Your search found 42 records
1 Higley, M. C.; Conroy, J. L. 2019. The hydrological response of surface water to recent climate variability: a remote sensing case study from the central tropical Pacific. Hydrological Processes, 33(16):2227-2239. [doi: https://doi.org/10.1002/hyp.13465]
Surface water ; Climate change ; Hydrological factors ; Remote sensing ; Case studies ; Freshwater ; Groundwater ; Evaporation ; El Nino-Southern Oscillation ; Satellite imagery ; Landsat ; Normalized difference vegetation index ; Islands / Pacific Islands / Kiribati / Kiritimati
(Location: IWMI HQ Call no: e-copy only Record No: H049284)
(2.56 MB)
For small tropical islands with limited freshwater resources, understanding how island hydrology is influenced by regional climate is important, considering projected hydroclimate and sea level changes as well as growing populations dependent on limited groundwater resources. However, the relationship between climate variability and hydrologic variability for many tropical islands remains uncertain due to local hydroclimatic data scarcity. Here, we present a case study from Kiritimati, Republic of Kiribati (2°N, 157°W), utilizing the normalized difference vegetation index to investigate variability in island surface water area, an important link between climate variability and groundwater storage. Kiritimati surface water area varies seasonally, following wet and dry seasons, and interannually, due to hydroclimate variability associated with the El Niño/Southern Oscillation. The NIÑO3.4 sea surface temperature index, satellite-derived precipitation, precipitation minus evaporation, and local sea level all had significant positive correlations with surface water area. Lagged correlations show sea level changes and precipitation influence surface water area up to 6 months later. Differences in the timing of surface water area changes and variable climate-surface water area correlations in island subregions indicate that surface hydrology on Kiritimati is not uniform in response to climate variations. Rather, the magnitude of the ocean–atmosphere anomalies and island–ocean connectivity determine the extent to which sea level and precipitation control surface water area. The very strong 2015–2016 El Niño event led to the largest surface water area measured in the 18-year data set. Surface water area decreased to pre-event values in a similarly rapid manner (<6 months) after both the very strong 2015–2016 event and the 2009–2010 moderate El Niño event. Future changes in the frequency and amplitude of interannual hydroclimate variability as well as seasonal duration will thus alter surface water coverage on Kiritimati, with implications for freshwater resources, flooding, and drought.
2 del Rio-Mena, T.; Willemen, L.; Tesfamariam, G. T.; Beukes, O.; Nelson, A. 2020. Remote sensing for mapping ecosystem services to support evaluation of ecological restoration interventions in an arid landscape. Ecological Indicators, 113:106182. (Online first) [doi: https://doi.org/10.1016/j.ecolind.2020.106182]
Ecosystem services ; Ecological control ; Remote sensing ; Arid zones ; Normalized difference vegetation index ; Revegetation ; Earth observation satellites ; Geographical information systems ; Essential oils ; Biomass ; Thicket ; Forage ; Land degradation ; Erosion control ; Water flow ; Regulations ; Livestock ; Indicators ; Models / South Africa / Baviaanskloof Hartland Bawarea Conservancy
(Location: IWMI HQ Call no: e-copy only Record No: H049672)
(1.27 MB)
Considerable efforts and resources are being invested in integrated conservation and restoration interventions in rural arid areas. Empirical research for quantifying ecosystem services – nature’s benefits to people – is essential for evaluating the range of benefits of ecological restoration and to support its use in natural resource management. Satellite remote sensing (RS) can be used to monitor interventions, especially in large and remote areas. In this study we used field measurements, RS-based information from Sentinel-2 imagery together with soil and terrain data, to estimate ecosystem service supply and evaluate integrated ecological restoration interventions. We based our research on the arid, rural landscape of the Baviaanskloof Hartland Bawarea Conservancy, South Africa, where several integrated interventions have been implemented in areas where decades of small livestock farming has led to extensive land degradation. Interventions included i) long term livestock exclusion, ii) revegetating of degraded areas, iii) a combination of these two, and iv) essential oil production as alternatives to goat and sheep farming. We assessed six ecosystem services linked to the objectives of the interventions: erosion prevention, climate regulation, regulation of water flows, provision of forage, biomass for essential oil production, and the sense of place through presence of native species. We first estimated the ecosystem service supply based on field measurements. Secondly, we explored the relationships between ecosystem services quantities derived from the field measurements with 13 Sentinel-2 indices and four soil and terrain variables. We then selected the best fitting model for each ecosystem service. Finally, we compared the supply of ecosystem services between intervened and non-intervened sites. Results showed that models based on Sentinel-2 indices, combined with slope information, can estimate ecosystem services supply in the study area even when the levels of field-based ecosystem services supplies are low. The RS-based models can assess ecosystem services more accurately when their indicators mainly depend on green vegetation, such as for erosion prevention and provision of forage. The agricultural fields presented high variability between plots on the provision of ecosystem services. The use of Sentinel-2 vegetation indices and terrain data to quantify ecosystem services is a first step towards improving the monitoring and assessment of restoration interventions. Our results showed that in the study area, livestock exclusion lead to a consistent increase in most ecosystem services.
3 Yu, B.; Shang, S. 2020. Estimating growing season evapotranspiration and transpiration of major crops over a large irrigation district from HJ-1A/1B data using a remote sensing-based dual source evapotranspiration model. Remote Sensing, 12(5):865. (Special issue: Remote Sensing in Agricultural Hydrology and Water Resources Modeling) [doi: https://doi.org/10.3390/rs12050865]
Crops ; Evapotranspiration ; Plant growth ; Irrigation water ; Remote sensing ; Satellite imagery ; Water balance ; Maize ; Sunflowers ; Models ; Normalized difference vegetation index / China / Inner Mongolia Autonomous Region / Hetao Irrigation District / Dengkou / Hangjinhouqi / Linhe / Wuyuan
(Location: IWMI HQ Call no: e-copy only Record No: H049725)
(6.10 MB) (6.10 MB)
Crop evapotranspiration (ET) is the largest water consumer of agriculture water in an irrigation district. Remote sensing (RS) technique has provided an effective way to map regional ET using various RS-based ET models over the past several decades. To map growing season ET of different crops and partition ET into evaporation (E) and transpiration (T) at regional scale, appropriate ET models should be further integrated with crop distribution maps in different years and crop growing seasons determined for each crop pixel. In this study, a hybrid dual-source scheme and trapezoid framework-based ET Model (HTEM) fed with HJ-1A/1B data was applied in Hetao Irrigation District (HID) of China from 2009 to 2015 to map crop growing season ET and T at 30 m resolution. The HTEM model with HJ-1A/1B data performed well in estimating ET in HID, and the finer spatial resolution of model input data can improve the estimation accuracy of ET. Combined with the annual crop planting map identified in previous study, and crop growing seasons determined from fitted Normalized Difference Vegetation Index (NDVI) curves for crop pixels, the spatial and temporal variations of growing season ET and T of major crops (maize and sunflower) were examined. The results indicate that ET and T of maize and sunflower reach their minimum values in the southwest HID with smaller crop planting density, and reach their maximum values in northwest HID with higher crop planting density. Over the study period with a decreasing trend of available irrigation water, ET and T in maize and sunflower growing seasons show decreasing trends, while ratios of T/ET show increasing trends, which implies that the adverse effect of decreased irrigation water diversion on crop growth is diminished due to the favorable portioning of E and T in cropland of HID. In addition, the calculation results of crop coefficients show that there is water stress to crop growth in the study area. The present results are helpful to better understand the spatial pattern of crop water consumption and water stress of different crops during crop growing season, and provide the basis for optimizing the spatial distribution of crop planting with less water consumption and more crop yield.
4 Ahsen, R.; Khan, Z. M.; Farid, H. U.; Shakoor, A.; Ali, I. 2020. Estimation of cropped area and irrigation water requirement using remote sensing and GIS. Journal of Animal and Plant Sciences, 30(4):876-884. (Online first) [doi: https://doi.org/10.36899/JAPS.2020.4.0103]
Farmland ; Estimation ; Irrigation water ; Water requirements ; Crop water use ; Remote sensing ; Geographical information systems ; Land use ; Land cover ; Cropping patterns ; Satellite imagery ; Landsat ; Normalized difference vegetation index / Pakistan / Punjab / Multan
(Location: IWMI HQ Call no: e-copy only Record No: H049766)
(0.57 MB) (588 KB)
Land use-land cover (LULC) mapping has immerged as a useful and important Remote Sensing (RS) and Geographic Information System (GIS) technique for improving the management of natural resources for the progress of a country like Pakistan. Therefore, a research study was conducted to develop LULC maps for the District of Multan, Pakistan. For this purpose, economically available multi temporal (time series) images with acceptable resolution from satellite (LANDSAT 7 ETM+) were obtained for Rabi and Kharif season of 2011-12 to perform supervised classification and identification of crops in the study area. Image Processing was performed in ERDAS Imagine 2011 version for obtaining the high-class time series normalized difference vegetation indices (NDVI) for each LANDSAT 7 imagery. Four classes were targeted for crops out of the seven clusters created using target crop signatures with 95% maximum likely-hood. The resulting crop types were validated by 86 ground truthing points. Over all 74 % efficiency was found using error matrix technique. The regional irrigation water requirements of specific crops were estimated using the generated LULC maps of exerted crop area. The calculated cropped areas through ArcGIS 9.3 version were of 0.226 Mha for cotton, 0.207 Mha for wheat, 0.014 Mha for rice and 0.007 Mha for sugarcane. The total regional crop water requirement of the study area was of 1653.62 Mm3 for cotton, 911.25 Mm3 for wheat, 97.93 Mm3 for rice and 112.25 Mm3 for sugarcane. The LULC mapping technique should be used to develop a decision support system for water, land and other natural resources management at regional scale for efficient resource utilization and sustainable development.
5 Bazzi, H.; Baghdadi, N.; Fayad, I.; Zribi, M.; Belhouchette, H.; Demarez, V. 2020. Near real-time irrigation detection at plot scale using sentinel-1 data. Remote Sensing, 12(9):1456. (Special issue: Irrigation Mapping Using Satellite Remote Sensing) [doi: https://doi.org/10.3390/rs12091456]
Irrigated farming ; Parcels ; Satellite imagery ; Remote sensing ; Mapping ; Soil moisture ; Normalized difference vegetation index ; Models ; Precipitation ; Rain / France / Spain / Montpellier / Tarbes / Catalonia
(Location: IWMI HQ Call no: e-copy only Record No: H049770)
(7.48 MB) (7.48 MB)
In the context of monitoring and assessment of water consumption in the agricultural sector, the objective of this study is to build an operational approach capable of detecting irrigation events at plot scale in a near real-time scenario using Sentinel-1 (S1) data. The proposed approach is a decision tree-based method relying on the change detection in the S1 backscattering coefficients at plot scale. First, the behavior of the S1 backscattering coefficients following irrigation events has been analyzed at plot scale over three study sites located in Montpellier (southeast France), Tarbes (southwest France), and Catalonia (northeast Spain). To eliminate the uncertainty between rainfall and irrigation, the S1 synthetic aperture radar (SAR) signal and the soil moisture estimations at grid scale (10 km × 10 km) have been used. Then, a tree-like approach has been constructed to detect irrigation events at each S1 date considering additional filters to reduce ambiguities due to vegetation development linked to the growth cycle of different crops types as well as the soil surface roughness. To enhance the detection of irrigation events, a filter using the normalized differential vegetation index (NDVI) obtained from Sentinel-2 optical images has been proposed. Over the three study sites, the proposed method was applied on all possible S1 acquisitions in ascending and descending modes. The results show that 84.8% of the irrigation events occurring over agricultural plots in Montpellier have been correctly detected using the proposed method. Over the Catalonian site, the use of the ascending and descending SAR acquisition modes shows that 90.2% of the non-irrigated plots encountered no detected irrigation events whereas 72.4% of the irrigated plots had one and more detected irrigation events. Results over Catalonia also show that the proposed method allows the discrimination between irrigated and non-irrigated plots with an overall accuracy of 85.9%. In Tarbes, the analysis shows that irrigation events could still be detected even in the presence of abundant rainfall events during the summer season where two and more irrigation events have been detected for 90% of the irrigated plots. The novelty of the proposed method resides in building an effective unsupervised tool for near real-time detection of irrigation events at plot scale independent of the studied geographical context.
6 Singh, R. P.; Paramanik, S.; Bhattacharya, B. K.; Behera, M. D. 2020. Modelling of evapotranspiration using land surface energy balance and thermal infrared remote sensing. Tropical Ecology, 61(1):42-50. [doi: https://doi.org/10.1007/s42965-020-00076-8]
Evapotranspiration ; Models ; Land cover ; Energy balance ; Remote sensing ; Satellite imagery ; Landsat ; Infrared imagery ; Water vapour ; Normalized difference vegetation index ; Air temperature / India / Odisha
(Location: IWMI HQ Call no: e-copy only Record No: H049897)
(1.90 MB)
Accurate estimation of crop evapotranspiration (ET) is a key factor in crop water scheduling. The objective of this study was to estimate ET from the high-resolution satellite remote sensing data with integration of in situ observation. The surface energy balance model, Mapping Evapotranspiration with Internalized Calibration (METRIC) was utilised in this study for its simplicity, advantages, and effectiveness. It is a one-source model, which calculates the net radiation, soil heat flux, and sensible heat flux at every pixel level, and estimates the latent heat flux as the residual term in that energy budget equation. Intermediate steps like calculation of NDVI, surface temperature, and albedo served as important input parameters for ET estimate. Landat-8 satellite images were used to compute the ET in paddy field near CRRI, Cuttack, Odisha state in eastern India. Results indicated that the METRIC algorithm provided reasonably good ET over the study area with marginal overestimation in comparison to field observation by eddy covariance data. The satellite-based ET estimates represented in spatial scale has potential in improving irrigation scheduling and precise water resource management at local scales.
7 Nouri, H.; Nagler, P.; Borujeni, S. C.; Munez, A. B.; Alaghmand, S.; Noori, B.; Galindo, A.; Didan, K. 2020. Effect of spatial resolution of satellite images on estimating the greenness and evapotranspiration of urban green spaces. Hydrological Processes, 34(15):3183-3199. [doi: https://doi.org/10.1002/hyp.13790]
Urban areas ; Evapotranspiration ; Satellite imagery ; Remote sensing ; Landsat ; Moderate resolution imaging spectroradiometer ; Soil water balance ; Estimation ; Normalized difference vegetation index ; Sustainability / Australia / Adelaide
(Location: IWMI HQ Call no: e-copy only Record No: H049915)
https://onlinelibrary.wiley.com/doi/epdf/10.1002/hyp.13790
https://vlibrary.iwmi.org/pdf/H049915.pdf
https://vlibrary.iwmi.org/pdf/H049915.pdf
(4.14 MB) (4.14 MB)
Urban green spaces (UGS), like most managed land covers, are getting progressively affected by water scarcity and drought. Preserving, restoring and expanding UGS require sustainable management of green and blue water resources to fulfil evapotranspiration (ET) demand for green plant cover. The heterogeneity of UGS with high variation in their microclimates and irrigation practices builds up the complexity of ET estimation. In oversized UGS, areas too large to be measured with in situ ET methods, remote sensing (RS) approaches of ET measurement have the potential to estimate the actual ET. Often in situ approaches are not feasible or too expensive. We studied the effects of spatial resolution using different satellite images, with high-, medium- and coarse-spatial resolutions, on the greenness and ET of UGS using Vegetation Indices (VIs) and VI-based ET, over a 780-ha urban park in Adelaide, Australia. We validated ET with the ground-based ET method of Soil Water Balance. Three sets of imagery from WorldView2, Landsat and MODIS, and three VIs including the Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI) and Enhanced Vegetation Index 2 (EVI2), were used to assess long-term changes of VIs and ET calculated from the different imagery acquired for this study (2011–2018). We found high correspondence between ET-MODIS and ET-Landsat (R2 > 0.99 for all VIs). Landsat-VIs captured the seasonal changes of greenness better than MODIS-VIs. We used artificial neural network (ANN) to relate the RS-ET and ground data, and ET-MODIS (EVI2) showed the highest correlation (R2 = 0.95 and MSE =0.01 for validation). We found a strong relationship between RS-ET and in situ measurements, even though it was not explicable by simple regressions; black box models helped us to explore their correlation. The methodology used in this research makes a strong case for the value of remote sensing in estimating and managing ET of green spaces in water-limited cities.
8 Mechiche-Alami, A.; Abdi, A. M. 2020. Agricultural productivity in relation to climate and cropland management in West Africa. Scientific Reports, 10:3393. [doi: https://doi.org/10.1038/s41598-020-59943-y]
Agricultural productivity ; Farmland ; Land management ; Crop production ; Climate change ; Rain ; Temperature ; Land degradation ; Remote sensing ; Solar radiation ; Normalized difference vegetation index ; Trends ; Policies / West Africa / Nigeria / Burkina Faso / Mali / Niger / Benin / Gambia
(Location: IWMI HQ Call no: e-copy only Record No: H049962)
(3.33 MB) (3.33 MB)
The climate of West Africa is expected to become more arid due to increased temperature and uncertain rainfall regimes, while its population is expected to grow faster than the rest of the world. As such, increased demand for food will likely coincide with declines in agricultural production in a region where severe undernutrition already occurs. Here, we attempt to discriminate between the impacts of climate and other factors (e.g. land management/degradation) on crop production across West Africa using satellite remote sensing. We identify trends in the land surface phenology and climate of West African croplands between 2000 and 2018. Using the combination of a an attribution framework and residual trend anlaysis, we discriminate between climate and other impacts on crop productivity. The combined effect of rainfall, land surface temperature and solar radiation explains approximately 40% of the variation in cropland productivity over West Africa at the 95% significance level. The largest proportions of croplands with greening trends were observed in Mali, Niger and Burkina Faso, and the largest proportions with browning trends were in Nigeria, The Gambia and Benin. Climate was responsible for 52% of the greening trends and 25% of the browning trends. Within the other driving factors, changes in phenology explained 18% of the greening and 37% of the browning trends across the region, the use of inputs and irrigation explained 30% of the greening trends and land degradation 38% of the browning trends. These findings have implications for adaptation policies as we map out areas in need of improved land management practices and those where it has proven to be successful.
9 Jin, Y.; Li, A.; Bian, J.; Nan, X.; Lei, G.; Muhammad, K. 2020. Spatiotemporal analysis of ecological vulnerability along Bangladesh-China-India-Myanmar economic corridor through a grid level prototype model. Ecological Indicators, 120:106933. (Online first) [doi: https://doi.org/10.1016/j.ecolind.2020.106933]
Ecological factors ; Vulnerability ; Indicators ; Sustainable development ; Human activity ; Remote sensing ; Biodiversity ; Models ; Principal component analysis ; Normalized difference vegetation index / Bangladesh / China / India / Myanmar
(Location: IWMI HQ Call no: e-copy only Record No: H050077)
(9.78 MB)
Bangladesh-China-India-Myanmar economic corridor, a critical part of the Belt and Road Initiative program, is subject to the impact of various natural disasters and intense human activities, which have led to serious ecological vulnerability. This study proposed a prototype model using geographically weighted principal component analysis to quantify ecological vulnerability at the grid level, and an analysis was conducted on the dynamic changes of ecological vulnerability along Bangladesh-China-India-Myanmar economic corridor during 2005–2015. An indicator system for 23 spatial variables was established based on Driver-Pressure-State-Impact-Response framework to calculate the ecological vulnerability index. The cluster principle was adopted to split the ecological vulnerability into five vulnerability levels, namely, potential, light, medium, heavy, and very heavy. Given the spatial recognition of ecologically vulnerable areas along Bangladesh-China-India-Myanmar economic corridor, several suggestions on ecological management were offered. As revealed from the results, the ecological vulnerability has been rising progressively, particularly in the mountainous areas, and most of the protected areas are at medial to very heavy vulnerability level. The ecological vulnerability was tightly correlated with vulnerability events and impacts. As suggested from the results, ecological restoration and protection measures should be strictly implemented to minimize the adverse impact on the protected areas under the construction of economic corridor. Our results indicated that the geographically weighted principal component analysis can effectively quantify environmental vulnerability, and these space management policies has implications for ecological protection, resource utilization, and sustainable development in other similar regions.
10 Simionesei, L.; Ramos, T. B.; Palma, J.; Oliveira, A. R.; Neves, R. 2020. IrrigaSys: a web-based irrigation decision support system based on open source data and technology. Computers and Electronics in Agriculture, 178:105822. [doi: https://doi.org/10.1016/j.compag.2020.105822]
Irrigation management ; Water management ; Decision support systems ; Databases ; Technology ; Irrigation scheduling ; Weather forecasting ; Soil water balance ; Irrigation water ; Irrigation systems ; Remote sensing ; Models ; Normalized difference vegetation index / Portugal / Sorraia Valley Irrigation District
(Location: IWMI HQ Call no: e-copy only Record No: H050091)
(2.85 MB)
IrrigaSys is a decision support system (DSS) for irrigation water management based on online, open source tools. The aim of this paper is to describe the structure of IrrigaSys and how it is implementation at the plot scale. The DSS includes remote access to local meteorological stations for weather conditions, a meteorological model for weather forecast, the MOHID-Land model for the computation of the soil water balance and irrigation scheduling, and a database for data repository. Despite its complexity, the data necessary to run IrrigaSys is minimal, and include as mandatory input information on the location of field plots, crop type, sowing and harvest dates, soil texture, irrigation method, and daily/weekly applied irrigation depths. Based on this information, the system automatically downloads the weather data from the meteorological station located closest to the agricultural plot, as well as the weather forecast for the seven incoming days. The soil water balance is then computed from sowing to the present date (updating always the system with newly acquired information) as well as the recommended irrigation schedule for the incoming week. Results are made available via a web interface, a mobile app, a SMS, and email. The IrrigaSys further provides the Normalized Difference Vegetation Index (NDVI) computed from the most recent Sentinel-2 imagery available with a resolution of 10 m. The IrrigaSys was developed in close cooperation with the Water Board from the Sorraia Valley irrigation district, southern Portugal, supporting 103 plots of 30 farmers over the last 5 years. This stakeholder has been fundamental for successfully running the system. This paper further discusses the main strengths and limitations of IrrigaSys, with the latter being naturally associated to difficulties in providing reliable estimates for all field plots based on limited data.
11 Qaiser, G.; Tariq, S.; Adnan, S.; Latif, M. 2021. Evaluation of a composite drought index to identify seasonal drought and its associated atmospheric dynamics in northern Punjab, Pakistan. Journal of Arid Environments, 185:104332. (Online first) [doi: https://doi.org/10.1016/j.jaridenv.2020.104332]
Drought ; Climate change ; Temperature ; Precipitation ; Monitoring ; Crop yield ; Normalized difference vegetation index ; Meteorological observations ; Moderate resolution imaging spectroradiometer / Pakistan / Punjab / Potwar Plateau / Islamabad / Attock / Chakwal / Jhelum / Rawalpindi
(Location: IWMI HQ Call no: e-copy only Record No: H050153)
(9.72 MB)
Drought is one of the most devastating climate extremes in terms of its spatial extent and intensity. Rainfed areas are extremely vulnerable to drought, but effective monitoring may lessen the impact of such events. This study developed a composite drought index (CDI) for monitoring and assessing seasonal droughts in rainfed areas of the Potwar Plateau of Pakistan, using remotely sensed and observed meteorological datasets. We identified four severe-to-extreme drought periods in the Rabi season (wheat; 2000–01, 2001–02, 2009–10, and 2011–12) and four such events in the Kharif season (maize; 2000–2002 and 2009). An intense agro-meteorological drought was experienced in 2000, which reduced the wheat and maize yields to -54.6% and -29.9%, respectively. Our analysis revealed that these conditions could be explained by the vertically integrated moisture flux divergence (MFD), moisture transport, and total precipitable water (TPW) anomalies. For example, the presence of a strong MFD anomaly over the study area was responsible for preventing moisture transport from the Arabian Sea and Bay of Bengal, resulting in dry conditions. The index developed here can effectively monitor seasonal droughts in rainfed areas, which may help inform strategies to lessen the impact of such events.
12 Prakasam, C.; Saravanan, R.; Kanwar, V. S. 2021. Evaluation of environmental flow requirement using wetted perimeter method and GIS application for impact assessment. Ecological Indicators, 121:107019. (Online first) [doi: https://doi.org/10.1016/j.ecolind.2020.107019]
Environmental flows ; Evaluation ; Impact assessment ; Geographical information systems ; Hydropower ; Rivers ; Discharges ; Normalized difference vegetation index ; Ecosystems / India / Himachal Pradesh / Kangra / Binwa Hydropower Project
(Location: IWMI HQ Call no: e-copy only Record No: H050158)
https://www.sciencedirect.com/science/article/pii/S1470160X20309584/pdfft?md5=0dbc1224951132e288ff127cc33a1140&pid=1-s2.0-S1470160X20309584-main.pdf
https://vlibrary.iwmi.org/pdf/H050158.pdf
https://vlibrary.iwmi.org/pdf/H050158.pdf
(7.99 MB) (7.99 MB)
The environmental flow requirement varies from project to project based on their location, need, and habitat. The Binwa hydropower project is in the Kangra district of the Himachal Pradesh and a small hydropower project of 6 MW capacity. Here an attempt is made to assess the environmental flow requirement using the hydraulic approach, wetted perimeter method, and compared with the currently maintained e-flow. It is one of the old and commonly used method of assessing the environmental flow based on the hydraulic characteristics such as the depth, width, and perimeter. The discharge is computed for each depth along with the profile and a graph is plotted to obtain the required environmental flow. The assessed minimum flow values are customarily validated using a habitat or holistic approach. Here, to validate the calculated minimal flow value for its sufficiency, the Geographical Information System application is employed as it calculates the vegetation and water indices. The average of the breakpoint discharge has been calculated as 0.7724 m3/s. The minimal flow maintained in the Binwa basin is 0.9 m3/s which is within the limit of the existing flow maintenance during the lean period. The Geographical Information System results support the sufficiency of the environmental flow maintained in the downstream side of the dam. The wetted perimeter helped in deriving the environmental flow while the Geographical Information System application assisted in evaluating the sufficiency spatially.
13 Nazeer, A.; Waqas, M. M.; Ali, S.; Awan, U. K.; Cheema, M. J. M.; Baksh, A. 2020. Land use land cover classification and wheat yield prediction in the Lower Chenab Canal System using remote sensing and GIS. Big Data In Agriculture, 2(2):47-51. [doi: https://doi.org/10.26480/bda.02.2020.47.51]
Crop yield ; Forecasting ; Wheat ; Land use ; Land cover ; Normalized difference vegetation index ; Remote sensing ; Geographical information systems ; Landsat ; Satellite imagery ; Canals / Pakistan / Lower Chenab Canal System / Khurrian Wala Distributary / Killian Wala Distributary / Mungi Distributary
(Location: IWMI HQ Call no: e-copy only Record No: H050212)
https://bigdatainagriculture.com/paper/issue2%202020/2bda2020-47-51.pdf
https://vlibrary.iwmi.org/pdf/H050212.pdf
https://vlibrary.iwmi.org/pdf/H050212.pdf
(1.40 MB) (1.40 MB)
Reliable and timely information regarding area under wheat and its yield prediction can help in better management of the commodity. The remotely sensed data especially in combination with Geographic Information System (GIS) can provide an important and powerful tool for both, land use land cover (LULC) classification and crop yield prediction. The study objectives include LULC classification and wheat yield prediction. The study was conducted for Rabi Season from Nov. 2011 to April 2012, in the command area of three distributaries i.e. Khurrian Wala, Killian Wala and Mungi of Lower Chennai Canal (LCC) system. The Landsat-7 imagery data with spatial resolution of 30 m was used for this study. Physical features were monitored and assessed using Normalized Difference Vegetative Index (NDVI). LULC classification was done for wheat and non-wheat area which shows wheat proportion and area 87.22% and 28867.95 Ha in Khurrian wala, 71.07% and 22423.20 Ha in Killian Wala and 79.18% and 17974.34 Ha in Mungi distributary, respectively. The correlation values between maximum NDVI value and yield data were 0.45, 0.36 and 0.39 for Khurrian Wala, Killian Wala and Mungi distributary, respectively. On the basis of this correlation, average wheat yield was estimated as 3.48 T/Ha, 3.83 T/Ha and 3.80 T/Ha for Khurrian Wala, Killian Wala and Mungi distributary, respectively.
14 Waqas, M. M.; Niaz, Y.; Ali, S.; Ahmad, I.; Fahad, M.; Rashid, H.; Awan, U. K. 2020. Soil salinity mapping using satellite remote sensing: a case study of Lower Chenab Canal System, Punjab. Earth Sciences Pakistan, 4(1):07-09. [doi: https://doi.org/10.26480/esp.01.2020.07.09]
Soil salinity ; Mapping ; Canals ; Irrigation schemes ; Satellite imagery ; Remote sensing ; Groundwater ; Landsat ; Normalized difference vegetation index ; Case studies / Pakistan / Punjab / Indus Basin / Lower Chenab Canal System
(Location: IWMI HQ Call no: e-copy only Record No: H050213)
https://earthsciencespakistan.com/archives/1esp2020/1esp2020-07-09.pdf
https://vlibrary.iwmi.org/pdf/H050213.pdf
https://vlibrary.iwmi.org/pdf/H050213.pdf
(0.31 MB) (318 KB)
Salinity is the most important factor of consideration for the water management policies. The water availability from the rootzone reduced with the increase in the soil salinity due to the increase in the osmatic pressure. In Pakistan, salinity is the major threat to the agriculture land due to the tradition practices of irrigation and extensive utilization of the groundwater to meet the cope the irrigation water requirement of high intensity cropping system. The salinity impact is spatially variable on the canal commands area of the irrigation system. There is dire need to map the spatially distributed soil salinity with the high resolution. Landsat satellite imagery provides an opportunity to have 30m pixel information in seven spectral wavelength ranges. In this study, the soil salinity mapping was performed using pixel information on visible and infrared bands for 2015. These bands were also used to infer Normalized Difference Vegetation Index (NDVI). The raw digital numbers were converted into soil salinity information. The accuracy assessment was carried out using ground trothing information obtained using the error matrix method. Four major classes of non-saline, marginal saline, moderate saline and strongly, saline area was mapped. The overall accuracy of the classified map was found 83%. These maps can be helpful to delineate hot spots with severe problem of soil salinity in order to prepare reciprocate measures for improvement.
15 Everard, M.; West, H. 2021. Livelihood security enhancement though innovative water management in dryland India. Water International, 25p. (Online first) [doi: https://doi.org/10.1080/02508060.2021.1874780]
Livelihoods ; Water security ; Water management ; Innovation ; Drylands ; Ecosystem services ; Community management ; Governance ; Assessment ; Groundwater ; Remote sensing ; Soil moisture ; Normalized difference vegetation index ; Semiarid zones ; Villages / India / Rajasthan / Salt Lake Region / Laporiya / Antoli
(Location: IWMI HQ Call no: e-copy only Record No: H050228)
(5.05 MB)
Locally nuanced community-based shallow groundwater management interventions have proven important in saline and sodic monsoonal regions. A mixed methods approach characterizes achievement of regeneration of the formerly degraded socio-ecological system of Laporiya village in the semi-arid Salt Lake region of Rajasthan state (India), with a focus on locally adapted chauka systems. Local people are key participants and agents as well as principal beneficiaries of innovative nature-based management interventions. Technological innovations and governance are adapted to environmental processes and local livelihood priorities, resisting imposed engineered solutions. Findings are transferrable to dryland areas facing similar challenges of declining water and livelihood security.
16 Panhwar, V.; Zaidi, A.; Ullah, A.; Edgar, T. N. 2021. Impact of water sector interventions on economy, equity, and environment in the rainfed region of Punjab, Pakistan. Environment, Development and Sustainability, 23(2):2190-2203. [doi: https://doi.org/10.1007/s10668-020-00669-2]
Water supply ; Dam construction ; Economic impact ; Equity ; Environmental impact ; Rainfed farming ; Groundwater ; Remote sensing ; Geographical information systems ; Satellite imagery ; Cropping patterns ; Normalized difference vegetation index ; Farmers ; Income ; Impact assessment ; Precipitation / Pakistan / Punjab / Potohar
(Location: IWMI HQ Call no: e-copy only Record No: H050257)
(1.07 MB)
This case study of rainfed Potohar region of Punjab, Pakistan, illustrates the impact of water sector interventions on the ‘three Es’ of integrated water resource management: economics, equity, and environment. Small and mini dams constructed with the support of the Agency for Barani Area Development have been selected for this study. For impacts assessment, interviews and field surveys were conducted and data from the Pakistan Bureau of Statistics and Agriculture Marketing Information Services were acquired. Moreover, precipitation data and imagery in Google Earth were also used in this study to further validate the impact of dams on agriculture. Remote sensing imagery was used to estimate vegetative cover through the normalized difference vegetation index. Overall, the study results show a significant increase in the vegetation cover between 2008 and 2016. Therefore, small and mini dams happened to be significant and effective interventions in improving the quality of livelihood and sustained agriculture in the Potohar region of Punjab. Thus, for efficient and sustainable rainwater management, small and mini dams can be considered as a feasible option not only in the unserved areas of the Potohar region but other rainfed areas as well.
17 Bhatti, Muhammad Tousif; Ashraf, M.; Anwar, Arif A. 2021. Soil erosion and sediment load management strategies for sustainable irrigation in arid regions. Sustainability, 13(6):3547. (Special issue: Sustainable Agricultural, Biological, and Environmental Engineering Applications) [doi: https://doi.org/10.3390/su13063547]
Soil erosion ; Sediment yield ; Irrigation systems ; Sediment transport ; Modelling ; Arid zones ; Sustainability ; Strategies ; Revised Universal Soil Loss Equation ; Rainfall-runoff relationships ; Normalized difference vegetation index ; Crop management ; Rivers ; Catchment areas ; Reservoirs ; Canals / Pakistan / Afghanistan / Gomal River
(Location: IWMI HQ Call no: e-copy only Record No: H050370)
(4.00 MB) (4.00 MB)
Soil erosion is a serious environmental issue in the Gomal River catchment shared by Pakistan and Afghanistan. The river segment between the Gomal Zam dam and a diversion barrage (~40 km) brings a huge load of sediments that negatively affects the downstream irrigation system, but the sediment sources have not been explored in detail in this sub-catchment. The analysis of flow and sediment data shows that the significant sediment yield is still contributing to the diversion barrage despite the Gomal Zam dam construction. However, the sediment share at the diversion barrage from the sub-catchment is much larger than its relative size. A spatial assessment of erosion rates in the sub-catchment with the revised universal soil loss equation (RUSLE) shows that most of the sub-catchment falls into very severe and catastrophic erosion rate categories (>100 t h-1y -1 ). The sediment entry into the irrigation system can be managed both by limiting erosion in the catchment and trapping sediments into a hydraulic structure. The authors tested a scenario by improving the crop management factor in RUSLE as a catchment management option. The results show that improving the crop management factor makes little difference in reducing the erosion rates in the sub-catchment, suggesting other RUSLE factors, and perhaps slope is a more obvious reason for high erosion rates. This research also explores the efficiency of a proposed settling reservoir as a sediment load management option for the flows diverted from the barrage. The proposed settling reservoir is simulated using a computer-based sediment transport model. The modeling results suggest that a settling reservoir can reduce sediment entry into the irrigation network by trapping 95% and 25% for sand and silt particles, respectively. The findings of the study suggest that managing the sub-catchment characterizing an arid region and having steep slopes and barren mountains is a less compelling option to reduce sediment entry into the irrigation system compared to the settling reservoir at the diversion barrage. Managing the entire catchment (including upstream of Gomal Zam dam) can be a potential solution, but it would require cooperative planning due to the transboundary nature of the Gomal river catchment. The output of this research can aid policy and decision-makers to sustainably manage sedimentation issues in the irrigation network.
18 Yan, Y.; Wu, C.; Wen, Y. 2021. Determining the impacts of climate change and urban expansion on net primary productivity using the spatio-temporal fusion of remote sensing data. Ecological Indicators, 127:107737. (Online first) [doi: https://doi.org/10.1016/j.ecolind.2021.107737]
Climate change ; Urbanization ; Remote sensing ; Net primary productivity ; Moderate resolution imaging spectroradiometer ; Normalized difference vegetation index ; Landsat ; Precipitation ; Fertilization ; Land use ; Land cover ; Ecosystems ; Grasslands ; Farmland ; Forests / China / Beijing
(Location: IWMI HQ Call no: e-copy only Record No: H050393)
https://www.sciencedirect.com/science/article/pii/S1470160X21004027/pdfft?md5=96d56d824ca51ab536802d836e7e164b&pid=1-s2.0-S1470160X21004027-main.pdf
https://vlibrary.iwmi.org/pdf/H050393.pdf
https://vlibrary.iwmi.org/pdf/H050393.pdf
(9.65 MB) (9.65 MB)
Climate change (CLC) and urban expansion (URE) have profoundly altered the terrestrial net primary productivity (NPP). Many studies have determined the effects of CLC and URE on the NPP. However, these studies were conducted at low resolutions (250–1000 m), making it difficult to detect many smaller new urban lands, and thus potentially underestimating the contribution of URE. To accurately determine the contributions of CLC and URE to the NPP, this study takes Beijing as an example and uses an Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM) to fuse the spatial resolution of the Landsat Normalized Difference Vegetation Index (NDVI) and the temporal resolution of the Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI to generate a new NDVI with a high spatio-temporal resolution. Compared with the Landsat NDVI, the NDVI fused by the ESTARFM is found to be reliable. The fused NDVI was then inputted into the Carnegie–Ames–Stanford Approach (CASA) model to generate the NPP with a high spatio-temporal resolution, namely, the 30-m NPP. Compared with the 250-m NPP generated by directly inputting the MODIS NDVI into the CASA model, the 30-m NPP as a new ecological indicator is more accurate than the 250-m NPP. Due to the high resolution of the 30-m NPP and its increased ability to detect more new urban lands, the total loss of the 30-m NPP caused by URE is much higher than that of the 250-m NPP. For the same reason, especially in rapidly urbanized areas, the contribution ratio of URE to the 30-m NPP is much higher than that to the 250-m NPP. Moreover, in natural vegetation cover areas, CLC, which is measured by the interannual changes in temperature, precipitation, and solar radiation, is the leading factor of the change in the NPP. However, within the urban areas, residual factors other than CLC and URE, such as the introduction of exotic high-productivity vegetation, irrigation, fertilization, and pest control, dominate the change in the NPP. The results of this study are expected to contribute to a deeper understanding of the influences of CLC and URE on terrestrial ecosystem carbon cycles and provide an important theoretical reference for urban planning.
19 Prasood, S. P.; Mukesh, M. V.; Rani, V. R.; Sajinkumar, K. S.; Thrivikramji, K. P. 2021. Urbanization and its effects on water resources: scenario of a tropical river basin in South India. Remote Sensing Applications: Society and Environment, 23:100556. [doi: https://doi.org/10.1016/j.rsase.2021.100556]
Urbanization ; Water resources ; River basins ; Groundwater ; Surface water ; Water demand ; Water security ; Forecasting ; Land use ; Land cover ; Surface temperature ; Normalized difference vegetation index ; Infiltration / India / Kerala / Karamana River Basin / Thiruvananthapuram
(Location: IWMI HQ Call no: e-copy only Record No: H050468)
(9.90 MB)
Karamana River Basin (KRB), set in the tropical monsoon climate (i.e., Koppen's Am), hosts the drinking water supply to the capital city of Thiruvanathapuram, one of the highly urbanized cities in the southwestern seaboard of India. Primary focus of the study is a scrutiny of future water security status of KRB, amidst the rising population and subsequent urban sprawl. The study was done through a combination of analysis of remotely sensed data, and collation of data on population growth, surface water distribution and decadal-level groundwater monitoring. An uptrend of the decadal-level population and unscientific constructions across KRB led to the decline of per capita water entitlement and causing conflicts around water service delivery. So this study has an imperative focus on the effects of rapidly growing urban life and its impact on water resources in KRB. This was accomplished by studying the land use, land surface temperature (LST), annual precipitation, and groundwater trend for two decades, followed by land use modeling and quantifying total water deposit. The estimated LST values in KRB, robustly substantiate an upward shift in surface temperature between 2001 (47.55%) to 2020 (64.01%), a testimony of urban sprawl and it may be the major cause to reduce the rate of rainwater infiltration and increase in runoff. The Normalized Difference Vegetation Index (NDVI), used to generate land use map, and LST of the basin have been assessed for the years 2001, 2011, and 2020 to model whether or not land use has been modulated by urbanization. Based on this, future trends of land use changes for 2030 and 2050 have been predicted using CA-Markov model - a model combining Cellular Automata and Markov chain. We also carried out a quantification of annual water deposit, potential evapo-transpiration, infiltration, surface runoff, and storage. Decadal trends of population change, degree of urbanization and consequent rise in domestic water demand and shrinkage of area of open space/soil cover have also been factored in assessing water security in KRB. The results show that, as of today, the city is facing an acute annual shortage of surface water by 321.51 MCM. Furthermore, we propose potential sources for future water security of the state's capital region.
20 Abdelhaleem, F. S.; Basiouny, M.; Ashour, E.; Mahmoud, A. 2021. Application of remote sensing and geographic information systems in irrigation water management under water scarcity conditions in Fayoum, Egypt. Journal of Environmental Management, 299:113683. (Online first) [doi: https://doi.org/10.1016/j.jenvman.2021.113683]
Irrigation water ; Water management ; Remote sensing ; Geographical information systems ; Water scarcity ; Land use change ; Land cover ; Urbanization ; Agricultural production ; Water demand ; Water requirements ; Irrigation systems ; Irrigation canals ; Cultivated land ; Normalized difference vegetation index ; Models / Egypt / Fayoum / Nile River
(Location: IWMI HQ Call no: e-copy only Record No: H050679)
(8.40 MB)
Egypt suffers from severe water scarcity, which affects the sustainability of agricultural production. Therefore, the sustainable use of available water resources under water scarcity requires the adoption of water allocation policies favoring conservative and efficient use. Water management with free satellite data and geographical information system modeling capabilities can be a valuable approach for optimizing the benefits from the available water resources to meet the requirements for agricultural lands. This study aims to (i) detect and evaluate changes in agricultural areas because of urbanization and reclamation activities using Landsat data in 1999, 2009, and 2019 and (ii) update the irrigation water demand by monitoring the seasonal changes of agricultural area based on normalized difference vegetation index. Water management of Fayoum Governorate in Egypt is characterized by a non-uniform distribution flow over its canals; thus, two pilot areas are selected. The first site is the Sinnuris canal, the served areas of which represents the urbanization problem. The other site is the Gharaq canal, the served areas of which represents the urbanization and agricultural expansion situations. The results reveal that changes in agricultural areas considerably affect the uniformity of water management. Urbanization activities reduce the agricultural area by ~5.0% and 5.7% in Sinnuris and Gharaq served areas, respectively. However, the newly cultivated lands in Gharaq preserve an increase of 5.8% in the total agricultural area. The considerably changed water allocation strategies in these districts since Sinnuris has an excess of 1.5 m3/s of water supply, while the Gharaq area faced an irrigation shortage of 0.26 m3/s in 2019. As per the proposed approach, the decision-makers can readjust the water allocation plan to satisfy the water requirements for other demand areas.
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