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1 Baker, R. E.; Yang, W.; Vecchi, G. A.; Metcalf, J. E.; Grenfell, B. T. 2020. Susceptible supply limits the role of climate in the early SARS-CoV-2 [Severe Acute Respiratory Syndrome Coronavirus 2] pandemic. Science, 10p. (Online first) [doi: https://doi.org/10.1126/science.abc2535]

Severe acute respiratory syndrome coronavirus 2 ; Pandemics ; Infection ; Climatic factors ; Disease transmission ; Population ; Susceptibility ; Immunity ; Humidity ; Models

(Location: IWMI HQ Call no: e-copy only Record No: H049701)

https://science.sciencemag.org/content/early/2020/05/15/science.abc2535.full.pdf
https://vlibrary.iwmi.org/pdf/H049701.pdf

(2.53 MB) (2.53 MB)

Preliminary evidence suggests that climate may modulate the transmission of SARS-CoV-2. Yet it remains unclear whether seasonal and geographic variations in climate can substantially alter the pandemic trajectory, given high susceptibility is a core driver. Here, we use a climate-dependent epidemic model to simulate the SARS-CoV-2 pandemic probing different scenarios based on known coronavirus biology. We find that while variations in weather may be important for endemic infections, during the pandemic stage of an emerging pathogen the climate drives only modest changes to pandemic size. A preliminary analysis of non-pharmaceutical control measures indicates that they may moderate the pandemic-climate interaction via susceptible depletion. Our findings suggest, without effective control measures, strong outbreaks are likely in more humid climates and summer weather will not substantially limit pandemic growth.

2 Liu, D.; Wang, X.; Aminjafari, S.; Yang, W.; Cui, B.; Yan, S.; Zhang, Y.; Zhu, J.; Jaramillo, F. 2020. Using InSAR [Interferometric Synthetic Aperture Radar] to identify hydrological connectivity and barriers in a highly fragmented wetland. Hydrological Processes, 14p. (Online first) [doi: https://doi.org/10.1002/hyp.13899]

Wetlands ; Hydrological factors ; SAR (radar) ; Radar imagery ; Water levels ; Satellites ; Remote sensing ; Interferometry ; Barriers ; Ecosystems ; Grasslands ; Vegetation / China / Baiyangdian Wetland

(Location: IWMI HQ Call no: e-copy only Record No: H049975)

https://onlinelibrary.wiley.com/doi/epdf/10.1002/hyp.13899
https://vlibrary.iwmi.org/pdf/H049975.pdf

(3.71 MB) (3.71 MB)

Hydrological connectivity is a critical determinant of wetland functions and health, especially in wetlands that have been heavily fragmented and regulated by human activities. However, investigating hydrological connectivity in these wetlands is challenging due to the costs of high-resolution and large-scale monitoring required in order to identify hydrological barriers within the wetlands. To overcome this challenge, we here propose an interferometric synthetic aperture radar (InSAR)-based methodology to map hydrologic connectivity and identify hydrological barriers in fragmented wetlands. This methodology was applied along 70 transects across the Baiyangdian, the largest freshwater wetland in northern China, using Sentinel 1A and 1B data, covering the period 2016–2019. We generated 58 interferograms providing information on relative water level changes across the transects that showed the high coherence needed for the assessment of hydrological connectivity. We mapped the permanent and conditional (temporary) barriers affecting connectivity. In total, 11% of all transects are permanently disconnected by hydrological barriers across all interferograms and 58% of the transects are conditionally disconnected. Areas covered by reed grasslands show the most undisturbed hydrological connectivity while some of these barriers are the result of ditches and channels within the wetland and low water levels during different periods of the year. This study highlights the potential of the application of Wetland InSAR to determine hydrological connectivity and location of hydrological barriers in highly fragmented wetlands, and facilitates the study of hydrological processes from large spatial scales and long-time scales using remote sensing technique.

3 Otto, F. E. L.; Zachariah, M.; Saeed, F.; Siddiqi, A.; Kamil, S.; Mushtaq, H.; Arulalan, T.; AchutaRao, K.; Chaithra, S. T.; Barnes, C.; Philip, S.; Kew, S.; Vautard, R.; Koren, G.; Pinto, I.; Wolski, P.; Vahlberg, M.; Singh, R.; Arrighi, J.; van Aalst, M.; Thalheimer, L.; Raju, E.; Li, S.; Yang, W.; Harrington, L. J.; Clarke, B. 2023. Climate change increased extreme monsoon rainfall, flooding highly vulnerable communities in Pakistan. Environmental Research: Climate, 2(2):025001. [doi: https://doi.org/10.1088/2752-5295/acbfd5]

Climate change ; Monsoon climate ; Rainfall ; Flooding ; Vulnerability ; Communities ; Infrastructure ; Precipitation ; Early warning systems ; Households ; Socioeconomic aspects ; Resilience / Pakistan / Balochistan / Sindh

(Location: IWMI HQ Call no: e-copy only Record No: H052368)

https://iopscience.iop.org/article/10.1088/2752-5295/acbfd5/pdf
https://vlibrary.iwmi.org/pdf/H052368.pdf

(4.36 MB) (4.36 MB)

As a direct consequence of extreme monsoon rainfall throughout the summer 2022 season Pakistan experienced the worst flooding in its history. We employ a probabilistic event attribution methodology as well as a detailed assessment of the dynamics to understand the role of climate change in this event. Many of the available state-of-the-art climate models struggle to simulate these rainfall characteristics. Those that pass our evaluation test generally show a much smaller change in likelihood and intensity of extreme rainfall than the trend we found in the observations. This discrepancy suggests that long-term variability, or processes that our evaluation may not capture, can play an important role, rendering it infeasible to quantify the overall role of human-induced climate change. However, the majority of models and observations we have analysed show that intense rainfall has become heavier as Pakistan has warmed. Some of these models suggest climate change could have increased the rainfall intensity up to 50%. The devastating impacts were also driven by the proximity of human settlements, infrastructure (homes, buildings, bridges), and agricultural land to flood plains, inadequate infrastructure, limited ex-ante risk reduction capacity, an outdated river management system, underlying vulnerabilities driven by high poverty rates and socioeconomic factors (e.g. gender, age, income, and education), and ongoing political and economic instability. Both current conditions and the potential further increase in extreme peaks in rainfall over Pakistan in light of anthropogenic climate change, highlight the urgent need to reduce vulnerability to extreme weather in Pakistan.