Your search found 3 records
1 Tischbein, B.; Manschadi, A. M.; Conrad, C.; Hornidge, A.-K.; Bhaduri, A.; Ul Hassan, M.; Lamers, J. P. A.; Awan, Usman Khalid; Vlek, P. L. G. 2013. Adapting to water scarcity: constraints and opportunities for improving irrigation management in Khorezm, Uzbekistan. Water Science and Technology: Water Supply, 13(2):337-348. [doi: https://doi.org/10.2166/ws.2013.028]
Water management ; Water scarcity ; Surface water ; Groundwater resources ; Irrigation management ; Irrigation scheduling ; River basins ; Rice ; Salinity control ; Soil water ; Soil moisture ; Vegetation ; Institutions / Uzbekistan / Khorezm
(Location: IWMI HQ Call no: e-copy only Record No: H045861)
(0.36 MB)
Like many irrigation schemes in Central Asia, the one in Khorezm faces a two-fold challenge: on the one side, the severe problems inherited from the past need to be remedied and on the other side, the rising supply–demand gap driven by sharpening competition for water and climate change must be dealt with. Located in the lower part of the Amu Darya basin, Khorezm irrigation and drainage scheme is particularly vulnerable to supply–demand gaps. Promising solutions towards adaptation comprise modified strategies of land and water use towards higher efficiency and flexibility in combination with measures to lessen the constraints of the system itself, which was initially designed for the management of a few, large and uniform production units and not for many diverse and small units. Solutions consist of flexible, modeling-based approaches, re-arranging institutional settings and establishing economic incentive systems. Flexible modeling allows an integrated use of surface and groundwater resources avoiding or minimizing the impact of water stress on yield. Institutional settings strengthen the position of water users via improved participation and transparency of processes in Water Consumers Associations (WCAs). Economic measures support sustainable resource use strategies and improve the functioning of WCAs. The findings could be extrapolated to other regions of Central Asia with similar conditions and challenges.
2 Usman, M.; Qamar, M. U.; Becker, R.; Zaman, M.; Conrad, C.; Salim, S. 2020. Numerical modelling and remote sensing based approaches for investigating groundwater dynamics under changing land-use and climate in the agricultural region of Pakistan. Journal of Hydrology, 581:124408. [doi: https://doi.org/10.1016/j.jhydrol.2019.124408]
Groundwater table ; Groundwater recharge ; Climate change ; Land use change ; Remote sensing ; Modelling ; Water balance ; Land cover ; Water use ; Precipitation ; Evapotranspiration ; Emission ; Irrigation systems / Pakistan / Punjab / Lower Chenab Canal
(Location: IWMI HQ Call no: e-copy only Record No: H049553)
(6.51 MB)
The shrinking groundwater resource is a major cause of ecosystem imbalance, which is further intensified by rapid changes in land use and land cover (LULC) and climate in the lower Chenab canal (LCC) of Pakistan. Present study aims to investigate groundwater dynamics using a novel approach by incorporating remote sensing data in combination with actual patterns of LULC, while statistical approach is employed for downscaling of climatic data under two emission scenarios including H3A2 and H3B2. A 3-D numerical groundwater flow model is used for evaluating current patterns of groundwater use and its dynamics. The results of water budget show a total horizontal groundwater inflow of 2844 Mm3 and an outflow of 2720.2 Mm3. The groundwater abstraction through pumping is about 17374.43 Mm3 as compared to groundwater recharge of 19933.20 Mm3, yields a surplus of 2682.87 Mm3, which raises groundwater levels in major parts of LCC. Change in rice cultivation has the highest impact on groundwater levels in upper regions of LCC, whereas higher negative changes are observed for lower parts under decreased fodder area in place of rice, cotton and sugarcane. For climate scenarios, a rise in groundwater level is observed for 2011 to 2025, whereas, its drop is expected for the periods 2026–2035 and 2036–2045 under H3A2 scenario. Due to no imminent threats to groundwater, there is an opportunity for groundwater development through water re-allocation. Groundwater status under H3B2 emission regime is rather complex during 2011–2025. Water management under such situation requires revisiting of cropping patterns and augmenting water supply through additional surface water resources. Considering the limitations of the current study, it is recommended to update model with river flow under changing climate, and to extend investigations for combined effects of LULC and climate change.
3 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.
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