scholarly journals Climate vs. Human Impact: Quantitative and Qualitative Assessment of Streamflow Variation

Water ◽  
2021 ◽  
Vol 13 (17) ◽  
pp. 2404
Author(s):  
Hamideh Kazemi ◽  
Hossein Hashemi ◽  
Fatemeh Fadia Maghsood ◽  
Seyyed Hasan Hosseini ◽  
Ranjan Sarukkalige ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Abrupt Change ◽  
Hydrological Cycle ◽  
Climate Variation ◽  
Climate Impacts ◽  
Data Availability ◽  
Qualitative Assessment ◽  
Area Reduction ◽  
Remote Sensing Techniques ◽  
Hbv Model

This paper presents a novel framework comprising analytical, hydrological, and remote sensing techniques to separate the impacts of climate variation and regional human activities on streamflow changes in the Karkheh River basin (KRB) of western Iran. To investigate the type of streamflow changes, the recently developed DBEST algorithm was used to provide a better view of the underlying reasons. The Budyko method and the HBV model were used to investigate the decreasing streamflow, and DBEST detected a non-abrupt change in the streamflow trend, indicating the impacts of human activity in the region. Remote sensing analysis confirmed this finding by distinguishing land-use change in the region. The algorithm found an abrupt change in precipitation, reflecting the impacts of climate variation on streamflow. The final assessment showed that the observed streamflow reduction is associated with both climate variation and human influence. The combination of increased irrigated area (from 9 to 19% of the total basin area), reduction of forests (from 11 to 3%), and decreasing annual precipitation has substantially reduced the streamflow rate in the basin. The developed framework can be implemented in other regions to thoroughly investigate human vs. climate impacts on the hydrological cycle, particularly where data availability is a challenge.

Water vapor measurements in central México using two remote sensing techniques: FTIR spectroscopy and GPS

2020 ◽  
Author(s):  
Alain Zuber ◽  
Wolfgang Stremme ◽  
Michel Grutter ◽  
David Adams ◽  
Thomas Blumenstock ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Water Vapor ◽  
Ftir Spectroscopy ◽  
Hydrological Cycle ◽  
Atmospheric Water Vapor ◽  
Central Mexico ◽  
Atmospheric Water ◽  
Transport Pathways ◽  
Rainy Weather ◽  
Remote Sensing Techniques

<p><span>Atmospheric water vapor plays a key role in weather and climate. Knowledge about its variability, diurnal and seasonal cycles, as well as its long-term trend is necessary to improve our understanding of the hydrological cycle. H2O total columns are measured by the two remote sensing techniques, ground-based solar absorption FTIR spectroscopy and a GPS (Global Positioning System) receiver, over a site in central Mexico. The Altzomoni Atmospheric Observatory (3989 m a.s.l., 19.32ºN, 98.65ºW) is a high altitude station located within the Izta-Popo national park, 60 km SE from Mexico City. The time series of GPS and FTIR show a high correlation between coincident hourly means. Both techniques are complementary since despite that GPS works throughout day and night and also in cloudy and rainy weather conditions, the FTIR data provides in addition altitude-resolved information about the atmospheric water vapor and permits to distinguish different isotopes.</span></p><p><span>In this study, we show water vapor columns in the 2013 to 2019 period for this region retrieved from FTIR and GPS measurements and preliminary results about their isotopic composition (H216O, H218O and HD16O). We discuss the opportunity to study the hydrological cycle in central Mexico using the relationship between light and heavy isotopes, a relationship that gives valuable information about the sources and transport pathways.</span></p>

scholarly journals Assessment of streamflow decrease due to climate vs. human influence in a semiarid area

2020 ◽  
Author(s):  
Hamideh Kazemi ◽  
Hossein Hashemi ◽  
Fatemeh Fadia Maghsood ◽  
Seyyed Hasan Hosseini ◽  
Ranjan Sarukkalige ◽  
...  
Keyword(s):  
Climate Variation ◽  
Human Influence ◽  
Annual Streamflow ◽  
Area Reduction ◽  
Negative Change ◽  
Irrigated Area ◽  
Hbv Model ◽  
Basin Area ◽  
Streamflow Trend ◽  
Karkheh River Basin

Abstract. This paper uses the Budyko method to investigate mean annual streamflow changes, due to climate variation and human influence, in the important Karkheh River Basin in western Iran. To validate the results, hydrological modelling (HBV model) and Landsat 5 Thematic Mapper (TM) images were used for the study period between 1980 and 2012. The recently developed DBEST (Detecting Breakpoints and Estimating Segments in Trend) method identified an abrupt negative change in the streamflow trend in 1994–5. The results show that the observed streamflow decrease in the Karkheh River is associated with both climate variation and human influence. The combination of increased irrigated area (from 9 to 19 % of the total basin area), reduction of forests (from 11 to 3 %), and decreasing annual precipitation has significantly reduced streamflow in the basin. Moreover, the results show that the streamflow reduction in the Karkheh Basin is more sensitive to the change in precipitation than temperature.

scholarly journals Extreme snowfall event analysis and its impacts on agriculture and horticultural crops in western Himalaya, India

MAUSAM ◽  
2021 ◽  
Vol 68 (3) ◽  
pp. 543-550
Author(s):  
RANBIR SINGH RANA ◽  
VAIBHAV KALIA ◽  
R. M. BHAGAT ◽  
SHARDA SINGH
Keyword(s):  
Remote Sensing ◽  
Hydrological Cycle ◽  
Crop Productivity ◽  
Himachal Pradesh ◽  
Event Analysis ◽  
Ground Truth Data ◽  
Mountainous Regions ◽  
Remote Sensing Techniques ◽  
The Impact ◽  
Snow Fall

Glaciers and snow are the important features of hydrological cycle and affect volume, variability and water quality in areas where these occur. Snow supplies more than half of water used for irrigation in Himachal Pradesh and other northern states of India and is an important contributor to hydropower and irrigation reservoirs. The fact that snow acts as water storage over the winter and provides soil moisture recharge in the spring is of particular importance to agriculture productivity in mountainous regions. The study on snowfall estimation during 2004-05 in Himachal Pradesh was carried out using remote sensing techniques and ground truth data to estimate total snowfall and assess the impact of snow fall on water availability and crop productivity. The snowfall estimates using remote sensing techniques for two periods by using two sets of imageries before snow fall (October, 2004) and after snowfall (May 2005). This indicated an increase of 28.7 per cent in snow cover compared to pre snowfall period. The ground data from 22 sites also indicated an increase of more than 50 per cent higher amount of snowfall during 2004-05 compared to last two decades. The area under different crops during rabi 2004 was found to be increased by 8.57 per cent, whereas, subsequent kharif season registered 1.85 per cent reduction in cropped area. The increase also reflected in higher productivity during rabi season 2004 and kharif 2005. The productivity of total food grains increased by more than 19.0 per cent during 2004-05 compared to 2003-04. The apple and other fruits registered 12.1 and 59.8 per cent higher productivity, respectively in 2004-05 compared to 2002-03 and 2003-04. The impact of extreme snow fall was more pronounced in short duration vegetables crops. The total vegetables arrivals in the market increased by 48.33 per cent during 2004-05 compared to last three year arrivals. This indicated that there was a positive and significant effect of heavy snowfall on agricultural as well as horticultural crop productivity in the mountains and downstream of Himachal Pradesh. 

Estimation of Deglaciation through Remote Sensing Techniques in Chandra-Bhaga Basin, Western Himalaya

2021 ◽  
Vol 7 (1) ◽  
pp. 79-88
Author(s):  
Shruti Dutta ◽  
AL. Ramanathan
Keyword(s):  
Remote Sensing ◽  
Continuous Monitoring ◽  
Hydrological Cycle ◽  
Western Himalaya ◽  
Western Himalayas ◽  
Hindu Kush ◽  
Micro Level ◽  
Spatio Temporal ◽  
Remote Sensing Techniques ◽  
Increasing Temperature

Glaciers act as natural indicators of climate response and natural buffers of the hydrological cycle. Hence, continuous monitoring of glaciers is very crucial for which remote sensing techniques have emerged as a powerful tool to understand the micro-level variation and dynamics of glaciers. Unfortunately, a database involving complete basin-level approach and an extensive temporal range is not available for the entire Chandra-Bhaga (CB) sub-basin. Thus, the present investigation attempts to account for the extent of deglaciation in the CB basin showing that 16.7 percent of the glaciated area has been lost during 1989-2019. Moreover, the last three decades have witnessed a rapid rate of loss for small and medium-sized glaciers as compared to larger glaciers. Adding to it, the basin has also shown an upwards shift of mean elevation in this period. Over the last decade, an increasing temperature in the western Himalayas and Hindu Kush regions, as asserted by previous studies, have led to spatio-temporal changes in the glaciated area. The extent of deglaciation alongwith the glacier-climate behaviour and response can also provide a link to measure the topographical parameters.

scholarly journals Landslide Susceptibility Mapping of Central and Western Greece, Combining NGI and WoE Methods, with Remote Sensing and Ground Truth Data

Land ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 402
Author(s):  
Charalampos Kontoes ◽  
Constantinos Loupasakis ◽  
Ioannis Papoutsis ◽  
Stavroula Alatza ◽  
Eleftheria Poyiadji ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Landslide Susceptibility ◽  
Ground Truth ◽  
Data Availability ◽  
Landslide Inventory ◽  
Landslide Susceptibility Mapping ◽  
Ground Truth Data ◽  
Landslide Occurrence ◽  
Remote Sensing Techniques ◽  
Western Greece

The exploitation of remote sensing techniques has substantially improved pre- and post- disaster landslide management over the last decade. A variety of landslide susceptibility methods exists, with capabilities and limitations related to scale and spatial accuracy issues, as well as data availability. The Interferometric Synthetic Aperture Radar (InSAR) capabilities have significantly contributed to the detection, monitoring, and mapping of landslide phenomena. The present study aims to point out the contribution of InSAR data in landslide detection and to evaluate two different scale landslide models by comparing a heuristic to a statistical method for the rainfall-induced landslide hazard assessment. Aiming to include areas with both high and low landslide occurrence frequencies, the study area covers a large part of the Aetolia–Acarnania and Evritania prefectures, Central and Western Greece. The landslide susceptibility product provided from the weights of evidence (WoE) method proved more accurate, benefitting from the expert opinion and the landslide inventory. On the other hand, the Norwegian Geological Institute (NGI) methodology has the edge on its immediate implementation, with minimum data requirements. Finally, it was proved that using sequential SAR image acquisitions gives the benefit of an updated landslide inventory, resulting in the generation of, on request, updated landslide susceptibility maps.

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