Potential Implications of Future Climate Change And Extremes On Health, Agriculture, Water, And Cryosphere Sectors In The Kabul River Basin

Increasing temperature and variability in precipitation are affecting different sectors in the Himalayan region. This study aims to quantify the future scenario and related extreme indices in the Kabul River Basin of the western Himalaya using high-resolution climate data sets. We selected the representative global climate model simulations for RCP4.5 and 8.5, based on their abilities to represent the historical climate cycle. By using a three-step methodology, we selected four models for RCP4.5 and four for RCP8.5. The analysis shows that, overall, precipitation will increase by 4 and 12 per cent for RCP4.5 and 8.5 respectively by the end of the 21st century, and the seasonal analysis shows decreasing pattern during the winter and pre-monsoon seasons. However, temperatures will increase consistently by 3 O C to 5 O C in RCP4.5 and 8.5 scenarios. The extreme indices were calculated based on the selected models. The extremes, like consecutive summer days, warm days, and heatwave will increase, whereas the frost days, cold nights, and cold waves will decrease towards the end of this century. Notably, more warm days and heatwaves than the baseline period are projected in future scenarios. Besides, the extremes are not homogenous in time and space. We also discussed the potential implications of these climatic extremes as related to human health, agricultural productivity, water availability, and the cryosphere. We strongly urge prompt climate actions in order to increase the adaptive capacity against these extreme changes and to build a resilient livelihood in the Kabul River Basin.


Introduction
Chen, and Xu 2016). The World Health Organization (WHO) estimates that every year about 150,000 deaths occur worldwide in low-income countries primarily due to the adverse effects of climate change; often the causes increase in vector-borne disease due to favourable temperatures, ood, crop failure, and extreme weather events (Kumaresan and Sathiakumar 2010). In the case of the agricultural sector, there have been signi cant reductions in crop yields due to change in soil quality and the menace of pests in uencing pollination (Rosenzweig, Iglesius, Yang, Epstein, and Chivian 2001). This has been threatening national and regional food security (Nelson et al. 2009). Moreover, the dependence of agriculture on rainfall, snowmelt, and glacier melt -entities that have been adversely impacted by climate changehas worsened the situation of food security and livelihoods. Meanwhile, the frequency, intensity, and duration of extreme water-related weather events such as excess precipitation, oods, and drought (Cann, Thomas, Salmon, Wyn-Jones, and Kay 2013) have altered the hydrological regime and the state of water availability, thereby increasing the demand for water for domestic and industrial purposes ( Wester, Mishra, Mukherji, and Shrestha 2019). So, often the information is generalized, and the few studies that have attempted to provide a detailed picture of the KRB have not been able to explicitly explain the reason behind selecting a particular global model for future projections. It is vital to conduct a detailed assessment while selecting a global model whereby its features, both in terms of time and space, are well understood (Shen et al. 2014); this is because these models are often in uenced by the regional signals and their ampli cation (Boberg and Christensen 2012). This study has selected the global climate model runs based on the characteristics of the KRB. The study not only presents the future changes in the average precipitation and temperature patterns of the region, it also looks at the changes in extremes events in the basin and discusses its implications for health, agriculture, water, and the overall state of the cryosphere. The novelty of this study lies in its use of climatic extremes and linking them with sectoral implications for the KRB; for this, we used high-resolution climate data sets (10 x10 km) that re ect the regional characteristics; this is a method that has not been applied before.

Methodological Approach
This section describes the methodological approach that was taken for the selection of the Global Climate Model (GCM) runs speci c to the KRB and outlines the sector-speci c indices that were used for the analysis.

Kabul River Basin
The KRB is one of the main tributaries of the Indus River (Fig. 1). The Kabul River originates from the Sanglakh Range of the Hindu Kush mountains in Afghanistan and sustains the livelihoods of millions of people in both Afghanistan and Pakistan (Hassanyar et al. 2017). The KRB covers 69312 km 2 and has an elevation range of 430-7,350 masl, with 3 per cent of the area being above 5000 m asl. The basin is dominated by 60 per cent rangeland, while forests and shrubs constitute 18 per cent of the upstream area. Then there are the irrigated lands that are located downstream (Najmuddin, Deng, and Siqi 2017). The basin, where agriculture is the main source of livelihood, accounts for about 20 per cent of the total irrigated land in Afghanistan (Lashkaripour and Hussaini 2008).
The KRB is also the most populated area in Afghanistan. The northern part of the basin has mostly high mountains while the central and south-eastern parts are low agricultural lands (Lashkaripour and Hussaini 2008). The basin has 1,364 km 2 of glaciers (2 per cent of the total area) and the region is mostly fed by snow and glacier melts. Water resources and the hydrological cycle act as important component in the sustainable development of the region (MeW 2019).

The climatic conditions for the reference period
The annual average precipitation sum of the basin is 722 mm/year (1981-2010), with February, March, and April being the months with the highest precipitation rates. The pre-monsoon season records the highest precipitation of 311 mm (43 per cent of the total), while the post-monsoon season, with 92 mm (12.8 per cent of the total), records the lowest level of precipitation. The precipitation amount, frequency, and intensity vary spatially and in uences the local weather. The spatial graph (Fig. 2) shows that the precipitation level ranges from 200 mm (central and north-eastern parts) to 1600 mm (northern part), and is more (> 1000 mm/year) in the northern part of the basin (especially in the 35°N-36°N latitude). The precipitation levels vary highly in the winter months, with the highest variability being in March.
The mean annual temperature of the basin is 1 o C; however, the mean monthly average temperature drops to -10 o C in December and January, while it increases to as high as 15 o C in July and August. Inevitably, the summer season shows the highest temperature (10.4 0 C), while the lowest (-9.3 0 C) is during the winter season. Spatially, the temperature is higher (> 3 0 C /year) in the southern part (below 35°N) of the basin (Fig. 2). The average monthly temperature shows similar variability throughout the year.
This study considered the regional data set prepared for the Himalayan Adaptation, Water and Resilience (HI-AWARE) Research (Lutz et al. 2014) as its reference data set. This data set on the average climatic condition of the basin shows the optimal precipitation and temperature ranges during the baseline period. This information helps in learning more about human adaptability in terms of precipitation and temperature ranges; it also provides a clear-cut picture about the climatic conditions that help support agricultural productivity; further, it gives us the baseline of water availability and the cryospheric condition.

Selection of the Global Circulation Model
In this study, we looked into two different climate change scenarios, RCP4.5 and RCP8.5, in order to understand the future scenario of the KRB. RCP4.5 describes a middle-range mitigation emission scenario, which assumes that the increase in radiative forcing will stabilize at 4.5 W/m 2 in 2100, while RCP8.5 corresponds to the pathway with the highest greenhouse gas emission scenario, which assumes that an increase in radiative forcing will stabilize at 8.5 W/m 2 in 2100 (Van Vuuren et al. 2011). RCP2.6, which is the optimistic scenario, requires a drastic and immediate reduction in fossil fuel consumption.
This does not seem plausible under the present condition of emissions in the world. As for the RCP6 scenario, it was not considered as it lies within the spectrum of the future scenarios of RCP4.5 and RCP8.5. Thus, based on these scenarios, the potential impact of extreme climate indices on four different sectors -health, agriculture, water resources, and the cryosphere -were studied.
There is great variability in the projections of precipitation and temperature made by different Global Circulation Models (GCMs). A total of 105 GCM runs for RCP4.5 and 77 for RCP8.5 from the Coupled Model Intercomparison Project (CMIP5) experimental design were considered for this study. Each GCM run and ensembles has represented atmospheric circulation differently, based on their physics, realization, and initialization; they have also represented the regional climatic conditions differently (Bader et al. 2008). To select the GCM runs that represent the study area, a three-step selection procedure integrating the envelope-based and past-performance approaches was used, as suggested by Lutz et al. (2016). This approach was also used for the National Adaptation Plan (MoFE 2019) as well as to understand future climate scenarios (Kaini, Nepal, Pradhananga, Gardner, and Sharma 2019). The following were the three steps: In the rst step, the changes in the annual mean air temperature (ΔT) and annual precipitation sum (ΔP) between 1981-2100 and 2071-2100 were calculated over the area of interest of all GCM runs. The distribution of change values provided four different spectra of possible climatic conditions: warm-dry, warm-wet, cold-dry, and cold-wet. Five models from each corner (from 20 GCM runs) were selected based on projections of temperature and precipitation change for both RCPs. Here, only those models that had data available at a daily time-step were selected.
In the second step, the 20 model runs obtained from the rst step were reduced to eight models, based on their projected changes in climatic extremes for both RCPs. Here, two climate change indices for both air temperature and precipitation were used (Peterson 2005). For temperature, the Warm Spell Duration Index (WSDI) and the Cold Spell Duration Index (CSDI) were analysed, while for the precipitation, the number of extremely wet days (R95pTOT) and Consecutive Dry Days (CDD) were considered. The percentage changes in the indices were calculated for 2071-2100 using the reference period of 1981-2010.
In the third step, the nal selection of four GCM runs for each scenario was based on the skill of these models represent the historical climate cycle (from 1981-2010) using reference data sets.. The regional data set prepared for the HI-AWARE Research ( Lutz et al. 2014) was considered as the reference data set, and summer, winter, and annual biases were considered for the analysis of both precipitation and temperature. Speci cally, we considered winter precipitation since the study area gets the majority of its precipitation during this season.

Sector-speci c climatic indices
We chose 10 extreme indices to indicate the implications for the sectors of health, agriculture, water resources, and the cryosphere, as de ned by the ET-SCI (Expert Team on Sector-Speci c Climate Indices). Some indices were applied to more than one sector (Table 1). For our analysis, we selected six indices for water resources (that included the cryosphere), nine for agriculture, and nine for the health sector. In the result section, the two opposite extremes indices are presented together for e cient visualization and understanding. Consecutive Summer Days (CSU) and Consecutive Frost Days (CFD) re ect the heat and cold indices of the area. CSU is counted as the maximum number of consecutive days when the maximum temperature is greater than the average daily maximum temperature, 6.2°C for the KRB. Similarly, CFD is the maximum number of consecutive days with a daily minimum temperature of less than 0°C.
The HWDI and the CWDI, with respect to the mean of the reference period, re ect excessive heat days or excessive cold days. The HWDI shows the number of consecutive days when the daily maximum temperature (TX) is greater than the mean (a ve-day window centred on each calendar day) of the daily maximum temperature of the reference period (TXnorm) and the temperature offset (T) ( i.e., HWDI = TX > TXnorm + T). More than 6 consecutive days are considered and the offset temperature is taken as 5 O C. Likewise, the CWDI indicates the number of days when: TN < TNnorm -T. Here, TN is the daily minimum temperature, TNnorm is the mean of the minimum temperatures of a given climate reference period (i.e., 1981-2010).
Warm days with respect to the 90th percentile of the reference period (TG90P) and cold nights with respect to the 10th percentile of the reference period (TN10P) help in understanding the sensitivity of the day and night-time temperatures in the KRB. To calculate the warm days, the percentage of warm days with respect to the 90th percentile of the daily mean temperatures of a ve-day window centred on each calendar day of the reference period (1981-2010) was calculated. Likewise, for calculating the cold nights, the percentage of cold days with respect to the 10th percentile of the daily minimum temperatures of a ve-day window centred on each calendar day of the reference period (1981-2010) was calculated. The percentage was then converted to the number of days per year by multiplying by 3.65.
CDD and CWD re ect the dryness and wetness of an area. CDD is the maximum number of consecutive precipitation days with less than 1mm during a year. Likewise, CWD is the maximum number of consecutive precipitation days greater than 1 mm during a year. In the visualization, the annual change is presented spatially to show the projected changes in the different areas of the basin. These two indices indicate whether there will be more dryness or wetness in the future.
Very high precipitation (RGT90P) and very low precipitation (RLT10P) re ect the extremes of precipitation. RGT90P is the number of days when the daily precipitation amount is more than the 90th percentile of the daily average precipitation. For this, at rst, the 90th percentile precipitation was calculated (5'mm for KRB); then this value was used to calculate the number of days with precipitation of at least more than 5 mm for the annual time series of the daily precipitation. Likewise, for very low precipitation, the threshold of the 10th percentile of precipitation (1 mm) was used. Based on this value, the number of days with a maximum of 1 mm of precipitation was counted. Figure 3 shows the projected changes in temperature and precipitation from the reference period  to the end of the century (2071-2100). The gure shows that the temperature would rise in the range of 3-10 o C and the precipitation would increase in the range of 0-50 per cent. From this rst step, ve GCM runs were selected from each corner, and altogether, 20 GCMs were selected. This corner represents four possible future climates: warm-dry, warm-wet, cold-wet, and cold-dry. Table 2 shows the selected 20 model runs that were selected from step 1 and how these model runs were ltered up to step 3. Table 2a shows the values of the climate change indices of the 20 models. From step 2, 12 model runs in RCP4.5 and eight in RCP8.5 were further selected. These were the model runs that showed the highest change in extreme values by the end of the century.  Table 2b shows the seasonal and annual biases of temperature and precipitation that were applied in the third step. The temperature and precipitation biases of summer and winter were calculated -to re ect the seasonal dynamics. The lowest bias models, i.e. models which better represent the historical cycles, were selected as the nal models at each corner of each RCP. The details of the selected models are presented in Table 3.

The future scenario of temperature and precipitation in the basin
The temperature of the KRB is projected to increase by 2.7 o C in RCP4.5 and by 5.1 o C in RCP8.5 scenarios, and the precipitation is projected to increase by 4.5 per cent in RCP4.5 and by 12.4 per cent in RCP8.5 compared to the reference period (Fig. 4). Table 4 shows that all the eight models signify increasing temperature in both scenarios. The standard deviation among the models in terms of temperature change is low (  The seasonal projection shows that the temperature of the basin will increase more in the winter and post-monsoon seasons, followed by monsoon (Table 5). There will be less precipitation in winter during RCP4.5, while in RCP8.5, it will decrease both in the winter and pre-monsoon seasons. This is similar to   Table 6 presents the values of extreme indices during the reference period (1981-2010 ), mid-century (2036-2065) and by the end of the century (2071-2100). Here, warm days and the HWDI are projected to increase at an alarming rate; 157 warm days are projected in RCP4.5 and 259 in RCP8.5; however, during the reference period, it is 35 warm days. As for heatwaves, they will occur for 79 days in RCP4.5 and for

Consecutive Summer Days and Consecutive Frost Days
Summer days will increase, and the frost days will decrease in the basin. On an average, the summer days (reference period: 142 days) are projected to increase to 199 in RCP8.5 and to 165 days in RCP4.5 by the end of the century. However, frost days would decrease to 177 in the RCP8.5 scenario (reference period: 243.5 days). In Fig. 5, the percent of change from the base period (1981-2010) is shown. The summer days will be more in the north-eastern part and the decrease in the frost days will be more in the south-eastern part of the basin, though similar changes will be observed throughout the basin. The northeastern part of the basin is mostly at a higher altitude, while the south-eastern part is at-land area, with human settlement. This means that there will be more summer in the upstream area, while the settlement area will have fewer frost days. This will likely in uence the livelihood and ecosystem of the region.

Heatwave Duration Index and Cold Wave Duration
Index with respect to the mean of the reference period Figure 6 shows the annual values of the HWDI and the CWDI. Here, the projections are of a continuous increase in heatwave and a decrease in cold wave. The HWDI will increase to an average of 79 days in RCP4.5 and 176 days in RCP8.5. The CWDI will decrease to 2.9 days in RCP4.5 and 1.9 days in RCP4.5. Thus, there is a higher possibility of uncomfortably hot and unusually humid weather in the future in the KRB.

Warm days and cold nights with respect to the 90th
and 10th percentiles, respectively, of the reference period Figure 7 shows that the number of warm days will continually increase, while the number of cold nights will decrease in the future scenario. The average of 35.5 days of warm days will rise to between 157 (RCP4.5) and 259 days (RCP8.5) by the end of the century. However, the average 36.2 days of cold days will decrease between 11.5 (RCP 4.5) and 5.8 days (RCP8.5) by the end of the century. The trend of increasing warm days in RCP8.5 is rather alarming. This increase in diurnal temperature and decrease in nocturnal temperature are likely to have serious impacts on different sectors.

Consecutive Dry Days and Consecutive Wet Days
Both CDD and CWD are likely to increase, but not in a distinct pattern. Figure 8 shows that during the reference period (1981-2010), the average number of CDD was 54 days; this will change to 47 days in RCP4.5 and to 56 days in RCP8.5 during 2071-2100. Further, while the number of CWD will remain almost the same during the base period, in the future, in both scenarios, it will nominally uctuate.
Spatially, CDD will occur prominently mostly in the west and CWD in the east. Figure 9 shows that the pattern of extreme precipitation will vary in the future scenario. The 10-year moving average shows that the number of days greater than the 90th percentile is likely to decrease, but with some variability. There is no clear trend, but the end of the century will see an average of 35 wet days, with a standard deviation of six days (reference period: 37 days). In the case of days with very low precipitation, they are likely to increase to 285 (baseline period: 278 days), with a standard deviation of nine days. This change in extreme precipitation patterns is likely to have a great bearing on the quality and quantity of rainfall utilized by human beings and natural resources.

Discussion
Our study presents the future scenario of precipitation and temperature patterns in the Kabul River Basin.
It shows that there will not only be gradual changes in the levels of precipitation and temperature, but there will also be a sharp rise in climatic extremes with pronounced changes in their magnitude and frequency. As communities tend to adapt poorly to climatic extremes, these changes will cause more harm to human health, food security, and the natural ecosystem compared to the gradual changes.
Moreover, since the responses of the communities and the natural ecosystem will not be linear and intuitive in response to these extreme events, the impacts they will cause will be much more damaging. In this regard, taking into account the extreme climatic events that are likely to occur in the KRB in the future and considering the heterogeneous nature of their impact in terms of time, space, and individual, we discuss below the effects this will have on the four areas of health, agriculture, water resources, and the cryosphere (Table 7). Importantly, these sectors are not stand-alone -they are interlinked; so, any negative in uence on them can lead to more stress on the social system in terms of adaptation, while there's also the danger of unhealthy competition to gain access to the resources (Bowles et al., 2014)..

Human health
The KRB accounts for 35 per cent of Afghanistan's population and has the fastest population growth rate compared to other parts of Afghanistan (MEW and World Bank 2013). The projected increase in heatwaves and summer days in the basin will lead to a surge in illnesses and deaths as the body's ability to regulate its temperature gets compromised. This is likely to have both direct (in the form of escalating  Table 7. Along with climatic factors, non-climatic factors such as demographic distribution, socio-economic status, cultural conditions, adaptive capacity, and access to health care, play a key role (CCSP 2008). Here, it has to be noted that it is the vulnerable section of the population, like women, children, the elderly, and the differently abled people, would be at the higher risk of mortality rate.

Agriculture and food security
Cereals such as wheat, corn, barley, sorghum, rice, and potatoes, and other entities such as cotton, fruits,  (Table 7) have provided examples on the risksand uncertainties regarding crop production and food security.
Moreover, it is likely, any adverse impacts on agricultural productivity will have harmful effects on mental health and well-being; they will also lead to con icts and compel unfair competition for the available natural systems. Then there's the likelihood of increased migration of humans and other species, and invasion by alien species. Nonetheless, the aggregate impacts of climate change and extreme events on agricultural productivity are complex to be reliably quanti ed, mainly due to the difference in climate type and associated agriculture processes and productivity (Gornall et al. 2010).

Water resources and hydrology
The increase in temperature and decrease in winter and pre-monsoon precipitation in the KRB in the future are likely to in uence the availability of water for household use and crop production. Likewise, as consecutive dry days increase and the precipitation days become more inconsistent, there's more likelihood of droughts and oods (Tabari 2020); they will also in uence hydropower generation and trigger changes in river ow, sediment load, and even in aquatic biodiversity (Whitehead, Wilby, Battarbee, Kernan, and Wade, 2009). Some examples from Kerala, the Colorado River, and Europe, as shown in Table 7, re ect the in uences on the natural cycle of water due to extreme events. Although water is inherently owing and continually being recharged (Oki and Kanae, 2006), the consistency, availability, and accessibility at a given location and time matter the most. Also, location-speci c, e cient water resource management approaches will be affected.

Cryosphere
The future scenarios indicate that the temperature of the KRB will increase by 2.6 0 C to 5.1 0 C and that the basin will have fewer frost days. This will create additional vulnerability in of the cryosphere. There is likely to be a shift from the solid form of precipitation to the liquid form. The major glaciers in the northwestern part of the basin are likely to decrease signi cantly. The examples (Table 7) from the Canadian Arctic show that rising temperatures have signi cantly affected the Arctic ecosystem, while in the Tibet region, glacier retreat has been detected. Similarly, changes in the patterns of ice melt, permafrost, and seasonally frozen ground are likely to affect the entire landscape of the basin, and also detract from its scenic appeal. This will also reduce slope stability, leading to natural hazards like landslide and erosion.
Considering the heterogeneous nature of the KRB, only a detailed assessment of the components of the cryosphere and the mass balance in the basin can quantify the exact magnitude of the impacts. • There occurred 20-49 per cent variance in yield anomalies due to extreme climate events, which were largely attributed to temperature-related extremes.
• The regions that are particularly susceptible are North America (in the case of maize, spring wheat, and soy production) and Asia (in the case of maize and rice production). Further, apart from these four sectors, the altered frequencies and amplitude of extreme events may change the demographic rates, tness, and the community structure of species (Ma, Rudolf and Ma 2015); they will also have a bearing on wind-power generation due to changes in the intensity and duration of wind speed. There is also the probability of an increase in disasters and adverse changes in the aquatic ecosystem; meanwhile, the availability of timber and non-timber forest products, too, will be under threat This list of implications in the different sectors can be extensive but along with the relative value of change in any hydro-meteorological characteristics of a location; the spatial extent, location's climatology, the adaptive capacity of the human and natural system also plays a crucial role in determining the impact of the change in that location .

Conclusion
This study has analysed the future climate change scenarios and extreme events in the Kabul River Basin by downscaling the four global climate model runs for RCP4.5 and 8.5. The models were selected by considering the changes in extremes and because of their skill to represent the historical climate cycle.
The selected global climate models suggest an increase in the average temperature (by 2.6-5.1 o C) and precipitation (by 4.5-12.2 per cent) levels in the KRB by the end of the century. However, the seasonal analysis shows that the precipitation level during the pre-monsoon season (which accounts for 43 per cent of the total precipitation) is likely to decrease by the end of the century. Likewise, winter precipitation will decrease (by -13 mm/year with a standard deviation of 14) in RCP4.5; while it will increase (by 16 mm/year with a standard deviation of 41.3) in RCP8.5. This variability in precipitation in the basin is accompanied by increasing temperatures in both scenarios, thereby escalating the state of climatic vulnerability.
Further, the analysis of the extreme events in the basin brought forth some noteworthy points: warm days, consecutive summer days, consecutive dry days, and the duration of heatwaves will increase; at the same time, the number of cold nights, consecutive frost days, and the duration of cold waves will decrease. The discussion section has highlighted the impacts of these extreme events on the sectors of health, agriculture, water resources, and the cryosphere. And these impacts are likely to threaten human health and well-being in diverse ways. As for extreme precipitation events, they can exacerbate water-related disasters like oods and ash oods. Similarly, agricultural productivity stands to be affected by the decrease in frost days and the increase in warm days. These changes can affect the overall ecosystem of the basin.
In a nutshell, this study presents a glimpse of how human health, agriculture, water, and the cryosphere can be adversely affected by extreme events. It also outlines the environmental challenges to the basin, which should compel urgent actions simultaneously on many fronts so that the basin is in a position to sustain itself. The detailed assessment of the hydro-climatic variables and their impact on different sectors would help in being better prepared for any climatic eventuality in the future. It has also got to be emphasized that there's a need for a robust and actionable climate information system at the sub-basin and regional levels and also an urgency for policy responses to climate change adaptation.

Con icts of interest/Competing interests:
There is no con ict of interest among the authors.
Availability of data and material: The global data were downloaded from the climate4impact.eu portal and downscaled data can be shared on request to the corresponding author

Code availability
The codes for sectorial analysis can be shared on request to the corresponding author Authors contributions: Kabi Raj Khatiwada conceptualized, designed and lead the overall analysis of the manuscript. Saurav Pradhanaga and Santosh Nepal helped in the methodology, analysis, interpretation, visualization of the results, and nalizing the manuscript Funding Not applicable