Runoff outputs from 11 atmosphere-ocean general circulation models (AOGCMs) participating in the fifth phase of Coupled Model Intercomparison Project were used to evaluate the changes in streamflow and agreement among AOGCMs at the end of 21st century. Under the highest emission scenario (Representative Concentration Pathways (RCP) 8.5), high flow is projected to increase in northern high latitudes of Eurasia and North America, Asia, and eastern Africa, while mean and low flows are both projected to decrease in Europe, Middle East, southwestern United States, and Central America. Projected changes under RCP4.5 show similar spatial distribution but with lower magnitude. The model spread of projected changes, however, is found to be large under both scenarios. Bootstrapped Mann-Whitney-Wilcoxon U test revealed that projected changes of streamflow regimes are statistically not significant in 8-32% (19-59%) of the world under RCP8.5 (RCP4.5). The model agreement on projected increase or decrease in mean and high flows is stronger under RCP8.5 than that under RCP4.5. On the other hand, the projected changes in low flow are robust in both scenarios with strong model agreement. In ∼7% (4%) of the world, high flow is projected to increase and low flow is projected to decrease, whereas in ∼29% (13%) all mean, high, and low flows are projected to increase under RCP8.5 (RCP4.5).
This study is focused on the water‐agriculture‐environment nexus as it played out in the Murrumbidgee River Basin, eastern Australia, and how coevolution of society and water management actually transpired. Over 100 years of agricultural development the Murrumbidgee Basin experienced a “pendulum swing” in terms of water allocation, initially exclusively for agriculture production changing over to reallocation back to the environment. In this paper, we hypothesize that in the competition for water between economic livelihood and environmental wellbeing, economic diversification was the key to swinging community sentiment in favor of environmental protection, and triggering policy action that resulted in more water allocation to the environment. To test this hypothesis, we developed a sociohydrology model to link the dynamics of the whole economy (both agriculture and industry composed of manufacturing and services) to the community's sensitivity toward the environment. Changing community sensitivity influenced how water was allocated and governed and how the agricultural sector grew relative to the industrial sector (composed of manufacturing and services sectors). In this way, we show that economic diversification played a key role in influencing the community's values and preferences with respect to the environment and economic growth. Without diversification, model simulations show that the community would not have been sufficiently sensitive and willing enough to act to restore the environment, highlighting the key role of sectoral transformation in achieving the goal of sustainable agricultural development.
Migration is often seen as an adaptive human response to adverse socioenvironmental conditions, such as water scarcity. A rigorous assessment of the causes of migration, however, requires reliable information on the migration in question and related variables, such as, unemployment, which is often missing. This study explores the causes of one such type of migration, from rural to urban areas, in the Jiangsu province of China. A migration model is developed to fill a gap in the understanding of how rural to urban migration responds to variations in inputs to agricultural production including water availability and labor and how rural population forms expectations of better livelihood in urban areas. Rural to urban migration is estimated at provincial scale for period 1985-2013 and is found to be significantly linked with rural unemployment. Further, migration reacts to a change in rural unemployment after 2-4 years with 1% increase in rural unemployment, on average, leading to migration of 16,000 additional people. This implies that rural population takes a couple of years to internalize a shock in employment opportunities before migrating to cities. The analysis finds neither any evidence of migrants being pulled by better income prospects to urban areas nor being pushed out of rural areas by water scarcity. Corroborated by rural-urban migration in China migration survey data for 2008 and 2009, this means that local governments have 2-4 years of lead time after an unemployment shock, not necessarily linked to water scarcity, in rural areas to prepare for the migration wave in urban areas. This original analysis of migration over a 30-year period and finding its clear link with unemployment, and not with better income in urban areas or poor rainfall, thus provides conclusive evidence in support of policy interventions that focus on generating employment opportunities in rural areas to reduce migration flow to urban areas.
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