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<title>Journal of Hydrologic Engineering</title>
<link href="http://yetl.yabesh.ir/yetl1/handle/yetl/19026" rel="alternate"/>
<subtitle/>
<id>http://yetl.yabesh.ir/yetl1/handle/yetl/19026</id>
<updated>2026-08-26T18:47:12Z</updated>
<dc:date>2026-08-26T18:47:12Z</dc:date>
<entry>
<title>Experimental Investigation and Parameter Inversion of Radial Solute Transport Accounting for the Skin Effect</title>
<link href="http://yetl.yabesh.ir/yetl1/handle/yetl/4311741" rel="alternate"/>
<author>
<name>Yuan, Kehan</name>
</author>
<author>
<name>Zhu, Qi</name>
</author>
<author>
<name>Ma, Teng</name>
</author>
<author>
<name>Wang, Ning</name>
</author>
<author>
<name>Li, Xu</name>
</author>
<author>
<name>Li, Na</name>
</author>
<id>http://yetl.yabesh.ir/yetl1/handle/yetl/4311741</id>
<updated>2026-08-20T11:08:12Z</updated>
<published>2026-01-01T00:00:00Z</published>
<summary type="text">Experimental Investigation and Parameter Inversion of Radial Solute Transport Accounting for the Skin Effect
Yuan, Kehan; Zhu, Qi; Ma, Teng; Wang, Ning; Li, Xu; Li, Na
AbstractRadial solute tracer tests are a key method for estimating aquifer parameters, yet
their accuracy often is compromised by skin effects around the wellbore resulting
from drilling or completion activities. A clear understanding of how skin ...
</summary>
<dc:date>2026-01-01T00:00:00Z</dc:date>
</entry>
<entry>
<title>Response of Wildfires to Concurrent and Consecutive Drought and Hot Extremes across the Globe</title>
<link href="http://yetl.yabesh.ir/yetl1/handle/yetl/4311740" rel="alternate"/>
<author>
<name>Ma, Qian</name>
</author>
<author>
<name>Hao, Zengchao</name>
</author>
<author>
<name>Xie, Lulu</name>
</author>
<id>http://yetl.yabesh.ir/yetl1/handle/yetl/4311740</id>
<updated>2026-08-20T11:08:10Z</updated>
<published>2026-01-01T00:00:00Z</published>
<summary type="text">Response of Wildfires to Concurrent and Consecutive Drought and Hot Extremes across the Globe
Ma, Qian; Hao, Zengchao; Xie, Lulu
AbstractWildfires can cause disastrous impacts on natural and human systems. Hydroclimatic
extremes, such as droughts and high temperature anomalies, can affect the occurrence,
intensity, and spread of wildfires. Moreover, these extremes may occur ...
</summary>
<dc:date>2026-01-01T00:00:00Z</dc:date>
</entry>
<entry>
<title>Climate-Driven Shifts in the Geographic Dependency of the NRCS Initial Abstraction Ratio</title>
<link href="http://yetl.yabesh.ir/yetl1/handle/yetl/4311739" rel="alternate"/>
<author>
<name>Moglen, Glenn E.</name>
</author>
<author>
<name>Miller, Julianne J.</name>
</author>
<author>
<name>Gifford, Justin</name>
</author>
<author>
<name>Chen, Tianyang</name>
</author>
<id>http://yetl.yabesh.ir/yetl1/handle/yetl/4311739</id>
<updated>2026-08-20T11:08:08Z</updated>
<published>2026-01-01T00:00:00Z</published>
<summary type="text">Climate-Driven Shifts in the Geographic Dependency of the NRCS Initial Abstraction Ratio
Moglen, Glenn E.; Miller, Julianne J.; Gifford, Justin; Chen, Tianyang
AbstractThe appropriate selection of the initial abstraction ratio in the Natural Resources
Conservation Service (NRCS) curve number method has been debated within the hydrologic
engineering community. Building on recent work that introduced the concept ...Practical ApplicationsThis work uses the future climate-based projections made available by the National
Oceanographic and Atmospheric Administration (NOAA) Atlas 15 pilot project that provides
future precipitation estimates across the State of Montana as ...
</summary>
<dc:date>2026-01-01T00:00:00Z</dc:date>
</entry>
<entry>
<title>Integrating Hydrological, Physical, and Chemical Factors for Soil Moisture Prediction Using Advanced Machine Learning Models</title>
<link href="http://yetl.yabesh.ir/yetl1/handle/yetl/4311738" rel="alternate"/>
<author>
<name>Al-Juaidi, Ahmed E. M.</name>
</author>
<id>http://yetl.yabesh.ir/yetl1/handle/yetl/4311738</id>
<updated>2026-08-20T11:08:05Z</updated>
<published>2026-01-01T00:00:00Z</published>
<summary type="text">Integrating Hydrological, Physical, and Chemical Factors for Soil Moisture Prediction Using Advanced Machine Learning Models
Al-Juaidi, Ahmed E. M.
AbstractAccurately predicting soil moisture content (SMC) is critical for effective water
management and sustainable agriculture. This study demonstrates that combining hydrological
factors, such as rainfall, with soil physical characteristics—including ...
</summary>
<dc:date>2026-01-01T00:00:00Z</dc:date>
</entry>
</feed>
