bartlett-Lewis rectangular pulses (BLRP) model, to disaggregate the daily in situ rainfall, which is then further used to derive more reliable IDF curves. Application of the proposed method in Singapore indicates that the disaggregated hourly rainfall, preserving both the hourly and daily statistic characteristics, produces IDF curves with significantly improved accuracy; on average over 70% of RMSE is reduced as compared to the IDF curves derived from daily rainfall observations.


2015 ◽  
Vol 12 (4) ◽  
pp. 4271-4314 ◽  
Author(s):  
S. Biskop ◽  
F. Maussion ◽  
P. Krause ◽  
M. Fink

Abstract. Lake-level fluctuations in closed basins on the Tibetan Plateau (TP) indicate climate-induced changes in the regional water balance. However, little is known about the region's key hydrological parameters, hampering the interpretation of these changes. The purpose of this study is to contribute to a more quantitative understanding of these controls. Four lakes in the south-central part of the TP were selected to analyze the spatiotemporal variations of water-balance components: Nam Co and Tangra Yumco (indicating increasing water levels), and Mapam Yumco and Paiku Co (indicating stable or slightly decreasing water levels). We present the results of an integrated approach combining hydrological modeling, atmospheric-model output and remote-sensing data. The hydrological model J2000g was adapted and extended according to the specific characteristics of closed lake basins on the TP and driven with "High Asia Refined analysis (HAR)" data at 10 km resolution for the period 2001–2010. Our results reveal that because of the small portion of glacier areas (1 to 7% of the total basin area) the contribution of glacier melt water accounts for only 14–30% of total runoff during the study period. Precipitation is found to be the principal factor controlling the water-balance in the four studied basins. The positive water balance in the Nam Co and Tangra Yumco basins was primarily related to larger precipitation amounts and thus higher runoff rates in comparison with the Paiku Co and Mapam Yumco basins. This study highlights the benefits of combining atmospheric and hydrological modeling. The presented approach can be readily transferred to other ungauged lake basins on the TP, opening new directions of research. Future work should go towards increasing the atmospheric model's spatial resolution and a better assessment of the model-chain uncertainties, especially in this region where observational data is missing.


2016 ◽  
Vol 9 (7) ◽  
pp. 2845-2875 ◽  
Author(s):  
Matthias Schneider ◽  
Andreas Wiegele ◽  
Sabine Barthlott ◽  
Yenny González ◽  
Emanuel Christner ◽  
...  

Abstract. In the lower/middle troposphere, {H2O,δD} pairs are good proxies for moisture pathways; however, their observation, in particular when using remote sensing techniques, is challenging. The project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) addresses this challenge by integrating the remote sensing with in situ measurement techniques. The aim is to retrieve calibrated tropospheric {H2O,δD} pairs from the middle infrared spectra measured from ground by FTIR (Fourier transform infrared) spectrometers of the NDACC (Network for the Detection of Atmospheric Composition Change) and the thermal nadir spectra measured by IASI (Infrared Atmospheric Sounding Interferometer) aboard the MetOp satellites. In this paper, we present the final MUSICA products, and discuss the characteristics and potential of the NDACC/FTIR and MetOp/IASI {H2O,δD} data pairs. First, we briefly resume the particularities of an {H2O,δD} pair retrieval. Second, we show that the remote sensing data of the final product version are absolutely calibrated with respect to H2O and δD in situ profile references measured in the subtropics, between 0 and 7 km. Third, we reveal that the {H2O,δD} pair distributions obtained from the different remote sensors are consistent and allow distinct lower/middle tropospheric moisture pathways to be identified in agreement with multi-year in situ references. Fourth, we document the possibilities of the NDACC/FTIR instruments for climatological studies (due to long-term monitoring) and of the MetOp/IASI sensors for observing diurnal signals on a quasi-global scale and with high horizontal resolution. Fifth, we discuss the risk of misinterpreting {H2O,δD} pair distributions due to incomplete processing of the remote sensing products.


2020 ◽  
Author(s):  
Saksham Joshi ◽  
Venkat Raju Pokkuluri ◽  
Annie Issac ◽  
Venkateshwar Rao ◽  
Pamaraju Venkata Rao ◽  
...  

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