Your search found 20 records
1 Jury, M. R. 2011. Climatic factors modulating Nile River flow. In Melesse, A. M. (Ed.). Nile River Basin: hydrology, climate and water use. Dordrecht, Netherlands: Springer. pp.267-280.
Climatic factors ; Rivers ; Rain ; Catchment areas ; Highlands ; Maps ; Forcing / Ethiopia / Nile River
(Location: IWMI HQ Call no: 551.483 G136 MEL Record No: H044033)
2 De Silva, Sanjiv; Curnow, J.; Ariyatne, A. 2016. Groundwater rising: agrarian resilience against climatic impacts on water resources. In Shamsuddoha, Md.; Pandey, M. S.; Chowdhury, R. K. (Eds.). Climate change in the bay of bengal region exploring sectoral cooperation for sustaiable development. Dhaka, Bangladesh: Coastal Association for Social Transformation (COAST) Trust. pp.93-109.
Groundwater ; Agrarian structure ; Climatic factors ; Climate change ; Water resources ; Surface water ; Water use ; Water storage ; Irrigation water ; Domestic water ; Industrial uses ; Rain ; Tank irrigation ; Food security ; Rice ; Dry season ; Rainfed farming ; Wells ; Cultivation ; Households ; Farmers ; Case studies / Sri Lanka / Bangladesh
(Location: IWMI HQ Call no: e-copy only Record No: H048070)
3 Kadyampakeni, Davie M.; Mul, Marloes L.; Obuobie, E.; Appoh, Richard; Owusu, Afua; Ghansah, Benjamin; Boakye-Acheampong, Enoch; Barron, Jennie. 2017. Agro-climatic and hydrological characterization of selected watersheds in northern Ghana. Colombo, Sri Lanka: International Water Management Institute (IWMI). 40p. (IWMI Working Paper 173) [doi: https://doi.org/10.5337/2017.209]
Watersheds ; Agricultural production ; Intensification ; Agroclimatology ; Hydrology ; Analytical method ; Agronomic practices ; Water balance ; Water quality ; Water management ; Water deficit ; Climatic factors ; pH ; Electrical conductivity ; Soil texture ; Soil quality ; Soil sampling ; Soil fertility ; Land cover mapping ; Land use ; Rain ; Temperature ; Evapotranspiration ; Farmers ; Wet season ; Dry season ; Reservoir storage ; Wells ; Rivers ; Irrigation schemes ; Catchment areas ; Cropping systems ; Crop production ; Meteorological stations ; Cation exchange capacity / Ghana
(Location: IWMI HQ Call no: IWMI Record No: H048209)
(1 MB)
This paper provides the climatic and biophysical context of three watersheds in northern Ghana. The objective of the study is to describe the agro-climatic and hydrological features of the watersheds from a landscape perspective. The analyses show that water surplus occurs about 3 months in a year, with only one month providing a significant surplus. Small-scale irrigation is, therefore, carried out in the dry months between November and June. The quality of water used for irrigation from wells, reservoirs and rivers is good for irrigation and domestic purposes. The soil chemical parameters across the study sites show that the soils are suitable for irrigation and crop system intensification, although it requires substantial fertilizer inputs. The paper concludes that there are opportunities from both a soil quality and water availability perspective to enhance sustainable intensification through small- and medium-scale irrigation in the selected watersheds.
4 Dar, E. A.; Brar, A. S.; Singh, K. B. 2017. Water use and productivity of drip irrigated wheat under variable climatic and soil moisture regimes in North-West, India. Agriculture, Ecosystems and Environment, 248:9-19. [doi: https://doi.org/10.1016/j.agee.2017.07.019]
Drip irrigation ; Irrigated farming ; Water use ; Water productivity ; Crop yield ; Wheat ; Climatic factors ; Rain ; Soil moisture ; Water balance ; Water conservation ; Irrigation management ; Irrigation scheduling ; Evapotranspiration ; Sowing date ; Experimental design / India / Punjab
(Location: IWMI HQ Call no: e-copy only Record No: H048319)
(0.92 MB)
In North-Western India, wheat is normally irrigated at an IW: CPE of 0.9, with 75 mm depth of irrigation water (conventional irrigation practice, CP) resulting in wastage of water. An effective irrigation strategy is required that will save irrigation water without compromising yield penalty. So, an experiment was conducted at Punjab Agricultural University, Ludhiana during 2014–15 and 2015–16 in split plot design, keeping four sowing dates {25th October (D1), 10th November (D2), 25th November (D3) and 10th December (D4)} in the main plots and five irrigation schedules {irrigation at 15 (FC15), 25 (FC25), 35 (FC35) and 45 (FC45)% depletion of soil moisture from field capacity (FC) and a conventional practice} in sub plots. The objectives of the study were to evaluate the effect of drip irrigation amounts on field water balance, yield and water productivity of wheat. The results revealed that mean grain yield decreased by 8.3 & 8.7, 10.7 & 10.6 and 13.1 & 13.4% from D1 to D2, D2 to D3 and D3 to D4 during 2014-15 and 2015-16, respectively. Pooled grain yield decreased by 29% with delay in sowing from D1 to D4. Reduction in ETc was 10% in D4 as compared to D1 during 2014-15 and 24% during 2015-16. The highest grain yield was obtained with irrigation applied at 15% depletion from FC. The pooled grain yield decreased by 30%, ETc by 21% and water productivity by 29% in FC45 as compared to FC15. The water saving in drip irrigation during 2014-15 was 62, 70, 77 and 83% in FC15, FC25, FC35 and FC45 respectively as compared to CP. The respective values during 2015-16 were 38, 44, 54 and 60%. The results demonstrate that irrigating wheat at 15% depletion of FC using drip method of irrigation as a novel concept that saves irrigation water in addition to higher grain yield.
5 Anarbekov, Oyture; Gaipnazarov, Norboy; Akramov, Isomiddin; Djumaboev, Kakhramon; Gafurov, Zafar; Solieva, Umida; Khodjaev, Shovkat; Eltazarov, Sarvarbek; Tashmatova, Mukhtabar. 2018. Overview of existing river basins in Uzbekistan and the selection of pilot basins. [Project Report of the Sustainable Management of Water Resources in Rural Areas in Uzbekistan. Component 1: National policy framework for water governance and integrated water resources management and supply part] Colombo, Sri Lanka: International Water Management Institute (IWMI) 89p. [doi: https://doi.org/10.5337/2018.203]
Integrated management ; Water resources ; Water management ; Water governance ; Water supply ; Water use ; International waters ; Sustainability ; Rural areas ; Climatic factors ; Meteorological factors ; Hydrometeorology ; Irrigation systems ; Irrigated land ; Land resources ; Land use ; River basin management ; Streams ; Pumps ; Assessment ; Population density ; Population growth ; Soil salinity ; Agricultural production / Uzbekistan
(Location: IWMI HQ Call no: e-copy only Record No: H048491)
(6 MB)
6 Joshi, N. M.; Subedee, S.; Pandey, D. R. (Eds.) 2017. Proceedings of the Seventh International Seminar on Irrigation in Local Adaptation and Resilience, Kathmandu, Nepal, 11-12 April 2017. Kathmandu, Nepal: Farmer Managed Irrigation Systems Promotion Trust. 348p.
Irrigation systems ; Irrigation management ; Irrigation practices ; Drip irrigation ; Farmer managed irrigation systems ; Climate change ; Climatic factors ; Small scale systems ; Water management ; Water availability ; Water distribution ; Water resources ; Water security ; Water governance ; Economic impact ; Multiple use ; Financing ; Highlands ; Sustainability ; Solar energy ; Economic aspects ; Cost benefit analysis ; Rural areas ; Food security ; Municipal authorities ; Socioeconomic environment ; Gender ; Women's participation ; Role of women ; Equity ; Decentralization ; Planning ; Case studies / Nepal / Nawalparasi District / Chiang Mai / Kapilavastu / Mae Rim District / Dhikurpokhari / Kaski / Andhikhola River Basin / Chapakot Irrigation System
(Location: IWMI HQ Call no: 333.913 G000 JOS Record No: H048568)
7 Rao, M. P.; Cook, E. R.; Cook, B. I.; Palmer, J. G.; Uriarte, M.; Devineni, N.; Lall, U.; D’Arrigo, R. D.; Woodhouse, C. A.; Ahmed, M.; Zafar, M. U.; Khan, N.; Khan, A.; Wahab, M. 2018. Six centuries of Upper Indus Basin streamflow variability and its climatic drivers. Water Resources Research, 54(8):5687-5701. [doi: https://doi.org/10.1029/2018WR023080]
River basins ; Stream flow ; Climatic factors ; Temperature ; Precipitation ; Discharges ; Forecasting ; Models ; Regression analysis ; Principal component analysis / Pakistan / Upper Indus Basin / Partab Bridge / Doyian / Gilgit / Kachora
(Location: IWMI HQ Call no: e-copy only Record No: H048920)
(3.32 MB)
Our understanding of the full range of natural variability in streamflow, including how modern flow compares to the past, is poorly understood for the Upper Indus Basin because of short instrumental gauge records. To help address this challenge, we use Hierarchical Bayesian Regression with partial pooling to develop six centuries long (1394–2008 CE) streamflow reconstructions at three Upper Indus Basin gauges (Doyian, Gilgit, and Kachora), concurrently demonstrating that Hierarchical Bayesian Regression can be used to reconstruct short records with interspersed missing data. At one gauge (Partab Bridge), with a longer instrumental record (47 years), we develop reconstructions using both Bayesian regression and the more conventionally used principal components regression. The reconstructions produced by principal components regression and Bayesian regression at Partab Bridge are nearly identical and yield comparable reconstruction skill statistics, highlighting that the resulting tree ring reconstruction of streamflow is not dependent on the choice of statistical method. Reconstructions at all four reconstructions indicate that flow levels in the 1990s were higher than mean flow for the past six centuries. While streamflow appears most sensitive to accumulated winter (January–March) precipitation and summer (May–September) temperature, with warm summers contributing to high flow through increased melt of snow and glaciers, shifts in winter precipitation and summer temperatures cannot explain the anomalously high flow during the 1990s. Regardless, the sensitivity of streamflow to summer temperatures suggests that projected warming may increase streamflow in coming decades, though long-term water risk will additionally depend on changes in snowfall and glacial mass balance.
8 Ghale, Y. A. G.; Baykara, M.; Unal, A. 2019. Investigating the interaction between agricultural lands and Urmia Lake ecosystem using remote sensing techniques and hydro-climatic data analysis. Agricultural Water Management, 221:566-579. [doi: https://doi.org/10.1016/j.agwat.2019.05.028]
Farmland ; Lakes ; Ecosystems ; Agricultural development ; Water management ; Hydroclimatology ; Remote sensing ; Techniques ; Landsat ; Satellite imagery ; Soil salinity ; Desertification ; Land cover change ; Irrigated land ; Anthropogenic factors ; Climatic factors / Iran / Urmia Lake
(Location: IWMI HQ Call no: e-copy only Record No: H049260)
(6.51 MB)
Urmia Lake (UL) located in the northwest of Iran, is one of the largest hypersaline lakes in the world. In recent years, most of the lake has been rendered to unusable lands. Drought and rapid increase in agricultural activities are the most important reasons behind the shrinkage of the lake. In this study, hydro-climatic data, Landsat satellite images and image processing techniques were used to detect the spatio-temporal land cover changes and salinization progress in Urmia Lake Basin (ULB) between 1975 and 2019. Increasing the area of irrigated lands from 1265 km2 in 1975 to 5525 km2 in 2011 in contrast to decreasing the water surface area of UL from 5982 km2 in 1995 to 586 km2 in 2014 and extension of salinization in the basin are the most important and thoughtful results of this study. Even the agricultural lands in the regions close to the lake have been affected by this environmental problem. The climatic conditions have gradually improved after 2014 and the government has released more water from dams to the lake. On the other hand, the area of irrigated lands has gradually decreased by 12% in the same period. As a result of these positive changes, the water surface area of the lake has gradually increased over 1000 km2. Based on the results of this study, both anthropogenic and climatic factors have played a positive role in UL restoration. Improvement of agricultural methods and providing a sustainable agricultural water management system under a changing climate can play the most effective role in the lake rehabilitation.
9 Gafurov, Zafar; Eltazarov, S.; Akramov, Bekzod; Yuldashev, Tulkun; Djumaboev, Kakhramon; Anarbekov, Oyture. 2018. Modifying Hargreaves-Samani equation for estimating reference evapotranspiration in dryland regions of Amudarya River Basin. Agricultural Sciences, 9(10):1354-1368. [doi: https://doi.org/10.4236/as.2018.910094]
River basins ; Evapotranspiration ; Estimation ; Forecasting ; Arid zones ; Temperature ; Irrigated land ; Climatic factors ; Statistical methods / Central Asia / Uzbekistan / Amu Darya River Basin / Karshi Steppe
(Location: IWMI HQ Call no: e-copy only Record No: H049270)
(2.21 MB) (2.21 MB)
Reference evapotranspiration (ETo) is a key factor in determining the amount of water needed for crops, which is crucial to correct irrigation planning. FAO Penman-Monteith (EToPM) is among the most popular method to estimate ETo. Apparently sometimes it is difficult to compute ETo using Penman-Monteith due to challenges on data availability. FAO Penman-Monteith method requires many parameters (solar radiation, air temperature, wind speed and humidity), while Hargreaves-Samani method calculates ETo based on air temperature. Because Central Asia is a data limited region with weather stations unable to provide all required parameters for the PM method, this study aimed to estimate ETo using the Hargreaves and Samani (HS) method in Karshi Steppe, in Kashkadarya province, in southern Uzbekistan, based on data from 2011 to 2017. Reference evapotranspiration calculated by non-modified HS method is underestimated during the summer months. The reason for this underestimation might be higher air temperature and wind speed during these months. Therefore, the HS method in its original form cannot be used in our study area to estimate ETo. Modification of the EToHS, through application of a bias correction factor, had better performance and allowed improving the accuracy of the ETo calculation for this region. The calculated ETo values can inform decision making and management practices regarding water allocation, irrigation scheduling and crop selection in dry land regions of Amudarya river basin and the greater Central Asia area.
10 Chuthong, J.; Liu, H.; Xu, F.; Cheng, D.; Zhang, W.; Leh, Mansoor; Lacombe, Guillaume. 2019. Joint research on hydrological impacts of the Lancang hydropower cascade on downstream extreme events: final report. Vientiane, Lao PDR: Mekong River Commission (MRC); Beijing, China: Lancang-Mekong Water Resources Cooperation Center (LMWRCC); Beijing, China: China Institute of Water Resources and Hydropower Research (IWHR); Colombo, Sri Lanka: International Water Management Institute (IWMI). 140p.
Hydropower ; Development projects ; Hydrological factors ; Extreme weather events ; Drought ; Flooding ; Precipitation ; Rain ; Water resources ; Reservoirs ; Rivers ; Dams ; Stream flow ; Discharges ; Water levels ; Runoff ; Dry season ; Climatic factors ; International waters ; Meteorological stations ; Salinity ; Models / China / Thailand / Lao People's Democratic Republic / Cambodia / Myanmar / Vietnam / Lancang-Mekong Basin / Lancang River / Mekong River / Mekong Delta / Chiang Saen Sub Basin / Luang Prabang Sub Basin / Jinghong / Nong Khai / Nakhon Phanom / Mukdahan / Pakse / Stung Treng / Kratie
(Location: IWMI HQ Call no: e-copy only Record No: H049432)
(11.10 MB)
11 Chen, M.; Luo, Y.; Shen, Y.; Han, Z.; Cui, Y. 2020. Driving force analysis of irrigation water consumption using principal component regression analysis. Agricultural Water Management, 234:106089 (Online first) [doi: https://doi.org/10.1016/j.agwat.2020.106089]
Irrigation water ; Water use ; Water resources ; Climatic factors ; Economic development ; Planting methods ; Models ; Techniques ; Principal component analysis ; Regression analysis ; Cluster analysis / China
(Location: IWMI HQ Call no: e-copy only Record No: H049567)
(4.91 MB)
The effective management of irrigation water consumption is one of the main countermeasures to combat water shortages. This paper introduced an integrated approach to determine the major factors influencing irrigation water consumption in China. It combined multiple linear regression and principal component analysis to analyze the relationship between irrigation water consumption and influencing factors and then applied analytic hierarchy process and cluster analysis to analyze the spatial variation in driving factors of irrigation water consumption. Based on statistical data from the 31 provinces of China from 2000 to 2015, the results showed that irrigation water consumption was positively affected by the planting size, the ratio of surface water in water consumption (RSW), the planting structure, the annual ET0 (AE) and the annual average temperature (AAT); in contrast, consumption was generally negatively affected by irrigation technique, economic development, and annual rainfall (AR). The water consumption structure, irrigation technique and planting structure were major influential factors in most provinces of China, and there were significant differences in different regions; thus, regions should be restructured to be studied as subregions. For the total consumption of irrigation water, Central China was mainly affected by the water consumption structure, irrigation technique and climatic conditions, and North and Northwest China were hardly influenced by planting structure. Northeast, Southwest and southeastern coastal China were slightly affected by climatic conditions. For the per unit area irrigation water consumption, Central China was mainly affected by the water consumption structure, irrigation technique, planting size and climatic conditions, Southwest, South, East and Northeast China were mainly affected by the planting structure and planting size, and Northwest and North China were mainly influenced by the irrigation technique, water consumption structure and planting size.
12 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
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.
13 Mukhamedjanov, S.; Mukhomedjanov, A.; Sagdullaev, R.; Khasanova, N, 2021. Adaptation to climate change in irrigated agriculture in Uzbekistan. Irrigation and Drainage, 70(1):169-176. [doi: https://doi.org/10.1002/ird.2529]
Climate change adaptation ; Irrigated farming ; Water resources ; Climatic factors ; Precipitation ; Air temperature ; Agricultural production ; Rain / Central Asia / Uzbekistan / Fergana Valley / Quva
(Location: IWMI HQ Call no: e-copy only Record No: H049997)
(1.06 MB)
In recent years, climate change in Central Asia, especially in Uzbekistan, has resulted in sharp alternation of dry and wet years. In such conditions, agriculture has turned into the most vulnerable sector. Agricultural producers have not been able to adapt to such variations of climatic conditions. Traditional irrigation approaches and agronomic operations are becoming unacceptable against the background of severe droughts or heavy rains. Moreover, intra-annual distribution of precipitation and air temperature has changed. Especially in agriculture, increased rainfall in spring and summer and decreased rainfall in autumn and winter has had a negative impact.
In 2013, the Global Water Partnership initiated the Water, Climate, and Development Programme for Caucasus and Central Asia. In the Fergana Valley of Uzbekistan, a project was implemented to study the possibility of agriculture adaptation to climate change within the framework of this programme. This article presents an analysis of long-term data received from 1960 to 2014 on air temperature and precipitation. As a result of these studies, it has been determined that we can forecast the current year's weather conditions if we find a similar year in recent years. For the Fergana Valley of Uzbekistan, it has been established that we have a stable spring, when winter is cold with heavy precipitation, and we have a cold spring and summer with high precipitation, when we have a warm winter with low precipitation. Past experience has shown that the use of water for irrigation, taking into account climatic conditions, has a significant impact on reducing irrigation water and increasing crop yields.
In 2013, the Global Water Partnership initiated the Water, Climate, and Development Programme for Caucasus and Central Asia. In the Fergana Valley of Uzbekistan, a project was implemented to study the possibility of agriculture adaptation to climate change within the framework of this programme. This article presents an analysis of long-term data received from 1960 to 2014 on air temperature and precipitation. As a result of these studies, it has been determined that we can forecast the current year's weather conditions if we find a similar year in recent years. For the Fergana Valley of Uzbekistan, it has been established that we have a stable spring, when winter is cold with heavy precipitation, and we have a cold spring and summer with high precipitation, when we have a warm winter with low precipitation. Past experience has shown that the use of water for irrigation, taking into account climatic conditions, has a significant impact on reducing irrigation water and increasing crop yields.
14 Qi, P.; Xia, Z.; Zhang,G.; Zhang, W.; Chang, Z. 2021. Effects of climate change on agricultural water resource carrying capacity in a high-latitude basin. Journal of Hydrology, 597:126328. (Online first) [doi: https://doi.org/10.1016/j.jhydrol.2021.126328]
Agriculture ; Water resources ; Carrying capacity ; Climate change ; Climatic factors ; Precipitation ; Temperature ; Drought ; Meteorological factors ; Evapotranspiration ; Crop production ; Wheat ; Soybeans ; Rice ; Maize ; Food safety ; River basins / China / Nenjiang River Basin
(Location: IWMI HQ Call no: e-copy only Record No: H050363)
(15.50 MB)
The agricultural water resource carrying capacity (AWRCC) is affected by climate change now as never before. However, it is still unclear how the AWRCC in high latitudes responses to climate change. In this study, spatiotemporal changes in climatic factors and AWRCC during the crop growing season from 1961 to 2014 in the Nenjiang River Basin (NRB), a high-latitude basin in China, were identified via multivariate statistical analysis. Meanwhile, the impact of climatic factors on AWRCC was analyzed by using cross-wavelet approaches and Pearson correlational analysis. The results showed that temperature has followed an increasing trend, especially the lowest temperature during crop growing season, with a trend of 0.57 /10a in the local region. There was no obvious change trend for precipitation, but the interannual change was large. The drought index increased first and then decreased, which was consistent with the trend of the ET0. Different spatial distributions of water resource carrying for all crops in a region were shown with a variation range of 0.22–0.76 kg/m2 in the NRB. It is worth noting that AWRCC showed an increasing trend, especially in the past decade. Precipitation, ET0, and meteorological drought were all key driving factors affecting AWRCC. The correlation was significant between the crop planting proportion and AWRCC under climate change. Moreover, adjusting the planting proportion of wheat, soybean and rice, and increasing that of maize, would be conducive to improving the AWRCC and facilitating the synergistic development of agriculture and wetlands in NRB.
15 Jena, S.; Panda, R. K.; Ramadas, M.; Mohanty, B. P.; Samantaray, A. K.; Pattanaik, S. K. 2021. Characterization of groundwater variability using hydrological, geological, and climatic factors in data-scarce tropical savanna region of India. Journal of Hydrology: Regional Studies, 37:100887. [doi: https://doi.org/10.1016/j.ejrh.2021.100887]
Groundwater ; Hydrogeology ; Climatic factors ; Land use ; Land cover ; Savannas ; Aquifers ; River basins ; Rain ; Geomorphology ; Topography / India / Odisha
(Location: IWMI HQ Call no: e-copy only Record No: H050697)
https://www.sciencedirect.com/science/article/pii/S2214581821001166/pdfft?md5=5803ba8adba3ab6a18c6c2bf86c59a78&pid=1-s2.0-S2214581821001166-main.pdf
https://vlibrary.iwmi.org/pdf/H050697.pdf
https://vlibrary.iwmi.org/pdf/H050697.pdf
(12.60 MB) (12.6 MB)
Study Region: State of Odisha, a data-scarce tropical savanna region in eastern India.
Study Focus: This study evaluated the temporal variability in depth to groundwater (DTW) in the study region with heavily stressed aquifers during 1995–2015 using the modified Mann Kendall test. Subsequently, Shannon’s entropy assessed spatial variability in DTW and determined the dominant Hydrological, Geological, and Climatological (HGC) factor regulating the observed spatio-temporal variability taking land use/ land cover (LULC), geomorphology, lithology, topography, and rainfall as HGC factors.
New Hydrological Insights: The overall and seasonal trend analysis revealed that the study region possessed both rising and declining trends with a slightly higher percentage of wells with a rising trend. The spatial distribution of trends and the associated magnitude accentuated the unforeseen groundwater temporal variability and higher-order susceptibility of DTW to rising and declining trends. The marginal entropy revealed the higher-order spatial variability associated with deeper DTW and vice versa. Evaluation of the HGC factors revealed that LULC could explain the maximum variability in the DTW as a dominant HGC factor. It was found that the impact of LULC features on DTW variability is not straightforward, necessitating impact assessment studies in the location with significant to highly significant trends. This formulated approach can immensely contribute to the planning and management in attaining groundwater sustainability in data-scarce regions.
Study Focus: This study evaluated the temporal variability in depth to groundwater (DTW) in the study region with heavily stressed aquifers during 1995–2015 using the modified Mann Kendall test. Subsequently, Shannon’s entropy assessed spatial variability in DTW and determined the dominant Hydrological, Geological, and Climatological (HGC) factor regulating the observed spatio-temporal variability taking land use/ land cover (LULC), geomorphology, lithology, topography, and rainfall as HGC factors.
New Hydrological Insights: The overall and seasonal trend analysis revealed that the study region possessed both rising and declining trends with a slightly higher percentage of wells with a rising trend. The spatial distribution of trends and the associated magnitude accentuated the unforeseen groundwater temporal variability and higher-order susceptibility of DTW to rising and declining trends. The marginal entropy revealed the higher-order spatial variability associated with deeper DTW and vice versa. Evaluation of the HGC factors revealed that LULC could explain the maximum variability in the DTW as a dominant HGC factor. It was found that the impact of LULC features on DTW variability is not straightforward, necessitating impact assessment studies in the location with significant to highly significant trends. This formulated approach can immensely contribute to the planning and management in attaining groundwater sustainability in data-scarce regions.
16 Srinet, R.; Nandy, S.; Padalia, H.; Ghosh, Surajit; Watham, T.; Patel, N. R.; Chauhan, P. 2020. Mapping plant functional types in Northwest Himalayan foothills of India using random forest algorithm in Google Earth Engine. International Journal of Remote Sensing, 41(18):7296-7309. [doi: https://doi.org/10.1080/01431161.2020.1766147]
Forests ; Highlands ; Normalized difference vegetation index ; Ecosystems ; Time series analysis ; Moderate resolution imaging spectroradiometer ; Digital elevation models ; Climatic factors ; Mapping / India / Himalayan Foothills
(Location: IWMI HQ Call no: e-copy only Record No: H050791)
(6.51 MB)
Plant functional types (PFTs) have been widely used to represent the vegetation characteristics and their interlinkage with the surrounding environment in various earth system models. The present study aims to generate a PFT map for the Northwest Himalayan (NWH) foothills of India using seasonality parameters, topographic conditions, and climatic information from various satellite data and products using Random Forest (RF) algorithm in Google Earth Engine (GEE) platform. The seasonality information was extracted by carrying out a harmonic analysis of Normalized Difference Vegetation Index (NDVI) time-series (2008 to 2018) from Moderate Resolution Imaging Spectroradiometer (MODIS) Terra surface reflectance 8 day 500 m data (MOD09A1). For topographic information, Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) derived aspect and Multi-Scale Topographic Position Index (MTPI) were used, whereas, for climatic variables, WorldClim V2 Bioclimatic (Bioclim) variables were used. RF, a machine learning classifier, was used to generate a PFT map using these datasets. The overall accuracy of the resulting PFT map was found to be 83.33% with a Kappa coefficient of 0.71. The present study provides an effective approach for PFT classification using different well-established, freely available satellite data and products in the GEE platform. This approach can also be implemented in different ecological settings by using various meaningful variables at varying resolutions.
17 Nandy, S.; Ghosh, Surajit; Singh, S. 2021. Assessment of sal (Shorea robusta) forest phenology and its response to climatic variables in India. Environmental Monitoring and Assessment, 193(9):616. [doi: https://doi.org/10.1007/s10661-021-09356-9]
Forests ; Phenology ; Climatic factors ; Shorea robusta ; Moderate resolution imaging spectroradiometer ; Time series analysis ; Remote sensing ; Temperature ; Rain ; Vegetation index / India / Assam / Chhattisgarh / Jharkhand / Madhya Pradesh / Meghalaya / Uttarakhand / West Bengal
(Location: IWMI HQ Call no: e-copy only Record No: H050795)
(2.27 MB)
Remote sensing-based observation provides an opportunity to study the spatiotemporal variations of plant phenology across the landscapes. This study aims to examine the phenological variations of different types of sal (Shorea robusta) forests in India and also to explore the relationship between phenology metrics and climatic parameters. Sal, one of the main timber-producing species of India, can be categorized into dry, moist, and very moist sal. The phenological metrics of different types of sal forests were extracted from Moderate Resolution Imaging Spectroradiometer (MODIS)-derived Enhanced Vegetation Index (EVI) time series data (2002–2015). During the study period, the average start of season (SOS) was found to be 16 May, 17 July, and 29 June for very moist, moist, and dry sal forests, respectively. The spatial distribution of mean SOS was mapped as well as the impact of climatic variables (temperature and rainfall) on SOS was investigated during the study period. In relation to the rainfall, values of the coefficient of determination (R2) for very moist, moist, and dry sal forests were 0.69, 0.68, and 0.76, respectively. However, with temperature, R2 values were found higher (R2 = 0.97, 0.81, and 0.97 for very moist, moist, and dry sal, respectively). The present study concluded that MODIS EVI is well capable of capturing the phenological metrics of different types of sal forests across different biogeographic provinces of India. SOS and length of season (LOS) were found to be the key phenology metrics to distinguish the different types of sal forests in India and temperature has a greater influence on SOS than rainfall in sal forests of India.
18 Haile, B.; Mekonnen, D.; Choufani, J.; Ringler, C.; Bryan, E. 2022. Hierarchical modelling of small-scale irrigation: constraints and opportunities for adoption in Sub-Saharan Africa. Water Economics and Policy, 8(1):2250005. [doi: https://doi.org/10.1142/S2382624X22500059]
Small-scale irrigation ; Modelling ; Farmer-led irrigation ; Irrigation water ; Water supply ; Technology ; Groundwater ; Irrigation schemes ; Smallholders ; Gender ; Agricultural extension ; Labour ; Climatic factors ; Risk ; Inorganic fertilizers ; Socioeconomic aspects / Africa South of Sahara / Ethiopia / United Republic of Tanzania / Ghana
(Location: IWMI HQ Call no: e-copy only Record No: H051137)
https://www.worldscientific.com/doi/epdf/10.1142/S2382624X22500059
https://vlibrary.iwmi.org/pdf/H051137.pdf
https://vlibrary.iwmi.org/pdf/H051137.pdf
(0.64 MB) (652 KB)
Irrigation has significant potential to enhance productivity, resilience to climatic risks and nutrition security in Sub-Saharan Africa. While the focus has historically been on large-scale dam-based schemes, farmer-managed small-scale irrigation (SSI) has gained increased attention in recent years. Using data from Ethiopia, Tanzania and Ghana, we first examine patterns of adoption of different SSI technologies. Next, we employ hierarchical modelling to examine which variables are associated with observed adoption patterns and cluster effects that explain variation in irrigation adoption. We document significant cross-country variation in adoption patterns and find a positive association between plot-level use of SSI and the intensity of agricultural labor and inorganic fertilizers applied on the plot. Community-level intra-cluster correlation (ICC) is the highest in Tanzania, where gravity-fed irrigation is most common while farm-level ICC is the highest in Ethiopia where motorized technologies are more common. These results suggest the need for localized investments to ease locale-specific potential constraints. For example, easing possible liquidity constraints to acquiring motorized technologies can be more effective in Ethiopia while the construction of dams and improved conveyance systems, as well as the strengthening of community-based irrigation management (e.g., through Water User Associations (WUAs)) can be more effective in Tanzania. Further research is needed to understand pathways for selected plot-level characteristics that affect use of SSI including status of plot ownership and the gender of the plot manager.
19 Kidane, R.; Wanner, T.; Nursey-Bray, M.; Masud-All-Kamal, Md.; Atampugre, G. 2022. The role of climatic and non-climatic factors in smallholder farmers’ adaptation responses: insights from rural Ethiopia. Sustainability, 14(9):5715. [doi: https://doi.org/10.3390/su14095715]
Climate change adaptation ; Strategies ; Climatic factors ; Smallholders ; Farmers ; Decision making ; Rural areas ; Livelihoods ; Vulnerability ; Rain ; Crops ; Diversification ; Policies ; Household surveys / Africa / Ethiopia / Tigray / Raya Azebo
(Location: IWMI HQ Call no: e-copy only Record No: H051184)
https://www.mdpi.com/2071-1050/14/9/5715/pdf?version=1652329978
https://vlibrary.iwmi.org/pdf/H051184.pdf
https://vlibrary.iwmi.org/pdf/H051184.pdf
(0.94 MB) (960 KB)
This paper discusses how climatic and non-climatic factors, either separately or together, shape the adaptation responses of smallholder farmers in the Raya Azebo district of Ethiopia. Their adaptation responses included adjusting planting periods, crop diversification, changing crop types, adopting improved seeds, using irrigation, conducting migration, participation in wage employment, selling local food and drinks, and owning small shops. These adaptation responses were motivated by various climatic (e.g., drought and rainfall variability) as well as non-climatic factors (e.g., market conditions, yield-related factors, land scarcity, labor shortages, soil fertility issues, crop diseases, and limited local employment options). We therefore argue (i) that successful adaptation requires a broader understanding not just of climatic factors but also of the various social-ecological factors that shape smallholder farmers’ adaptations; and (ii) that the successful design and implementation of locally appropriate planned adaptation interventions require the inclusion of both climatic and non-climatic factors.
20 Masenyama, A.; Mutanga, O.; Dube, T.; Sibanda, M.; Odebiri, O.; Mabhaudhi, T. 2023. Inter-seasonal estimation of grass water content indicators using multisource remotely sensed data metrics and the cloud-computing Google Earth Engine platform. Applied Sciences, 13(5):3117. (Special issue: Remote Sensing Applications in Agricultural, Earth and Environmental Sciences) [doi: https://doi.org/10.3390/app13053117]
Grasslands ; Plant water relations ; Estimation ; Remote sensing ; Datasets ; Leaf area index ; Vegetation index ; Climatic factors ; Indicators ; Satellite observation ; Forecasting ; Spatial distribution ; Models / South Africa / KwaZulu-Natal / Vulindlela
(Location: IWMI HQ Call no: e-copy only Record No: H051820)
https://www.mdpi.com/2076-3417/13/5/3117/pdf?version=1677581546
https://vlibrary.iwmi.org/pdf/H051820.pdf
https://vlibrary.iwmi.org/pdf/H051820.pdf
(4.12 MB) (4.12 MB)
Indicators of grass water content (GWC) have a significant impact on eco-hydrological processes such as evapotranspiration and rainfall interception. Several site-specific factors such as seasonal precipitation, temperature, and topographic variations cause soil and ground moisture content variations, which have significant impacts on GWC. Estimating GWC using multisource data may provide robust and accurate predictions, making it a useful tool for plant water quantification and management at various landscape scales. In this study, Sentinel-2 MSI bands, spectral derivatives combined with topographic and climatic variables, were used to estimate leaf area index (LAI), canopy storage capacity (CSC), canopy water content (CWC) and equivalent water thickness (EWT) as indicators of GWC within the communal grasslands in Vulindlela across wet and dry seasons based on single-year data. The results illustrate that the use of combined spectral and topo-climatic variables, coupled with random forest (RF) in the Google Earth Engine (GEE), improved the prediction accuracies of GWC variables across wet and dry seasons. LAI was optimally estimated in the wet season with an RMSE of 0.03 m-2 and R2 of 0.83, comparable to the dry season results, which exhibited an RMSE of 0.04 m-2 and R2 of 0.90. Similarly, CSC was estimated with high accuracy in the wet season (RMSE = 0.01 mm and R2 = 0.86) when compared to the RMSE of 0.03 mm and R 2 of 0.93 obtained in the dry season. Meanwhile, for CWC, the wet season results show an RMSE of 19.42 g/m-2 and R2 of 0.76, which were lower than the accuracy of RMSE = 1.35 g/m-2 and R 2 = 0.87 obtained in the dry season. Finally, EWT was best estimated in the dry season, yielding a model accuracy of RMSE = 2.01 g/m-2 and R2 = 0.91 as compared to the wet season (RMSE = 10.75 g/m-2 and R2 = 0.65). CSC was best optimally predicted amongst all GWC variables in both seasons. The optimal variables for estimating these GWC variables included the red-edge, near-infrared region (NIR) and short-wave infrared region (SWIR) bands and spectral derivatives, as well as environmental variables such as rainfall and temperature across both seasons. The use of multisource data improved the prediction accuracies for GWC indicators across both seasons. Such information is crucial for rangeland managers in understanding GWC variations across different seasons as well as different ecological gradients.
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