A probabilistic assessment of agricultural water scarcity in a semi-arid and snowmelt-dominated river basin under climate change

2017 ◽  
Vol 193 ◽  
pp. 142-152 ◽  
Author(s):  
Hossam Moursi ◽  
Daeha Kim ◽  
Jagath J. Kaluarachchi
Author(s):  
Asif M. BHATTI ◽  
Toshio KOIKE ◽  
Patricia Ann JARANILLA-SANCHEZ ◽  
Mohamed RASMY ◽  
Kohei YOSHIMURA ◽  
...  

2020 ◽  
Vol 3 (1) ◽  
pp. 481-498
Author(s):  
G. Sireesha Naidu ◽  
M. Pratik ◽  
S. Rehana

Abstract Catchment scale conceptual hydrological models apply calibration parameters entirely based on observed historical data in the climate change impact assessment. The study used the most advanced machine learning algorithms based on Ensemble Regression and Random Forest models to develop dynamically calibrated factors which can form as a basis for the analysis of hydrological responses under climate change. The Random Forest algorithm was identified as a robust method to model the calibration factors with limited data for training and testing with precipitation, evapotranspiration and uncalibrated runoff based on various performance measures. The developed model was further used to study the runoff response under climate change variability of precipitation and temperatures. A statistical downscaling model based on K-means clustering, Classification and Regression Trees and Support Vector Regression was used to develop the precipitation and temperature projections based on MIROC GCM outputs with the RCP 4.5 scenario. The proposed modelling framework has been demonstrated on a semi-arid river basin of peninsular India, Krishna River Basin (KRB). The basin outlet runoff was predicted to decrease (13.26%) for future scenarios under climate change due to an increase in temperature (0.6 °C), compared to a precipitation increase (13.12%), resulting in an overall reduction in water availability over KRB.


2018 ◽  
Vol 11 (3-4) ◽  
pp. 25-36 ◽  
Author(s):  
Berny Bisselink ◽  
Ad de Roo ◽  
Jeroen Bernhard ◽  
Emiliano Gelati

Abstract This paper presents a state-of-the-art integrated model assessment to estimate the impacts of the 2°C global mean temperature increase and the 2061-2090 warming period on water scarcity in the Danube River Basin under the RCP8.5 scenario. The Water Exploitation Index Plus (WEI+) is used to calculate changes in both spatial extent and people exposed to water scarcity due to land use, water demand, population and climate change. Despite model and data uncertainties, the combined effects of projected land use, water demand and climate change show a decrease in the number of people exposed to water scarcity during the 2°C warming period and an increase in the 2061-2090 period in the Danube River Basin. However, the projected population change results in a decrease of exposed people in both warming periods. Regions with population growth, in the northwestern part of the Danube River Basin experience low water scarcity or a decrease in water scarcity. The largest number of people vulnerable to water scarcity within the Danube River Basin are living in the Great Morava, Bulgarian Danube and Romanian Danube. There, the combined effects of land use, water demand and climate change exacerbate already existing water scarce areas during the 2°C warming period and towards the end of the century new water scarce areas are created. Although less critical during the 2°C warming period, adjacent regions such as the Tisza, Middle Danube and Siret-Prut are susceptible to experience similar exposure to water scarcity within the 2061-2090 period. Climate change is the most important driver for the increase in water scarcity in these regions, but the strengthening effect of water demand (energy sector) and dampening effect of land use change (urbanization) does play a role as well. Therefore, while preparing for times of increased pressures on the water supply it would be advisable for several economic sectors to explore and implement water efficiency measures.


Author(s):  
A. C. S. Silva ◽  
C. O. Galvão ◽  
G. N. S. Silva

Abstract. Extreme events are part of climate variability. Dealing with variability is still a challenge that might be increased due to climate change. However, impacts of extreme events are not only dependent on their variability, but also on management and governance. In Brazil, its semi-arid region is vulnerable to extreme events, especially droughts, for centuries. Actually, other Brazilian regions that have been mostly concerned with floods are currently also experiencing droughts. This article evaluates how a combination between climate variability and water governance might affect water scarcity and increase the impacts of extreme events on some regions. For this evaluation, Ostrom's framework for analyzing social-ecological systems (SES) was applied. Ostrom's framework is useful for understanding interactions between resource systems, governance systems and resource users. This study focuses on social-ecological systems located in a drought-prone region of Brazil. Two extreme events were selected, one in 1997–2000, when Brazil's new water policy was very young, and the other one in 2012–2015. The analysis of SES considering Ostrom's principle "Clearly defined boundaries" showed that deficiencies in water management cause the intensification of drought's impacts for the water users. The reasons are more related to water management and governance problems than to drought event magnitude or climate change. This is a problem that holdup advances in dealing with extreme events.


2018 ◽  
Vol 10 (11) ◽  
pp. 3953 ◽  
Author(s):  
Farzad Emami ◽  
Manfred Koch

For water-stressed regions/countries, like Iran, improving the management of agricultural water-use in the wake of climate change and increasingly unsustainable demands is of utmost importance. One step further is then the maximization of the agricultural economic benefits, by properly adjusting the irrigated crop area pattern to optimally use the limited amount of water available. To that avail, a sequential hydro-economic model has been developed and applied to the agriculturally intensively used Zarrine River Basin (ZRB), Iran. In the first step, the surface and groundwater resources, especially, the inflow to the Boukan Dam, as well as the potential crop yields are simulated using the Soil Water Assessment Tool (SWAT) hydrological model, driven by GCM/QM-downscaled climate predictions for three future 21th-century periods under three climate RCPs. While in all nine combinations consistently higher temperatures are predicted, the precipitation pattern are much more versatile, leading to corresponding changes in the future water yields. Using the basin-wide water management tool MODSIM, the SWAT-simulated water available is then optimally distributed across the different irrigation plots in the ZRB, while adhering to various environmental/demand priority constraints. MODSIM is subsequently coupled with CSPSO to optimize (maximize) the agro-economic water productivity (AEWP) of the various crops and, subsequently, the net economic benefit (NEB), using crop areas as decision variables, while respecting various crop cultivation constraints. Adhering to political food security recommendations for the country, three variants of cereal cultivation area constraints are investigated. The results indicate considerably-augmented AEWPs, resulting in a future increase of the annual NEB of ~16% to 37.4 Million USD for the 65%-cereal acreage variant, while, at the same time, the irrigation water required is reduced by ~38%. This NEB-rise is achieved by augmenting the total future crop area in the ZRB by about 47%—indicating some deficit irrigation—wherefore most of this extension will be cultivated by the high AEWP-yielding crops wheat and barley, at the expense of a tremendous reduction of alfalfa acreage. Though presently making up only small base acreages, depending on the future period/RCP, tomato- and, less so, potato- and sugar beet-cultivation areas will also be increased significantly.


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