Your search found 12 records
1 Ahmad, Waqas; Fatima, A.; Awan, U. K.; Anwar, Arif. 2014. Analysis of long term meteorological trends in the middle and lower Indus Basin of Pakistan: a non-parametric statistical approach. Global and Planetary Change, 122:282-291. [doi: https://doi.org/10.1016/j.gloplacha.2014.09.007]
Climate change ; Rain ; Air temperature ; River basins ; Meteorological factors ; Parametric programming ; Case studies / Pakistan / Indus Basin
(Location: IWMI HQ Call no: e-copy only Record No: H046663)
(1.09 MB)
The Indus basin of Pakistan is vulnerable to climate change which would directly affect the livelihoods of poor people engaged in irrigated agriculture. The situation could be worse in middle and lower part of this basin which occupies 90% of the irrigated area. The objective of this research is to analyze the long term meteorological trends in the middle and lower parts of Indus basin of Pakistan. We used monthly data from 1971 to 2010 and applied non-parametric seasonal Kendal test for trend detection in combination with seasonal Kendall slope estimator to quantify the magnitude of trends. The meteorological parameters considered were mean maximum and mean minimum air temperature, and rainfall from 12 meteorological stations located in the study region. We examined the reliability and spatial integrity of data by mass-curve analysis and spatial correlation matrices, respectively. Analysis was performed for four seasons (spring—March to May, summer—June to August, fall—September to November and winter—December to February). The results show that max. temperature has an average increasing trend of magnitude +0.16, +0.03, 0.0 and +0.04 °C/decade during all the four seasons, respectively. The average trend of min. temperature during the four seasons also increases with magnitude of +0.29, +0.12, +0.36 and +0.36 °C/decade, respectively. Persistence of the increasing trend is more pronounced in the min. temperature as compared to the max. temperature on annual basis. Analysis of rainfall data has not shown any noteworthy trend during winter, fall and on annual basis. However during spring and summer season, the rainfall trends vary from -1.15 to +0.93 and -3.86 to +2.46 mm/decade, respectively. It is further revealed that rainfall trends during all seasons are statistically non-significant. Overall the study area is under a significant warming trend with no changes in rainfall.
2 Awan, U. K.; Ismaeel, Ali. 2014. A new technique to map groundwater recharge in irrigated areas using a SWAT model under changing climate. Journal of Hydrology, 519:1368-1382. [doi: https://doi.org/10.1016/j.jhydrol.2014.08.049]
Groundwater recharge ; Irrigated sites ; Irrigation schemes ; Climate change ; Models ; Soils ; Assessment ; Evapotranspiration ; Energy balance ; Algorithms ; Calibration ; Canals ; Land cover ; Cropping patterns ; Remote sensing / Pakistan / Lower Chenab Canal Irrigation Scheme / Indus Basin
(Location: IWMI HQ Call no: e-copy only Record No: H046715)
(4.92 MB)
The Lower Chenab canal irrigation scheme, the largest irrigation scheme of the Indus Basin irrigation system was selected for an estimate of groundwater recharge using the soil and water assessment tool (SWAT) at high spatial and temporal resolution under changing climate. Groundwater recharge was simulated using the SWAT model for representative concentration pathways (RCP) 4.5 and 8.5 climate change scenarios for the period 2012–2020. Actual evapotranspiration (ETa) was estimated using the SWAT model for the period 2010–2011. This was compared with the ETa determined using the surface energy balance algorithm (SEBAL) calibrated using data for the period 2005–2009. We concluded that the SWAT ETa estimates showed good agreement with those of SEBAL (coefficient of determination = 0.85 ± 0.05, Nash–Sutcliffe efficiency = 0.83 ± 0.07). The total average annual groundwater recharge to the aquifer was 537 mm (±55 mm) with the maximum occurring during July (151 mm). The results showed that groundwater recharge would increase by 40%, as compared to the reference period, by the end of 2020 under RCP 4.5 and by 37% under RCP 8.5. The SWAT can thus be a handy tool for not only estimating the recharge at high spatial and temporal resolution, but also under changing climate.
3 Usman, M.; Liedl, R.; Awan, U. K.. 2015. Spatio-temporal estimation of consumptive water use for assessment of irrigation system performance and management of water resources in irrigated Indus Basin, Pakistan. Journal of Hydrology, 525:26-41. [doi: https://doi.org/10.1016/j.jhydrol.2015.03.031]
Irrigation systems ; Irrigation management ; Performance indexes ; Water use ; Water resources ; Water conservation ; Surface water ; Water supply ; Satellite imagery ; Rain ; Evapotranspiration ; Land use / Pakistan / Indus Basin / Lower Chenab Canal Irrigation Scheme / Rechna Doab Irrigation Scheme
(Location: IWMI HQ Call no: e-copy only Record No: H047408)
(3.79 MB)
Reallocation of water resources in any irrigation scheme is only possible by detailed assessment of current irrigation performance. The performance of the Lower Chenab Canal (LCC) irrigation system in Pakistan was evaluated at large spatial and temporal scales. Evaporative Fraction (EF) representing the key element to assess the three very important performance indicators of equity, adequacy and reliability, was determined by the Surface Energy Balance Algorithm (SEBAL) using Moderate Resolution Imaging Spectroradiometer (MODIS) images. Spatially based estimations were performed at irrigation subdivisions, lower and upper LCC and, whole LCC scales, while temporal scales covered months, seasons and years for the study period from 2005 to 2012. Differences in consumptive water use between upper and lower LCC were estimated for different crops and possible water saving options were explored. The assessment of equitable water distribution indicates smaller coefficients of variation and hence less inequity within each subdivision except Sagar (0.08) and Bhagat (0.10). Both adequacy and reliability of water resources are found lower during kharif as compared to rabi with variation from head to tail reaches. Reliability is quite low from July to September and in February/March. This is mainly attributed to seasonal rainfalls. Average consumptive water use estimations indicate almost doubled water use (546 mm) in kharif as compared to (274 mm) in rabi with significant variability for different cropping years. Crop specific consumptive water use reveals rice and sugarcane as major water consumers with average values of 593 mm and 580 mm, respectively, for upper and lower LCC, followed by cotton and kharif fodder. The water uses for cotton are 555 mm and 528 mm. For kharif fodder, corresponding values are 525 mm and 494 mm for both regions. Based on the differences in consumptive water use, different land use land cover change scenarios were evaluated with regard to savings of crop water. It is found that such analyses need to be complemented at more fine spatial resolutions (i.e. irrigation subdivisions).
4 Awan, U. K.; Tischbein, B.; Martius, C. 2015. Simulating groundwater dynamics using feflow-3D groundwater model under complex irrigation and drainage network of dryland ecosystems of Central Asia. Irrigation and Drainage, 64(2):283-296. [doi: https://doi.org/10.1002/ird.1897]
Groundwater recharge ; Surface water ; Water levels ; Hydrology ; Water balance ; Simulation models ; Drainage systems ; Irrigation efficiency ; Water user associations ; Arid zones ; Ecosystems / Central Asia / Uzbekistan / Khorezm Region
(Location: IWMI HQ Call no: e-copy only Record No: H047442)
(2.19 MB)
Surface and groundwater resources are often conjunctively used to cope with water scarcity in irrigated agriculture. Farmers in the dryland ecosystems of central Asia also utilize shallow groundwater in addition to surface water withdrawn from rivers. This study modelled groundwater dynamics in an irrigation and drainage network in Khorezm region, Uzbekistan. The system, characterized by a vast, unlined channel network used to convey water mainly for flood irrigation and an open drainage system, is typical of Central Asian irrigated areas. Groundwater levels in the region are shallow—this contributes to crop water requirements but threatens crop production through secondary salinization. High losses during irrigation in fields and through the irrigation network are the main causes of these shallow groundwater levels. The main objective of this study was thus to simulate groundwater levels under improved irrigation efficiency scenarios. The FEFLOW-3D model, applied in a case study to the water users’ association (WUA) of Shomakhulum in south-west Khorezm, was used to quantify the impact of improved irrigation efficiency scenarios on groundwater dynamics. The modelled scenarios were: current irrigation efficiency (S-A, our baseline), improved conveyance efficiency (S-B), increased field application efficiency (S-C), and improved conveyance and application efficiency (S-D). Recharge rates were separately determined for six hydrological response units (differing in groundwater level and soil type) and introduced into the FEFLOW-3D model. After successful model calibration (R2 = 0.94) and validation (R2 = 0.93), the simulations showed that improving irrigation efficiency under existing agro-hydroclimatic conditions would lower groundwater levels from the baseline scenario (S-A) in August (the peak irrigation period) on average by 12 cm in S-B, 38 cm in S-C and 44 cm in S-D. Any interventions which would improve irrigation efficiency will lower the groundwater levels and hence policy makers should consider them and formulate the policy accordingly.
5 Awan, U. K.; Anwar, Arif; Ahmad, Waqas; Hafeez, M. 2016. A methodology to estimate equity of canal water and groundwater use at different spatial and temporal scales: a geo-informatics approach. Environmental Earth Sciences, 75(5):1-13. [doi: https://doi.org/10.1007/s12665-015-4976-4]
Groundwater extraction ; Groundwater irrigation ; Equity ; Irrigation systems ; Irrigation canals ; Water use ; Water scarcity ; Water requirements ; Water demand ; River basins ; Basin irrigation ; Farmers ; Evapotranspiration / Pakistan / India / Indus River Basin / Hakra Branch Canal
(Location: IWMI HQ Call no: e-copy only Record No: H047450)
(1.54 MB)
Indus basin irrigation system (IBIS) is one of the largest contiguous irrigation systems of the world. The surface canal water supplies are far less than the crop water demands which lead farmers to use groundwater to cope surface water scarcity. Although many studies in the IBIS are conducted to analyze the equitable distribution of canal water, there is hardly any study which comprehensively analyze the equitable use of canal water and groundwater at different spatial and temporal scales. One of the main reasons is lack of reliable information on the volume of groundwater abstraction. The objective of the current study is to develop an approach for estimating the equity of canal water and groundwater use at different spatial (canal command, distributaries, head, middle and tail end reaches) and temporal (daily, monthly and seasonal) scales of Hakra canal command area of IBIS. Results show that canal water and groundwater use to meet actual evapotranspiration is 34 and 42 %, respectively, which makes groundwater as an integral part of the large canal irrigation schemes of IBIS. The canal water and groundwater use varies significantly during the cropping colander. The maximum groundwater use is during May (51 mm) whereas the maximum canal water use is during August (24 mm). Farmers located at the head end reaches of Hakra canal use 42 % groundwater of total groundwater use whereas farmers located at the middle and tail end reaches use only 35 and 23 %, respectively. The canal water use at the head, middle and tail end reaches is 40, 34 and 26 %, respectively. These results show that the farmers located at the head of Hakra canal command area use more canal water and groundwater as compared to those located at the middle and tail end reaches. This methodology can provide guidelines to water managers in the region for equitable use of both canal water and groundwater.
6 Liaqat, U. W.; Awan, U. K.; McCabe, M. F.; Choi, M. 2016. A geo-informatics approach for estimating water resources management components and their interrelationships. Agricultural Water Management, 178:89-105. [doi: https://doi.org/10.1016/j.agwat.2016.09.010]
Water resources ; Water management ; GIS ; Remote sensing ; Groundwater extraction ; Groundwater recharge ; Water supply ; Water use ; Water requirements ; Water scarcity ; Crops ; Evapotranspiration ; Irrigation schemes ; Irrigation canals ; Surface water ; Energy balance ; Models ; Weather data ; Satellite surveys ; Spatial distribution / Pakistan / Indus Basin / Hakra Canal
(Location: IWMI HQ Call no: e-copy only Record No: H047849)
(4.67 MB)
A remote sensing based geo-informatics approach was developed to estimate water resources management (WRM) components across a large irrigation scheme in the Indus Basin of Pakistan. The approach provides a generalized framework for estimating a range of key water management variables and provides a management tool for the sustainable operation of similar schemes globally. A focus on the use of satellite data allowed for the quantification of relationships across a range of spatial and temporal scales. Variables including actual and crop evapotranspiration, net and gross irrigation, net and gross groundwater use, groundwater recharge, net groundwater recharge, were estimated and then their interrelationships explored across the Hakra Canal command area. Spatially distributed remotely sensed estimates of actual evapotranspiration (ETa) rates were determined using the Surface Energy Balance System (SEBS) model and evaluated against ground-based evaporation calculated from the advection-aridity method. Analysis of ETa simulations across two cropping season, referred to as Kharif and Rabi, yielded Pearson correlation (R) values of 0.69 and 0.84, Nash-Sutcliffe criterion (NSE) of 0.28 and 0.63, percentage bias of -3.85% and 10.6% and root mean squared error (RMSE) of 10.6 mm and 12.21 mm for each season, respectively. For the period of study between 2008 and 2014, it was estimated that an average of 0.63 mm day-1 water was supplied through canal irrigation against a crop water demand of 3.81 mm day-1. Approximately 1.86 mm day-1 groundwater abstraction was estimated in the region, which contributed to fulfil the gap between crop water demand and canal water supply. Importantly, the combined canal, groundwater and rainfall sources of water only met 70% of the crop water requirements. As such, the difference between recharge and discharge showed that groundwater depletion was around -115 mm year-1 during the six year study period. Analysis indicated that monthly changes in ETa were strongly correlated (R = 0.94) with groundwater abstraction and rainfall, with the strength of this relationship significantly (p < 0.01 and 0.05) impacted by cropping seasons and land use practices. Similarly, the net groundwater recharge showed a good positive correlation (R) of 0.72 with rainfall during Kharif, and a correlation of 0.75 with canal irrigation during Rabi, at a significance level of p < 0.01. Overall, the results provide insight into the interrelationships between key WRM components and the variation of these through time, offering information to improve the management and strategic planning of available water resources in this region.
7 Awan, U. K.; Ibrakhimov, M.; Benli, B.; Lamers, J. P. A.; Liaqat, U. W. 2017. A new concept of irrigation response units for effective management of surface and groundwater resources: a case study from the multi-country Fergana Valley, Central Asia. Irrigation Science, 35(1):55-68. [doi: https://doi.org/10.1007/s00271-016-0521-9]
Water resources ; Surface water ; Groundwater table ; Water management ; Irrigation requirements ; Irrigation water ; Irrigation schemes ; Water requirements ; Water supply ; Water loss ; Water user associations ; Cropping patterns ; Evapotranspiration ; Soil texture ; Salinity ; Case studies / Central Asia / Fergana Valley / Oktepa Zilol Chashmasi Water Consumers Association
(Location: IWMI HQ Call no: e-copy only Record No: H047967)
(2.62 MB)
When estimating canal water supplies for large-scale irrigation schemes and especially in arid regions worldwide, the impact of all factors affecting the gross irrigation requirements (GIR) are not properly accounted for, which results in inefficient use of precious freshwater resources. This research shows that the concept of irrigation response units (IRU)—areas having unique combinations of factors effecting the GIR—allows for more precise estimates of GIR. An overlay analysis of soil texture and salinity, depth and salinity of groundwater, cropping patterns and irrigation methods was performed in a GIS environment, which yielded a total of 17 IRUs combinations of the Oktepa Zilol Chashmasi water consumers’ association in multi-country Fergana Valley, Central Asia. Groundwater contribution, leaching requirements, losses in the irrigation system through field application and conveyance and effective rainfall were included in GIR estimates. The GIR varied significantly among IRUs [average of 851 mm (±143 mm)] with a maximum (1051 mm) in IRU-12 and a minimum (629 mm) in IRUs-15, 16. Owing to varying groundwater levels in each IRU, the groundwater contribution played a key role in the estimation of the GIR. The maximum groundwater contribution occurred in IRUs dominated by cotton–fallow rotations as evidenced by an average value of 159 mm but a maximum of 254 mm and a minimum of 97 mm. Percolation losses depended on irrigation methods for different crops in their respective IRUs. The novel approach can guide water managers in this and similar regions to increase the accuracy of irrigation demands based on all the factor effecting the GIR.
8 Ibrakhimov, M.; Awan, U. K.; George, B.; Liaqat, U. W. 2018. Understanding surface water–groundwater interactions for managing large irrigation schemes in the multi-country Fergana Valley, Central Asia. Agricultural Water Management, 201:99-106. [doi: https://doi.org/10.1016/j.agwat.2018.01.016]
Surface water ; Groundwater recharge ; Irrigation schemes ; Large scale systems ; Irrigation management ; Water balance ; Groundwater table ; Discharges ; Crops ; Water requirements ; Water user associations ; Evapotranspiration ; Precipitation ; Models / Central Asia / Uzbekistan / Fergana Valley / Oktepa Zilol Chashmasi Water Consumers Association
(Location: IWMI HQ Call no: e-copy only Record No: H048584)
(0.97 MB)
Traditionally, surface water supplies are the sole sources to satisfy crop water requirements in large irrigation schemes such as those in the Fergana Valley, Central Asia. Recent studies indicate that 23–30% of these requirements are met from shallow groundwater, but this is not usually quantified. To manage favorable groundwater levels – i.e., without increasing soil salinity and nutrient leaching and reducing crop yields – information on, and quantification of, groundwater recharge and discharge rates at large spatial and temporal scales, as well as understanding their mechanisms of interaction, is indispensable. With the aim to quantify groundwater recharge, discharge and their interaction, a conceptual water balance model at a scale of a Water Consumers’ Association was established on a monthly basis for a 10-year period. Average groundwater recharge was estimated as 780 ± 75.7 mm, representing 62% of surface water supplies. The highest average annual recharge (930 mm) driven by excessive precipitation and water supply was in 2010 and the lowest (667–726 mm) was in years of lower water availability: 2006–2008 and 2012. The net groundwater recharge was 82.4 ± 79 mm, and determined the groundwater level fluctuations. The highest positive net groundwater recharge rate (247 mm) and the shallowest groundwater level (123 cm) also occurred in 2010. The negative net recharge in 2006 (–11 mm), 2008 (–41 mm) and 2012 (–5 mm) indicated deeper groundwater levels during these periods. The groundwater recharge values were excessively high even for this large irrigation scheme. To save limited freshwater resources, groundwater discharge should be reduced, with one option being to reduce excessive drainage outflow.
9 Ibrakhimov, M.; Awan, U. K.; Sultanov, M.; Akramkhanov, A.; Djumaboev, Kakhramon; Conrad, C.; Lamers, J. 2019. Combining remote sensing and modeling approaches to assess soil salinity in irrigated areas of the Aral Sea Basin. Central Asian Journal of Water Research, 5(2):100-116. [doi: https://doi.org/10.29258/CAJWR/2019-R1.v5-2/64-81eng]
Soil salinization ; Irrigated land ; Remote sensing ; Modelling ; Forecasting ; Techniques ; Soil profiles ; Groundwater ; Irrigated farming ; Cotton ; Case studies / Uzbekistan / Aral Sea Basin / Khorezm
(Location: IWMI HQ Call no: e-copy only Record No: H049745)
(1.14 MB) (1.14 MB)
Accurate assessment of the soil salinization is an important step for mitigation of agricultural land degradation. Remote sensing (RS) is widely used for salinity assessment, but knowledge on prediction precision is lacking. A RS-based salinity assessment in Khorezm allows for modest reliable prediction with weak (R2=0.15–0.29) relationship of the salinity maps produced with RS and interpolation of electromagnetic EM38 during growth periods and more reliable (R2=0.35–0.56) beyond irrigation periods. Modeling with HYDRUS-1D at slightly, moderately and highly saline sites at various depths showed that irrigation forces salts to move to deeper layers: salts reappear in the upper profile during dry periods. Beyond irrigation events, salts gradually accumulated in the upper soil layers without fluctuations. Coupling RS techniques with numerical modeling provided better insight into salinity dynamics than any of these approaches alone. This should be of interest to farmers and policy makers since the combination of methods will allow for better planning and management.
10 Jalil, A.; Akhtar, F.; Awan, U. K.. 2020. Evaluation of the AquaCrop model for winter wheat under different irrigation optimization strategies at the downstream Kabul River Basin of Afghanistan. Agricultural Water Management, 240:106321. [doi: https://doi.org/10.1016/j.agwat.2020.106321]
Irrigation scheduling ; Strategies ; Winter wheat ; Crop water use ; Water productivity ; Models ; Water scarcity ; Deficit irrigation ; Irrigation water ; Irrigated sites ; Soil moisture ; River basins ; Farmers ; Biomass production / Afghanistan / Kabul River Basin / Attawor Irrigation Scheme
(Location: IWMI HQ Call no: e-copy only Record No: H050211)
(1.81 MB)
Afghanistan has an arid to semi-arid climate where irrigated agriculture largely depends on scarce irrigation water supplies from snowmelt from the high raised mountains. Under growing water scarcity, farmers not only need to use the available water more wisely but have to develop alternative options for coping water scarcity. Deficit irrigation schedule can be one of the options to mitigate the adverse impacts of water scarcity on crop production. In the current study, FAO’s crop water productivity model (AquaCrop) was calibrated and validated with field data in Kabul River Basin (KRB) for wheat crop to simulate four different water scarcity scenarios (S-A: business-as-usual scenario, S-B: refilling the soil profile to field capacity upon 50 % water depletion, S-C: refilling the soil profile upon 100 % depletion and S-D: refilling the soil profile upon 130 % depletion occurrence) for resultant yield, water productivity (WP) and biomass production. Two wheat fields, namely A and B were monitored intensively for soil moisture content, meteorological situation, irrigation application and post-harvest data. Results show that the measured WP was 1.4 kg m-3 ETa and 1.5 kg m-3 ETa whereas, the actual (measured) water use efficiency (WUE) was 0.58 kg m-3 and 0.66 kg m-3 for Field A and Field B, respectively. The WP of the scenarios S-A, S-B, S-C and S-D was 2.0-2.1 kg m-3 ETa (for plot B and A), 2.5 kg m-3 ETa, 2.74 kg m-3 ETa and 2.8 kg m-3 ETa respectively. Similarly, yield under these scenarios was 6.4 ton ha-1 , 8.7 ton ha-1 , 7.4 ton ha-1 and 6.7 ton ha-1 respectively while the above ground biomass was 21.3 ton ha-1 , 21.8 ton ha-1 , 19 ton ha-1 and 18.3 ton ha-1 respectively. As a consequence, WP could increase by 92.8 %, 78 % and 95 % in S-B, S-C and S-D, respectively with reference to the measured WP. The optimized scenarios developed in this study can provide guidelines for policy makers and farming communities to mitigate the adverse impact of water scarcity through such innovative interventions.
11 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.
12 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.
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